Jad Jebara, Founder and President at Hyperview explains why the infrastructure that powers AI deserves just as much attention as trends such as tokenmaxxing.
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The race to adopt AI inside enterprises has created a new metric for success: usage. Across Silicon Valley and increasingly, the wider business world, organisations are being encouraged to maximise internal AI consumption as aggressively as possible. More prompts, more AI-assisted workflows, more automation and more model interaction are becoming signs of AI maturity, a trend referred to as “tokenmaxxing.”
On the surface, the logic is understandable. Businesses do not want to fall behind on AI adoption, executives are under pressure to demonstrate AI maturity, and employees are increasingly being encouraged to integrate AI into everything from software development and analytics to customer service and internal productivity. However, underneath the excitement sits a much larger operational reality that the industry is only beginning to confront.
The AI conversation is shifting away from experimentation and towards the operational reality of sustaining infrastructure demand at scale, where the challenge is no longer simply whether AI works, but whether the infrastructure supporting it can scale sustainably, securely, reliably and efficiently as usage accelerates. That distinction matters because AI consumption behaves very differently from previous waves of enterprise technology adoption.
AI consumption changes the infrastructure equation
Most users interact with AI through relatively simple interfaces such as chatbot windows, coding assistants or summarisation tools, which makes the experience feel lightweight, fast and almost frictionless.
What remains invisible is the infrastructure required behind every interaction. Each AI request triggers compute workloads running across highly power-intensive GPU infrastructure inside data centres. Those environments require enormous amounts of electricity, cooling capacity and operational coordination to sustain performance. As enterprise usage expands from isolated pilots into everyday operational dependency, the infrastructure implications become exponentially larger. This is one of the reasons governments are dramatically revising their environmental forecasts around AI.
The UK Government originally estimated AI compute would generate around 0.25 MtCO₂ over the decade to 2035. The forecast has now been revised upwards to at least 34 MtCO₂. AI data centres are also projected to account for between 0.9% and 3.4% of the UK’s total carbon emissions by 2035. These are not marginal adjustments, but a reflection of how quickly the scale of long-term AI demand has been underestimated.
Early AI discussions largely assumed usage would remain relatively focused on specialised tasks. Instead, AI is now being embedded simultaneously across productivity platforms, software engineering, search, analytics, cybersecurity and customer operations, with organisations actively encouraging employees to use AI continuously. This shift changes the operational equation entirely.
The hidden cost behind the chatbot interface
One of the biggest misconceptions around AI adoption is that the cost sits primarily inside the model itself, when in reality the operational burden extends far beyond inference costs or API pricing.
AI-heavy environments introduce sustained power loads that traditional enterprise infrastructure was never designed to support at this scale, with GPU workloads creating dense thermal profiles, more volatile cooling requirements and far less predictable capacity behaviour than conventional enterprise applications.
Many operators are still managing these environments across fragmented infrastructure systems built long before AI workloads became mainstream, with power monitoring sitting in one platform, environmental telemetry in another, asset inventories elsewhere and sustainability reporting often remaining disconnected entirely. The result is that infrastructure teams are forced to make operational decisions without a unified understanding of how workloads, energy usage, cooling behaviour and capacity constraints interact in real time.
As AI demand continues to scale, that fragmentation becomes increasingly risky because the challenge is no longer simply about building more compute capacity, but about understanding how infrastructure behaves under sustained AI load and being able to optimise it continuously in real time. Without that level of visibility and operational context, inefficiencies can compound very quickly.
Infrastructure limits are becoming more visible
There is still an assumption in many parts of the market that infrastructure will continue scaling indefinitely to absorb AI demand, but in practice, operators are already encountering very real physical and operational constraints.
Power availability is emerging as one of the biggest bottlenecks, with utilities across multiple regions struggling to keep pace with projected AI-driven demand growth. Unlike many previous enterprise workloads, AI consumption creates highly persistent energy demand concentrated across specific locations, placing increasing pressure on grid resilience, cooling infrastructure and long-term power planning.
Organisations are also facing growing pressure to meet sustainability targets and regulatory obligations at the same time governments are accelerating AI investment and adoption alongside broader net-zero strategies. Those priorities are beginning to collide, creating a difficult balancing act between economic competitiveness, AI innovation and environmental sustainability that will only become more pronounced as enterprise AI usage shifts from optional tooling to core operational dependency.
This is why the conversation around AI infrastructure can no longer focus purely on speed and scale, because efficiency, orchestration and operational intelligence are becoming just as important as compute capacity itself.
Why visibility will matter more than raw compute
The next phase of AI growth will place far greater emphasis on infrastructure visibility and coordination rather than simply adding more hardware.
Operators need a clearer understanding of how environments are performing in real time, including where power is being consumed, how workloads are affecting cooling efficiency and where capacity risks are beginning to emerge. That becomes even more important as AI workloads push organisations to distribute infrastructure across hyperscale facilities, colocation environments and edge locations.
As these environments become more dynamic, operators will increasingly need the ability to orchestrate workloads intelligently across multiple locations while balancing power, performance and efficiency constraints simultaneously. This is where AI-driven operational management becomes increasingly valuable, not because AI is a universal solution to infrastructure complexity, but because the scale and operational density of modern environments are becoming too difficult to manage through fragmented oversight alone.
The organisations that adapt successfully will not necessarily be the ones consuming the largest volume of AI. They will be the ones capable of managing the infrastructure underneath that demand intelligently, efficiently and sustainably.
Moving beyond the AI consumption race
The broader issue with trends like tokenmaxxing is not that organisations are adopting AI too aggressively. It is that the market is increasingly treating AI consumption itself as a measure of progress, where more prompts, more workflows and more automation are becoming signals of AI maturity without enough consideration for the infrastructure required to sustain that demand efficiently over the long term.
As adoption scales further, operational realities become much harder to ignore. Power constraints, cooling pressures and sustainability targets are no longer theoretical concerns sitting in the background of AI growth, but operational challenges that infrastructure teams are already dealing with in real time.
Generating more AI activity is relatively easy by comparison. Sustaining that demand efficiently, reliably, cost-effectively, and in a continuously optimised way at scale is the far greater challenge now beginning to emerge.
William Thackray, Operations Director, of AGT Computer Services, explains how geofencing can add an extra layer of security to your login credentials.
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For almost two decades, enterprise security has revolved around identity. If you can prove who you are through password management, then you’re in. Which is why Identity and Access Management (IAM), Multi-Factor Authentication (MFA), Privileged Access Management (PAM), and more recently, Zero Trust have evolved. Businesses use ID to manage access and every improvement in authentication has made that process better. But security is not the only thing to have evolved.
In many cases, authentication isn’t even an issue for attackers. Adversary-in-the-middle attacks mean they can bypass logins altogether. Tokens can be extracted from compromised devices. And where login details are needed, they can be stolen or bought, so access doesn’t look like intrusion. And identity ceases to be a barrier.
Identity isn’t enough
The thing about a successful login is that it only tells you that someone has provided the appropriate details to access your system. But when there are so many ways to navigate that step, it’s really not enough. What you really need to know is whether a login makes sense. Could a person who normally works in Luton log in from Singapore at 3am, when they were in the office just a few hours earlier?
Identity goes no way towards answering that question. All it does is establish who someone claims to be, not whether the claim is viable. And that’s a really important distinction. Especially with hybrid working, cloud services and globally distributed teams becoming more common. The traditional network perimeter has largely disappeared, making contextual signals, like geofencing, much more useful.
Geofencing is more than a geographical boundary
Geofencing is often thought of as a simple way to block access from certain locations. But it holds so much more potential than that. And some new identity platforms are already taking advantage of it. Microsoft Entra and Okta, for example, use location as part of their Conditional Access policies. Using cues such as device health, previous activity and session information to decide how a login should be handled. And they’re opening the potential for more than access or denial.
A login might be allowed immediately, trigger an additional authentication challenge, or be blocked, depending on the overall level of risk. People travel and work remotely, so not every unfamiliar location poses a threat. And blocking locations arbitrarily can limit the potential for productivity. The true value of geofencing is that it provides another piece of evidence that can support informed decision-making. And that matters, because different logins carry different degrees of risk.
Context supports understanding
When used alone, geofencing is rarely effective. But when integrated with a wider security strategy, it carries real value.
When connected to Security Information and Event Management (SIEM) platforms, location information can be combined with other signals – impossible-travel events, unusual login times, privilege escalation attempts, unmanaged devices and behavioural anomalies – to deliver missing context. Creating a complete picture of what’s happening. And enabling businesses to more fully assess whether a login request is likely to be valid or fraudulent.
Location isn’t always what it seems
Like any security control, geofencing has limitations. VPNs can hide a user’s location. Cloud infrastructure can make legitimate activity appear to originate from an unexpected country. And IP-based geolocation isn’t always precise, particularly on mobile networks. Businesses also have to account for executives who travel, contractors working across borders and field employees who move between offices, sites and home.
Authentication tokens add in another complication. Some apps can continue operating during an authenticated session without repeatedly reassessing the user’s location, so a location check at login doesn’t necessarily tell the whole story of what happens afterwards.
So, geofencing isn’t infallible and it’s not 100% effective. But neither is any other form of digital security. And that reinforces a principle that every business needs to understand: no single signal should be trusted in isolation.
Better questions are needed
For most businesses, adding location-based controls doesn’t require a new security architecture. Conditional Access policies are already supported by a number of platforms. They have the capability to use location as part of an access decision. They can even apply these policies selectively, identifying privileged accounts, sensitive applications and higher-risk regions; anywhere they think it necessary. It’s just that businesses either don’t know those options are there, or that they’ve listened to the dismissal of geofencing for too long.
Attackers will keep on finding ways to breach companies. And the businesses that rely on identity authentication alone will keep falling prey. But the option is there to make things harder. And that starts with the question, ‘Who are you?’, but continues with asking ‘Where are you?’, ‘Does that location make sense?’ and ‘Why are you logging in?’
Serge Bejjani, Co-Founder & CEO of Shootday, on the importance for FinTechs of treating brand indentity as intellectual property
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It’s a pervasive idea that reproducing the visual language of credible, established institutions lets new FinTech entrants borrow trust by association. It’s also wrong, and the consequences are real.
Familiarity isn’t reassuring anyone
FinTech customers have, over the last decade, run into all manner of low-trust players dressed in the same polished aesthetic. The reassuring visual cues that once signalled FinTech’s credibility have been hijacked by unscrupulous outfits as a cheap disguise.
Where generic branding might once have read as safely conventional, it now reads as deliberately evasive. Sameness has become the hallmark of a company with nothing much to say for itself, a shrug that leaves the customer with nothing to go on when deciding whether it’s worthy of their trust.
Trust in financial services isn’t built through aesthetic conformity but through demonstrable reliability and a coherent identity. That takes time, and for a weak FinTech, time only increases the odds that its shortcomings get exposed.
At a moment when customers have every reason to approach fintech with caution, messaging that whispers “this could be any FinTech” is a red flag. Customers who can’t tell one FinTech from another aren’t reassured by the homogeneity, it just strips them of any basis to form an opinion, good or bad, which is a poor foundation for a relationship built on money.
Similar by accident
No firm decides, one day, to become generic as a strategy. Product, growth and marketing teams independently optimised toward frictionless onboarding, familiar messaging and low-risk visuals. Because those choices tested well, cleared compliance faster and reassured investors used to recognisable patterns. Individuality got lost across a decade of small, rational decisions. What comes next will happen a great deal faster.
Copy and paste
Generative tools now produce marketing copy and design at a pace no internal FinTech team can match, and they’re doing it by training on a body of content that’s already remarkably homogenous.
Ask any AI model to design a “trustworthy landing page” for the sector and, in an afternoon, it will hand back the same blues, the same reassuring sans-serif type and the same promises of ease and control that already define the sector’s digital presence, because that’s what the training data mostly contains.
Every firm using these tools without creative oversight is baking the same clichés into its marketing at scale. The firms moving fastest to fold AI into their marketing stack may, in practice, be moving fastest toward irrelevance. In 18 months, those who let AI construct their identity may wake up to find they don’t really have one.
Trust your people
This isn’t a problem a better font or a wider colour palette will fix. As AI increasingly shapes what FinTech content looks like, the advantage shifts to firms with a genuinely distinctive identity, one AI can’t replicate.
Executive headshots and stock imagery still have their place. They fill a LinkedIn profile or an investor deck. But a templated one, the same backdrop and the same pose every other firm is using, does nothing to separate one FinTech from the next, and an AI-generated stand-in does even less. What actually differentiates is real footage from real moments: a founder in an actual client meeting, a team at an actual product launch, a conference stand that looks like the people running it rather than a template.
That means treating brand identity as intellectual property worth protecting, and giving marketing and product teams room to choose to look different, rather than defaulting to the safest option every time.
Serge Bejjani is co-founder and CEO ofShootday, a global photo and video production partner providing corporate event photography, event videography, and headshot services for businesses in 150+ cities worldwide.
Strategic technology leader and former Department of the Air Force CIO, Lauren Knausenberger, appointed by Defense Unicorns to accelerate growth and advance software as a deterrent to war.
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Defense Unicorns, the market leader in airgap-native software delivery and national security missions, has appointed Lauren Knausenberger as it’s Chief Business Officer. Knausenberger has vast experience of advancing technology, digital transformation, cybersecurity, and innovation across mission-critical government and defense environments. She will help drive Defense Unicorns’ growth strategy, strengthen strategic partnerships and expand the company’s impact across the defense ecosystem.
Knausenberger most recently served as Executive Vice President and Chief Innovation Officer at SAIC, where she led strategy, AI-enabled transformation, rapid capability development, strategic technology partnerships and SAIC Ventures. She previously served as Chief Information Officer (CIO) of the Department of the Air Force, where she was responsible for Enterprise IT, Cybersecurity, Data and Artificial Intelligence. Additionally, she sits on the board for Enersys, a member of the AFCEA Executive Committee, and an advisor to private capital investing in defense technology.
“Lauren brings the rare combination of technical depth, business leadership and mission focus that Defense Unicorns needs as we continue to scale,” said Dr. Rob Slaughter, CEO of Defense Unicorns. “She understands the urgency facing our mission customers and the role software and AI can play in helping them move faster, operate more securely and deliver greater mission impact. We are thrilled to welcome her to the team and look forward to the leadership and perspective she will bring.”
About Defense Unicorns
Founded in 2021 by Rob Slaughter, Jeff McCoy and Andrew Greene, Defense Unicorns is a veteran-owned defense technology company that makes software a strategic deterrent for the U.S. Department of War. The company builds open-source, airgap-native technologies that enable the secure development, delivery and sustainment of mission software across cloud, on-premises and tactical edge environments.
Knausenberger’s appointment comes as Defense Unicorns continues to expand its role in modernising defense software and enabling the rapid delivery of secure, interoperable capabilities to the warfighter.
“One of my core missions since serving as CIO of the Department of the Air Force has been to make software a true deterrent to war by giving our military and our allies the speed, resilience, interoperability and the technological advantage they need to prevent conflict first, and fight and decisively win when we must,” said Lauren Knausenberger, Chief Business Officer of Defense Unicorns.
Rhys Sharp, Solution Director at Six Degrees talks to us about how businesses can build their resilience to ensure they can maintain operations, respond to disruption and adapt to change.
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Business resilience has traditionally been treated as a form of technical insurance. In many organisations, the goal has been simple: recover quickly when something breaks and minimise disruption.
That perspective is still deeply embedded. Research from the Six Degrees Business Resilience Index 2026 shows that nearly three-quarters of technology and security leaders define resilience primarily through a security lens. Yet when presented with a broader definition, 91% said they learned something new about what resilience actually involves.
The reason is clear. Modern organisations face a far wider range of risks than cyber threats alone. Operational disruption, third-party dependencies, supply-chain fragility, regulatory change, economic volatility and increasing technology complexity all shape whether a business can continue to operate effectively.
True resilience is therefore not just about protecting systems. It is about ensuring the organisation can maintain operations, respond to disruption and adapt to change.
The resilience perception gap
Despite growing awareness of broader risks, there remains a disconnect between how resilience is discussed at leadership level and how it is delivered operationally.
Almost all respondents in the Business Resilience Index research (97%) agreed that strong leadership and governance would improve resilience. Yet board-level commitment ranked only tenth among the factors organisations associate with actually delivering it.
This gap often leads organisations to overestimate their readiness. Resilience activities may exist within IT or security teams, but they are rarely embedded into strategic decision-making across the business. As a result, organisations can feel prepared until disruption reveals hidden weaknesses.
Understanding resilience maturity
Resilience is not a fixed state but a spectrum. Most organisations sit somewhere along a maturity curve made up of five stages:
At risk – highly vulnerable organisations with fragmented processes, limited planning and largely manual recovery capabilities.
Reactive – able to respond to incidents but unable to anticipate them, often experiencing repeated disruptions.
Stable – controls exist and major failures are less likely, but resilience is still process-driven rather than embedded into operations.
Agile – people, processes and platforms align to support rapid response and organisational flexibility.
Strategically resilient – resilience is embedded across governance, operations and innovation, supporting both performance and long-term growth.
Research suggests most organisations sit in the middle of this curve. They can manage disruption when it happens but lack the foresight, integration and adaptability required to move beyond reactive measures.
The five pillars of resilient organisations
Progress along the maturity curve depends on how well organisations integrate five core capabilities across their operations: Continuity, Security, Scalability, Efficiency and Innovation.
When these pillars operate in isolation, resilience efforts often remain limited in impact. When aligned across infrastructure, governance and strategy, they reinforce one another and create a more adaptable operating environment.
Continuity: the weakest link
Among the five pillars, continuity consistently emerges as the most fragile.
The Business Resilience Index research shows that nearly one in three organisations (28%) are classified as At Risk in this area, while fewer than one in ten (9%) reach the Strategically Resilient level.
Operational data reinforces the challenge. Mean uptime across critical services in the past year was just 73%, meaning businesses experienced downtime more than a quarter of the time, whether planned or unplanned.
Mean Time to Recover (MTTR) also varies significantly between sectors. Technology companies report average recovery times of around 9.7 hours compared with an overall average of 6.7 hours, suggesting that their focus on client uptime could be coming at the expense of enhancing their own.
The findings highlight an important point: continuity cannot simply exist as a disaster recovery plan on a shelf. It must be embedded, tested and coordinated across the entire organisation.
Strengths and gaps across the other pillars
While continuity presents the greatest risk, the other pillars show a mixed picture of progress.
Scalability is relatively strong. More than half of organisations fall into the Agile or Strategically Resilient tiers, reflecting growing adoption of flexible infrastructure and cloud-based services.
Efficiency shows significant potential but limited maturity. Only 7% of organisations reach Strategically Resilient status, although 39% are progressing toward greater automation and smarter decision-making.
Innovation is widely present but rarely embedded. Nearly half of organisations operate at an Agile level, but just 2% integrate innovation deeply enough to achieve strategic resilience.
Security, while widely prioritised, still has room for improvement. Only 5% reach the Strategically Resilient tier, even though most organisations cluster at the Agile stage.
Different sectors, different pressures
Resilience challenges also vary significantly between industries.
Financial services organisations often demonstrate stronger resilience profiles due to strict regulatory oversight, structured governance and consistent investment in operational stability.
Manufacturing organisations, by contrast, tend to sit closer to the middle of the maturity curve. Operational intensity and complex supply chains make resilience harder to embed, resulting in higher numbers of organisations classified as At Risk and fewer reaching Agile levels.
Technology companies face another challenge entirely: managing the complexity of large-scale digital environments while maintaining speed and innovation.
These differences highlight that resilience strategies must be tailored to the operational realities of each sector.
The growing role of automation and AI
Technology priorities are also evolving. The Business Resilience Index research shows that automation and AI are now viewed as the most important drivers of resilience, ranking above traditional incident response, recovery and continuity planning.
These technologies allow organisations to detect issues earlier and respond more quickly by reducing reliance on manual processes that can slow recovery. They also enable more continuous, data-driven operations that help anticipate risks before they escalate.
However, infrastructure limitations can still create bottlenecks. Many organisations report that existing resilience strategies cannot scale quickly enough during sudden demand spikes or operational disruptions. Ensuring platforms and services can adapt rapidly is therefore becoming a central focus of resilience strategies.
Turning resilience into a growth platform
The most resilient organisations approach the challenge differently. Rather than treating resilience purely as a defensive safeguard, they see it as an operational capability that supports growth and adaptability.
In practice, this means embedding resilience into everyday operations and decision-making. High-performing organisations design systems that can sense operational signals and emerging demand, allowing them to identify opportunities as well as risks. Continuity is treated as routine operating hygiene, with systems tested regularly and responsibility shared across the organisation rather than confined to IT teams.
They also build scalability directly into system design through elastic infrastructure, self-service capabilities and automation, enabling the business to respond quickly to change without unnecessary friction. At the same time, efficiency is driven by cost transparency rather than simple cost-cutting, helping leaders invest where resilience clearly delivers value. Finally, innovation is actively protected through governance and resource allocation, ensuring experimentation and future-readiness remain part of the organisation’s long-term strategy.
Together, these practices transform resilience from a reactive safeguard into a strategic platform that enables organisations not only to withstand disruption but also to evolve and grow in response to it.
Bodo Philipp, CEO at MHP Consulting UK, explains how the successful adoption of new ERP systems alongside digital transformation, will enable automotive companies to respond to today’s challenges and understand how to build a successful future.
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Successful adoption of new ERP systems such as SAP S/4 HANA and digital transformation will not only enable automotive companies to respond to today’s challenges by improving efficiency and productivity, but also provide the data required to better understand how to build a successful future, explains Bodo Philipp, CEO, MHP Consulting UK.
Agile operations
Automotive manufacturers have long been lauded for highly efficient manufacturing and logistics processes. But in a fast-changing market, agility is now a priority. New market entrants, a changing sales model and fundamental technology changes combine to create a new customer driven paradigm that demands faster, dynamic reaction.
While the priority for many organisations’ SAP S/4HANA migration strategy has been adding efficiency to manufacturing and logistics processes, the adoption of modern cloud-based ERP also provides the opportunity to drive additional value from customer data. Automotive is not alone in facing pressure on market share, changing customer perception, even core values, alongside agile and innovative new market entrants. Industries globally face changing customer demands and in response, tailored customer experience is scaling new heights – from AI led engagement to real-time customised offers and the creation of new routes to market.
For successful brands, this level of personalisation and customer recognition must become part of the automotive buying and critically, owning process. Customers expect car brands to reflect their needs, whether that is AI driven air conditioning that automatically adjusts to each different driver’s preferences, or seamless integration with social media accounts to enhance the entire journey experience.
Informing change
One of the most pressing issues to address is how to counter the rise in intended vehicle brand defection, up to 56% in the UK in 2025. In addition to understanding and responding to customers’ continually evolving attitudes towards ICE versus Electric Vehicles versus hybrid, the industry must also address changing perceptions of vehicle ownership. While attitudes vary globally, there is a marked shift towards Mobility as a Service (MaaS) over vehicle ownership amongst younger consumers.
The migration from legacy ERP to cloud-based SAP S4 HANA provides the foundation for automotive companies to respond to changing customer behaviours. With a single source of all operational data, automotive manufacturers can leverage powerful analytics to better understand customer expectations and experiences.
This insight can inform the transformation of customer engagement throughout the changing sales model. It can flag opportunities to safely use AI, both within vehicles and throughout the ownership experience. Critically, it can surface information to support complex decisions about future business models and brand direction – such as carving a niche in the luxury car market or being at the forefront of the self-driving market.
Conclusion
In an industry that is enduring change from every direction, future success will require a different approach at every level, from the way brands interact with and engage customers throughout a vehicle’s lifespan to the pace of innovation and the evolution of vehicle sales and finance models. The migration to SAP S/4 HANA is now pressing, given the deadline, but with the right approach, the shift to the cloud-based ERP solution presents an essential opportunity to redefine the automotive industry.
It will enable automotive manufacturers to gain enormous value from highly accurate predictions and forecasts; it will transform agility and offer the chance to drive, rather than just respond to customer perceptions. It will introduce new opportunities to leverage AI both to support faster product iteration and improve customer engagement.
Improvements in efficiency and productivity will underpin the business case for migration; but it is the information held within an integrated, end to end ERP system that will play a vital role in creating the foundation for future automotive success.
MHP Consulting is Porsche-owned, and is a leading global consulting firm specialising in strategy, digital transformation, and performance improvement across various industries, including automotive, manufacturing and technology.
Cody Barrow, CEO of EclecticIQ, tell us how we can counter the ever growing threat that AI poses to our cybersecurity.
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Security teams now face more than 550,000 new malware variants every day, which is roughly one every 0.15 seconds. This scale illustrates how drastically the tempo of cyber threats has changed. Attackers are not just becoming more sophisticated; they are becoming significantly faster.
Artificial intelligence is now embedded across the entire threat lifecycle. Adversaries are generating polymorphic malware that constantly changes its code. They create deep-fake audio and video to impersonate executives. They are launching highly targeted phishing campaigns at volumes and speeds that would have been impossible only a few years ago. One such operation targeting European energy companies produced more than 50,000 tailored phishing emails in 14 languages.
AI also gives attackers new strategic advantages. Some threat groups use machine-learning to study defender behaviour, identifying ideal moments to strike. In extreme cases, attacks that once took days can now succeed in a matter of hours.
This acceleration is creating what many in the industry now call the speed differential crisis. Human analysts, no matter how capable, cannot investigate, correlate and respond at the pace required to stop attacks that evolve at machine speed. The gap between the time it takes to launch an attack and the time it takes to detect and contain it continues to widen.
Why traditional defences are falling behind
Many organisations still operate with fragmented tooling and limited visibility. Rapidly expanding attack surfaces, cloud growth and unsanctioned ‘shadow AI’ projects make it harder to maintain an accurate picture of risk. A third of security teams find it difficult to operationalise the intelligence they collect (ESG, 2025), while 42 per cent say their biggest challenge is monitoring a rapidly changing attack surface.
This operational pressure benefits attackers. They no longer need to outthink defenders; they only need to outrun them.
Moving towards proactive, predictive security
Defenders now need to adopt an operating model built for speed. That means transitioning from reactive investigation to proactive and predictive security. Automated attack-surface discovery, continuous exposure assessment and dynamic attack-path modelling are becoming essential. These approaches enable organisations to focus resources on the areas most likely to be targeted and to take action before an intrusion occurs.
In our work with European financial institutions, we have seen the impact of this shift. Automation and intelligent correlation have reduced mean time to detection by around 70 per cent and lowered false positives by 85 per cent. These improvements are not derived from larger teams or bigger budgets, but from embracing AI as a force multiplier.
Beyond generative AI: the rise of autonomous agents
Generative AI has helped streamline tasks like alert triage and report writing, but the next step is the adoption of fully autonomous agents. These agents operate continuously, collaborate across systems and initiate responses in milliseconds. They do not wait for prompts. They monitor, correlate and defend as part of an integrated security fabric.
By 2027, many security teams will rely on specialised agents for intelligence collection, analysis and rapid response. This represents a significant shift in how cyber operations will be structured in the coming years.
Guardrails, trust and the evolving role of humans
Greater autonomy does not eliminate the need for human oversight. Every action taken by an intelligent system must be auditable, explainable and aligned with organisational risk thresholds. The most effective operational model is one built around graduated autonomy, where AI initially handles low-risk or repetitive tasks and expands its remit as confidence grows.
For analysts, this transition is empowering. Instead of spending their days chasing alerts, they focus on strategic priorities: understanding adversary intent, shaping defensive posture and strengthening organisational resilience.
The new operating model for cybersecurity
The next stage of cyber defence will be defined by effective collaboration between humans and intelligent systems. Human creativity and judgement will combine with machine speed and precision. In our Intelligence Center deployments, this partnership has already proven its value. Analysts spend less time on manual research and more time guiding and validating autonomous processes.
AI is not only changing the nature of threats; it is changing the nature of time within cybersecurity. Detection, decision and defence are beginning to merge into a single, near-instant cycle. In this environment, success will not favour the biggest organisations or even the smartest ones. It will favour those that can act the fastest.
A new urgency
The speed gap is real, and it is widening. Security leaders now have a narrow window to redesign their operating models and adopt the autonomous capabilities that will define the next decade of cyber defence. Those who act now will be positioned to outrun the next generation of threats. Those who wait will simply be overtaken.
Sara Sullivan, SVP of Solution Engineering, explains how to avoid getting caught up in the ‘workslop economy’.
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Have you ever read a piece of work, suspected generative AI was involved, and thought the result felt… sloppy? The term “workslop”, used to describe low-quality, AI-generated content that lacks substance, has quickly entered the lexicon. Many teams are now navigating unnecessarily convoluted emails, low-context reports, inaccurate summaries and surface-level content, to name a few. But a bigger challenge emerges when this same low-quality AI-generated content is published externally. Over time, it erodes brand voice and creates a sea of sameness.
But the issue is that core content doesn’t necessarily mean better content. Generative AI has made production effortless, but without discipline and human creativity guiding it, scale can come at the expense of clarity and differentiation.
And this is more than just a quality-control problem. It’s often a signal that organisations are adopting AI tools faster than they are adapting the culture, governance and working practices around them. It’s not the technology itself, but how it is being operationalised. What’s often missing is a shared understanding of how AI should fit into everyday workflows and expectations.
A closer look at marketing
Marketing teams are on the front line of this shift. They’re under constant pressure to increase output, with more channels, more formats and more personalisation, so it’s no surprise AI adoption is accelerating here.
But without disciplined content architecture and governance, AI risks creating what some are calling a ‘workslop economy’; more output, but less value. Organisations also need shared norms around how AI-generated work should be questioned, refined and improved before it reaches customers or colleagues.
Teams want to move fast (40% of marketers say ‘fast and efficient execution’ defines success) while also delivering quality content (42% say it is ‘high content quality and consistency’). These stats from a global report conducted by Contentful and Atlantic Insights, also found that nearly half (48%) of marketers are looking to AI-powered content tools to help them find the middle ground.
The tension is understandable. Marketing has always been a function under pressure to do more with less and AI appears to offer a release valve, promising speed and scale.
As AI tools become faster and more capable, the value of human judgement, context and editorial discipline only increases. The ability to combine human creativity with AI-driven insights is becoming essential to producing and scaling ideas with measurable impact. The marketing skills that matter most today are data analysis and interpretation (46%) and digital experience design (40%), followed by personalisation strategy (37%) and writing for AI tools (37%).
This shift requires a reframing of what good work looks like. It is no longer about who can generate the most content the fastest, but who can apply judgement, context and relevance to ensure that every piece of output serves a clear strategic purpose. Otherwise, the risk is that teams become curators of AI-generated drafts rather than creators of differentiated ideas.
The organisational cost of ‘workslop’
Beyond marketing, the ‘workslop economy’ carries wider organisational implications. Leaders may assume productivity is increasing because there is more visible output. In reality, this is often a cultural signal. When organisations reward visible activity rather than thoughtful outcomes, AI simply amplifies the behaviour already present. Meanwhile, employees quietly absorb the hidden tax of reviewing, editing, clarifying and sense-checking AI-generated material, in addition to maintaining a new set of tools that require continuous inputs. If not managed thoughtfully, this can erode both efficiency and morale.
There is also a reputational risk. Sloppy AI-assisted content can introduce factual inaccuracies, generic phrasing, or inconsistent messaging that chips away at brand credibility. Customers and stakeholders may not always detect the use of AI, but they can detect when something feels off, such as language that’s overly verbose yet oddly vague, polished yet impersonal, confident yet lacking depth.
Crucially, the proliferation of ‘workslop’ can mask deeper strategic gaps. If teams rely on AI to fill in thinking that has not yet been done, the technology amplifies ambiguity rather than resolving it. In this sense, AI becomes a mirror, reflecting the clarity (or lack thereof) within an organisation’s strategy and decision-making processes.
Key steps to pivot away from the “workslop” trap
AI’s real enterprise advantage lies in both acceleration and augmentation. Structured content, clear operating models and strong data foundations are what separate meaningful transformation from short-term experimentation. To avoid the ‘workslop’ trap, organisations need to move beyond ad hoc usage and towards intentional operations.
First, establish clear content architecture. AI performs best when it operates within well-defined frameworks, which includes brand guidelines, tone-of-voice principles, audience personas and approved messaging pillars. Without this scaffolding, outputs will default to generic patterns drawn from the broadest possible training data. With it, AI can become a powerful assistant that reinforces, rather than dilutes, brand distinctiveness.
Second, embed human-in-the-loop workflows. Rather than relying on individuals to apply judgement inconsistently, organisations should design automated workflows that define exactly when and where human review is required. This ensures that AI-generated outputs are systematically validated before reaching customers or stakeholders, particularly for high-impact or high-risk content. Making human oversight a built-in step helps maintain quality at scale.
Third, implement auditability by default. Organisations need visibility into how AI is being used across the content lifecycle: who generated content, where AI was applied, what changes were made and who approved the final output. This level of transparency is critical for accountability, compliance and continuous improvement. It also enables senior leaders to move beyond assumptions and understand how AI is actually being operationalised across teams.
Fourth, invest in AI literacy, as well as AI tools. Employees need to understand how generative models work, where they are strong and where they are prone to hallucination. Training should focus on prompt design, critical evaluation of outputs and ethical considerations. Building literacy also builds confidence, allowing teams to challenge AI outputs rather than accept them at face value. When people feel confident challenging AI-generated suggestions, they are more likely to use the technology as a collaborator rather than a crutch.
Fifth, align incentives with impact. Incentives shape behaviour and behaviour ultimately shapes culture. If performance metrics reward speed and volume alone, ‘workslop’ will inevitably proliferate. Instead, organisations should measure success through outcomes such as engagement quality, customer relevance, strategic clarity and measurable business impact. This encourages teams to use AI selectively and thoughtfully, rather than indiscriminately.
Finally, organisations must be explicit about how AI is expected to reshape each role. More senior leaders, for instance, may need to spend more time critically evaluating AI-assisted outputs, while junior team members may take greater responsibility for drafting and iterating with these tools. Clearly defined, AI-related responsibilities help distribute accountability across the team and ensure that low-quality outputs do not slip through the cracks.
Reclaiming substance in an AI-boosted workplace
The rise of the ‘workslop economy’ is not inevitable, but it is a real risk if organisations conflate technological adoption with meaningful transformation. Ultimately, the organisations that benefit most from AI will be those that double down on the uniquely human strengths of good judgement, curiosity, creativity and contextual understanding.
They will treat AI as a partner that enhances thinking. And they will recognise that the true competitive advantage lies not in producing more content, but in producing better, clearer and more purposeful work.
James Lawrence, Insurance Specialist at Netcall and Paul Bermingham, CEO at Ecliptic, on why in today’s market, the holy trinity of service, efficiency and compliance isn’t a luxury. It’s a competitive advantage
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For years, the insurance industry has operated under a persistent myth: that you can deliver excellent customer service, achieve operational efficiency, or maintain rock-solid compliance – but not all three at once. This idea of an inevitable trade-off between competing priorities has shaped countless transformation strategies, often limiting progress and frustrating innovation.
It’s a myth rooted in the industry’s history. Insurance has long been a world of complexity – fragmented systems, legacy platforms, and regulatory demands that make even minor changes feel high-risk. As a result, when businesses talk about improving the customer experience, it often comes at the cost of back-office control. When they talk about driving efficiency, compliance is treated as a barrier. And when compliance leads the agenda, service and speed are typically sacrificed.
But that mindset no longer holds. Technology has evolved. The tools now exist not just to manage this tension, but to eliminate it. And for insurers willing to rethink how they approach transformation, the so-called “holy trinity” of service, efficiency, and governance is no longer out of reach – it’s entirely achievable.
The low-code shift
What’s changed is the rise of low-code platforms. These technologies allow insurers to build and evolve business-critical applications using visual development tools rather than traditional coding. Crucially, low-code doesn’t require ripping out existing systems. Instead, it enables insurers to layer new capabilities on top of their core infrastructure – adding intelligence, automation, and user-friendly interfaces without destabilising the foundations.
In practice, this means change can happen faster, at lower cost, and with less risk. Processes like first notification of loss (FNOL), for example, can be rebuilt around modern expectations: triaged instantly, validated in real time, and – for low-value, low-risk claims – automated to settlement. At the same time, audit trails are maintained, compliance rules are enforced by design, and customers are kept informed with timely, personalised updates. Service, efficiency, and governance – working together, not competing for attention.
Automation and AI: Turning governance into a competitive edge
The evolution of intelligent automation and agentic AI has opened up new possibilities for insurers – not just in streamlining operations, but in embedding trust and control into every digital decision. These systems are no longer limited to simple rule-based tasks. They can interpret data, make context-aware decisions, learn from interactions, and adapt over time. In complex environments like claims processing, delegated authority, and regulatory reporting, this level of intelligence has real operational value.
But the success of automation doesn’t hinge on speed alone. It depends on trust. In regulated sectors like insurance, automation must be auditable, transparent, and capable of upholding internal policies and external obligations. This is where low-code plays a crucial role. Rather than retrofitting governance onto a system after it’s built, these tools allow insurers to embed governance by design – integrating rules, audit trails, escalation logic, and data safeguards directly into the workflow.
This approach changes the dynamic. Governance is no longer a limiting factor or a compliance hurdle. It becomes a source of confidence. Teams know that AI-driven decisions are accountable. Regulators can trace every step. And customers receive outcomes that are fast, fair, and well-documented.
Low-code also makes it easier to align AI with real business needs. Instead of chasing innovation for its own sake, insurers can focus on solving specific challenges – like improving FNOL response times or reducing the risk of customer complaints – and use automation to enhance outcomes without compromising oversight. Because platforms are configurable, not hard-coded, insurers maintain flexibility as policies, risks, and regulatory expectations evolve.
In this context, governance isn’t the price of innovation – it’s the foundation. It ensures that transformation is not only fast and scalable, but sustainable and defensible. The result is a smarter, safer path forward – one where automation improves service, boosts efficiency, and strengthens compliance in equal measure.
Meeting customers where they are
That experience is more important than ever. Today’s policyholders aren’t comparing insurers only to each other – they’re comparing them to tech giants like Amazon, which set new standards for simplicity, speed and personalisation. Insurance doesn’t get a pass. Yet too many customers still face long response times, unclear communication channels and paper-heavy processes that feel stuck in another decade.
The right approach changes that. European insurance company, Baloise, for example, used a low-code platform to quadruple straight-through processing (STP) from 15% to 65%. This meant faster responses, reduced error rates and a better overall experience for both customers and teams. By processing over 11,000 documents a day with greater accuracy and speed, Baloise could resolve enquiries and claims faster, without adding operational burden.
The impact went beyond efficiency. Customers benefited from a smoother, more consistent service that felt faster and more seamless at every touchpoint. Internally, employees were freed from repetitive, manual tasks and empowered to develop broader skill sets and handle more diverse work. That flexibility made it easier to respond to demand and reduced reliance on siloed roles.
These kinds of results don’t come from massive system overhauls. They come from smart, focused improvements – starting with the moments that matter most to customers. Low-code allows insurers to build around those touchpoints, while keeping core systems intact and compliance fully in check.
From compromise to convergence
The key is integration – not just of systems, but of skills. Transformation efforts succeed when business leaders, consultants, and technology teams work together from the outset. Today’s automated process mapping tools allow organisations to automatically capture, visualise, and analyse real-time workflows – highlighting friction points, inefficiencies, and opportunities for simplification before taking action. This upfront clarity ensures insurers aren’t simply digitising legacy inefficiencies but reimagining how work gets done.
It’s this combination of smart technology and domain expertise that moves the needle from compromise into convergence. When transformation is designed with strategy, service, and compliance in mind – from day one – insurers can build experiences that work for everyone: customers who want speed, regulators who want rigour, and teams who want tools that actually help them do their jobs.
The truth is, the trade-off is a choice – and it’s no longer a necessary one. With the right approach, insurers can achieve all three pillars of the holy trinity. Service doesn’t have to come at the cost of efficiency. Governance doesn’t have to slow things down. And efficiency doesn’t have to mean cutting corners.
Setting a new standard
Insurers that understand this – and act on it – will lead the next chapter of the market. Not because they’ve chosen a side, but because they’ve built systems where no one has to lose. In a market that’s only getting more competitive, that’s not just good strategy – it’s business-critical.
It’s time to retire the idea that you can’t have it all. You can. And you must. Because in today’s market, the holy trinity of service, efficiency and compliance isn’t a luxury. It’s a competitive advantage.
Dr Abdulrahman Kerim, Computer Science Tutor at Superprof, on how AI will eventually take over time-consuming routine tasks, and will free educators up for supporting students, cultivating curiosity, and shaping meaningful learning experiences
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With education systems continuing to push for more efficient and personalised learning experiences, AI is proving to be a major factor and catalyst for achieving these goals. This year alone, 60% of educators said that they use AI to assist with their workload, a jump from around 48% in 2024.
Here are 5 key predictions of how AI is set to reshape the classroom, the evolving role of tutors, and the overall student educational journey in 2026.
Personalised learning will replace one-size-fits-all classrooms
Despite the progress made when it comes to the adoption of AI, classrooms still rely on fixed reading levels, static worksheets, and uniform methodologies that fail to reflect the diverse backgrounds of students, their interests, strong points, and even goals for the future.
However, in 2026, we’re expecting to see this gap starting to close. AI systems will begin to assist with drawing student data, including assessment results and learning objectives, to automatically update and adapt course materials in real time. This means that students will receive an education that matches their level, and that’s aligned with their goals. This new process will certainly not get rid of human tutors who will still be vital to the learning process. However, their role will become of a more strategic nature where, instead of content creators, they will become learning experience designers, guiding and refining a student’s personalised learning journey.
Immediate, insight driven, grading and feedback
As of this year, manual grading still dominates the educational system. Tutors still spend hours reviewing assignments, and students wait for weeks for feedback. This process certainly delays and weakens the learning process overall.
Next year, we will see a higher rate of adopting the AI-powered grading and feedback systems, which will contribute dramatically to the process. The tools will have the ability to evaluate submissions within minutes, highlight errors, shed light on common patterns of misunderstanding, and provide tailored recommendations of improvement. The result of this will be more consistent and efficient grading, and deeper insights that will guide both students and educators alike.
Around the clock student support
Student support teams continue to be thinly stretched, resulting in long waits for answers to academic or administrative questions. This does not only cause frustration, but also results in missing deadlines a lot of the time.
In 2026, AI chatbots will become more intelligent, responsive, and deeply embedded across educational platforms. These systems will provide immediate support, during or after hours, answering academic queries, clarifying assignments requirements, guiding students through enrolment processes, and reminding them of deadlines and outstanding tasks. The AI chatbot will enhance the FAQ responses with their ability to understand context, and personalise guidance accordingly. This will enhance both engagement and retention.
Clear, consistent, and scalable assessment of soft skills
Soft skills such as leadership, communication, and problem solving remain very hard to measure accurately. This measurement still relies on manual observation, which is often subjective, inconsistent, and nearly impossible to scale.
In 2026, however, AI is set to start cracking the code of these competencies. By analysing group interactions, patterns of students participation, communications dynamics, and even study behaviours, AI tools will generate concise, data-driven insights in students’ performance and progress. Tutors will greatly benefit from this feature by receiving detailed summaries of strengths, and gaps, allowing them to design a more targeted and achievable approach to support.
Rapid and customisable curriculum design
Similar to some of the key things discussed in this article, curriculum design still remains fairly slow and fragmented, with learners looking to move into new fields often struggling to find coherent and updated learning pathways.
In the next year, AI will significantly accelerate curriculum development. The systems will be capable of identifying gaps, recommending learning methodologies, align content with standards, and even generate fully customised learning plans. The tools will be informed by large scale data on how thousands of similar learners have progressed in their subjects, the challenges they faced, the resources that helped them navigate those challenges, and the skills that are highly in demand.
In conclusion, AI is set to dramatically change the way people both teach and learn. However, this certainly does not mean it will replace educators. Instead, it will empower them. AI will eventually take over time-consuming routine tasks, and will free educators up for supporting students, cultivating curiosity, and shaping meaningful learning experiences.
Matthew Biboud-Lubeck, General Manager EMEA at Amperity, on finding the key to creating meaningful engagements that build brand loyalty, drive up the lifetime value of a customer and, ultimately, give businesses the competitive edge
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It’s no secret that personalisation is vital for building lasting customer relationships and nurturing brand loyalty. AI holds the key to creating and delivering successful personalised engagement. And travel and airline businesses are keen to adopt this technology in their customer-facing applications.
The reality, however, is that few are currently able to scale AI across their organisation. According to industry research, published in Amperity’s 2025 State of AI for Hotels & Airlines, AI adoption is widespread across the sector, but applications remain experimental. Just 12.5% of companies say they are ready to scale their use cases.
The challenge isn’t ambition. Nearly all (96%) businesses in the sector are planning to maintain or increase AI spending over the next 12 months. The problem lies in two major barriers that prevent AI from scaling effectively. A lack of technical expertise within teams. And low confidence in the data that AI tools rely upon, due to fragmented or unreliable customer information.
How to reduce reliance on technical teams
Keeping pace with rising consumer expectations means tailoring customer engagement and presenting meaningful, real-time offers based on individual preferences. Although travel businesses know that AI is going to help them achieve this true personalisation, at scale, only 35% currently use AI in guest experiences.
One reason for this is the inability of non-technical teams to independently access data they need, and act on the information provided. AI usage among travel and airline brands remains concentrated in marketing, customer support and sales. But less than a third of professionals in these teams say they can manage customer data without the support of their IT department. This is delaying, and in many cases denying, teams the ability to tailor customer communications.
What teams need are intuitive tools, empowered by GenAI, that simplify the process of accessing customer insight. These platforms allow non-technical people to ask questions using natural language. And discover such things as: what their most valuable customers purchase most often, what form of content they are most likely to engage with and on which channels they are doing this.
AI training is still an important consideration for all business users, who need to understand how AI can add value, where its limitations lie and what safeguards should be put in place to ensure responsible use. But these GenAI capabilities are now helping teams to access crucial intelligence quickly and apply this to customer engagements at scale.
How to build confidence in customer data
Accessing data is one thing, but having confidence in that information is another. This is an area where travel companies struggle. Less than a quarter claim to be very confident in their ability to understand and act on customer data.
This is often because data is separated and siloed across different systems and channels. More than half of businesses (58%) report that their customer data is fragmented or incomplete. This can impair visibility, lead to inaccurate reporting and increase the risk of human error, while also adding IT costs. It also increases the chances that duplicate customer profiles will be created across those different channels.
Consumers commonly engage with travel brands across several touch points including email, mobile, apps and in-store. They will also use various identifiers, such as abbreviated names, alternative email addresses, etc., when they do so. Companies need to deploy AI tools that can unify this data and stitch together information coming from different channels. If they don’t, there is the real possibility that they will end up sending conflicting or irrelevant communications to the same person. The consequences of this can be damaging as it risks annoying and alienating customers.
Building a solid customer data foundation
To enable fast and accurate omnichannel communications, it’s vital for companies to have a customer data platform (CDP) that is enabled by identity resolution. To build high levels of confidence in the operational identities required for personalisation and broader marketing audience targeting, companies will need to blend deterministic and probabilistic matching strategies.
The research shows, however, that just 18% of travel businesses have this identity resolution technology in place. This is preventing companies from accurately viewing booking histories, identifying behaviour patterns and unlocking the potential of AI for the tailored engagements necessary for building brand loyalty and increasing the lifetime value of a customer.
The evidence shows that organisations with a CDP are much better placed to ensure customer data is ready for use in marketing or analytics. The latest generation of CDPs will automatically consolidate data across various communication channels, detect and resolve identity issues. And provide travel businesses with a true, 360 degree profile of each customer, based on all interactions across each channel.
These platforms are also enabling businesses to advance their AI deployments. More than half (54%) of businesses with a CDP report daily use of AI – this compares to 28% for those without. Half of CDP-enabled businesses use AI in guest-facing deployments, compared to less than a fifth (19%) of those without. Businesses are also five times more likely to have adopted AI across business units, when they have a CDP.
Preparing for an Agentic AI era
Next generation CDPs are also helping companies prepare for another major trend reshaping customer data management – the rise of agentic AI. Agents are already capable of observing behaviour, interpreting what it means and taking action autonomously.
For example, imagine a situation where a flight has been delayed or cancelled. In this scenario, a combination of agents can now work together to provide customers with a solution. In an instant, one can spot the problem, another will find alternate solutions, while a third will send the best options to the customer. The customer doesn’t need to wait – they simply receive a notification in real-time. Some human orchestration is still required and guardrails are important to ensure communications hit the mark. Most important to note, however, is that it only works if those agents have access to accurate data.
The travel sector is clearly at an inflection point on its road to full AI adoption. It’s moving from pilot projects and early stage experimentations to broader deployments and scaled execution. Success in customer facing applications, however, will depend on an organisation’s ability to provide non-technical teams with access to high quality, unified customer profiles.
Modern CDPs help businesses to make faster, smarter decisions that will help to drive growth. With these solid data foundations in place, businesses can deploy and scale AI-enabled customer facing applications more readily. This is the key to creating meaningful engagements that build brand loyalty, drive up the lifetime value of a customer and, ultimately, give businesses the competitive edge.
Peter Pugh-Jones, EMEA Field CDO at Confluent, explains why as more AI projects move into production, that gap will become harder to ignore. The conversation will shift away from what AI could do and towards what organisations are actually able to support in practice
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AI is no longer an experiment in financial services. It’s already embedded in day-to-day operations.
Banks are rolling out AI-driven customer service, investing in automation, and exploring how generative and agentic systems can improve decision-making. Around 92% of global banks are already using AI in at least one core function, which suggests the industry is well on its way.
As these initiatives scale, however, a different reality starts to emerge.
What works in a pilot often becomes more complex, not to mention expensive, when rolled out across the business. In many cases, the issue is not the AI itself, but the environment it is being deployed into.
There is no ‘magic bullet’ for AI in financial services. Its impact is shaped by how well organisations can access, connect, and act on their data — increasingly through real-time approaches such as data streaming.
When AI meets reality
This is particularly visible in customer service.
AI-powered chatbots and virtual assistants are now widely used to handle routine queries, categorise transactions, and guide users through basic processes, and in the right conditions they can deliver real efficiency gains.
Scaling those systems, however, is a different challenge altogether. Despite the level of investment, many of these systems continue to rely on fragmented or outdated information, which sees the experience quickly starts to break down.
For example, customer context can be missing or inconsistent. Conversations don’t carry across channels. Employees are forced to double-check or correct outputs, removing much of the efficiency they were meant to deliver.
In a sector where trust matters, that’s difficult to ignore.
Legacy systems are still doing most of the damage
Frameworks like the EU AI Act are shaping how organisations deploy AI, particularly in high-impact use cases such as credit scoring, fraud detection, and customer risk assessment. Requirements around transparency, auditability, and data governance are raising the bar for how AI systems are built and monitored. And rightly so, given the importance of trust in financial services.
In practice, though, legacy infrastructure is often the bigger issue. When data is fragmented across systems or difficult to access in real time, it becomes far harder to evidence how decisions are made or ensure models are operating on complete, up-to-date information.
In many cases, it is these underlying data limitations — rather than regulation itself — that slow progress. With many banks reliant on systems built up over decades through mergers, upgrades, and workarounds, they struggle to create a single, reliable view of a customer or transaction — something AI depends on.
This also helps explain how FinTech startups can outmaneuver industry giants. Free of technical or technological baggage, they can build around modern data architectures from the start and bring new ideas to market more quickly.
AI can’t reach its potential, or in some cases even run, in a legacy environment. Sticking with the customer service example, one such example is personalisation.
Personalisation only works if the data is current
Personalisation has been a goal in financial services for years, but in many cases it has been closer to segmentation than true individualisation. If AI is going to change that, it needs a flow of data that can tell it exactly what’s happening in the moment.
Hyper-personalised experiences depend on real-time context — understanding a customer’s behaviour and situation as it evolves, often enabled by data streaming to ensure systems are working from the most up-to-date information. Without that, interactions quickly become disconnected.
A customer might start a query in an app, follow up by email, and then call support, only to repeat the same information each time. This is not a limitation of AI, but of how information moves between systems.
When that flow is in place, interactions become far more seamless, with context carrying across channels and experiences feeling more consistent.
AI should support people, not replace them
There is a lot of discussion about AI replacing human roles in financial services, but a fully automated model is unlikely.
AI is highly effective at handling repetitive, high-volume tasks, like triaging customer queries or processing transactions. But more complex interactions still require human judgement, empathy, and context — particularly in areas such as lending, investments, or financial advice.
Customer expectations also play a role. While digital channels continue to grow, many customers still value the option to speak to a person, particularly in more sensitive or high-stakes situations.
As a result, the most effective model is increasingly a hybrid one. AI handles routine processes and surfaces insights, while people focus on more complex and sensitive interactions — provided both are working from the same reliable, up-to-date information.
Early investment has focused on what AI can do. Attention is now turning to what is needed to make it work properly.
That starts with data. Organisations need to ensure data is connected, governed, and available when it is needed. Too often, this work is treated as something to address later, when in practice delaying it tends to create more complexity and cost over time.
There is also a cultural element to consider. In many organisations, established ways of working can slow progress just as much as technology. Addressing that is just as important as modernising systems, particularly when AI initiatives span multiple teams.
A question of readiness
Financial services organisations are being asked to move quickly while maintaining high levels of control and accountability. That is not easy.
The organisations that make progress will be those that focus less on AI as a standalone capability and more on the conditions that allow it to work. If those conditions are not in place, results will remain inconsistent.
As more AI projects move into production, that gap will become harder to ignore. The conversation will shift away from what AI could do and towards what organisations are actually able to support in practice.
In most cases, it comes down to a simple question: is the data ready?
Frank Jaquez, Head of Talent & Culture at Skillsoft, on why an AI skills strategy built without skills visibility is not just incomplete; it is fundamentally blind
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Organisations are accelerating their adoption of AI, with 33% of UK businesses planning investment and training in 2026. As investment rises and competitive pressure mounts, leaders increasingly recognise that AI capability will distinguish high-growth performers from the rest. Yet a key question remains unanswered: are workforces equipped with the skills to use AI effectively and productively?
Without clear skills visibility – a transparent picture of required skills & capabilities, existing strengths, emerging gaps and role-specific proficiency – AI strategies rest on assumptions rather than evidence. Leaders are forced to guess who can adapt, which teams need development and whether to prioritise upskilling, reskilling or the deployment of AI agents.
Too often, organisations launch AI initiatives without understanding whether their employees can use these tools effectively. Or translate them into measurable outcomes. The result is predictable: pilots lose momentum, adoption slows, and ROI remains uncertain. When organisations lack skills visibility, decisions around investment, talent and transformation become guesswork. And guesswork is no foundation for a successful AI strategy.
Why skills visibility must come first
The foundation of any effective AI strategy is a clear view of workforce capabilities. Understanding what employees can do today, identifying the skills they will need tomorrow, and how those capabilities align to business goals. It also requires clarity on what AI can currently deliver and the new capabilities it introduces into the organisation. When skills are measurable and tied directly to real tasks, organisations can move decisively from experimentation to execution.
However, this clarity cannot be achieved through learning content alone. High-quality learning is essential, but when it sits apart from roles, skills and outcomes, it cannot provide the clarity, validation or evidence of proficiency that leaders now require. Completing training does not automatically translate into performance, confidence or capability.
The scale of this challenge is reflected in recent data. Nearly a third of UK employers lack a clear view of the skills their workforce will need in the next two to three years. Whilst 60% identify workforce planning as a critical or high priority, only 25% base their approach on skills. This gap highlights a growing disconnect. Between the urgency of AI adoption and the visibility organisations have into the workforce capabilities required to sustain it.
Building a connected ecosystem
To achieve genuine visibility, organisations need to start by identifying the critical skills required to deliver their strategy, and then integrate skills mapping, assessment, development and measurement into a single, connected system. When these elements operate within one environment, leaders gain a consistent, evidence-based view of workforce capability. This highlights areas of risk and readiness as priorities shift.
Skills-aligned learning pathways ensure development efforts directly build the capabilities that matter most. When those skills are connected to clear, strategic goals, employees understand how their development ties to business priorities. Clear milestones and measurable indicators give leaders confidence that learning is translating into real-world performance where it is needed most.
AI-powered learning is becoming central to this approach. By analysing skills data, identifying gaps in real time and recommending targeted development aligned to roles and organisational priorities, AI enables a dynamic, continuous ‘skills supply chain’. Instead of relying on infrequent skills audits, organisations benefit from an adaptive system that evolves alongside the business.
This model supports skill development at scale. It educes reliance on costly external hiring,. This helps organisations to unlock business results by developing and redeploying existing talent through more strategic upskilling and reskilling.
Linking skills to business priorities
Skills visibility is most powerful when it is tightly linked to organisational priorities. When leaders understand which skills matter most and how their workforce measures against them, they can make informed decisions about where to invest and how to focus development.
This alignment enables organisations to build capabilities that will drive the biggest impact, accelerate AI adoption through capability-led learning pathways, prioritise roles critical to future growth and track workforce readiness with confidence.
A connected skills supply chain ensures these insights continuously inform both development and execution, creating a workforce that is responsive, targeted and future ready.
AI transformation depends on skills visibility
Technology may enable AI transformation, but people determine whether it drives meaningful results. Without a transparent understanding of workforce capability, even the most ambitious AI strategy risks becoming costly and ineffective. Skills visibility is the differentiator between organisations that keep pace with AI and those that lead.
Organisations that invest in understanding their people, their current capabilities, their growth potential and how their skills align to business needs will be best positioned to unlock AI’s full value. A strategy built without skills visibility is not just incomplete; it is fundamentally blind.
First United Bank: Combining Community Banking Values with Modern Technology
Executive Vice President and transformation leader Tadd Tobkin reveals the evolution of community banking helping First United Bank customers ‘Spend Life Wisely’.
“Our goal is not to become a technology company that happens to be a bank. It is to become a great community bank with the modern capabilities required to serve people for generations…”
NBME: Embracing Decisive Leadership and Human-Led Technology
Andy Farella, CIO of the National Board of Medical Examiners (NBME), talkshuman-centred leadership and how the organisation is leveraging technology for its betterment. “We’ll always have appropriate humans in the loop – they’ll just be leveraging AI in thoughtful ways.”
Ultra Clean Technology: Back-to-Basics Cybersecurity in an Advanced World
Mandy Huth, CISO of Ultra Clean Technology, believes in embracing a back-to-basics approach to cybersecurity because cyber-attacks are a case of ‘not if, but when’. “I love that security is ever-evolving and ever-changing… Every decision my team makes should be to help UCT win, because that’s how we all win.”
The EBRD: Building Global Technology Foundations for the Future
Our cover story revisits the work of Chief Information Officer Subhash Chandra Jose. He reveals the strategy, leadership and continued purpose at the heart of a digital transformation across The European Bank for Reconstruction and Development (EBRD) global network. Under his leadership the digital journey has become as much about culture and collaboration as it is about cloud, artificial intelligence and cybersecurity.
“We have made a lot of advancements on AI and cloud and all the greatest and latest technologies. But we mustn’t forget what actually makes the technology experience on the ground. It’s about network and connectivity.”
BSP: Securing the Future of Digital Banking for Fiji
By placing customers, community and practical innovation ahead of technology for its own sake, BSP is building a digital banking platform designed for long-term growth. CIO Omid Saberi explains how sixteen years of transformation have helped create the technological foundations for Fiji’s largest corporate bank while preparing customers for an increasingly digital future.
“Corporate banking is where you change a country because you’re enabling businesses to grow.”
OSB Group: Building the FinTech Foundations for Faster, Safer Growth
For Debra Bailey, Chief Information Officer at OSB Group, working on technology transformation with Publicis Sapient is not about chasing the latest innovation. It is focused on outcomes: giving colleagues better tools, helping brokers move faster, improving customer journeys and creating the operating model needed for sustainable growth.
“Publicis Sapient architected this overall proposed platform and the FinTechs that we work with. It’s a very logical and open architecture.”
Publicis Sapient: AI Belongs in the Engine room, Not Just the Front Office
Following the launch of its Core Modernisation Playbook, Publicis Sapient‘s Dave Murphy, Head of Financial Services- EMEA & APAC, explores why so many banks struggle to modernise despite investing heavily in AI. The challenge is no longer knowing what to transform, but how to execute transformation safely.
“The banks that move first will not simply modernise faster. They will build the AI-ready foundations that determine how quickly every future innovation can be delivered.”
Get your copy of the latest White Paper from Publicis Sapient here
Also in this issue, we learn from Expereo why network resilience must be front of mind to drive digital transformation and TDK Ventures offer a solution to AI’s power problem. And check our events guide with all the key dates for your diary for global networking opportunities at the latest tech conferences across the globe this autumn.
Simon Ritter, Deputy CTO at Azul, on how the Java ecosystem is adapting (quickly) to the needs of AI applications
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If you ask most people in IT which programming language is most commonly used for AI applications, they’ll almost all answer Python. Which raises the obvious questions: why, and why not Java instead?
Python is actually older than Java by over 4 years, so its AI popularity is not because it is newer than other alternatives. Python’s origins have nothing to do with AI (or even numerically intensive applications). It was originally developed as a high-level scripting language for writing system utilities and applications on the Amoeba distributed operating system (which I doubt most people have even heard of). Python is also a poor choice for numerically intensive operations, which is a lot of what AI and LLMs need to do.
The real reason for Python’s popularity is that the mathematicians working on AI found it easy to learn. It could serve as a simple interface to high-performance computing libraries, typically written in complex low-level languages such as C and C++. This initial popularity led to many industry-standard frameworks, such as PyTorch and TensorFlow, being written in Python.
Does this mean Java has no place in AI?
Far from it, as was demonstrated recently by Azul’s AI4J online conference. This brought together nine AI proponents, most of whom are Java Champions, to present various ways Java can be used in this area.
The general theme that came across was that “Java owns the enterprise data”. Given Java’s enduring popularity for server-side applications, this is a statement that’s hard to dispute. This underscores the importance of Java when considering Retrieval Augmented Generation (RAG). Training an LLM uses a wide array of data and can deliver a model that is easy to communicate with in natural language. To change this from being smart to helpful (another quote from the conference), you need to access enterprise data in real time. The most valuable data for an organisation is contained in systems like those for ERP and CRM, as well as a plethora of databases. Most of that data is managed by Java-based applications.
What we end up with is the usual layered IT architecture, each layer providing an abstraction of the one below it. As was explained in one session, the LLM sits at the bottom, with vector search (or naïve RAG) above that and Graph RAG above that.
Java delivers powerful technologies
Java can deliver powerful technologies that fit well into this critical space. Instead of searching flat text files, a RAG system can use tools like Neo4j and Cyrock.AI to model complex relationships among concepts, people, and documents. This allows the AI to fetch deep, interconnected context that standard vector databases might miss. Enterprise Java application platforms like Jakarta EE and Spring are rapidly adapting to the needs of AI systems; Josh Long of Pivotal and James Ward of Amazon provided details of how Spring and AWS Bedrock can be used in this way.
Another significant takeaway from the AI4J sessions was the use of predictive, or analytical AI rather than the high-profile generative AI (or GenAI). One session quoted a report from Deloitte on the State of AI that said that “30% of GenAI projects will be abandoned due to a lack of clear business value”. Predictive AI has many benefits for an enterprise, not least of which is its deterministic quality. This means it does not hallucinate (which you really don’t want when making mission-critical, enterprise-wide decisions).
AI with context
Context for AI was another recurring theme in these sessions. Better coordination of input to an LLM-based AI system is critical to success. Providing that bridge from smart to helpful is what enterprise users need the most.
This, in turn, led to the conclusion that one of the most important aspects of any AI system is performance. In its over thirty-year history, Java has gone from a platform teased for being slow to one that, using techniques like just-in-time (JIT) compilation, can even outperform native C and C++ code.
The AI4J sessions discussed a number of ways that Java delivers optimum performance:
Project Panama for easier Java integration with lower-level C++ frameworks such as CUDA and ONNX Runtime.
Virtual threads, capable of delivering massively greater scalability for applications that spend a lot of time blocking, which is what AI applications do as they wait for tokens to be processed.
Project Babylon, which is exploring ways to target specific hardware architectures at runtime. Moving beyond JIT, this allows code to be targeted at GPUs or even FPGAs as and when necessary.
Azul’s Prime JVM that delivers lower latency and higher throughput through different garbage collection (GC) and JIT implementations. All whilst maintaining full adherence to the Java SE specification, making it a drop-in replacement for other JVMs. No code changes or recompilations required.
Overall, the AI4J conference provided a fascinating insight into how the Java ecosystem is adapting (quickly) to the needs of AI applications.
About Simon Ritter
Simon has been in the IT business since 1984 and holds a Bachelor of Science degree in Physics from Brunel University in the UK. Simon joined Sun Microsystems in 1996 and started working with Java technology from JDK 1.0; he has spent time working in both Java development and consultancy. Having moved to Oracle as part of the Sun acquisition, he managed the Java Evangelism team for the core Java platform. Now at Azul, he continues to help people understand Java as well as Azul’s JVM technologies and products. Simon has twice been awarded Java Rockstar status at JavaOne and is a Java Champion. He represents Azul on the Java SE Expert Group, OpenJDK Vulnerability Group and Adoptium Steering Committee. He is also the author of OpenJDK Migration for Dummies.
About Azul
Azul is the trusted leader in enterprise Java for today’s AI and cloud-first world. Its open source-based Java platform empowers organizations to optimize the entire Java lifecycle to accelerate performance, strengthen security, reduce licensing and cloud costs, and boost developer productivity. Azul powers mission-critical systems for 36% of the Fortune 100, 50% of the Forbes Top Ten World’s Most Valuable Brands, and the world’s top 10 financial trading companies. Learn more at azul.com and follow @azulsystems.
Jeevithan Muttu, GM & SVP – Device Management at Motive, on why the operators that combine network intelligence, device awareness and entitlement orchestration into a unified, real-time control framework will be positioned to capture the opportunities these network capabilities create
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Networks today generate volumes of data never seen before. From broadband home Wi-Fi performance to IoT deployments and smart meters, battery health and application usage patterns, communications service providers (CSPs) now have unprecedented visibility into how their networks and connected devices are being used.
For many operators, valuable intelligence remains confined to dashboards and analytics platforms rather than shaping live service decisions. Turning network data into sustainable revenue calls for more than insight; it requires the ability to act instantly at the device and entitlement layer.
What’s clear is that access to information is no longer the constraint. The real constraint is execution, and the shift from understanding to action will define the next phase of telecoms monetisation.
From network data to commercial action
Over the past decade, CSPs have invested heavily in 5G, edge computing and advanced analytics. These investments have significantly increased network capability, yet monetisation has not progressed at the same pace.
The reason is structural. Networks can detect patterns, predict demand and analyse performance. However, unless that intelligence can be translated into immediate policy enforcement, defining who receives which service, under what conditions, and on which device, revenue opportunities remain theoretical.
Real-time device intelligence bridges this gap.
When operators can evaluate device capabilities, subscriber entitlements, and current network conditions simultaneously, they can execute services dynamically rather than statically.
Instead of analysing congestion after it affects customers, they can prioritise traffic in the moment. Instead of offering rigid plans, they can introduce usage-aware tiers, temporary performance boosts or device-specific service enhancements.
This is not about generating more telemetry. It is about operationalising the intelligence already available. Device intelligence is also used for effective root cause analysis in near real-time.
Turning network capabilities into revenue
Many of the capabilities required to unlock new revenue streams already exist within today’s networks. However, the ability to monetise them depends on translating network intelligence into real-time delivery.
5G network slicing enables guaranteed performance for enterprise workloads or premium consumer tiers. Edge analytics can identify latency-sensitive applications or location-specific congestion patterns. Open Gateway APIs, standardised by CAMARA, allow operators to expose network capabilities, such as quality-on-demand, device verification, and secure authentication, to third-party ecosystems.
Yet, none of these capabilities generates revenue without real-time entitlement validation and enforcement. Whether delivering a performance guaranteed SLA or temporary service upgrades, operators must be able to provision and enforce those entitlements instantly across the network, device and billing environments.
Real-time device intelligence enables:
On-demand service upgrades
Premium quality-of-service tiers
Dynamic network slicing monetisation
Usage-based or event-based pricing models
Device lifecycle management as a managed service
Secure and scalable exposure of network APIs
In each case, the differentiator is not simply the network technology. It is the orchestration layer that determines whether services can be delivered securely, consistently and at scale.
Improving service quality and reducing churn
Monetisation and customer experience are increasingly inseparable.
Subscribers expect activation, onboarding and service changes to work immediately. They expect transparency into what they are entitled to access. Even minor friction, such as failed provisioning, inconsistent access to features, or delayed upgrades, can undermine trust and increase churn.
By aligning device intelligence with real-time entitlement control, CSPs can:
Reduce activation and provisioning failures
Ensure consistent feature enablement across multiple devices
Automatically adapt services based on network conditions
Proactively manage performance before issues escalate
Minimise support calls and operational costs
For example, when an enterprise application requests a temporary upgrade via Quality-on-Demand APIs, entitlement systems can dynamically apply a gold-tiered service profile to the subscriber. Similarly, when edge analytics detect sustained congestion in a particular cell, automated policy adjustments can prioritise premium traffic to preserve the quality of experience for enterprise customers
This capability shifts operators from reactive remediation to proactive assurance, directly improving both service quality and commercial resilience.
Enabling the API economy securely
As operators participate in initiatives such as the GSMA Open Gateway APIs, exposing standardized network APIs to developers and enterprise partners, control becomes even more critical.
APIs unlock monetisation potential. Entitlement ensures that potential is realised securely.
SIM-based silent authentication, quality-on-demand and device-status APIs all rely on real-time validation. Without a robust entitlement and device management framework, operators risk inconsistent execution, revenue leakage or increased exposure to fraud.
Edge analytics may surface opportunities for contextual offers or performance guarantees. However, unless analytics outputs are directly integrated with policy enforcement mechanisms, they remain advisory rather than actionable.
Connecting data insight to automated control is what transforms network intelligence into billable services.
Unlocking innovation on top of legacy systems
There is a common perception that enabling these new revenue models requires wholesale replacement of legacy OSS/BSS systems. In reality, operators can achieve this by modernising the control layer while integrating with existing infrastructure.
A real-time entitlement and device management platform can sit between network functions, OSS/BSS systems and device ecosystems, acting as the policy decision and enforcement point.
By taking this approach, CSPs gain the ability to launch new commercial models without extensive rearchitecture, stay aligned with evolving GSMA standards and OEM requirements, maintain compliance across multiple markets, reduce engineering overhead and accelerate time to market.
Turning intelligence into action
The telecoms industry has already made substantial infrastructure investments. 5G is deployed. Edge computing is expanding. Device ecosystems are evolving rapidly. Data volumes continue to grow.
Digital-native connectivity providers can introduce new offers in a matter of days. Enterprise customers increasingly expect on-demand, configurable services. Developers engaging with network APIs demand predictable, automated access to capabilities.
However, only the operators that combine network intelligence, device awareness and entitlement orchestration into a unified, real-time control framework will be positioned to capture the opportunities these network capabilities create. Those that continue to treat entitlement and device management as background utilities risk remaining infrastructure providers in a market increasingly defined by service agility. The opportunity to unlock new revenue models is already embedded within today’s networks. The differentiator will not be who collects the most data, but who can convert intelligence into action first
Oz Nicco-Annan, CFO at InfraPartners – the prefabricated data centre solutions specialist – on why developers should align deployment with evolving demand, while also adapting flexibly to keep pace with AI
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Behind the excitement of AI infrastructure, from hyperscale data centres to GPU compute mega-campuses, lies a growing concern. While long-term demand for AI is widely expected to grow, the shape and timing of that demand is still taking form. The market is shaped by rapid chip cycles, fluctuating pricing and shifting workload demands, and the old ‘build it and they will come’ approach has resurfaced. Only now, the stakes are far higher and there is an expectation to get more certain on when ‘they will come’.
Financial analysts are beginning to flag the tension between rapid AI infrastructure expansion and the pace at which demand is materialising. Some reports suggest AI infrastructure spend is outpacing realistic demand projections, and there is an increasing focus on how quickly demand can convert into committed, revenue-generating workloads.
Yet projections do point to strong long-term growth. While questions are emerging about who bears the risk if utilisation levels fall short, the answer is not to halt or slow the development of vital infrastructure. Instead, utilising more flexible and phased deployment models will enable operators to better align capacity with usage and meet AI ambitions. Therefore, infrastructure can be deployed, adapted and expanded in line with realistic, evolving workload requirements.
The demand complexities
There is a widely held assumption that demand for AI compute will be effectively unlimited. That if capacity is built, it will inevitably be used. This assumption is likely because projections point to sustained growth in training and inference workloads, with data centre capacity demand expected to grow by around 20–25% annually through 2030.
In reality, AI demand is complex and still evolving. Enterprise adoption remains uneven, many organisations are still in pilot (or experimentation phases) and not all workloads require large-scale, always-on infrastructure. Recent research shows that only around 20% of companies have scaled AI capabilities across their organisations, highlighting the gap between investment and real, sustained usage. At the same time, AI interest is undeniably accelerating, driven by rapid advances in generative models and increasing enterprise confidence. Most importantly, there is clear risk of over-cautious investment that could leave markets underprepared and unable to keep pace with national and commercial AI ambitions.
Speed versus commercial discipline
Historically, large data centre developments were underpinned by long-term agreements with hyperscalers or enterprise tenants before construction began. These commitments provided a clear route to secure revenue, reducing exposure to market volatility. Across the last few years, however, projects are increasingly moving forward while long-term customer commitments and workload requirements are still taking shape.
This shift in commercial models is partly driven by the speed of the market. The pressure to deliver capacity quickly has intensified, particularly as new entrants such as GPU-as-a-service providers compete alongside established hyperscalers. In this fast-paced environment, the ability to deploy infrastructure rapidly can outweigh the discipline of securing customers in advance. But this comes with risk that needs addressing.
Without committed users, developers are exposed to two key challenges. First, the utilisation risk; the possibility that capacity cannot be filled. Yet this is only likely if the facility is designed around specific architectures or hardware configurations that do not align with actual customer requirements. Where data centres were once built to operate for 10 to 15 years with minimal change, operators are now dealing with hardware refresh cycles closer to three to five years. The right technology for today’s infrastructure may not be fit for tomorrow.
The second challenge is slower-than-expected customer adoption. Capacity may ultimately be utilised, but not at the pace required to support the investment case. This issue can extend timelines, delaying revenue generation and placing pressure on project economics. Delayed customer adoption, whether due to economic conditions, regulatory constraints or shifts in AI development priorities, can leave newly built facilities underutilised for extended periods.
Rethinking deployment models
How does the industry respond to these risks? In short, we must rethink how infrastructure gets deployed. Instead of committing to large, monolithic builds, there is a growing case for more upgradeable and phased approaches. Upgradeable data centres, built offsite with advanced manufacturing processes, allow operators to align capacity deployment more closely with confirmed demand. This technique reduces the risk of overbuilding; organisations can start small and add capacity as required, rather than building for a future that may not play out in the way expected. Delayed customer adoption suddenly becomes less of a concern. Critically, upgrades can also be performed while the rest of the site remains operational, avoiding prolonged downtime and revenue loss.
As AI hardware evolves with increasing power densities and shifting cooling requirements, this upgradability also allows infrastructure to adapt and remain relevant as technology changes unfold. AI is evolving much too fast for rigid designs and, instead, flexibility should be built in to ensure this infrastructure can cater for the needs of tomorrow. In other words, we should be manufacturing building blocks that have the capability to evolve and scale, therefore reducing risk around utilisation. Rather than designing and building an AI factory that works only for the hardware we know, developers should be looking at power and structural systems that can scale to higher densities, or support a transition to new cooling methods, without the need for a full re-build or retro fit.
From a financial perspective, this level of upgradability means the model can shift from large upfront capital commitments towards more incremental investment. Developers can then scale in line with both technological developments and customer demand.
Demand-led infrastructure
How effectively capacity is matched to real, sustained demand will be crucial in the coming years. The risk of building without guaranteed users is not new, but the scale at which it is now occurring is. The industry must quickly learn the art of balancing speed with discipline.
Developers should align deployment with evolving demand, while also adapting flexibly. Understanding who is committed to using these facilities is critical to determining the sustainability of the AI boom. But it’s also key that we design facilities not just for today’s technology, but for tomorrow’s unknowns, ensuring they can evolve at the same pace as AI itself.
Chris Wallis, Founder & CEO of Intruder, on why the case for AI pentesting is well established but the work now is in building the programmes around it that will stand up to scrutiny
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The cybersecurity landscape is accelerating at a pace that would have seemed unthinkable just a few years ago. The number of published common vulnerabilities and exposures (CVEs) surged 263% between 2020 and 2025, while mean time-to-exploit has collapsed, with some projections putting it at minutes by late 2026.
As attackers are moving faster than ever, and exploit windows are shrinking, penetration testing needs to evolve. In the post-Mythos landscape, AI pentesting is providing a much-needed new approach to the challenges stretched security teams face in identifying and remediating vulnerabilities and other risks across their digital estates.
Where the scanning/pentesting distinction is blurring
Security teams have historically worked with two very distinct approaches to assessing risk.
Vulnerability scanners cover a lot of ground cheaply and can run on a continuous basis, but what they cannot do is tell you whether a finding matters in your environment. They detect, but do not interpret.
Penetration testing works differently. A skilled tester gets inside an application, understands how it is built and looks for weaknesses the way an attacker would. The findings tend to be higher quality and better contextualised, but the model has obvious constraints. It is expensive, happens infrequently, and whatever it surfaces reflects a snapshot of the environment at one point in time. A lot can change between tests.
That gap has always been a problem, but it’s become a critical threat in the age of AI. With a growing volume of vulnerabilities and threat actors able to identify and exploit them faster than ever, the old scheduled pentest approach lags dangerously behind. The recent arrival of models like Mythos that can identify huge volumes of flaws at lightning speed has accelerated the issue to breaking point. In the long term the pentest as we know it is set to become a thing of the past.
How pentesting is set to evolve
The question is no longer whether AI will change pentesting, but how completely it will do so. As AI-powered tools become capable of autonomously identifying vulnerabilities at machine speed, the assumptions that have underpinned security testing for decades are coming under pressure.
For now, the pentest report isn’t going anywhere. In the short term the cost and time required to run a pentest will fall, but what it produces still needs to meet established expectations. We are at the beginning of the AI adoption curve, not the end of it. Compliance frameworks move slowly, and auditors expect deliverables that conform to standards built up over many years.
What is changing is the frequency and the trigger for pentesting. Rather than a single substantial engagement each year, the emerging model is one of smaller, more targeted assessments initiated automatically when something in the environment changes, such as when code is shipped, a new service is exposed, or a configuration is modified. The barriers of cost and expertise that made continuous pentesting impractical are eroding and, with them, the case for accepting the gaps that annual testing leaves behind.
This is the direction that pentesting is heading; a transformation into something that runs in the background continuously, surfacing findings as the environment evolves rather than at a fixed point in time.
Providing context and speed by leveraging AI
AI pentesting agents can support the work that human analysts do, particularly with triage, investigation and validation which are the slowest parts of the remediation cycle. For the 42% of midmarket security teams already stretched, overwhelmed or consistently behind, that is time they do not have.
That investigative depth shows up in practice. In our own testing, an AI system correlated a vulnerability on a user’s laptop with that user’s cloud infrastructure permissions, a finding no conventional scanner would have surfaced because it can’t reason across those two layers at the same time. That kind of contextual correlation has not been possible before, and it has a direct impact on how effectively a team can prioritise its workload.
Pentesting agents can investigate a wide range of issues
While AI-powered pentesting is in its infancy, it’s already clear where the model is especially powerful.
When it comes to information disclosure risks, it provides investigative depth that goes further than any scanner. Rather than simply flagging that configuration details or storage buckets are exposed, an AI agent can review what is accessible, evaluate how an attacker might use it and, in some cases, attempt to verify whether exposed credentials are valid.
On injection flaws, an AI agent can reproduce the finding using multiple techniques (error-based, timing-based and UNION-based) to confirm whether an attacker could manipulate the application’s commands or queries to gain unauthorised access.
The difference also shows when it comes to client-side issues such as clickjacking Here, a scanner will flag any page missing the relevant headers, but an AI agent can assess whether the page is actually frameable in a way that poses genuine risk.
These capabilities matter, but the principle of human oversight in all AI deployments still holds true.
The end of pentesting as we know it?
The long-term trajectory points toward continuous testing becoming the default rather than the exception. As the tooling matures and the user base grows, new ways of validating security posture will gain acceptance with auditors, insurers, and compliance bodies. The annual pentest, built on the assumption that depth and frequency are mutually exclusive, will look increasingly like a product of its time.
Getting there will require the industry to resolve some genuinely difficult questions. Demonstrating the rigour of a continuous programme to an auditor is a different challenge to presenting a point-in-time report. The signals that should trigger an automated assessment, the liability implications for insurers, and the appropriate degree of AI autonomy versus human control are all areas where standards and expectations are still forming.
Teams adopting AI security testing today are operating ahead of that settled framework. Going in with clear criteria and a defined approach to oversight is essential, not because the tools aren’t capable, but because the context in which they operate is still evolving. The case for AI pentesting is well established. The work now is in building the programmes around it that will stand up to scrutiny.
Cien Solon, CEO & Co-Founder of LaunchLemonade, on why the future of financial services will be shaped by those who can balance AI innovation with responsibility
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Every industry is racing to implement artificial intelligence. In financial services and other heavily regulated sectors, that race has been cautious. From automated underwriting and fraud detection to hyper-personalised customer experiences, AI offers FinTech companies unprecedented opportunities to innovate and scale. Yet alongside this promise comes the growing weight of regulation.
Different approaches to AI governance are already taking shape. In Europe, the EU is introducing a structured, risk-tiered framework that sets clear obligations depending on how AI is used. The UK is pursuing a more flexible, principles-based approach, allowing individual regulators to apply guidance tailored to their sectors. The US has a more decentralised model, blending federal direction with a growing patchwork of state-level rules. For FinTech founders operating across borders, this diversity can feel complex and, at times, overwhelming.
With these frameworks emerging, many fintech founders are beginning to hesitate. Questions around compliance costs, legal complexity and potential liability are causing some to reconsider or delay AI adoption altogether. For smaller fintech firms and scale-ups, the concern feels especially acute. Is the risk worth the reward?
It is. And founders who treat regulation as a strategic advantage, rather than a barrier, will be the ones who pull ahead.
Regulation as a Trust Multiplier
In financial services, trust is everything. Customers entrust FinTech platforms with their most sensitive data and critical financial decisions. Investors and partners demand reliability, transparency and accountability. Regulators expect firms to operate with integrity and control.
Robust AI governance can enhance trust across all of these stakeholders. FinTech companies that proactively adopt transparent and responsible AI practices signal maturity beyond their size. They demonstrate operational discipline alongside technical capability.
This matters especially now, when AI systems can appear opaque or unpredictable. Clearly communicating how AI is used, what decisions it informs, what data it relies on, and how risks are mitigated allows fintechs to differentiate themselves in a crowded market.
Compliance, when done well, builds credibility. And credibility, in financial services, is a powerful competitive advantage.
The Myth of ‘Compliance Paralysis‘
One of the most common misconceptions among FinTech SMEs is that AI regulation requires building entirely new compliance infrastructures from scratch. This belief often leads to what I call “compliance paralysis,” a reluctance to act because the problem feels too big to start.
In reality, much of AI governance maps directly onto frameworks that fintech companies already use. Risk management, model validation, data protection, auditability. These are familiar disciplines. AI extends them into new domains, but the foundations are already there.
Take model risk management. The steps a compliance team follows to validate a human-led underwriting process can be adapted to validate an AI-driven one. The logic is the same. The documentation requirements are the same. What changes is the technology performing the task, and the speed at which it operates.
I see this with our own clients. Regulated businesses assume they need to start from zero when it comes to AI governance. When we walk them through what they already have in place, the gap between current practices and regulatory expectations is almost always smaller than they feared.
The Agility Advantage of FinTech SMEs
Large banks may have dedicated compliance teams and significant legal budgets, but they also carry the weight of legacy systems. Retrofitting AI governance into complex, decades-old infrastructure is both costly and time-consuming.
Fintech SMEs have the advantage of agility. They can design and implement responsible AI practices from the ground up, embedding governance directly into their products and processes from day one.
This is exactly how we built LaunchLemonade. Every AI agent on our platform operates within a governance framework by default. Audit trails, data handling rules, transparency requirements. They are baked into the architecture, because bolting them on later is always harder and more expensive.
This compliant approach delivers real advantages. Long-term costs stay lower because governance is structural rather than retrofitted. Adapting to evolving regulatory requirements becomes faster because the foundations are already solid. And AI-enabled products reach the market ready to meet governance standards, rather than needing months of remediation after launch.
Regulation, in this sense, levels the playing field. Larger incumbents may have more resources, but smaller firms can move faster and design smarter. Those that embrace this will outpace competitors who delay.
Practical Steps for Leaders
For finance leaders looking to navigate AI regulation without overwhelming their teams, the key is to focus on pragmatic, high-impact actions.
Start by classifying AI risk early. A chatbot handling customer queries carries a very different risk profile from an algorithm making credit decisions. Understanding where your use cases sit on the risk spectrum allows you to prioritise governance efforts where they actually matter.
Be transparent by default. Inform users when AI is being used, explain its role in decision-making, and provide avenues for human review where appropriate. Clear communication builds trust and reduces regulatory friction.
Leverage what you already have. Map AI governance onto your existing risk and compliance processes rather than building a parallel system. This reduces duplication and accelerates implementation.
Build lightweight governance structures. You do not need a large compliance team to implement effective oversight. Documenting model assumptions, maintaining audit trails and assigning internal accountability can go a long way. At LaunchLemonade, we see regulated SMEs achieve meaningful governance with lean teams precisely because they focus on these fundamentals.
And know when to bring in expert input. Legal and regulatory expertise is valuable, but it does not need to be engaged at every step. Focus external support on high-risk use cases or areas of genuine uncertainty.
The Cost of Standing Still
If financial SMEs retreat from AI because of regulatory anxiety, innovation will not stop. It will simply concentrate in the hands of large incumbents and major technology companies with the resources to navigate complex compliance landscapes.
That concentration has broader implications. Competition reduces. Innovation cycles slow. Diversity in financial products and services narrows. Opportunities to improve financial inclusion and accessibility are missed.
Fintech and finserve has historically been a driver of disruption, challenging traditional models and expanding access to financial services. AI represents the next wave of that transformation. If smaller players step back now, they risk ceding that ground entirely.
Regulation as an Enabler
The conversation around AI regulation in financial services needs a shift in perspective. Regulation creates the guardrails that allow new technologies to scale safely and sustainably. It builds the trust required for widespread adoption. And it ensures that innovation benefits broadly, across industries and communities, rather than being concentrated among those who can afford to figure it out alone.
For fintech and finserve founders, the real question is how to innovate responsibly and strategically. Those who embrace that question will find that regulation is part of the answer.
AI is too important an opportunity for FinTech to ignore. Regulatory frameworks may seem daunting, but they are neither insurmountable nor inherently restrictive. When approached thoughtfully, they strengthen trust, streamline operations and unlock new avenues for growth.
Financial SMEs are uniquely positioned to lead in this space. Their agility, focus and ability to embed governance from the outset give them a distinct edge over larger, slower-moving competitors. The future of financial services will be shaped by those who can balance innovation with responsibility. The firms that recognise this will define the age of AI, rather than simply surviving it.
Cien Solon is the CEO and Founder of LaunchLemonade, a secure governed platform of AI agents for regulated industries. An experienced AI transformation leader, Cien has been building AI-powered solutions since 2018 and working with generative AI since 2022. Her mission is to ensure that smaller businesses in regulated sectors can adopt AI confidently, without the enterprise price tag. LaunchLemonade was included in Entrepreneur UK’s Top 100 Startups to Watch, and Cien was shortlisted in the Technology category of the 2025 Investec Early-Stage Entrepreneur of the Year Awards.
Sam Hill, Investment Analyst at TDK Ventures tells us why electrical transformers must evolve to enable them to deal with the power demands of the AI age.
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The electrical transformer is one of the 19th century’s most enduring engineering achievements. Designed to step voltage up or down, conventional iron-core transformers have been the backbone of our power grids for over a century. As a testament to their ingenuity, the technology has remained largely unchanged in its fundamentals, consistently facilitating power delivery to cities, factories and data centres alike.
However, as the demands on the grid fundamentally shift, so too must the transformer. The boom in demand for energy infrastructure – driven by renewables, BESS proliferation, electrification, and more recently, the massive requirements of AI compute – has placed the conventional transformer at the centre of an emerging bottleneck.
Inherently passive, these devices cannot adapt to the bidirectional power flows of distributed solar, nor can they respond to real-time fault conditions on a dynamic grid. Modern applications, such as data centres and megawatt-scale charging facilities, demand significantly higher power densities and efficiencies, creating a growing mismatch with legacy infrastructure and necessitating eventual replacement of the installed base. The U.S. grid alone hosts an estimated 60 to 80 million distribution transformers today; well over half of these units are more than 35 years old and are rapidly approaching the end of their design life.
Despite burgeoning demand, supply is failing to scale. Lead times for manufacturing, fabrication and delivery now exceed 24 months, while prices in certain categories have risen as much as ninefold. Even as lead times extend, incumbent manufacturers have remained reluctant to expand capacity, concerned with geopolitical and policy uncertainty, questions over the sustainability of demand growth and structural incentives to maintain constrained supply. Ultimately, the conventional transformer is becoming the grid’s most consequential bottleneck.
Solid state transformers for expanded capability
The solid-state transformer (SST) is emerging to solve this bottleneck. While a conventional transformer relies on copper windings around a laminated ferrous metal core to inductively transfer energy, an SST performs the same voltage conversion using high-frequency power semiconductors. Often based on silicon carbide, these semiconductors switch thousands of times per second, resulting in a device that is smaller and lighter, yet far more efficient and robust.
Power flow is actively controlled by software at all times. This enables SSTs to function as dynamic, programmable power platforms rather than passive components. The SST can accept and deliver both AC and DC inputs and outputs across a range of voltages, each reconfigurable within the same device. This level of control means SSTs can absorb the functions of several conventional components – step-down transformers, UPS systems, protection switchgear and power factor correction banks – into a single integrated platform.
Because SSTs are built from semiconductor components rather than wound copper and electrical steel, their manufacturing lead times align with electronics supply chains instead of the volatile commodity metal markets. Consequently, their cost trajectory follows semiconductor learning curves rather than commodity price cycles. Furthermore, modular SST architectures can handle failures through redundancy and be repaired in minutes through hot swapping of individual power stages, bringing significant reliability benefits to critical infrastructure.
SSTs on the critical path for data centres
The most immediate and commercially urgent application for SSTs is the AI data centre. Power architectures underpinning today’s hyperscale facilities were originally designed for rack densities measured in single-digit kilowatts. However, NVIDIA’s latest GPU clusters demand hundreds of kilowatts per rack — a trajectory pointing toward megawatt-scale densities within the decade.
The industry has rapidly coalesced around DC bus architectures as the solution, such as the 800 VDC architecture proposed by NVIDIA. These designs bring medium-voltage power closer to the rack, reducing copper runs, cutting resistive losses and improving end-to-end efficiency margins.
In this shift to DC, SSTs are becoming a key building block. Only a solid-state platform can directly convert medium-voltage grid power to 800V DC while simultaneously integrating backup energy storage. This eliminates the need for UPS rooms, grey-space switchgears and step-down transformer banks that currently consume a significant share of a data centre’s physical footprint.
These efficiency gains, often spanning multiple percentage points, directly expand the “compute-per-megawatt” available within a fixed power envelope – a metric that now drives decisions from board-level components through to the siting of entire campuses. Furthermore, SSTs accelerate deployment speeds in the race to bring compute capacity online, as they benefit from both structurally shorter lead times and the consolidation of multiple pieces of equipment in the powertrain into a single unit.
Not if but when
Historically, the industry has questioned whether the technology has been ready. That question has now largely been answered. Power electronics, particularly silicon carbide devices, have matured dramatically over the past decade, driven largely by the EV and solar industries’ demand for higher voltage, high-efficiency inverters. These sectors have cultivated a new generation of power electronics talent – engineers with deep experience in translating power electronics technology advances into commercially viable products. SSTs will be deployed in 2026.
Simultaneously, the supply crunch in the conventional transformer market is creating a durable market opening. The massive AI infrastructure build-out is creating a class of motivated customers willing to support first-wave commercial deployments at scale. With DC architectures now squarely on the industry roadmap, SSTs have moved onto the critical path for AI. As these products take shape and real data is generated in pilots, customers can quantify a compelling business case, demonstrating that the cost of this new technology is justified.
The benefits of SSTs, first realised in data centres, will soon extend to a wider array of transformer applications. For high-power EV charging sites, where construction timelines and physical footprints often constrain site development, SSTs offer higher power density and shorter build cycles than conventional electrical infrastructure. On the distribution grid, replacing aging transformers with SSTs would introduce capabilities such as active voltage control, automatic fault isolation, phase balancing, and reactive power support. This would enable a more distributed, dynamic, and software-defined grid while enabling utilities to extract substantially more kilowatt-hours from existing poles and wires. As early adopters such as data centres drive SSTs down the cost curve, these mass-market utility applications will become increasingly viable.
In short, the commercial moment for SSTs has arrived. In recognition of this, Amperesand (a TDK Ventures portfolio company) raised an $80 million Series A in late 2025. The company is preparing to deploy 30 MW of medium-voltage SSTs with hyperscale and critical power customers in 2026, ahead of a projected volume ramp in 2027. Their value proposition is stark: an 80% reduction in electrical footprint, a 50% cut in installation labour and a 10x acceleration in time-to-power compared to conventional methods. Meanwhile, challengers like Heron Power and DG Matrix have collectively raised >$200m to date and incumbents across the ecosystem, including heavyweights like Infineon, Delta, GE Vernova and Eaton, are actively developing solutions to meet the clear market signal for SSTs.
Solid-state transformers are one of the essential building blocks needed to overcome the power wall AI is currently facing. The companies that combine technical performance with scalable manufacturing and system-level integration will define the category. Those that arrive at scale first will shape the power architecture of the AI era.
Now the hype is settling, 2026 is the year organisations must prove AI will deliver ROI. Matt Fuller, Co-founder and Vice President of AI/ML Products at Starburst, explains why measurement is only meaningful if organisations embed AI into core business processes and workflows.
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Over the past 18 months, many organisations have experimented with AI through pilots and isolated initiatives. While those experiments have generated excitement and much speculation, they have also created a measurement challenge. The question is no longer whether AI works, but whether it will deliver the measurable return on the significant investments companies have made in data infrastructure, skills and systems.
Today, AI’s impact is often assessed through activity metrics – usage rates, prompts generated, or time saved – rather than whether it improves business performance. Yet, activity does not equal impact. If organisations want to measure AI’s real contribution, they must anchor it to business outcomes that define competitive position: win rate, customer retention, time-to-market, risk exposure, cost per case, or revenue growth. Therefore, measuring AI meaningfully requires a shift in thinking – from treating AI as a standalone tool to embedding it directly into how the business operates.
Redesigning workflows for the AI era
The main reason AI initiatives fail to scale and, subsequently, prove business value is that they are introduced into existing processes. AI tends to be added as a “bolt-on” step in a legacy workflow rather than being part of the redesigned process.
To unlock value, organisations must therefore rethink and redesign end-to-end workflows around AI rather than inserting it after the fact. I believe that the real opportunity lies in improving decision-making across the whole process – from data architecture to insight generation to operation execution.
When AI is embedded in business operations from the start, its impact becomes measurable through outcomes such as faster product launches, improved forecasting accuracy, reduced operational losses, or stronger customer retention. However, redesigning workflows in this way quickly exposes another challenge: ensuring reliable access to trusted enterprise data.
Building the data foundation for scalable AI
As I’ve outlined, AI pilots often rely on fragmented, project-based datasets, where the data often sit outside of the organisation’s data architecture. While those datasets may be useful for experimentation, they rarely provide the reliability or governance required for enterprise-wide deployment, compromising scalability.
To embed AI into core business processes, organisations must therefore adopt a ‘data product’ mindset. This means creating curated, domain-owned datasets with clear ownership, quality standards and built-in governance. The data products then become reusable assets capable of supporting analytics, operational systems and AI models across the organisation.
It is only when AI operates on trusted data products, instead of one-off extracts, that it can be reliably integrated into operational workflows, scaled across the enterprise and measured meaningfully. At that point, AI stops being an experimental capability and becomes a business asset.
But getting to that point requires another shift to happen. Data must be treated as a governed, enterprise-wide strategic asset rather than a by-product of IT systems or a collection of disconnected silos. The shift here isn’t about better AI models; it’s about building a unified data foundation that enables AI to drive durable competitive advantage.
Scaling up security in the AI era
As organisations start embedding AI into decision-making processes, data governance becomes critical. Scaling AI without robust upstream governance structures introduces significant legal, operational and reputational risks. Before AI influences business-critical decisions, it is imperative that organisations can ensure clear data ownership, enforceable access controls, lineage visibility, and compliance with regional and regulatory requirements.
Importantly, governance cannot simply exist as policy documentation. It must be technically enforced across the entire data estate so that organisations can confidently scale AI while maintaining control over how and what data is accessed and used. Without that level of governance, AI risks amplifying existing data fragmentation and compliance challenges rather than delivering enterprise value.
People first, every time
AI adoption also raises the important question of the relationship between human expertise and machine intelligence. Much of an organisation’s competitive advantage exists not in data, but in tribal knowledge held by humans – judgment, context and business understanding built over years of activity.
AI systems are only as strong as the data and the context they are given. While organisations should progressively codify that institutional knowledge into governed data products, metadata and documented business rules, we are still far from a point where AI can fully replicate that depth of human expertise.
Today, AI is enhancing human capabilities rather than replacing them – surfacing insights, accelerating analysis and providing decision support – while experts remain in the loop to validate, refine, apply judgment and ensure decisions reflect the broader business context.
As institutional knowledge becomes more structured and accessible, AI’s role will naturally expand. But in the near term, as I’ve outlined, the most successful organisations will be those that use AI to augment their workforce rather than attempt to automate expertise prematurely.
From experimentation to enterprise value
Organisations are now moving beyond AI experimentation, shifting the focus from novelty to measurable business impact. Achieving true AI business value requires embedding AI into how the business actually operates – supported by trusted data foundations, strong governance and workflows redesigned around better decision-making. It is my view, then, that AI should ultimately be judged not by how often it’s used, but by whether it delivers meaningful business results.
ByMatt Fuller, Co-founder and Vice President of AI/ML Products at Starburst.
CTOs have piled into digital AI. The next advantage lies in connecting it to the real world, argues Nick Thompson, co‑founder and CEO of OLO Robotics
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Spend any time with CTOs and the chat is almost always about AI. Copilots, chatbots, analytics pipelines, document understanding – the digital side of the business is getting plenty of attention. But in most of those conversations the AI stops at the edge of the screen while the warehouse, factory floor and inspection bay still run much as they were a decade ago.
Physical automation has always existed. But it has sat behind a wall of specialist expertise, capital and long lead times that most IT and software teams could not see past. That wall is now coming down. The question for technology leaders is whether they treat that change as part of their AI strategy, or leave it as somebody else’s problem.
From niche tech to mainstream platform
My background is in software rather than robotics. After two decades building software teams and technology businesses, I started to look more closely at the intersection of AI and physical automation. What I found was familiar: a specialist domain starting to look like a platform that generalist development teams can use.
Cloud computing is the obvious precedent. Before cloud, running infrastructure meant capital expenditure, specialist skills and lengthy procurement cycles. The arrival of platforms such as AWS, Azure and Google Cloud abstracted that complexity into services that a small team could consume in hours rather than months. The systems did not become simpler; they became accessible through a different model.
Robotics is moving in the same direction. ROS2, the standard framework for programming industrial robots, is powerful and open source but difficult to learn. Making progress has meant understanding a large stack of concepts and tools, which has kept robotics in the hands of specialist roboticists who are in short supply. For many organisations, that has been enough to keep robots on the ‘future plans’ slide.
But recently, platforms have emerged on top of ROS2 that provide browser‑based environments, integrated simulation and SDKs in common languages. Instead of assembling their own mix of simulators, dashboards and custom scripts, development teams can work in one place and treat robots as just another class of endpoint in the architecture. These capabilities are already in production; what is lagging is recognising them as part of mainstream AI and automation strategy.
The robot team you already employ
As perception and planning increasingly rely on AI models, the bottleneck in robotics is shifting away from low‑level control towards data management, orchestration and integration – areas where existing software and IT teams are already experienced.
A developer can now log into a web‑based environment, spin up a simulated industrial robot and experiment with behaviours before any hardware is ordered. Large language models can generate ROS2 code from natural‑language descriptions. Developers review that code, run it in simulation and refine it as they would any other component. The code sits in the same repositories, goes through the same review processes and is deployed through the same pipelines as other software.
This changes who can own automation strategy. Rather than building a separate robotics function, organisations can draw on engineers who already understand their systems and data, and treat robots as part of the same stack rather than as isolated projects.
Rethinking how you buy robots
Traditionally, each robotics deployment has been treated as a bespoke project. You hire specialist roboticists, engage systems integrators, commit capital to hardware and integration, then discover over time whether the automation meets expectations. It is a familiar process for anyone who remembers pre‑cloud infrastructure projects.
A platform‑based approach alters both the economics and the sequence of decisions. Development starts in simulation. Use cases are validated before hardware is purchased. Organisations can run small pilots, discard the ones that do not deliver and scale up the ones that do. Robots become standardised endpoints running defined behaviours, rather than one‑off builds.
Consumption models are evolving too. Some providers now offer robot‑as‑a‑service, where customers pay for hours of operation instead of owning the asset outright. Combined with sim‑first development, this changes the risk profile of automation projects in a way that mirrors the move from owned hardware to cloud computing.
For IT leaders who lived through cloud procurement debates – build versus buy, capex versus opex, open versus proprietary – these patterns should be recognisable. Organisations that engaged with cloud early, in a measured way, gained advantages that compounded over time. The same potential exists in physical automation.
The ‘last mile’ of your AI projects
The highest‑profile robotics deployments tend to be in warehousing and logistics, where autonomous mobile robots move goods between zones and robotic arms pick from shelves. But for many organisations, the more immediate opportunities sit at the boundary between digital programmes and the physical environment.
For predictive maintenance, for example, many manufacturers have invested in sensors, data pipelines and AI models to forecast equipment failures. In practice, these initiatives often culminate in dashboards and alerts on control‑room screens. When an alert sounds, a technician still walks the floor, inspects the asset and performs a standard intervention. Detection has been automated; the response remains manual.
Robots can handle parts of that response. A mobile platform equipped with a camera and basic tooling can be dispatched to a machine, collect visual or sensor data and carry out a simple inspection or reset. The workflow from model output to physical action can be orchestrated by the same software teams that built the predictive maintenance system.
A similar story appears in warehouse operations. Many facilities now use AI‑driven demand forecasting and sophisticated warehouse management systems to decide what to pick, when and to where. Execution can still often be manual however, with staff walking long distances to carry out those decisions. Autonomous mobile robots and robotic picking systems can take the instructions those systems already generate and turn them into physical movement on the warehouse floor.
Organisations have digitised much of the data layer through sensors, telemetry and analytics; but the connection to consistent physical action is still developing. In sectors facing acute labour shortages such as warehouses, ports, construction, brownfield manufacturing and field service, combining human expertise with robotic assistance is becoming a practical response to current constraints.
A strategic choice, not a technical one
Every significant technology shift creates a period in which early adopters can build advantages that are difficult to replicate later. Cloud, mobile and data platforms all followed that pattern. Organisations that engaged early, took time to understand new models and built internal capability now operate differently as a result.
Physical automation is entering that phase. The factors that kept robotics at arm’s length from mainstream IT – the need for scarce specialist skills, the capital intensity of hardware purchases, the complexity of bespoke integration – are being reduced by open frameworks, platform layers, simulation environments and new consumption models.
For CTOs, the question is not whether physical systems will become part of IT strategy, but when and on what terms. If competitors are quicker to connect their AI investments to physical systems, closing the loop from predictive maintenance alerts to automated inspection, or from demand forecasts to in‑facility logistics, they will accumulate operational advantages over time.
The practical move is to treat physical automation the way you would treat any emerging technology. Understand the procurement models. Run a contained pilot that links one existing digital programme to a simple physical workflow. Build internal capability in the teams who already know your systems. If you are still treating robotics as a one‑off patch at the edge of operations, that is now a choice, not a technical inevitability.
Nick Thompson is co‑founder and CEO of Sheffield-based OLO Robotics.
Following the launch of its Core Modernisation Playbook, Publicis Sapient’s Dave Murphy, Head of Financial Services – EMEA & APAC, explores why so many banks struggle to modernise despite investing heavily in AI. The challenge is no longer knowing what to transform, but how to execute transformation safely
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Most banks have spent the last decade applying AI where its impact is most visible, in chatbots, fraud scoring and personalised product recommendations. The results have been real, and in places significant, however, they have also been contained. AI has been working at the edges of the organisation, improving the surfaces that customers and compliance teams interact with, while the actual machinery of the bank carries on untouched. The core systems, the batch processing logic, the settlement rules written in COBOL three decades ago, have continued to run exactly as they always have, insulated from the transformation happening around them.
Meeting the AI Execution Challenge
That insulation is starting to break down. For CTOs weighing where AI investment should go next, the implications are considerable. The question is no longer whether banks need to modernise. Every major institution already knows it needs real-time payments, AI-ready operations, API-enabled architectures and cleaner data foundations. The challenge is execution. How do you modernise decades of critical systems without introducing unacceptable operational risk?
That is where AI is beginning to change the equation. Rather than focusing solely on customer experience or analytics, it is being applied to the engineering process itself. The discovery, extraction, transformation and validation work that has traditionally been the slowest, riskiest and most expensive phase of core modernisation is becoming increasingly automated. This is where the greatest opportunity now exists.
The Core Modernisation Playbook
Publicis Sapient explores this shift in its recent Core Modernisation Playbook. At the centre of that approach is Sapient Slingshot, a platform designed to apply AI across the engineering lifecycle rather than simply the coding stage. Slingshot applies AI across the entire modernisation lifecycle, from understanding legacy systems through to transformation and continuous validation within a governed workflow. The objective is not simply to write code faster. It is to make large-scale modernisation more predictable, auditable and easier to execute.
One global bank recently used this approach to analyse three million lines of COBOL and produce verified functional specifications in eight weeks, work that would previously have taken well over a year and required scarce legacy expertise that is becoming increasingly difficult to find. What changed was not the strategy or destination. It was the execution model.
Core banking code written over thirty or forty years rarely comes with a user manual. Business rules become embedded directly in software, operational workarounds accumulate over time, and critical knowledge often exists only in the minds of engineers who built the systems. As those engineers retire, banks are not simply losing people. They are losing the institutional knowledge needed to modernise safely.
This reflects a broader shift in how modernisation is delivered. Instead of treating discovery, code generation and testing as separate phases owned by different teams, they become part of a connected execution model. Understanding legacy systems, building modern services and validating every change happen as part of the same continuous process. That reduces risk while improving speed, which is exactly what heavily regulated organisations require.
AI-Powered Business
AI-powered business rule extraction is a direct response to that problem. Rather than depending on interviews with legacy experts and time-consuming manual code walkthroughs, automated analysis can surface the logic embedded in legacy programs, cross-reference it against actual processing behaviour, and generate specifications that engineers who’ve never touched the original COBOL can read and act on. In the case above, specification accuracy came in at 95%, and the time needed to analyse individual batch feeds dropped from 35 days to five. That compression changes the shape of what a modernisation programme looks like in its early phases. Work that used to occupy teams for the better part of two years can be substantially completed in months, and what comes out the other end isn’t an informal summary but a set of audit-ready specifications and, in this instance, more than 200 implementation-ready backlog items that become the foundation for everything that follows.
Establishing Strong Foundations For AI
Foundations matter because the validation phase of modernisation is where most programmes break down. There’s no shortage of ambition or strategic clarity in banking transformation. Most major institutions have roadmaps, target architectures and detailed business cases. What consistently falls apart is proving, with sufficient rigour, that a rewritten system behaves identically to the one it’s replacing.
Core banking processes handle exceptions, regulatory edge cases and accumulated business logic in ways that are difficult to fully enumerate up front, let alone test exhaustively by hand. Traditional testing models depend heavily on manually created test cases, subject-matter-expert review and long validation cycles. Coverage gaps are hard to detect, particularly when the legacy behaviour they’re meant to validate against is poorly documented in the first place. Banks end up completing the development work and then getting stuck proving the new system does what it’s supposed to.
AI-driven testing changes that equation by generating and executing test cases at a scale manual teams can’t match, covering standard transactions, edge cases and downstream dependencies systematically rather than sampling them. That doesn’t remove the need for human judgement on what ‘correct’ looks like, but, it does remove the bottleneck of generating enough coverage to have confidence in the answer.
Modernisation Strategy
None of this means banks can modernise the way digital natives do. Core banking platforms sit inside dense ecosystems of payments networks, risk engines, regulatory reporting systems and third-party providers. A change in one system can create consequences dozens of steps downstream, and banks must modernise around uptime, auditability and customer trust in a way a retailer redesigning a checkout flow simply doesn’t. That’s precisely why execution has become the defining challenge. Every bank already knows what it wants to build. The competitive advantage now lies in how effectively it modernises the foundations that make those ambitions possible.
Sapient Slingshot – Deploying An Execution Engine
What AI applied to the engineering process offers is a way to close that gap without pretending the underlying complexity has gone away. Understanding what a legacy system actually does, generating modern code and architecture that preserves the business behaviour underneath it, and validating the result continuously rather than at the end of a multi-year build: these are the three things that have historically made core modernisation slow, expensive and prone to stalling.
Applying AI across the engineering lifecycle does not remove the need for governance, auditability or human judgement. It strengthens them by making documentation, traceability and validation part of the execution process rather than activities completed afterwards. This is where platforms such as Sapient Slingshot are emerging as execution engines for modernisation, enabling banks to modernise with greater speed, control and confidence rather than simply generating code more quickly.
For CTOs, the practical takeaway is less about any single tool and more about where in the lifecycle AI is being pointed. The customer-facing layer of banking has benefited from a decade of AI investment. The engine room is only just beginning. The banks that move first will not simply modernise faster. They will build the AI-ready foundations that determine how quickly every future innovation can be delivered.
The Core Modernisation Playbook
Get your copy of the latest White Paper from Publicis Sapient here
Nicholas Batten, Co-founder and CTO at Nuumad explains how a combination of probabilistic and deterministic AI can help pharmacies adapt for the future.
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As funding pressures on the NHS grow, community pharmacies are reaching a turning point. What used to focus mainly on dispensing medicines is evolving into a more patient facing healthcare network. But this shift is not guaranteed. Without the right technology in place, pharmacies may struggle to keep up with rising demand, regulatory requirements and increasingly complex patient needs.
The conversation around artificial intelligence (AI) has, to date, been dominated by hype. In healthcare particularly, this is problematic. Clinical environments are highly regulated systems where safety, traceability and accountability are non negotiables. The real opportunity, therefore, is not AI adoption, but understanding how intelligent systems, both probabilistic and deterministic, can be deployed responsibly to scale care without compromising compliance or cybersecurity.
AI as a force multiplier, not a replacement
One of the most persistent misconceptions is that AI will replace clinical expertise. In practice, the opposite is true. Across progressive pharmacy networks, intelligent systems are being deployed instead to augment healthcare professionals.
AI, when used appropriately, acts as a force multiplier. It can assist with triage, summarise patient inputs, support protocol adherence and reduce administrative burden. This allows pharmacists to focus their attention where it matters most: clinical judgement and patient interaction.
However, it is critical to recognise that not all intelligence in healthcare needs to be AI driven. In many cases, structured workflows, exact data matching and rules based logic can deliver similar operational gains with greater predictability, reducing the need for human checks. For technology leaders, this distinction is essential. The goal is to optimise system design as opposed to AI usage.
In clinical settings, augmentation is the defining principle, not automation. Human oversight remains central, but it is enhanced by systems that increase throughput, reduce error and standardise care delivery.
Deterministic systems vs probabilistic models
A key strategic decision when deploying intelligent infrastructure in healthcare is choosing where AI is appropriate and where it is not.
Probabilistic AI models, such as large language models, excel in handling unstructured data and generating flexible outputs, at the same time they also introduce uncertainty. Even with high accuracy, their non deterministic nature can create challenges around explainability, auditability and regulatory approval.
By contrast, deterministic logic systems operate on predefined rules and structured data. Every decision pathway is traceable, reproducible and auditable – delivering a clear advantage in highly regulated environments such as pharmacy consultations, especially when paired with an intuitive, best in class user experience.
This is not an argument against AI, but rather in favour of balance. In practice, the most effective architectures combine both approaches: AI at the edges to enhance usability and efficiency, and deterministic systems at the core to guarantee compliance and safety.
For example, AI can help organise patient inputs or highlight relevant information, while final decisions are handled by rule based systems aligned with clinical protocols. This hybrid approach enables organisations to benefit from AI while keeping risk under control.
Beyond individual technologies, the real transformation lies in how systems are orchestrated.
Modern consultation platforms have become dynamic orchestration layers that manage the entire patient journey. From pre-consultation risk assessment and structured symptom capture, to real-time clinical support and automated follow-up, these systems create a continuous, data-driven workflow.
This orchestration reduces fragmentation. Pharmacists no longer need to navigate multiple disconnected systems or manually reconcile information. Instead, they operate within a unified environment where clinical protocols, patient data and decision support are seamlessly integrated.
The impact is significant. Consultations become faster and more consistent, training time for new staff is reduced, and perhaps most importantly, the standard of care becomes repeatable across locations with more empowered healthcare professionals.
Scale can now come into play. Pharmacies can expand private services such as travel health, weight management or preventative care without proportionally increasing operational complexity or risk – avoiding the additional cost and resources typically required to manage and mitigate these challenges on an ongoing basis.
Structured data is the foundation of this model. By capturing patient information in a consistent, machine-readable format, pharmacies can unlock automation, reporting and continuous improvement, all while maintaining compliance with regulatory requirements.
Balancing innovation with regulatory responsibility
The UK regulatory landscape for AI in healthcare is still evolving, with frameworks being shaped by bodies such as the MHRA (Medicines & Healthcare Products Regulatory Agency), creating both opportunity and uncertainty. Organisations that move too slowly risk falling behind and those that move too quickly risk non compliance.
Navigating this requires a disciplined approach to innovation where every system, whether AI-powered or not, must be clinically validated, fully auditable and aligned with existing healthcare regulations. Transparency is critical as if a system cannot clearly explain how it reaches a decision, it is unlikely to meet the standards required for clinical deployment.
Equally, leaders must resist the temptation to prioritise cost or speed over safety. In healthcare, the consequences of failure extend beyond financial penalties and can impact clinicians trust, organisational reputation and mostly importantly patient outcomes.
Responsible digital transformation, therefore, is about making deliberate, informed decisions about where technology adds value and where it introduces risk.
The intelligent pharmacy era
Pharmacies are no longer just dispensing centres, they are becoming decentralised healthcare providers. Intelligent systems are enabling this shift, but success depends on how they are implemented.
AI has a role to play, particularly in enhancing efficiency and user experience. But it is only one component of a broader ecosystem that includes deterministic logic, structured data, secure infrastructure and workflow orchestration.
For technology leaders, the challenge now is to build systems that scale and can be trusted at the same time. The technology is already available. What matters now is leadership and choosing the right architectural approaches, embedding governance from day one and recognising that true innovation in healthcare is measured by reliability, safety, and impact.
Simon Hayward, GM & VP Sales International at Freshworks explains why AI needs to work effectively for mid-sized organisations to truly succeed.
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Determining the impact AI will have on the future of enterprises lies in the hands of the global mid-market sector. Sitting between SMEs and large corporations with revenues between £25m and £500m – mid-market businesses employ 40% of the global workforce and are vital growth engines to the global economy and determining the extent of AI’s global impact.
The path to successful AI adoption
Investors and board-level decision makers will spend much of 2026 identifying key target markets and the mid-market should be top of every list.
Identifying and assuring investors’ delivery of AI ROI is critical to not only the future of the technology but also the success of so many global businesses. Mid-market companies represent roughly a third of private-sector GDP and around 40% of global employment.
They sit at the heart of the global economy, yet they are often overlooked in AI discussions that focus primarily on hyper-scalers or the largest enterprises. These companies do not have the luxury of multi-year transformation programs or unlimited budgets. For them, AI must deliver tangible value quickly or it simply will not stick.
Speed, simplicity and real outcomes
Mid-sized organisations are under constant pressure. They compete with far larger players while working with fewer resources. Cost efficiency matters, meaning time to value is critical.
Software that takes months to deploy or requires swathes of consultants is a non-starter. AI that creates more complexity than it removes will fail, regardless of how sophisticated the underlying models may be.
For AI to succeed in the mid-market, it must be designed around how people actually work. It must integrate easily into existing systems, automate real tasks and deliver measurable outcomes in weeks, not years. Anything less becomes shelfware.
This is where the conversation around AI needs to mature. The future of AI adoption is not about who has the most advanced models. It is about who can turn intelligence into impact, at speed, for teams that are already stretched thin.
The companies powering the economy
The future impact of AI will not be determined by a handful of global giants. It will be shaped by the millions of companies powering the economy every day.
Businesses with revenues of around a billion dollars, not ten or one hundred billion, are using AI to help their teams work more effectively, serve customers better and grow more efficiently. When AI works for them, it scales across the economy.
What is especially encouraging is how traditional businesses are embracing this shift. Companies with decades of history are using AI to modernise core operations, automate routine work and improve both employee and customer experiences. These are not abstract experiments or innovation theatre. They are practical applications that free up investment, improve productivity and support sustainable growth.
This is where AI becomes truly transformative for the mid-market: not as a futuristic concept, but as a tool that helps people focus on higher-value work and helps businesses compete more effectively.
Reducing complexity, not adding to it
If AI is going to deliver meaningful economic impact, we need to meet companies where they are.
That means reducing complexity, not adding to it. It means building technology that is intuitive by design, not powerful but inaccessible. And it means focusing relentlessly on outcomes, not features.
The most successful AI deployments I see share a common trait. They are invisible when they work well. They remove friction instead of introducing it. They make teams faster, smarter and more effective without requiring a fundamental rewrite of how a business operates.
This approach is especially critical for the mid-market, where every investment must justify itself quickly and clearly.
The real test for AI
The mid-market does not need more hype. It needs AI that works. If AI can help these companies scale, compete and grow more efficiently, the economic impact will be great. Productivity gains will compound. Innovation will accelerate. Opportunity will spread more evenly across industries and regions.
The real test for AI is not whether it can impress in a demo. It is whether it can deliver value where it matters most. And that future will be defined by how well we serve the companies at the heart of the global economy.
Benoit Charnallet from TSC Auto ID Technology explains why your networked devices might leave you at risk of a cyber attack.
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Over half (51%) of organisations such as manufacturers and retailers, predict their operational technology (OT) environments will be targeted by cyber attacks.
As cyber threats become ever more frequent and advanced, it’s vital that cybersecurity strategies include all networked devices, including thermal printers and enterprise mobile computers (EMCs). A global mobile threat report revealed that 50% of mobile devices are running outdated operating systems, creating significant vulnerabilities.
Today’s organisations, from small manufacturers to global operators and public bodies, rely on vast networks of connections to operate. While this is undoubtedly essential, such connections also present potential entry points for hackers to access, breach, or disrupt enterprise systems.
Among such entry points are thermal printers. While they’re becoming more integrated into enterprise networks and support critical functions like shipping, product marking and compliance labelling, they’re often overlooked in cybersecurity planning, even though their connection to critical systems makes them vulnerable if unprotected.
Media outlet, Cybernews, did an experiment to determine how many unsecured printers it could potentially hack. Its results made for sober reading. Through readily available IoT search engines, the publication hijacked nearly 28,000 unprotected printers, amounting to a 56% success rate.
Cyber breaches dominated UK headlines in 2025, crippling manufacturers, retailers and others. The risk of threats is escalating, and attackers are said to be using advanced technologies to target weaknesses faster than organisations can protect themselves. Unsecured printers and EMCs pose a significant risk, so are a vulnerability you cannot afford to ignore.
Recognise your printers as potential attack surfaces
As thermal printers become increasingly embedded within enterprise networks, they face similar threats as any connected device. Understanding these risks is the first step in mitigating them. When evaluating thermal printer security, take a structured approach that addresses both technical vulnerabilities and organisational requirements. Key vulnerabilities to consider include:
Unauthorised access: printers with open network ports or unsecured web interfaces can be exploited
Data interception: print jobs containing sensitive data such as shipping labels may be intercepted
Malware infiltration: printers can be used as a bridge to deploy malware into broader enterprise systems.
Align printer security with industry models and standards
Organise your security measures methodically and effectively around key cybersecurity principles, frameworks, and regulations. These include the CIA Triad, a foundational model in information security emphasising three core principles: confidentiality, integrity and availability.
Another is the NIST Cybersecurity Framework. It provides a comprehensive, structured lifecycle for managing cybersecurity risks across five key functions: Identity, Protect, Detect, Respond, Recover.
In 2024, Gartner reported that 63% of global organisations had implemented a zero-trust strategy, another model that assumes no device or user is inherently trusted, regardless of location inside or outside enterprise networks. Every access request must be verified, making zero-trust especially applicable to networked printers operating on the edge of security perimeters.
As regards other regulations, there’s governmental ones like the EU’s Radio Equipment Directive (RED) for devices with wireless communication functions, including printers equipped with Wi-Fi, Bluetooth, or RFID.
Using printers with embedded security features
By understanding potential vulnerabilities and security frameworks, and by fully leveraging security capabilities built into printers like those from TSC Auto ID, you can mitigate risks and protect your operations without sacrificing efficiency.
TSC devices come equipped with many security capabilities, including firmware authentication, TLS/SSL encryption, and remote management tools. TSC also maintains a dedicated vulnerability disclosure program to report and resolve security issues. It offers a secure channel for customers and partners to report vulnerabilities. Such a proactive approach helps maintain transparency, minimises risk exposure, and supports responsible disclosure best practices, all critical elements for enterprise trust.
A proactive stance on mobile device security
If you’re looking to protect mobile devices like enterprise smartphones, tablets and specialised mobile computers, it can be achieved by implementing robust mobile security best practices from providers such as Bluebird, a TSC Auto ID company.
Protecting devices and sensitive data is vital for ensuring seamless workflows and driving strong business performance. Bluebird actively mitigates security risks and vulnerabilities by integrating multiple layers of protection into its devices and solutions. Every component of its offerings is meticulously crafted to defend against common security threats like malware, phishing, cryptographic failures, and insecure design, all without compromising essential productivity or accessibility.
As businesses become increasingly interconnected, their networks and valuable data are more susceptible to unauthorised access and various security vulnerabilities. Bluebird addresses these risks by adhering to foundational cybersecurity principles and implementing a defence-in-depth approach throughout its architecture and design processes. Through its smart, highly configurable technology, Bluebird empowers organisations to achieve an optimal balance between critical operational objectives and robust security postures.
Learning from vulnerabilities
Bluebird continuously analyses mobile device vulnerabilities, from historical attacks to recent discoveries. This drives its commitment to develop smarter, more resilient security solutions, specifically engineered to tackle today’s complex mobile computing security challenges.
Whenever a new vulnerability is identified, Bluebird swiftly prepares and deploys a patch, informed by a rigorous classification system based on the Common Vulnerabilities and Exposures (CVE) list, which is diligently managed by the National Vulnerability Database. Each vulnerability/threat is assigned a severity level, ranging from 0.1 (low) to 10 (critical) according to the Common Vulnerability Scoring System (CVSS), which details essential actions businesses must take for protection.
Bluebird also monitors the Open Web Application Security Project (OWASP), which provides annual insights and reports on top mobile vulnerabilities. Bluebird’s devices undergo extensive security testing phases, including rigorous internal security assessments (static and dynamic code analysis) as well as independent third-party penetration testing. This external testing ensures its security controls are robust, as pen testers simulate real-world hacker attempts to bypass various layers of protection.
Development of its devices strictly adhere to a corporate-mandated Software Development Lifecycle (SDLC). This ensures all Bluebird’s software is designed and tested following stringent security guidelines embedded within its SDLC. The strict implementation of the principle of least privilege, as well as robust Application Programming Interface (API) controls, prevents unauthorised users from accessing devices. Thorough end-to-end application testing consistently enhances security.
Bluebird diligently tracks Android™ vulnerabilities and threats by monitoring CVE and OWASP. It collaborates with vendors, leveraging its expertise to provide appropriate patches, ensuring all mobile devices are protected against low and critical threats. It ensures every critical mobile vulnerability is thoroughly analysed, including hardware and software.
Elevated trust
A key mechanism used to protect cryptographic operations and sensitive material is a Trusted Execution Environment (TEE). This environment operates in isolation from a device’s Rich Execution Environment (REE), where main operating systems and applications reside. Within the TEE, code executes with a high level of trust, as its environment is completely isolated from the rest of the system. Any threats detected in REE cannot impact TEE and, even if the REE is compromised, data within the TEE remains secure.
Bluebird adds another layer of security to organisations’ TEEs, integrating features like its BOS™ Kiosk / Enterprise Launcher. For example, its enterprise launcher allows administrators to control which users have access to specific environments, ensuring sensitive or confidential data remains secure. By consistently following TEE best practices, which are integrated into all recently produced Bluebird devices, TEEs are robustly protected against new and emerging security threats.
Building pillars of security
As cyber threats become more frequent and more complex, a people, process and technology (PPT) framework can also help you structure your thermal printer and EMC security.
Ben Kitson, Head of Business Development at Precision Micro explains how chemical etching is quietly powering some of the most advanced technologies around.
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In a world driven by the demand for cleaner, smarter and more efficient technologies, energy has become the common thread, pulling together innovation across multiple industries. Whether on the ground in electric vehicles, deep in the hydrogen supply chain, soaring through the skies in next-gen aircraft or even orbiting the Earth aboard space missions, energy systems are evolving. At the heart of many of these breakthroughs is chemical etching.
Chemical etching might not grab headlines, but it’s quietly powering some of the most advanced technologies around, from satellites to hydrogen fuel systems. By using controlled chemical reactions to remove metal with pinpoint precision, it creates complex, stress-free components that traditional methods like stamping or laser cutting can’t match.
However, as demand for high-complexity components continues to rise, etching is stepping into the spotlight. This shift is most visible in energy systems across multiple sectors.
Space
Recent surveys suggest a boom in space missions from both public agencies and private operators. This has created a demand for small but vital components like thin, etched nickel interconnects used in lithium-ion batteries for satellites and exploration vehicles that will study exoplanets.
Although the components may sound simple, their applications are anything but. They are used in systems built to operate in the extreme conditions of deep space, as seen in projects like the Mars Rover. That’s a remote-controlled robotic vehicle developed to explore the Martian surface and the upcoming ExoMars mission in 2028, which aims to search for signs of past life on Mars.
This is engineering at its toughest. It’s not about producing large volumes of simple components, but about processing specialist materials burr-fee, stress-free, quickly, flexibly and with precision.
Chemical etching is ideal for this because it keeps tooling costs low and allows for rapid design changes, making it perfectly suited to high-precision work where there’s no room for error.
Aerospace
Aerospace is made up of a blend of legacy and future-facing technology. Today’s innovation is not just on electric or hydrogen-powered aircraft, but also on making current combustion engines cleaner and more efficient.
Thermal management is a key area of focus here. Compact aluminium heat exchangers rely on etched aluminium flow plates used in aircraft engines to manage cooling airflow with higher efficiency. These plates, with their intricate channel designs, are evolving into fuel cell bipolar plates in hydrogen systems.
They’re not speculative, they’ve been in the market for over a decade, but evolving manufacturing capabilities are helping to revisit and optimise them for the next generation.
Hydrogen and electric
The conversation continues with on-land vehicles too. Electric vehicles and hydrogen fuel systems are often seen as competitors, but the reality is more complementary, particularly when you zoom out and look at where each is most viable.
Wondering why this might be the case? Well, the European International Council on Clean Transportation (ICCT) highlights that hydrogen fuel cell vehicles could soon outperform EVs in emissions reduction, provided they run on renewable hydrogen.
The study suggests FCEVs could emit 79 per cent fewer emissions than internal combustion engine vehicles over their lifetime, which is slightly better than battery EVs using renewable electricity.
That said, this doesn’t mean hydrogen will replace battery-electric vehicles across the board. It’s likely we’ll see a combination of the two. EVs dominate the passenger car market, while hydrogen is gaining real traction in heavy-duty transport, long-haul logistics and commercial fleets.
Behind both are systems built around connectivity, not of data, but of energy. Battery packs, fuel cells and heat exchangers all rely on etched components such as busbars, bipolar plates and printed circuit heat exchangers to enable power delivery and thermal management.
In hydrogen, this might involve supplying plates for electrolysers that generate hydrogen, or the heat exchanger flow plates that help compress and dispense it into a truck. The same principles apply inside the vehicle itself, whether that’s a hydrogen-powered lorry or a new-generation aircraft using fuel cell systems.
What’s interesting is how naturally this transition follows on from existing capabilities. Etching has long played a role in combustion-era automotive manufacturing, from injector components to under-the-hood systems. Now, the same process is enabling fuel cells, EV battery connections and the entire hydrogen ecosystem.
And unlike combustion, where the goal was incremental efficiency, the stakes here are existential. Hydrogen isn’t a side story, it’s a key piece of the energy transition puzzle.
Autonomous vehicles
That crossover is part of a broader trend in autonomous vehicles. For example, in the US, etched copper bus bars are being used in the battery packs of autonomous robo-taxis. As for the UK, a fuller rollout of self-driving taxis will come after the Automated Vehicles Act fully takes effect in late 2027.
These packs sit under the passenger seat, with rows of AA-sized cells connected by precisely engineered bus bars featuring break points that isolate failures and prevent full-pack shutdown.
It’s a classic pre-series development setup, with thousands of parts produced in moderate volumes, all within tight turnaround windows and changing specs. Chemical etching shines here, offering speed, precision and flexibility. While these vehicles may move to high-volume stamping processes later, etching helps in the early stages where design isn’t yet locked.
And there’s a wider trend to acknowledge, the technology used in an autonomous vehicle’s battery is structurally similarly to that used in satellites. The context shifts, but the engineering need remains constant to connect, conduct and control power. Yet, unlike in space, the development volumes are still in the thousands before higher production methods take over.
A cross-sector reality
The underlying message here is that there’s sectorial convergence. Energy systems in space, air, land and sea are being determined by the same fundamental forces. That’s demand for cleaner power, the need for agility in design and the pressure to deliver quickly.
Chemical etching can support rapid prototyping, deliver precision without introducing stress and work across a wide range of materials, making it a natural fit for the pace and complexity of modern engineering.
From pure nickel in satellites to copper in EVs and specialised alloys in space-grade systems, the process adapts across applications while maintaining consistency in outcome.
Energy is the thread connecting progress across multiple applications, whether that’s orbiting satellites or on-road innovation. After all, the future isn’t just on the horizon — in many cases, it’s already in production.
By Ben Kitson, Head of Business Development at Precision Micro.
Graeme Donnelly, Founder & CEO of 1st Formations, on how small businesses can master cash flow and target growth
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As British small businesses navigate a landscape of rising digital subscriptions and fluctuating utility costs, many are overlooking thousands of pounds in potential savings. While large corporations chase complex R&D credits, many limited companies are often leaving money on the table through sheer habit.
In partnership with leading company formation agent, 1st Formations, we have identified 10 of the most effective, yet frequently ignored, financial hacks specifically tailored for UK SMEs.
As Graeme Donnelly, founder and CEO of 1st Formations, puts it: “In 2026, operational efficiency is the new profitability. Many directors are so focused on top-line growth that they ignore the ‘silent drain’ of legacy bank fees, incorrect VAT categories, and dormant software subscriptions. Saving £200 a month through smarter digital choices is the equivalent of adding thousands to your annual turnover without the cost of acquisition. It’s about being as lean as you are ambitious.”
1. The power of the ‘sector group’
Many directors believe the Federation of Small Businesses (FSB) or local Chambers of Commerce are only for established firms. In reality, the membership fee is often offset by the discounts they provide on business insurance, legal HR support, and software packages like Xero or Microsoft.
2. The voluntary VAT advantage
If your turnover is under the £90,000 threshold, you aren’t required to register for VAT, but doing so voluntarily allows you to reclaim VAT on everything from stock and web hosting to digital ads. While it does introduce an extra layer of administration, the ability to reclaim input VAT often far outweighs the effort involved. It also levels the playing field when pitching to larger corporate clients.
3. Stress-test your small businesses VAT flat rate
The VAT Flat Rate Scheme can significantly reduce your administrative burden, but many businesses are stuck in the wrong sector category. Reviewing your percentage, for instance 14.5% for IT consultancy vs. 7.5% for certain retail, could instantly boost your margins.
4. Hunt for ‘hyper-local’ micro-grants
While national grants get the headlines, local Growth Hubs and Local Enterprise Partnerships (LEPs) often have pots of £500–£5,000 earmarked for digital upgrades or energy efficiency. These are often poorly advertised but easier to secure than larger funds.
5. Kill the manual spreadsheet
Directors often miss out on tax deductions by forgetting small receipts. Using real-time scanning apps like Dext (for receipts), Pleo (for spending rules), or Expensify (for reimbursements) ensures every deductible expense is captured. Connecting these directly to your bank feed via QuickBooks or Xero turns a year-end headache into a streamlined process and makes bookkeeping easier.
6. Look beyond the “big four” banks for funding
Traditional loans are increasingly difficult for micro-companies to secure. Modern alternatives like Tide’s Funding Options, Uncapped (for revenue-based growth), or invoice finance platforms like Kriya offer the flexibility SMEs actually need without the long-term fixed commitments many traditional loans carry.
7. Ditch the merchant account legacy
If you’re still paying monthly rental fees for a card machine, you’re overpaying. Switching to fintech providers, such as Square, Zettle, or SumUp, eliminates fixed monthly costs and integrates sales data directly with your bookkeeping.
8. Master the ‘work from home’ deduction
If you run your limited company from home, you can charge relevant costs back to the business. These are essential business costs, such as a portion of your broadband bills, mobile phone contracts, and mileage or petrol costs.
Whether using the flat-rate method (£6/week) or a formal rental agreement to claim a portion of mortgage interest and utilities, ensure you are documenting this correctly to stay HMRC-compliant.
9. The quarterly subscription audit
The ‘SaaS drain’ is real. Using tools like Cledara to flag duplicate project management tools or unused licences can shave hundreds off your monthly outgoings. To ensure this doesn’t slip through the cracks, set a recurring calendar reminder to audit your tools every quarter. Always negotiate at renewal; most providers have “retention rates” they don’t advertise.
10. Stop paying for basic banking
Many small firms are still paying monthly fees for basic banking, something digital-first providers have all but eliminated. Digital-first banks, such as Starling or Monzo Business, offer fee-free banking with superior app integration, saving both money and administrative hours.
Jeremy Vianna, Vice President, Strategic Growth at Nearform explains how AI-native engineering (AINE) is rewriting software creation.
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Agile is no longer the differentiator it once was. In fact, it’s now table stakes, with nine in 10 organisations practicing it.
Agile originally emerged as a response to the rigid, adversarial Waterfall model, replacing years‑long requirement gathering and disappointing final releases with rapid iteration, continuous learning and tight alignment between business and technology. By the mid‑2010s, agile thinking spread beyond software into the broader enterprise, becoming a baseline practice, rather than a competitive differentiator – most teams now use it, differing only in execution quality.
Because Agile inherently keeps teams moving in the right direction through constant feedback, the real shift today isn’t about methodology, but about what AI‑native engineering introduces: a new step‑change in capability. Just as early adopters of Agile once dramatically outpaced those on Waterfall, organisations who adopt AI‑driven engineering practices can achieve a similar – but far greater – velocity advantage, amplified by machine‑speed iteration rather than human‑speed process.
The next competitive edge isn’t about how you run ceremonies, it’s about how you produce software – and that’s changing fast. AI-native engineering (AINE) is rewriting software creation. It’s not about using AI as a bolt-on, but instead as a new means of production for intelligent organisations.
The impact of this shift is already visible: early enterprise adopters of AINE report a 20% productivity lift across development and service functions, and some engineers adopting coding assistants noticed their productivity increase by 10-20%. That’s before you even account for agents and closed-loop learning.
What is AI-native engineering?
AI-native engineering is all about using AI tools to create AI solutions – resulting in systems that are built from the ground up, and designed to scale, with AI. The agents execute governed tasks, while the AI-native architecture compounds performance over time, ensuring the system keeps improving.
As an example, at Nearform, we recently embedded governed agents inside an AI-powered cross-product search for a global pharma client. This enabled usage to feed the adaptation of prompts, retrieval and policies. Naturally, relevance improved instantly. But the biggest impact was seen in the discovery timeline, which compressed from six weeks to just two, and the AWS infrastructure came up in minutes, instead of weeks.
But why is this relevant now? Because enterprises aren’t struggling with model accuracy anymore, they’re struggling with operationalising AI at scale. Most companies still haven’t been able to move pilots into measurable production value, only 26% have the capabilities to move beyond proof of concept, and 74% are still failing to realise tangible AI value. AINE is the missing operating model.
The new innovator’s dilemma
Unlike previous delivery models, AI-native engineering introduces compounding velocity. This means automated code generation and tests reduce release cycles from weeks to a matter of hours. Governed AI agents run multi-step workflows, keep context inside the system and reduce rework and handoffs. Meanwhile, continuous evaluation pushes improvements back into prompts, retrieval and policies.
Early AI-native engineering systems may look ‘worse’ on legacy control metrics, as they’re packed with unfamiliar governance paths. But AI-native startups, unburdened by process debt, adopt AI-native engineering from day one – driven by smaller, senior teams supported by streams of governed agents. This immediately results in higher velocity and less waste – and as tooling and methods mature, cost advantage and learning loops become an insurmountable advantage.
McKinsey’s State of AI report evidences this, showing how most organisations are still experimenting, while a minority of high performers – who are redesigning workflows – are realising outsized value.
Failing to adopt AI-native engineering risks the AI-edition of the innovator’s dilemma – protecting today’s governance and delivery model, while tomorrow’s competitors compound away from you.
AI-native engineering erodes yesterday’s moats
The old moats were legacy codebases, hard-won internal knowledge and proprietary data. AI-native engineering attacks each of these.
With AI-native engineering, automated refactoring and code generation significantly drop the cost of rebuild vs. maintain – eroding the value of legacy codebases. Similarly, copilots and agents encode decision history, meaning internal expertise becomes portable across teams, instead of being trapped inside handoffs. And the proprietary data advantage is narrowed by foundation models and synthetic data. In fact, foundation models already encode massive general knowledge, meaning smaller players aren’t starting from zero anymore.
We’ve also seen institutional knowledge become more portable. In the pharma use case above, copilots and agents codified decision history and evaluation criteria into the system, meaning context is able to travel with the work.
The barrier to high-performing systems is collapsing. It’s no longer about “who owns the most data” or what you’ve built – it’s about how fast you’re able to learn and improve.
The measurement problem nobody wants to admit
Currently, most CTOs trying to prove AI’s value are measuring the wrong things. Velocity, story points, lines of code, etc, are all proxies for human labour – friction points getting in the way of progress. When you move at machine speed, these measures collapse to zero. What actually matters is whether AI is solving the problem, not how fast a human would have solved it.
Agile teams often ask the business for time, trust and a year of dedicated resources, so they can ship iteratively, learn continuously and ultimately, deliver the most valuable outcome – without knowing upfront exactly what that will be. Finance however, works on annual planning and wants clear commitments on cost, scope and ROI at the outset, creating a long‑standing tension between agile delivery and fiscal predictability. Traditionally, software engineering could bridge this gap because it relied on decades of experience, solid estimation models and deterministic systems.
But AI-native engineering’s value is compounding. It’s not just seen in sprint velocity, it’s seen through the reduction of rework cycles, the acceleration of the second and third release after the first, and the rate of technical reduction debt over time. These are harder to measure in the short-term, and therefore often easier to dismiss – which is precisely why many organisations stay trapped in pilots. Not because the technology failed, but because large delivery models and metrics aren’t designed to capture compounding value, making it difficult to justify the next investment.
The CTOs realising true value aren’t necessarily those with the best agents, they’re the ones who started by instrumenting their workflows before introducing AI. This gives them a genuine baseline to measure against, meaning ROI conversations become more of a demonstration than a negotiation.
A pragmatic path forward
Start with a thin-slice in production: pick a workflow that has real P&L impact as a starting point. Then ship a governed agent and closed-loop evaluation and measure against the baseline.
Build the AI-native engineering backbone: introduce governance as code into the workflow, embed evaluation into CI/CD, and centralise shared memory to preserve context and knowledge across teams.
Reshape the talent mix: create senior-led pods that combine domain leaders with engineers who are fluent in agents, retrieval and testing automation.
Scale by compounding: each release becomes a reusable capability, which you can use to grow horizontally over time, into adjacent workflows.
AI-native engineering moves beyond bolting AI-features onto existing workflows, towards changing how you build. While Agile made delivery scalable for almost every organisation, AI-native engineering makes it compounding.
The organisations that internalise that now will set the pace for the next decade. The rest will be catching up… at human speed.
By Jeremy Vianna, Vice President, Strategic Growth, Nearform.
Hamish White, Founder and CEO of telecom firm Mobilise, tells us how a multitenant MVNE platform can launch a multi-brand mobile portfolio at speed.
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Enterprises established in managed connectivity, cloud communications and enterprise networking are extending into mobile to support digital-first MVNOs and IoT service providers. But what does this look like in practice? Here, Hamish White, founder and CEO of MVNE platform provider Mobilise, explains how a US technology firm deployed a multitenant MVNE platform to launch a multi-brand mobile portfolio at speed.
A leading US technology firm sought to extend its established portfolio into mobile services to support MVNO (Mobile Virtual Network Operator) partners. The timing aligned with industry dynamics that reduce barriers to market entry for MVNOs: GSMA Intelligence projects that “76 per cent of global smartphone connections will use eSIM by 2030”, with the US acting as an early catalyst following eSIM-only device launches, fostering the perfect environment for MVNOs to launch with ease and competitively.
The firm selected Mobilise to deliver the MVNE (Mobile Virtual Network Enabler) platform required to launch quickly, scale efficiently and meet the operational rigour required in the US market. This meant developing a solution designed from the outset to support multiple digital brands, unify operational control and provide the flexibility required to adapt to changing commercial models and regulatory requirements.
The challenge
Breaking into mobile at portfolio scale required more than network integration. It required a multitenant MVNE solution capable of onboarding and operating multiple MVNOs with distinct propositions without duplicating infrastructure or processes and integrate with tier-one US carrier AT&T.
This led to further complexity and a demanding set of essential requirements. The solution needed to connect seamlessly to AT&T’s network through asynchronous APIs while also incorporating intelligent IMEI-based device compatibility logic to guarantee clean activations and prevent unsupported device scenarios.
It had to deliver to a range of demands. This includes end-to-end provisioning workflows that mapped every step of activation with precision, accommodate complex porting — both in and out — in line with regulatory standards and embed robust reconciliation between billing, subscriber management and carrier-side systems to eliminate leakage and resolve discrepancies quickly. To preserve plan integrity and customer experience, it required dynamic features and bolt-on compatibility management so users could stack services without conflicts or performance degradation.
Above all, the architecture had to be scalable, supporting multi-MVNO operations and tens of thousands of subscriptions under a single orchestrated platform to enable growth without fragmenting tools or teams. This project had to enable growth at scale, delivering enterprise-grade reliability and transforming complexity into a strategic asset.
Making it happen
To meet these requirements, Mobilise implemented its HERO®MVNE Platform as a single, cloud-native, multi-tenant layer that unified multiple tools for the client and its MVNO partners.
HERO® is designed not simply as a connectivity layer, but as a complete MVNO enablement platform that combines carrier integration, product and pricing configuration, subscriber management, retention and customer engagement tools within a single, cloud-native environment. By consolidating what are often fragmented systems into one orchestrated stack, the platform reduces operational overhead, accelerates onboarding and lowers total cost of ownership for enterprises entering the mobile connectivity market.
Unlike traditional MVNE deployments that rely on separate legacy components stitched together over time, the multitenant architecture allows multiple MVNOs to operate within a shared infrastructure while maintaining distinct branding, propositions and commercial models. Configurable workflows ensure that each brand can tailor plans, bolt-ons and lifecycle journeys without duplicating systems or engineering effort: preserving agility while maintaining governance and control at the portfolio level.
The deployment was engineered to simplify mobile service delivery, support multiple MVNOs from one centralised interface and integrate smoothly with existing operations, replacing fragmented, per-brand stacks with shared, configurable workflows. By connecting to AT&T, the platform delivered reliable nationwide coverage from day one and exposed asynchronous interfaces that aligned with the carrier’s integration model, ensuring resilient activations and in-life changes at scale.
HERO®’s integrated analytics and reporting deliver real-time visibility into activations, revenue and subscriber behaviour, allowing enterprises and MVNO partners to optimise service offerings, reduce churn and make data-driven operational decisions.
By abstracting carrier complexity and managing event-driven communication flows internally, HERO® insulated MVNO partners from low-level network dependencies, enabling faster troubleshooting, more streamlined provisioning, and more predictable service delivery. This approach reduced operational risk while supporting high-volume activations across multiple brands simultaneously.
Once onboarded, each MVNO gained immediate access to the full set of enablement services needed to operate as a digital-first brand. The inclusion of white-labelled mobile apps and consumer self-service management interfaces empowers subscribers to manage accounts, activate eSIMs and purchase add-on services autonomously, reinforcing digital-first engagement while reducing operational load on MVNO support teams.
Partners integrated their existing systems through APIs, managed operations in a back-office CRM, acquired customers via a branded consumer website and empowered subscribers with a mobile app for self-care and account management. Taken together, these capabilities transformed a complex, multi-brand launch into a unified operating model that accelerated time-to-market while preserving reliability, compliance and customer experience.
A proven success
A year into operation, the results demonstrate that the platform met its objectives and scaled as intended. With HERO® MVNE in place, the enterprise successfully onboarded 25 MVNOs on one, unified platform, including eleven brands delivered with end-to-end web and mobile app experiences to support digital acquisition and self-care.
Over the course of 2025, the overall user base expanded by 360 per cent, reflecting sustained growth in partner activations and in-life adoption across the portfolio. The largest MVNO in the group grew 6.6x and average subscriptions per MVNO grew 3.2x, indicating that consolidation of carrier integration, operational workflows and customer experience tooling into a single MVNE environment can convert operational efficiency into measurable subscriber growth.
For enterprises already strong in connectivity and cloud, the lesson is clear — a multitenant MVNE is a growth engine that simplifies complexity and sustains expansion across consumer and IoT segments. The move towards more eSIM-centric activation, broader carrier support and standardised IoT provisioning will continue to favour digital MVNOs that can onboard, port and scale with minimal friction.
Robbie Tilleard, GM EMEA at Lorikeet, on why you don’t need a year, a team of twenty engineers, or a bespoke model trained on your data to deploy an AI in CX
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Revolut launched its AI financial assistant in April this year. Starling launched one three weeks before that. An in-app AI financial assistant has become table stakes for FinTechs overnight.
The good news is you don’t need a year to get there. All you need is a plan and the right data.
Eight Years or Eight Days
Revolut’s AI assistant took a year from announcement to launch, and Starling describes their assistant as the culmination of eight years of work. Both were building the infrastructure before it existed off-the-shelf.
FinTechs we work with deploy an AI assistant in weeks, not months. They don’t build from scratch. They buy infrastructure that’s already solved the hard parts… Knowing when to escalate, handling ambiguity without hallucinating, navigating the tone of a conversation where someone has had their card blocked and is not in the mood for corporate language.
Sound familiar? It should. Every technology shift in financial services has looked like this for a period. Early movers build bespoke, the rest wait for the case studies, and then someone works out you don’t need to build when you can buy much faster. Then it simply comes down to having the right data in place, connecting your systems, and putting in place a clear implementation plan. Financial services knows the playbook. The difference is that the loop has simply gotten a lot faster with AI.
Why Not Wait Longer Then?
Customer expectations have moved, shaped by AI interactions people have outside financial services (support queries answered in seconds, refunds processed mid-conversation), and the gap between ChatGPT responses and waiting for a queued ticket to a human agent is becoming visible in churn data. The FinTechs that move first will set the bar for what customers expect from anyone in the same category.
There is also a regulatory dimension. In the UK, the FCA moved Consumer Duty into more active supervision this year. The review published in March 2025 found that vulnerable customers continue to receive worse outcomes than other customers, particularly where firms have primarily digital customer journeys, and that most firms have underestimated the depth of outcomes monitoring required.
The reaction to AI in many compliance teams looks a lot like the reaction to autonomous vehicles. Every time a Waymo crashes, the genuine safety improvements (fewer accidents overall, faster hazard detection, no fatigue) get less coverage than the single incident.
Yet AI is going to help Consumer Duty over time, not hinder it. Autonomy with the right guardrails produces more consistent outcomes than human handling at scale. An AI system can understand a customer’s problem immediately, resolve it on the spot where it can, and route to the right internal team where it can’t, without queue times, without agent fatigue, without twenty different people interpreting the same policy differently. This ensures the core customer care team remains focused and can prioritise the cases with the most need. And this isn’t a far off future for consumers. The infrastructure to build it already exists off the shelf.
The European Dimension
There are additional points to consider if you operate in Europe. The EU AI Act’s full compliance requirements for high-risk AI sees financial services explicitly on the list.
Being compliant means documented risk management, transparency mechanisms, human oversight baked into the architecture and a traceable record for every decision that the system makes. The cost of getting this wrong is high: up to €35 million or 7% of global revenue for the most serious breaches.
Most organisations aren’t close to achieving requirements. More than likely they’ve rolled out AI as an experiment (that’s good!) but without a plan to get it scaled in production (not so good). Systems built purely to retrieve and respond weren’t designed with auditability or explainability in mind and it isn’t something you can bolt on later.
If you operate in Europe and have not mapped your current customer experience AI stack against these requirements, the time is now.
What You Actually Need
You don’t need a year, a team of twenty engineers, or a bespoke model trained on your data. You need focused use cases, infrastructure that handles the compliance layer, and a team willing to run a tight pilot with clear success criteria and a plan to scale.
You can move now. The companies that don’t are still lacing up.
Callum Pennington, CEO & Co-founder of HBHR, tells us why HR teams that don’t embrace AI risk being left behind.
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Across Europe, AI used in hiring, promotion, workforce management and performance evaluation, is being formally classified as ‘high-risk’ under the recent EU AI Act. HR is now on the regulatory front line. This year, most of the core rules for those systems will begin to apply, with further obligations phasing in through 2027.
That label is supposed to be a safeguard, but inside many HR teams it often lands more like a warning: if something is ‘high-risk’, it is safer to keep your hands off it altogether. Faced with new regulation, loud debate and limited capacity, many business leaders are quietly concluding that the safest option is to delay, restrict or avoid AI in HR altogether.
In my view, that instinct, however understandable, is now one of the biggest risks HR faces. Over-caution does not freeze risk, it freezes progress. The real choice for HR leaders is no longer ‘AI or no AI’. It is what kind of AI they use, under what controls, and with whom in charge.
High risk doesn’t mean ‘don’t touch‘
The EU AI Act organises systems by risk. At the top are prohibited practices, such as emotion recognition in workplaces or social scoring, which are simply banned. Below that sit the ‘high-risk’ systems, including many HR and people management tools, where stricter rules apply. These include documentation, human oversight, transparency and robust data governance.
On paper, that is a familiar pattern. Medical devices, credit scoring and critical infrastructure controls are all treated as high-risk too. The message isn’t ‘never use them’, it’s ‘treat them as important, design them carefully, and put them under proper governance’.
In HR, though, ‘high-risk’ can sound scary. If something goes wrong in a recruitment algorithm or workforce-planning tool, it is not hard to imagine the headlines. That fear is pushing some organisations towards a defensive posture, to park AI projects, ban tools outright, and stay in the comfort zone of manual decisions.
The problem is that ‘going manual’ isn’t the same as ‘being safe’. It simply hides risk better. Spreadsheets do not come with model cards or audit logs, but they can still embed bias, errors and inconsistency.
In many ways, this moment mirrors the shift from paper records to spreadsheets. At the time, some organisations worried that digital tools would introduce new risks. In reality, spreadsheets improved accuracy, visibility and accountability. AI represents a similar shift today — the difference being that well-designed systems can now surface risks earlier rather than burying them inside manual processes.
According to HBHRʼs own research drawing on a survey of 2,000 UK employees, ongoing manual payroll errors are already having an immense impact on the workforce. Twenty percent of workers say a single payslip error has caused them to miss a bill, while 18% report having to borrow money because of payroll mistakes.
A well designed, well documented AI system with human oversight is not the opposite of compliance. Increasingly, it is exactly how compliance will be demonstrated.
The hidden cost of over-caution
When organisations freeze on AI, they push more strain onto already stretched HR teams juggling legacy systems and manual workarounds. Modern tools are simply an expectation, with HBHRʼs research demonstrating that 85% of employees expect their employers to use up-to-date technology to minimise mistakes, with 72% saying that the technology their employer uses directly correlates to the confidence they feel in their pay being accurate and on time. Outdated legacy tools not only contribute to a lack of trust among employees, but create extra work and pain for employers.
You see it most clearly in high-volume processes, where recruiters spend days sifting through CVs, whilst payroll teams are forced to manually reconcile inputs, hoping nothing has been mistyped along the way. At the same time, boardrooms are being told that AI is a once-in-a-generation opportunity, and that countries like the UK face a huge economic gap if they fail to develop the right skills and adopt the right tools. HR simply cannot sit that conversation out and still claim to be a strategic partner.
Over-caution creates its own risk: higher error rates in core people processes, slower responses to regulatory change, and HR teams so buried in admin that they have no capacity left for culture, capability or workforce planning. These errors and barriers are not without consequence – 61% of employees surveyed by HBHR would look for a new job after six months of repeated payroll errors and delays.
Moving beyond ‘AI vs humans‘
Public debate often frames AI as a direct threat to HR roles, as algorithms that replace recruiters and chatbots that replace HR advisers. This narrative is just not true. Most HR teams I meet are not short of work, rather theyʼre short of capacity. The opportunity is a symbiotic HR function, where each does what it is best at.
In practical terms, AI is very good at repetitive, pattern-recognition tasks at scale. It can scan thousands of CVs for clearly defined, job-relevant criteria and hand recruiters a shortlist that is actually manageable. It can monitor payroll and pension data for anomalies, payments that do not match any live employee, or contributions that look out of line with policy, and flag them long before they become front-page stories. It can power assistants, like our own HRGenie at HBHR, that answers routine questions about holiday, pay and policies on demand, instead of sending employees into ticket queues.
People, by contrast, are good at context, empathy and ethical judgement. They are the ones who should decide whether a flagged pattern is a genuine risk or a perfectly reasonable exception, whether a candidate is the right fit for a team, whether a performance signal points to misconduct, burnout or a problem with the role itself.
The most effective HR functions I see are not those that automate everything they can, nor those that reject automation outright. They are the ones that deliberately design people-led, AI-supported processes, with humans making the calls that actually affect jobs, pay and progression.
From admin to engine
Across organisations, three clear camps are emerging in the approach to AI: those that use it with clear intent by starting with real operational problems, those that experiment widely but lack a coherent strategy and those that reject it outright as too risky. The third, overly cautious group is already beginning to fall behind, not because they lack talent, but because they lack the tools to scale it.
Everyone talks about wanting ‘strategic HR’. But strategy requires headroom and trustworthy data. If HR leaders are still spending most of their week reconciling numbers between three systems, or chasing down the source of basic discrepancies, it is almost impossible to play that strategic role.
The combination of the EU AI Act and accelerating workplace change makes this an inflection point. HR can either retreat into manual, reactive processes in the name of caution, or step forward and shape a people-led, AI-enabled function that is more resilient, more compliant and more human than what came before.
That does not mean turning HR into a testing ground for experimental tools. It means getting the foundations right: unified HR and payroll systems rather than fragmented stacks of disconnected tools, clear governance for AI, and HR leaders who are confident asking hard questions about how technology works, not just what the sales slide promises.
Handled thoughtfully, AI will not replace the ‘people’ side of HR. If anything, it will finally give HR teams the time, visibility and capacity to focus on it properly.
In an era where regulations are tightening, skills are shifting and expectations are rising, an overly cautious approach to AI in HR is no longer the safest option. Standing still may ultimately prove far riskier than moving forward thoughtfully.
Diederik Wirtz, Director of Business Development at Aryza, explains why your RCSA data contains far more intelligence than any quarterly heatmap conveys
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Every organisation running a Risk and Control Self-Assessment programme is sitting on a goldmine of intelligence. Most treat it like a compliance filing cabinet. Updated periodically, reviewed by committee, archived until the next cycle. Heatmaps get produced, RAG statuses get refreshed, and everyone moves on.
Meanwhile, the COO is trying to understand operational fragility, the CFO is modelling downside scenarios, and the CEO is preparing for a board challenge on risk appetite. All receive dashboards that tell them what happened, but almost nothing about what is likely to happen next.
This is the gap between compliance-grade GRC and enterprise-grade GRC. The difference is whether your risk and control data produces outputs executives can use to make decisions or simply confirms that an assessment process took place. The signals are already in your RCSA data, the question is whether your tools are designed to extract them.
The Problem with Snapshots
Traditional RCSA programmes produce point-in-time snapshots. A risk is assessed, a control evaluated, a residual score assigned. But snapshots tell you almost nothing about trajectory, volatility, or the compounding effects of interconnected control weaknesses.
Consider a risk assessed as “medium” with controls rated “effective” for four consecutive cycles while three of its five mitigating controls have seen their effectiveness scores decline marginally each time. No single assessment raises an alarm. But the trend line tells a different story: gradual erosion that will eventually result in a control environment that can no longer hold.
This is the slow drift, the first and most fundamental signal organisations miss. It doesn’t show up on a heatmap. But it is visible the moment you analyse RCSA data longitudinally. The executive insight is simple: “This process area has looked stable for two years, but the controls underpinning it are weakening at a rate that will become material within 12 months.” That is enterprise-grade intelligence. A static heatmap is not.
Correlation Patterns Hiding in Plain Sight
Most RCSA frameworks assess risks individually within assigned business areas. A control weakness in procurement is evaluated separately from a similar weakness in vendor management. Each looks manageable in isolation.
But when you map data across domains, clusters emerge. Control effectiveness scores for anything related to manual data handling might have declined across four different business units simultaneously, a pattern revealing a systemic issue invisible to siloed programmes. These cross-domain correlations are precisely what a COO needs when deciding where to invest in process improvement, or a CRO needs when presenting enterprise-wide exposure to the board.
The Overconfidence Indicator
When a business unit consistently rates it controls as highly effective while simultaneously reporting rising operational incidents or audit findings in the same risk category, that disconnect is one of the clearest indicators of assessment bias and it is remarkably common.
The data to identify this gap already exists. RCSA scores sit in the GRC platform. Incident data sits in the loss event database. Audit findings sit in the internal audit tracker. The challenge has always been bringing these datasets together. When you do, the mismatches become immediately apparent and points directly to the areas of your control environment most likely to fail under stress. For an executive, this is not a technical finding. It is a credibility issue.
RCSA: From Assessment to Simulation
The real step change comes when you move from descriptive analysis to predictive modelling. Monte Carlo simulation transforms RCSA utility by running thousands of scenarios against your actual assessment data, applying random variation within defined probability distributions to produce a range of probable outcomes rather than a single point estimate.
The practical applications are directly executive-relevant. In merger and integration planning, simulation allows executives to see the impact of colliding control environments before they materialise. For capital allocation, it reveals which control improvements deliver the greatest reduction in probable exposure, enabling resource decisions based on quantified impact rather than qualitative judgment. For regulatory stress testing, it provides evidence that controls have been tested against plausible scenarios, grounded in operational data.
Signals Most Organisations Miss
Several patterns consistently emerge when RCSA data is examined with greater rigour:
Concentration risk in control ownership — a small number of individuals responsible for a disproportionate share of highest-rated controls, creating single points of failure invisible to traditional reporting.
Assessment fatigue — scoring clustering around previous assessments as cycles progress, indicating the programme may be generating the appearance of oversight rather than reliable information.
Phantom controls — controls receiving regular effectiveness ratings that have never been independently tested or are linked to processes that have fundamentally changed since the control was designed.
Velocity mismatches — risk categories (cyber, regulatory change) evolving faster than the assessment cycle, monitoring them, signalling where continuous monitoring should replace periodic review.
Your RCSA data contains far more intelligence than any quarterly heatmap conveys. Monte Carlo simulation, longitudinal trend analysis, and cross-domain correlation mapping turn RCSA from a compliance exercise into genuine executive decision-support. The signals are already in your data. Analysis is what locates them.
Dmitry Panenkov, founder and CEO of emma, the cloud management platform, explains how to find the path out of accidental multi-cloud chaos.
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Multi-cloud refers to the practice of using services from two or more cloud providers, such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI), within the same organisation. Rather than hosting all applications, workloads and data in a single environment, companies distribute them across several platforms. In theory, this approach offers greater flexibility, reduced vendor lock-in and the ability to run every workload in its most optimal environment.
However, while multi-cloud is often promoted as a strategic advantage, very few organisations adopt it intentionally. One team may choose a cloud for customer-facing applications, another may favour a different provider for analytics, and a third may adopt specialised cloud services for AI workloads. Over time, this results in a multi-cloud footprint that was never part of a deliberate plan. This organic expansion creates operational blind spots that accumulate quietly and grow larger if they are not addressed with purpose.
Multi-cloud as a double-edged sword
Multi-cloud itself is not the enemy. When executed intentionally, it offers genuine advantages such as improved resilience, performance optimisation, regulatory compliance and freedom from reliance on a single vendor. However, when these environments develop without a unified approach to management, the complexity becomes its own form of technical debt.
As workloads become distributed across several providers, visibility deteriorates quickly. Teams lose a clear view of what is running, how it’s performing and what it costs. Instead of gaining agility, organisations often find themselves spending more time reconciling dashboards, invoices and operational processes. Decisions that should be straightforward become slow and difficult because no one has a complete picture. At that point, the flexibility initially promised by multi-cloud becomes a bottleneck.
The operational challenges organisations encounter
Several recurring pain points appear as companies scale across multiple cloud platforms, especially when no single team owns the full multi-cloud picture.
Governance fragmentation
Each cloud platform comes with its own identity system, policy engine, security defaults and tagging requirements. Without one centralised governance framework, policies drift, access controls become inconsistent, and compliance gaps appear. Because no single cloud provider is built to work natively with another, these inconsistencies compound over time.
Lost cost discipline
Cloud billing models differ dramatically across providers. Without centralised cost visibility, finance teams struggle to normalise invoices, and engineering teams lack real-time insight into what their deployments actually cost. As unused resources accumulate and workloads are placed without a financial context, waste becomes unavoidable.
Partial observability
Monitoring tools may work well within a single platform, but they are rarely designed to provide a holistic view across several clouds. With logs, metrics, alerts and traces scattered across multiple systems, incident response slows down. Operational teams lack a complete view of performance, utilisation and dependencies.
Higher operational overhead
When each cloud requires different skills, automation patterns and deployment approaches, the operational load increases dramatically. Engineers spend more time learning platform-specific quirks and troubleshooting subtle configuration differences and less time building new features.
How to regain clarity before flexibility turns into a bottleneck
The path out of accidental multi-cloud chaos isn’t consolidation. Multi-cloud environments will only continue to grow as AI accelerates, regulatory requirements tighten, and organisations seek best-of-breed capabilities. Instead, the solution is to create a unified way to manage it, even if the underlying infrastructure remains distributed.
There are three proactive steps leaders can take to regain control:
1. Establish a single source of truth for visibility
A centralised platform that aggregates resource inventories, performance data, cost insights and security status across all cloud environments restores the transparency teams have lost. When all teams have the same real-time view, decisions become faster and more accurate.
2. Rebuild governance into a cross-cloud framework
Rather than applying policies cloud by cloud, organisations should enforce consistent identity, access control, tagging, encryption and compliance rules across all environments. This ensures that multi-cloud does not mean multi-policy.
3. Standardise operations through a single control layer
By adopting a platform-agnostic control layer, organisations can deploy, scale, secure and govern workloads consistently. This restores operational efficiency, reduces risk and helps teams regain confidence in their multi-cloud architecture.
The future of multi-cloud
Multi-cloud is shifting from an accidental architectural outcome to a deliberate, strategic model. In the next few years, cloud-agnostic platforms will play a central role by providing unified layers for deployment, governance and cost optimisation across all providers. These platforms will reduce the need for cloud-specific tooling and give teams consistent control over distributed environments.
AI will transform workload placement. Instead of relying on manual decisions, organisations will increasingly use machine learning to automatically select the most efficient cloud for each workload based on real-time variables such as latency, pricing, resource availability and compliance requirements. This will make workload optimisation faster, more accurate and cost-effective.
At the same time, advances in workload mobility, as well as the growing availability of sovereign cloud options, will allow applications to move between providers with minimal friction. This will support dynamic optimisation and ensure organisations can meet region-specific compliance obligations.
As these trends converge, multi-cloud environments will become increasingly autonomous, intelligent and compliance-driven.
Multi-cloud isn’t the enemy; unmanaged complexity is
The industry often talks about multi-cloud as though it is inherently complex, but the real complexity comes from using multiple clouds without a clear management strategy, governance model or unified operational foundation. Multi-cloud remains a powerful approach that enables choice, resilience, innovation and compliance. However, without visibility and control, the very flexibility that makes it attractive becomes a source of risk.
Organisations that address these issues today will eliminate the blind spots that have built up over time. More importantly, they will transform multi-cloud from an accidental by-product of organic growth into a strategic capability that drives long-term success.
Cirata CEO Stephen Kelly tells us why having fully centralised data is the key to creating seamless AI access for companies.
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MIT reported that up to 95% of enterprise AI projects fail. Businesses are racing to adopt the technology and rushing execution in the process, significantly eroding ROI and potentially leaving thousands of businesses at risk of regulatory exposure.
Despite the urgency, there lies an invisible burden which is undermining progress. It is called AI debt and it may be the single greatest obstacle standing between AI ambitions and commercial reality.
AI debt is the accumulated result of incomplete digital transformation. It is every decision which meant legacy infrastructure was never fully retired, or the fragmented data siloes that were never unified. Any new platforms layered on top of such large and complex data sets that haven’t been organised properly, are creating complexity rather than clarity.
On their own, these shortcuts may have seemed pragmatic but collectively, they are now stalling innovation.
The risk of unfinished business
Recent analysis from McKinsey highlights the scale of the missed opportunity. Despite AI tools becoming commonplace today, 63% of organisations reported that they are still experimenting or piloting early-stage AI projects. This shows that most organisations are yet to embed AI deeply enough into their workflows and processes to capture its full value, estimated globally at between $2.6 trillion and $4.4 trillion.
The number one reason for this is years of bolt-on systems that have created tangled IT estates that slow decision-making and make rapid innovation nearly impossible. Running legacy and modern environments side by side inflates maintenance costs and introduces operational confusion which can result in failed implementations. These poorly executed migrations waste capital and introduce security and compliance risk, particularly under regulations such as General Data Protection Regulation (GDPR) and Digital Operational Resilience Act (DORA).
These consequences are measurable. Projects are delayed by months, which has a knock-on effect for budgets. Overall, the whole process inevitably grinds to a standstill because the data required to fuel AI models remains locked away in silos. Estimates suggest that between 50 and 70 per cent of enterprise data remains unconnected and inaccessible for advanced analytics.
The rise of AI debt
The push towards autonomous systems capable of independent decision-making is amplifying this risk of failure. While a majority of organisations plan to deploy AI agents in the near term, only a fraction have centralised their data or ensured their infrastructure can handle the projected surge in workloads.
The statistics are sobering. A recent report from Cisco found that fewer than one in five companies have fully centralised their data for seamless AI access. Over 60 per cent expect workloads to increase by more than 30 per cent within the next few years. Less than a third feel fully prepared to secure agentic AI systems against emerging threats.
Even the most digitally advanced firms are grappling with spiralling compute costs and persistent talent shortages in cybersecurity and AI engineering. In the same way that technical debt slowed software development in the 1990s and 2000s, AI infrastructure debt threatens to stall the current wave of transformation before it delivers meaningful returns.
At its core, AI debt is a data problem. AI systems amplify whatever they are trained on. If the data is incomplete or contextually degraded, the outputs will be flawed, often in ways that appear plausible but lack integrity. This phenomenon, sometimes described as AI slop, is not merely a technical nuisance but a commercial and reputational risk.
This occurs when organisations migrate or modernise without preserving metadata, lineage and governance and so its meaning is lost along with trust. In regulated industries, that erosion has legal implications. In competitive markets, it has revenue implications.
The path forward requires paying down the debt.
Paying off AI debt
At Cirata, we always advise that the best way to eliminate AI debt is to address fragmentation at its source. This means employing a system that can create a unified, interoperable data foundation that supports AI at scale. By decoupling data orchestration from underlying infrastructure, organisations can move, replicate and integrate data seamlessly across on-premises, hybrid and multi-cloud environments without disrupting production systems.
This approach delivers several strategic advantages. Automated data flows across clouds and platforms ensure models are trained and updated with the latest data. Businesses should always look to leverage open standards, such as Apache Iceberg, to prevent vendor lock-in and preserve long-term flexibility.
IT leaders should explore solutions to help them make sense of their data. By centralising governance and eliminating brittle integrations, organisations can feel confident they’ll be on the right side of AI project success. Most importantly, they can break the cycle of making short-term compromises that accumulate into long-term risk.
No algorithm will compensate for structural weakness
The promise of AI remains immense. Autonomous systems and generative models will continue to reshape industries. But no algorithm can compensate for a weak foundation. Just as a building requires structural integrity before additional floors are added, AI requires a unified and trusted data infrastructure before it can deliver sustained value. The organisations that thrive in 2026 and beyond will not be those that launched the most pilots. They will be those that had the discipline to eliminate their AI debt first.
Luke Trayfoot, Global Head of Strategic Partnerships at YouLend, on how embedded finance can help create a more resilient and inclusive lending ecosystem for SMEs
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Bank‑to‑business lending growth is expected to halve to just 3.5% this year, driven by global tensions, higher funding costs and ongoing economic uncertainty. For many small and medium‑sized enterprises (SMEs), this means tighter credit conditions and a growing risk of a funding gap. And at a time when fast, flexible capital is essential.
Traditional lenders will remain central to SME finance, but slower lending growth naturally limits how quickly banks can meet demand. SMEs often need capital at short notice to manage cash flow, invest in stock or respond to new opportunities. When bank lending slows, the pressure on these businesses increases. This is where alternative lenders and embedded finance providers are stepping in, offering models that work alongside the traditional system to ensure SMEs still have access to funding when they need it most.
A New Reality for SME Embedded Finance?
The slowdown in bank lending does not mean traditional finance is stepping back from the SME sector. UK Finance data shows that while gross SME lending rose for the second consecutive year in 2025, approval volumes have begun to flatten. Meanwhile, average loan sizes are trending downward, which signals that traditional lending capacity is tightening. What this really highlights is the need for a more diversified and resilient lending ecosystem. Alternative lenders, from online credit platforms to embedded finance providers, are becoming an important part of that shift by offering additional, data‑driven routes to capital.
These lenders are not here to replace banks. They are absorbing the demand that banks cannot meet quickly enough. Especially for SMEs that need fast decisions or more flexible repayment options. By using real‑time business performance data, alternative lenders can assess risk in a more dynamic way and offer funding that reflects how SMEs actually trade, rather than relying solely on historical, static credit files.
This becomes particularly valuable during periods of economic uncertainty. When traditional credit conditions tighten, SMEs with strong underlying performance can still access the capital they need, which helps prevent stalled growth or operational disruption.
Platforms as Distribution Hubs
E‑commerce marketplaces, payment providers and business software platforms are quickly becoming some of the most important channels for SME finance. A trend reflected in the scale of the market, with global embedded finance transactions projected to exceed $7 trillion by the end of 2026. These platforms sit at the centre of day‑to‑day business activity, which gives them a clear view of trading patterns, cash flow and overall performance. Because of that, they are in a strong position to offer funding at the exact moment a business needs it, whether that is during checkout, inside a dashboard or alongside a payment settlement.
For SMEs, this creates a much smoother path to capital. They can access funding without the paperwork or delays that often come with traditional loan applications. For platforms, it deepens customer relationships and opens the door to new value‑added services that support long‑term loyalty.
The Infrastructure Powering Embedded SME Finance
Behind the scenes, specialised FinTech providers supply the underwriting, risk modelling and compliance infrastructure that allows capital to move responsibly through non-financial channels. This infrastructure layer is what enables these business platforms to offer financing without becoming lenders themselves, while ensuring SMEs receive funding that is both fast and sustainable. It’s also creating a more standardised, interoperable foundation for SME credit delivery across the digital economy.
Government data shows that late payments continue to impact the UK economy to the tune of £11 billion annually, which creates a significant cash‑flow friction. By combining platform‑level insights with advanced risk analytics, embedded finance providers can tailor funding to real‑time business performance. This reduces default risk, improves capital efficiency and strengthens the resilience of the wider SME lending ecosystem, ultimately leading to better outcomes for both SMEs and the capital providers supporting them.
Smarter Underwriting is Becoming the Backbone of SME Finance
Real‑time performance data and AI‑enabled underwriting are reshaping SME finance by making funding decisions more accurate, more inclusive and more responsive to how businesses actually operate. Instead of relying solely on traditional credit scores, lenders can assess SMEs based on real trading activity such as sales patterns, seasonality and customer behaviour. This moves underwriting closer to the operational reality of a business, rather than a backwards-looking snapshot.
This approach opens the door for more businesses to access capital, including those that may be underserved by conventional credit models. It also helps ensure funding decisions remain stable even when market conditions are volatile, supporting business continuity and long‑term resilience. As these models continue to mature, they are becoming a core part of how lenders manage risk, price capital and build a more adaptive SME finance ecosystem.
Where SME Finance Goes from Here
As traditional lending growth slows, there is a real opportunity to build stronger partnerships between banks, FinTechs and digital platforms so SMEs can continue to access the capital they need. Embedded finance is becoming a mainstream, complementary channel that broadens access, speeds up decision‑making and supports day‑to‑day business growth.
The priority now is scaling these models responsibly. That means keeping transparency front and centre, maintaining strong risk frameworks and ensuring long‑term stability as more capital flows through embedded channels. If the industry can combine the strengths of traditional finance with the agility of modern FinTech infrastructure, we can create a more resilient and inclusive lending ecosystem for the SMEs that drive economic growth.
Errol Rodericks, Director of product marketing EMEA and LATAM at Denodo, on why the future of insurance will be defined by whether humans and AI agents have the right data, in the right form, to make the right decisions
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AI adoption across the UK insurance sector continues to accelerate, yet the impact is falling short of the industry’s expectations. The narrative is now shifting beyond systems that analyse data and generate recommendations towards agentic AI. Capable of taking action, whether that means initiating claims processes, identifying potential fraud in real time, refining underwriting decisions or triggering next-best actions. Many see this as the next major leap forward for insurance, and they may be correct, but not for the reasons most people think.
While AI development certainly doesn’t lack pace, most of the insurance industry remains constrained by a more fundamental issue. AI cannot make trusted business decisions until it first understands the business. That understanding depends on trusted, relevant data being delivered in the right context and at the right time. Without it, insurers will struggle to give AI systems meaningful autonomy, however advanced the models become.
This is not because insurers lack data or technology. Over the past decade, the industry has invested heavily in data lakes, advanced analytics and AI tools, and integration and data engineering pipelines. Yet despite these investments, many organisations continue to struggle to move AI beyond proof-of-concept projects and into day-to-day operations.
Meeting the Challenge
The challenge is not data availability. It is ensuring data is trusted, relevant and readily accessible when decisions need to be made.
Few industries experience this challenge quite like the insurance industry. Decision-making depends on information drawn from multiple policy, claims and customer systems, alongside external data sources such as telematics, weather and credit data. When that information is fragmented or delayed, even the most advanced AI systems are left working with an incomplete picture, making it difficult for AI to understand the wider business context behind every decision.
Agentic AI does not solve this problem. It exposes it.
Access Alone Is Not Enough
Many organisations respond by building a shared data foundation consisting of a unified layer where humans and AI agents can access the same information. While this is directionally right, it is incomplete. The challenge is not that organisations lack a shared data layer. They struggle to deliver the right version of data for each decision, at the moment it matters.
Insurance operates on multiple, decision-specific views of data, each with distinct requirements:
Claims decisions depend on real-time, enriched incident data.
Underwriting relies on forward-looking risk models and external signals.
Fraud detection requires cross-entity patterns and behavioural analysis.
Customer servicing depends on a simplified, current policyholder context.
These are not variations of the same dataset; they are purpose-built representations of data, shaped by different latency, governance, and semantic needs, which becomes even more critical with agentic AI. Different agents operate at different points in the decision lifecycle, and require different data, in different forms, at different times.
A shared data layer can improve access to information, but access alone does not guarantee better decisions. Context transforms data into business understanding, and business understanding is what enables trusted decisions.
Turning Data Into Action
This is where many AI strategies stall. Most architectures are designed to store, process, and analyse data, but not to activate it at the point of decision. There is a fundamental gap between data being available and data being usable within real-time workflows.
Agentic AI operates directly in this gap. Without access to live, governed, and contextually aligned data, agents operate with partial understanding, and their outputs become unreliable. This is why many AI initiatives remain stuck in experimentation.
To move forward, insurers need to rethink how data is delivered. Not as raw datasets or reports but as data products. A reusable, governed, and outcome-aligned data asset designed to support a specific decision or workflow is what’s needed. Instead of exposing raw data, insurers should deliver contextualised, decision-ready views, with embedded governance and policy controls, consistent business semantics, and real-time access to internal and external sources.
For example:
A claims data product unifying FNOL, policy data, repair estimates, and external signals.
A fraud data product combining claims history, network relationships, and behavioural indicators.
An underwriting data product integrating internal risk data with third-party enrichment.
These are not static datasets. They are decision-ready data assets, designed to deliver the right information, in the right context, for a specific business outcome.
Why Data Quality Matters Now More Than Ever
For agentic AI to deliver value, data must be live, governed at access, semantically consistent, and traceable. This is where a logical data layer becomes critical, not just as an integration approach, but as a way to connect distributed data in real time, apply governance dynamically, and deliver consistent, business-ready views across systems. This enables both humans and AI agents to act with confidence, without introducing further fragmentation.
The insurers that lead in 2026 will not be those with the most advanced models. They will be the ones that connect AI directly to business outcomes. That means starting with the outcome, such as reducing claims cycle time, improving fraud detection, increasing underwriting precision, or enhancing customer experience, and working backwards to define the decisions, data and systems required to support them.
This is how AI moves from experimentation to operational impact.
Where AI Initiatives Succeed or Fail
The next phase of AI in insurance will not be defined by advances in model performance. It will be determined by how well AI understands the business it is supporting. That requires trusted, relevant data, but it also needs the business context that allows AI to interpret that data correctly and make decisions insurers can trust.
Agentic AI accelerates this realisation. It makes clear that data must be trusted, contextual, available at the moment of decision, and aligned to outcomes. The goal is not simply to give AI more information. It is to help AI understand how the business works well enough to make confident, consistent decisions. Those who solve this will scale AI successfully, and those who do not will continue to pilot without transformation.
The future of insurance will not be defined by whether humans and AI agents share the same data. It will be defined by whether they have the right data, in the right form, to make the right decisions. That requires a shift from shared data to decision-ready data, from access to activation, and from experimentation to measurable outcomes. The real inflection point for AI in insurance will come when organisations enable AI to understand the business well enough to make decisions that customers, employees, and regulators can trust.
Hugh Scantlebury, CEO and Founder of Aqilla , on why the finance teams that benefit most from AI will likely be the ones that strike the right balance between automation and oversight
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At first glance, finance and accounting appear to be ideal environments for AI integration. The work is structured, rules-driven and built on numerical data, which AI can automate and process at scale and speed. As such, it’s ideal for much of the repetitive work — such as invoice capture, reconciliations, reporting, and anomaly detection. These tasks still consume so much time and reduce space and capacity for strategic and creative thinking.
But as confidence in AI grows across the sector, and as the technology is integrated into accounting and finance software, is there a risk that organisations once fearful of the technology may go to the other extreme? What might happen if they lean so deeply into AI that finance and accounting professionals become distant and removed from the numbers?
These questions matter because the decisions that sit behind the numbers are rarely driven by pure logic. Financial strategy is shaped by risk appetite, leadership judgement, organisational priorities and sometimes even internal politics.
So many entrepreneurial success stories include a fateful risk, gamble or moment of inspiration that defies established financial wisdom. A founder deciding whether to invest in growth or a charity balancing financial sustainability with its mission does not rely on numbers alone. That means a surprisingly high number of commercial decisions have a human dimension that AI cannot, and arguably should not, replace.
Balancing AI and Human Strengths
So how can organisations maintain the human intuition and instinct that sits behind so many corporate transactions while embracing AI? The answer is to use the technology to remove repetition rather than people from core financial processes. In practical terms, that means using automation to reduce cognitive load so people can focus on interpretation, creativity and decision-making — the human parts of finance and accounting.
That’s a sensible approach because poorly implemented automation accelerates errors and obscures decision-making processes. It can also cut humans out of the process exactly at the point where instincts and experience are most needed. In that situation, AI-enabled systems simply become faster at making poor decisions. And those poor decisions end up costing time as well as money.
Once that happens, the space, time and resources that finance and accounting leaders are trying to create for more strategic work will rapidly shrink. By contrast, when humans actively guide AI systems, review outputs and set boundaries, automation becomes a powerful extension of human capability rather than a substitute for it.
The Limits of Automation in Decision-Making
In finance and accounting, numbers often create a sense of objectivity and certainty. But financial reporting still involves interpretation, context and judgement. A technically correct output is not always the same thing as the right commercial decision for a business, its employees or its long-term strategy.
As such, it’s important that accounting and finance professionals at every level do not lose a grip on their data when engaging with AI and automation. Aside from losing an understanding of the systems and processes behind the outputs, there’s still an ethical responsibility to deploy AI in a way that preserves human oversight, authority and compliance in financial reporting. That’s because, for the first time, we’re asking technology, in the form of AI, to provide an opinion on our data — not just deliver the logic and the numbers.
For that reason, finance leaders still need visibility into how AI-generated outputs are reached, the ability to challenge them when necessary, and a clear understanding of the underlying data behind the results. That’s important because AI output is ultimately based on prediction, and prediction is not the same as established and quantifiable truth.
Keeping Score
One possible middle ground is confidence scoring and validation workflows. Rather than unquestioningly trusting every AI-generated output, organisations can introduce processes that flag lower-confidence results for human review before action is taken. That creates a more balanced relationship between automation and oversight, while also giving finance teams clearer visibility into how reliable or complete AI-generated outputs actually are. The goal should be confidence in AI-supported workflows, not unquestioning reliance.
That visibility, however, should not sit solely with grads and junior finance staff. They need to understand the manual calculations and processes sitting behind automated systems so they can properly challenge the results. But the same principle applies at senior levels too. Experience and seniority should not create distance from the underlying logic behind the numbers. If anything, AI makes that visibility even more important.
Otherwise, organisations risk creating the worst of both worlds: juniors who can’t challenge AI outputs because they haven’t learned the manual processes, and complacent seniors who know the manual systems and assume AI is following them. It means organisations can end up with more information at their fingertips than ever before, while simultaneously becoming more detached from the underlying data and logic behind it.
That risk becomes even more significant at senior levels, where financial decisions often carry wider operational, commercial and strategic consequences. The more detached leaders become from the logic behind the outputs, the greater the impact when reliability or credibility issues emerge within the data.
Conclusion
Productivity gains from AI and automation have the potential to create more space for higher-value thinking rather than remove people from the process. The information AI surfaces can ultimately help senior leaders make more creative and strategic decisions by revealing connections, patterns and insights that may previously have remained hidden within the data.
Leaders have always relied on summaries, dashboards, and reporting layers to help them make decisions. But AI dramatically widens the gap between decision-makers and the operational reality beneath the numbers. The danger is not simply inaccurate data. It’s overconfidence. When systems appear highly intelligent and highly efficient, organisations can gradually stop questioning how conclusions are reached in the first place.
Ultimately, organisations may wish to focus on people-led automation rather than handing complete control to systems. The goal should be confidence in AI-supported workflows, not unswerving reliance on automated outputs — with AI acting as an extension of human capability rather than a replacement for judgement.
The finance teams that benefit most from AI will likely be the ones that strike the right balance between automation and oversight. Hand over the repetition and the manual processing, but don’t lose visibility into the data itself. Because if organisations surrender that understanding completely, all the entrepreneurial instinct, creativity and commercial judgement in the world may no longer be enough to compensate for the decisions being made underneath them.
Louis Landry, Chief Technology Officer at Teradata explains why it’s an exciting time for enterprises who are leveraging agents to transform their processes.
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Technological advances such as agentic AI have completely changed the way enterprises work for the better, but they have also posed several challenges. Businesses are not struggling with AI because the technology isn’t ready, but because the infrastructure beneath it isn’t.
Several demonstrations will have you believe that AI implementation is just another straightforward process, but this is not the case at all. Such presentations are impressive because the data is already polished, the queries are direct, and the answers are predictable, while the overall environment is controlled. But this is not the enterprise reality.
The typical enterprise runs multiple different SaaS applications, each with its own platform, data models and methods for showcasing the same business concepts. Not only that but they’re layered on top of millions of relationships and contextual rules that no demo was ever designed to handle. As a result of the complex state some enterprises’ systems are in, most of their AI adoption projects end up stalling or failing. This was also confirmed by last year’s MIT report which stated that 95% of businesses don’t see a return on their AI investment despite spending $30 to $40 billion.
So what are so many enterprises doing wrong and how can they revert it?
What’s hindering enterprises’ AI journey
Most AI models are impressive in isolation, but an enterprise environment doesn’t operate in siloes. Businesses have layered systems, interdependencies and nuanced rules that AI models will need to be able to support, otherwise they’ll fall short. Without the ability to act autonomously, they will not be able to provide meaningful change to the business.
With this in mind, a successful AI deployment needs proper orchestration. The 5% of enterprises that are winning this race coordinate their AI agents to own different areas within the business and come together through an integrated foundation instead of depending on a single model for everything. Successful enterprises see AI as a strategic differentiator, grounded in integrated, proprietary datasets that competitors can’t duplicate. They also ensure their systems are following the business objectives and operational limitations, as well as compliance requirements and competitive pressures.
AI autonomy in four levels
In terms of what successful enterprises have in common, they are all in what I refer to as the “AI autonomy journey” where they usually go through four different levels to build a robust foundation that transforms agentic AI deployments to capable and trusted advisors. Each business will achieve different levels of autonomy depending on how technologically advanced they are, their complexity and business value.
Level 1
Looking into these levels in more detail, the first stage is where most businesses sit today. Their AI systems are taught to respond to basic interactions in natural language and collect data, though humans are still needed to validate the results.
Level 2
The next level sees AI tools taking a more trusted analyst position. They start to comprehend context and intricacies while understanding connections between datasets. Such systems are able to recognise business terminologies and manage scenarios independently.
Here’s an example to help you visualise the two levels. An enterprise in the banking sector wants to understand its loan repayment rates across different customer segments and product types. A level one system will be able to retrieve and share the repayment figures with the exact criteria, while a level two system will not only gather the numbers, but will also flag which customer profiles are showing signs of risk and recommend next steps for the analyst. This stage goes beyond simply reporting figures, as it is able to translate complex financial patterns into clear and actionable intelligence.
Level 3
Then we move on to level three, which is a significant turning point for an enterprise’s AI autonomy level. At this stage, the technology is able to make connections across your business and recommend actions with insights, including retention strategies, adjusting contract terms or raising potential risks.
Level 4
And finally, at level four, we see AI stop advising and instead start acting. For example, if you prompt it to optimise customer retention while keeping margins at a certain point the system will autonomously identify at-risk customers, deploy the right strategies and track the results while adjusting its tactics in real-time. With that said, employees are still in control of defining the goals and setting the risk tolerance levels and compliance requirements.
The above levels reveal a clear progression. If level one is “prompt and prove” and level two is “prompt and trust,” then level three is “prompt, understand and suggest” and level four is “define, deploy, adapt”. Through this autonomous journey, the system gradually becomes an intelligent business analyst that actively improves how decisions are made, enabling the business to operate at a scale that simply wasn’t possible before.
The road to competitive advantage
As enterprises start exploring what their AI autonomy journey looks like, we will also see a gap forming between businesses at different stages. Companies moving on to higher levels of AI autonomy will gain real competitive advantage much faster than others. Having said that, achieving this isn’t as simple as a matter of deploying more powerful AI models. It requires a robust knowledge base that AI systems can actually depend on, otherwise they become unreliable and decisions get misaligned. This is where context engineering comes into play as a critical tool helping autonomous agents become more accurate and useful, and shaping how AI systems interact with the broader business. Context engineering also enables agents to perform complex tasks without worrying about errors coming up in the process.
It’s an exciting time for enterprises who are leveraging agents to transform their processes. The ones who are successful in their adoption will be those who understand early on that AI is only as powerful as the foundation it sits on. This means that it’s crucial to get the datasets, context and orchestration right from the beginning, to be able to progress with your AI autonomy journey and set yourself apart from competition.
Sascha Giese, Tech Evangelist at SolarWinds talks to us about how to manage the transition from AI experimentation to delivery.
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When Johnson & Johnson revealed a shift in its AI strategy last year, it signalled the end of a period of experimentation for the pharmaceutical giant and the beginning of a more disciplined, results-driven era.
At its peak, J&J employees were pursuing nearly 900 individual AI-related use cases. But as the WSJ reported at the time, this was a position that was simply unsustainable. Instead, the company decided to change tack and home in on high-value generative AI use cases in areas such as drug discovery and supply chains.
For many in the tech sector, this was a high-profile example of a business deciding to call time on pilots and trials in favour of a more structured approach where AI finally has to earn its keep.
Fast forward to the beginning of 2026, and the State of AI in the Enterprise report by the Deloitte AI Institute suggests that many companies are also following a similar path, with business leaders becoming impatient and wanting to see a return on their investment.
AI is shifting from a one-off investment to an ongoing operational expense
And it’s easy to see why. Amid the current AI boom, a recent report by Mavvrik, a US-based IT financial management platform, found that 80% of enterprises missed their AI infrastructure cost forecasts by more than 25%. It claimed that AI costs are “crushing margins” and that AI-related overheads are harder to manage than cloud costs because AI introduces new variables where “minor changes in usage can spike spend by 100x”.
It’s a good point. Unlike traditional software, which tends to follow predictable instructions, AI systems explore multiple possible paths to reach a solution. Sometimes that could mean resolving an issue in five minutes. At other times, it might mean AI systems retrying, looping and testing alternatives for hours, leading to additional expense.
But there are other unforeseen costs as well. The dash to embed AI can often expose shortcomings in existing IT infrastructure. Legacy systems and on-prem environments, for example, that might have been perfectly suited to a pre-AI world may now lack the necessary processing capacity required.
What rightsizing AI adoption really looks like
As a result, this may force organisations to bring forward plans to upgrade their technology. But at what cost? It’s not simply a case of writing a cheque and flicking a switch. In practice, it means being clear about the task AI is meant to improve, and defining measurable indicators and a baseline against which to judge impact.
But rolling out AI isn’t just about the technology. One of the lessons we’ve all learned over the last couple of years is that if workflows are unclear or the quality of data is poor, then AI will expose those shortcomings. Without a proper assessment of whether the company is ready for AI, such a project could quickly turn out to be unsuccessful, becoming a time and money sink.
Equally, if AI is embedded into structured environments – with defined responsibilities and feedback loops – then we also know that AI can genuinely improve outcomes.
For instance, a recent report by SolarWinds sought to understand how generative AI (GenAI) has been incorporated into ITSM (IT Service Management) workflows. It focused on those areas within helpdesks designed to reduce manual effort, such as automatically suggesting ticket responses, sourcing relevant knowledge base articles and generating incident summaries.
The report wanted to discover whether AI was genuinely making life easier for IT teams or merely adding another layer of complexity. The findings showed helpdesks saw a significant decrease in average incident resolution time after enabling the GenAI features.
Savings and Benefits
On its own, that saving of just under five hours per ticket – or just under 20% of the time spent per support request – is impressive. But it’s only when you multiply that efficiency gain across the hundreds, if not thousands, of tickets generated each year that the true scale of AI’s impact becomes clear.
While the savings clearly point to GenAI’s benefits, the report also highlighted a common thread around that all-important pivot from pilot to operations. Instead of viewing GenAI as a test or side project, those teams that integrated AI tools into their daily service desk workflows appeared to have better outcomes.
“These results show what’s achievable when AI adoption is combined with effective change management and a focus on process improvements,” said the report. “They also act as a benchmark for other organisations evaluating the potential impact of similar tools,” it said.
Proper safeguards are key
But perhaps the biggest lesson learned from the last couple of years is that if we’re to truly maximise ROI, then we need to look at the bigger picture and develop AI systems in a much more methodical way. In effect, we need to develop AI by design. What does that mean? Well, in terms of privacy and security, it means establishing clear rules around not just the use of data but also how AI tools act and behave.
We also need to look beyond bias checks during model training to ensure that fairness is woven into AI right at the start, while ensuring that humans have the final say. And to build confidence in a new generation of tools, we need a proper paper trail to ensure that AI decisions can be traced and analysed so that, in the event something goes wrong, people can understand not simply what happened but why. It’s a good practice to ask an AI vendor which models are in use, where the training data came from, and what happens to the data users feed into the AI.
It’s too soon to say definitively whether Johnson & Johnson’s pivot signalled the end of AI’s pilot phase and the beginning of a more disciplined era. What we do know, though, is that the organisations most likely to succeed are the ones that are able to successfully manage the transition from AI experimentation to delivery while keeping a keen eye on outcomes and cost.
Asdrubal Picardo, CEO at Squalify, explains why cyber risk now sits alongside credit, liquidity and operational risk as a driver of enterprise value.
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For most of its history, cyber risk was somebody else’s problem – at least, that’s how the boardroom saw it. It lived in IT, spoke in acronyms, and was measured in things boards neither understood nor needed to. Firewalls. Patch cycles. Vulnerability scores. Important, certainly, but not the kind of thing that kept a CFO awake.
That era is over. Cyber risk now sits alongside credit, liquidity and operational risk as a driver of enterprise value. It shapes valuations, influences M&A decisions, and moves shareholder confidence in ways that are very visible and very fast. When something goes seriously wrong, it isn’t logged as an IT incident; it lands in the boardroom as a business crisis with a price tag.
The problem is that most organisations are still trying to govern a 2025 risk with 2005 tools.
How we got here – and why the approach most organisations use isn’t fit for purpose
The discipline has evolved considerably over the past two decades. But that evolution has been uneven, and the methods many organisations still rely on were designed for an earlier set of problems.
Stage one: heat maps and gut feel
For the better part of two decades, cyber risk management was essentially a technical exercise dressed up as governance. Risks were mapped onto colour-coded grids based on control assessments and vulnerability scans. Teams asked whether the firewall was configured correctly, whether patches were current, whether access rights matched the policy.
There was nothing wrong with this, as far as it went. It gave security teams a shared framework. It helped prioritise remediation. But it told you almost nothing that a board could act on. What does “high” actually mean? High compared to what? What would it cost? The heat map couldn’t say. A risk rated red in one business unit and amber in another might represent wildly different financial exposures. Or identical ones. There was no way to tell, and no common unit of account to compare them.
The board got a dashboard. What it needed was an answer.
Stage two: financial quantification, built from the bottom up
The next wave addressed the most glaring gap: it put numbers on risk. Frameworks like FAIR gave analysts a structured way to estimate monetary losses, drawing on probability distributions and loss modelling. For the first time, cyber risk could be expressed in terms that the rest of the business understood. That matters, because when you can denominate risk in money, you can compare it to other risks, weigh it against the cost of controls, and start making defensible decisions.
But the bottom-up approach carried its own limitations, and they’re serious ones. It works at the asset level (individual systems, individual threats, individual control failures) and tries to work upward toward an enterprise view. In practice, this requires granular technical data that is often incomplete, unreliable, or simply unavailable. Building a single quantification can consume months. And the further you zoom out, the more the analysis starts to wobble: aggregating dozens of system-level assessments into a coherent company-level picture is an exercise in compounding assumptions.
The result is analysis that can feel rigorous in its detail while being strategically useless at the level where decisions actually get made. You end up knowing a great deal about the risk inside individual rooms while remaining largely ignorant about the building.
Stage three: start with the business, not the systems
The most recent evolution flips the logic entirely, and it’s the one that finally produces something boards can use.
Instead of starting with IT assets and working up, a top-down approach starts with the business: how does this organisation make money, what would a serious cyber event actually disrupt, and how exposed are those critical functions right now? It calibrates against real-world loss data drawn from insurance markets and large-scale incident histories, rather than from internal workshops and expert estimates. That means it captures what analysts might miss: unknown vulnerabilities, systemic exposures, and the full chain of second-order consequences that bottom-up models routinely undercount.
The outputs look different too. Risk expressed as a potential financial loss at the company or group level, broken down by business unit, tracked over time, and stress-tested against different investment scenarios, is something a board can actually govern. It fits into the same mental model as every other material risk on the register. It enables comparison, accountability, and decisions that can be explained and defended after the fact.
For groups operating across subsidiaries or jurisdictions, this matters even more. A consistent, top-down model makes it possible to compare entities on the same basis, set improvement targets proportionate to actual exposure, and track whether the aggregate risk position is moving in the right direction. Bottom-up methods, stitched together from incompatible local assessments, simply can’t do that.
What this demands of leadership
The shift creates clear obligations, and they run in both directions.
CISOs and CIOs need to stop thinking of financial fluency as someone else’s job. The ability to explain how a specific control investment reduces a measurable financial exposure (not just improves a risk rating) is now a core part of the role. Boards are increasingly asking for it, and those who can’t provide it are increasingly losing the argument for budget. Boards, for their part, should be asking harder questions. Not about the technical detail – that’s management’s job – but about the quality of the evidence behind the numbers. Does the reporting show how exposure has moved over time? Does it flag concentrations of risk? Are the assumptions visible and defensible? A report that can’t answer those questions isn’t risk governance; it’s risk theatre.
The standard has shifted
The principle that risk has to be measurable to be manageable isn’t new. It underpins how serious organisations have governed credit, liquidity and operational risk for decades. Entire disciplines were built on it: stress testing, capital modelling, scenario analysis. The assumption was always that if you can’t quantify an exposure, you can’t really manage it; you’re just hoping.
Cyber is now being held to that same standard. Regulators are demanding it. Insurers are pricing for it. And boards that have watched enough crises unfold in public are no longer willing to accept dashboards as a substitute for answers.
Cyber risk has earned its place at the table. The question is whether the people presenting it are ready to speak the language of everyone else in the room.
Sean Evers, VP of Sales & Partner at Pipedrive explains why using AI effectively involves redesigning workflows around business problems, whilst maintaining a focus on the human experience.
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AI appears to be everywhere, but clear results and a quantifiable ROI are not so common.
Many businesses are learning that simply adopting the latest tools doesn’t guarantee efficiency, innovation or growth. It’s a lesson that must be re-learned from time to time as the latest new tech paradigm comes upon the business world faster than the wisdom to make best use of them. And to be fair, faster than new technology itself becomes mature.
Too often in the past two years AI initiatives have been slower than desired in showing value because they’ve been treated as backend tech upgrades rather than strategic, human-centred transformations. An organisation is not a server rack, able to work at double the output when a new blade is inserted. Working with the grain of the business will always lead to better outcomes as the people and processes mix better with the changing variables being introduced.
Businesses can move beyond reflexive actions brought on by AI hype by embedding new technologies into problem-shaped workflows, creating meaningful impact through strategy, culture and human-centred implementation. AI tools are designed to solve specific challenges, not every challenge. We’re not at AGI yet (artificial general intelligence). Use tools wisely in limited areas, train teams well, and ensure a clearly communicated strategy supports team efforts. Then, all of a sudden, those investments in new tech will really move the needle on what’s been carefully defined as critically important.
Redesigning workflows
There is no best-in-class AI ‘Swiss army knife’. Even the most cutting-edge tech can’t deliver value unless workflows are redesigned around real business problems. AI succeeds when aligned to clear strategy, not when applied to broken processes like a sticking plaster. Firms positioning AI purely as an IT project will often encounter resistance, poor uptake and disappointing outcomes. The tech cycle has been this way forever, likely since fire and the wheel. Success always depends on employee understanding, willingness and trust in both their leadership and the ability of the tech to deliver on vendors’ promises.
Pipedrive’s ‘The evolving role of AI in sales workload management report’, highlighted how artificial intelligence has been reshaping sales roles and optimising workload distribution. In some areas, like in the sales function, the findings reveal that AI has become a co-pilot for professionals, enhancing efficiency and helping them focus on high-value activities:
One takeaway from the report was that AI users spend more time on strategic activities compared to non-users.
AI usage was still higher among sales managers (41%) than among salespeople (31%), indicating a need for more accessible AI tools and tailored training programmes.
Focus on what matters
AI centred on the human experience and business problems is what delivers real results. Thus, so-called soft skills and processes like corporate transparency, workplace empathy and ethical AI governance in practice are not really ‘soft’ considerations. Only a hard-headed, machine-minded person would fail to consider them as the essential enablers of organisational uptake and progress.
When employees are informed participants in change, AI becomes empowering rather than disruptive. That shift does not happen by accident. It requires leaders to articulate what problem AI is solving, for whom, and how success will be measured. Now, in many SMEs, the temptation is to deploy AI features because competitors are doing so, or because vendors promise transformational gains. But transformation without direction is simply noise.
Take a typical sales team in a growing business. Introducing AI-driven forecasting or automated lead scoring will not improve performance if the underlying pipeline stages are unclear or data hygiene is poor. In that scenario, AI merely accelerates existing inefficiencies. However, when leadership first defines what a qualified lead actually looks like, standardises processes and sets clear accountability, AI can enhance decision-making and free up time for higher-value conversations and really make a difference.
This is where cautiously redesigning workflows becomes critical. AI should be introduced at friction points like repetitive admin, inconsistent reporting, or slow handovers between teams. This is better than when added as a layer across every function. A targeted deployment creates quick wins, builds confidence and demonstrates measurable returns. Over time, those incremental gains compound and any cultural and technological lessons can be carefully applied in a virtuous cycle.
Managing the transition
The role of leadership is equally important. When AI is positioned as a cost-cutting mechanism employees will view it with suspicion. When it is brought in as a productivity partner to reduce manual tasks and allow individuals to focus on creative, relational or strategic work then adoption improves. Communication must be clear about what will change and what will not. Ambiguity will always breed a very understandable resistance.
Ethical considerations also need to move from policy into well-understood daily practice. For SMEs in particular, governance can feel like a burden reserved for larger enterprises who can ‘do it properly’. In reality, lightweight but explicit guardrails are often enough. Define what data AI tools can access. Establish human review points for high-impact decisions. Be transparent with customers about how AI is being used in interactions. These measures build trust internally and externally, which protects the long-term value of relationships and contracts.
There is also a mindset shift required. AI is not a one-off implementation. At the current rate of change it appears that it will be an evolving capability for many years. Teams will need space to repeatedly test, refine and learn. That may mean starting with a single department, gathering feedback and iterating before scaling. It may mean accepting that some pilots will fail. The objective is not perfection at launch, but steady alignment between technology and business requirements.
Being an SME can be advantageous
For SMEs, this disciplined approach can actually be a competitive advantage. Larger organisations often struggle with legacy systems and complex approval chains. Smaller businesses can be more agile, provided they resist the urge to chase every new feature release. Clarity of purpose becomes their differentiator.
Ultimately, fitting AI to the problem is about respecting the fundamentals of good management. Define the objective. Align people and process. Introduce technology where it adds measurable value. Review and refine. The companies seeing real returns from AI in 2026 are not those with the most tools, but those with the clearest strategy.
AI will continue to evolve rapidly. New capabilities will emerge, and expectations will rise. But the principle remains constant: technology works best when it amplifies well-designed human systems. Organisations that remember this will find AI soon stops being overwhelming when enabled as a controlled, practical tool for growth.
Paul Done, Field CTO at MongoDB talks to us about why people who think ‘vibe coding’ is all just lazy, AI generated code, are missing the valuable contribution AI can make to high-quality coding.
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Very few phrases in software have spread as quickly, or been as misunderstood, as “vibe coding”. For some, it signals the democratisation of software development, or the practise of causal programming for throw-away applications. But to its loudest critics, vibe coding represents a shortcut culture: developers tossing four‑line prompts into an AI model, then flooding production systems with fragile code. Many engineers also dislike the term because it implies coding without really understanding the code itself or blindly accepting AI output. In turn, some see vibe coding as trivialising the real effort and expertise required in software development.
I’ve been in the industry long enough to have heard similar complaints before: a new technology trend or tool that will make developers lazy, hollow out engineering skills, and ultimately leave organisations exposed. But that framing misses the point, because it has become a catch-all to describe two very different practises, with very different implications for developer teams and enterprises.
AI-driven coding is not vibe coding
Vibe coding often distracts and undermines the very real and positive impact of adding AI to the programming workflow. The leaps in the past few months alone have meant that AI agents have rapidly transformed how software is developed. Rather than manually writing code line by line, developers can now assign complex tasks to AI agents in plain English and have them independently research solutions, write code, debug errors, and deploy systems. These agents are capable of handling long, multi-step workflows – for example, setting up infrastructure, integrating tools, testing functionality, and documenting the results – often completing in minutes what previously took days.
As a result, programming is shifting from direct coding to orchestrating and supervising AI-driven processes, where developers focus more on defining problems, guiding agents, and reviewing outcomes, rather than implementing every technical detail themselves.
This style of development still requires a comprehensive understanding of engineering principles. As a result, it should not be confused or conflated with vibe coding, where code may also get generated rapidly, but lacks proper reviews, and is deployed with limited consideration for scalability, security or ownership. When critics warn about insecure “slop” code entering production, they are often pointing to failures of process and governance. That is a legitimate concern. But it is a concern about how teams operate, not about the inherent properties of AI-assisted development.
Even long-standing sceptics are beginning to acknowledge this distinction. Figures such as Linus Torvalds, Donald Knuth, and Robert C. Martin have recognised that AI can play a constructive role when it sits within disciplined engineering practice. The conversation is shifting away from whether AI should be used at all, and towards how it should be governed.
AI accelerates existing coding practises
Teams that have always kept strong review standards, testing rigour and capable leadership will not have those practises washed away if AI enters part of their workflow. For these teams, AI helps to increase the output without lowering standards. This is because it amplifies the culture already there.
The same principle applies to security. Secure software depends on threat modelling, dependency management, access controls and continuous monitoring. If those disciplines are weak, vulnerabilities will surface regardless of whether the first draft was written by a human or generated by a model. AI changes velocity, not responsibility.
For CIOs and technology leaders, this has practical implications. Prohibiting AI tools is unlikely to succeed and may drive their use underground – and given the advances in AI-driven coding, it may even amount to a serious competitive disadvantage. The more effective response is to strengthen the controls around them. Clear coding standards, automated testing, AI-driven code review, policy-driven code scanning, and runtime observability must become the default.
As AI accelerates the pace of software development, traditional human-centric code review workflows will struggle to keep up. When code can be generated much faster than it can be manually reviewed, human reviewers quickly become the bottleneck. The emerging model is one where AI systems enforce standards, review and validate code continuously, and flag risks at machine speed, while human engineers focus on defining requirements, architecture and higher-level oversight, rather than line-by-line review. AI belongs inside a structured software development lifecycle with guardrails, traceability and accountability.
A higher baseline for good code
With these in place, AI can raise the bar for what “good” looks like in our industry. Junior developers can receive immediate feedback on idiomatic patterns, security pitfalls and performance trade-offs. Senior engineers can offload repetitive tasks and focus on architectural coherence and long-term design. Test generation, documentation updates, refactoring and coding standards enforcement can become continuous activities rather than deferred clean-up exercises.
In many organisations, technical debt accumulates because improvement work competes with delivery deadlines. AI is reducing that tension by lowering the cost of maintaining standards. It can flag inconsistencies, suggest improvements and reinforce agreed conventions across large codebases.
This is particularly relevant for modern, data-intensive applications where distributed architectures and complex data models leave little margin for error. AI can support good engineering principles by improving validation, surfacing edge cases and increasing visibility into how systems evolve.
The debate around vibe coding muddies the waters about AI in our industry – the question is not whether AI will be part of software development. It already is. The differentiator will be how seriously organisations treat governance, architecture and long-term maintainability in an era of accelerated output.
Markus Nispel, Head of AI Engineering & EMEA CTO at Extreme Networks explains why your strategy and budget aren’t holding up your AI network initiatives – your execution is.
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The pilot phase is over. A third of companies have now scaled AI into production. For everybody else, the holdup isn’t strategy or budget – it’s execution.
Many AI initiatives struggle to deliver meaningful ROI for familiar reasons: missed business objectives and clearly defined KPIs, limited AI expertise, processes that haven’t been redesigned for AI, gaps in AI and data governance, and persistent challenges around data availability and siloes, quality, and preparation.
At the same time, supporting AI at scale requires infrastructure that can keep pace with continuous data flows, shifting workloads, and real-time decision-making. Traditional networks were built for stable, predictable workloads – not the speed, volume, and variability that AI-driven systems demand.
As AI moves from experimentation into production, networks must handle continuous data flows, adapt instantly to shifting demand, and operate at a scale that manual intervention simply cannot match. Meeting these demands requires a shift in network design and operation. This is where AI-powered, autonomous networking becomes essential.
Autonomous networking in practice
Autonomous networking allows systems to detect disruptions early, adjust traffic flows and configuration dynamically, and continuously optimise performance in real time, rather than reacting after issues occur.
This is made possible through multi-agent systems. Individual agents manage narrow tasks such as bandwidth monitoring, anomaly detection, and routing optimisation. Others sit above them, orchestrating them, interpreting user and business needs, and pulling the right capabilities together.
The system also works within defined governance frameworks. Humans stay involved in critical decisions, with full visibility, transparency and explainability into system activity, planning, reasoning and decision-making. Every automated action is logged and can be traced, verified and audited if necessary.
Trust, as in real life, is built through repeated positive outcomes. When networks keep making the right decisions, teams gain confidence, reduce oversight and can focus on higher-value work rather than constant troubleshooting.
This transition is already underway. Recent data reveals that 88% of organisations already rely on multiple AI-powered tools for networking and security operations. For stretched-thin teams, autonomous networking has grown into a necessity. Meanwhile, the strain is evident, with 92% of leaders reporting that AI places heavier demands on bandwidth and computing resources.
In this environment, network performance becomes a defining factor in whether AI systems can operate reliably and deliver measurable value.
Security through intelligent boundaries
Scaling AI also changes the security landscape. Networks are no longer connecting only users and devices; they are supporting a growing number of non-human identities. Agents across finance, marketing, engineering and operations interact with systems and data, often without human involvement.
Traditional security models were not designed for this level of autonomy. Access can no longer be broad or static. It must be tightly scoped, context-aware, and continuously verified. Every action must be visible and traceable.
But confidence is climbing. In fact, 93% of executives now say AI-powered networking reduces security risk rather than increasing it. That shift matters. It shows organisations are moving past scepticism and starting to take control.
That doesn’t mean we should be giving agents free rein. It means tightening the boundaries around what they’re allowed to do and enforcing strict agent governance. Access can’t be broad or permanent. It has to be specific, context-aware, and continuously verified. Every action should be traceable through a clear audit trail as AI for networking is implemented.
Where fabric architecture makes the difference
Networking for AI will not work without visibility. Real-time traffic monitoring and system connection mapping make enforcement possible. From there, segmentation becomes essential to contain risk and prevent unintended access or lateral movement – especially in the agentic era we have entered.
Fabric architecture enables this level of control at scale. By creating a unified network environment, it ensures that policies are applied consistently across all users, devices, and workloads.
This allows organisations to automatically isolate sensitive systems and tightly control how entities interact. If an AI agent behaves unexpectedly or is compromised, its access can be contained immediately, preventing wider impact.
Organisations that get this right bring identity, access control, visibility and threat detection together into a single, cohesive system. Autonomy can then operate within clearly defined boundaries, giving IT teams the confidence to guide, verify and trust every action the network takes.
Real-world application
The impact of this shift is visible across industries. Take retail in 2026. AI allows hyper-personalised shopping through cameras, IoT sensors, mobile apps and edge devices. Inventory data, customer preferences and behavioural patterns flow nonstop. Shelf labels, RFID systems and automated checkouts all require connectivity.
Healthcare follows similar patterns. AI supports diagnostics and robotic-assisted procedures, with patient data moving continuously across EMR systems, monitoring devices and analysis platforms. Without well-designed enterprise networks and access controls, those same systems can become exposure points rather than protection.
Manufacturing uses AI to predict equipment failures, optimise production lines and coordinate autonomous robots as sensors and machinery continuously communicate.
Across industries, without unified enterprise networks, stringent access control and defined human checkpoints, a single misconfigured AI agent could compromise sensitive data, disrupt operations or even endanger lives.
From experimentation to production
The era of experimentation is over. Organisations that operationalise AI effectively move faster, operate more securely, and respond to change with greater agility. Achieving this requires networks that can anticipate demand, enforce boundaries, and adapt continuously without compromising performance.
When that foundation is in place, AI can deliver on its promise – reducing operational friction, minimising disruption, and enabling teams to focus on innovation rather than maintenance.
Taran Rai, Corporate Sustainability Manager at Epson explains why the digital vs print sustainability debate isn’t as straight forward as it may seem.
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The sustainability debate around digital vs print has become deeply polarised, with digital widely perceived as the environmentally responsible approach and print positioned as inherently and inescapably wasteful.
But is it as simple as that? The short answer to that question is no, particularly as organisations scale their use of digital technologies (some exponentially) and the environmental impact of these activities becomes apparent.
Arguably, the most striking and alarming example of this trend is the dramatic growth of AI and its associated digital infrastructure. If predictions about the sector’s resource demands are even remotely accurate, the world faces a significant and sustained increase in consumption.
According to the International Energy Agency (IEA), for example, driven largely by AI growth, “global electricity consumption for data centres is projected to double to reach around 945 TWh by 2030”. To put this in context, from 2024 to 2030, data centre electricity consumption will grow by around 15% per year, “more than four times faster than the growth of total electricity consumption from all other sectors.”
Increases in water consumption are also raising serious concerns. According to the UK government, “AI is predicted to lead to an increase in global water usage from 1.1bn to 6.6bn cubic metres by 2027. This is equivalent to more than half of the UK’s total water usage.”
As the study goes on to point out, “The water demand of AI technologies is likely to threaten global and national water security, especially in areas of existing water stress, which can in turn threaten the biodiversity of local areas and the needs of human populations.”
Digital good, print bad?
But what does this mean for print? After all, the prevailing assumption is that digital would enable organisations to phase out print and, by definition, improve their environmental performance. But given the enormous sustainability challenges now facing the global digitalisation movement, the comparison between digital and print needs to be reframed, not as a question of substitution, but as a question of relative impact in context.
Indeed, if we go back a couple of decades to the early days of digitalisation, reducing reliance on paper was a central part of the case for change. Many of those arguments were valid, particularly given the inefficiencies in how organisations used print at the time. Something had to change, and it did.
Fast forward to 2026, and the landscape looks very different. Print is no longer defined by the inefficiencies that once characterised it, as advances in production processes and technology have significantly improved its environmental performance.
For example, improved production processes have reduced energy consumption and streamlined workflows by eliminating stages that previously produced excess material, especially for limited print runs. At the same time, the ability to produce on demand enables organisations to align output more closely with actual requirements, helping to reduce overproduction and unnecessary inventory.
More specifically, digital and inkjet-based print processes can significantly reduce water consumption, with studies showing reductions of 50–90% compared to traditional techniques. And, in some industrial applications, such as textile printing, digital methods can reduce water use even further, with estimates of up to 95% savings due to the removal of washing and post-processing stages.
Striking a better balance
The underlying issue is not which format is “better”, but that digital and print have different environmental impact profiles. Print impact is typically more visible and often concentrated at the point of production, whereas digital impact is less visible but continues over time through ongoing energy use.
Moving from print to digital does not eliminate environmental impact; it shifts it to other parts of the value chain. As digital usage scales, particularly with always-on services and data-intensive applications, this ongoing impact becomes more significant. As a result, defaulting to digital-first strategies can lead to environmental costs that are not always fully understood.
Rather than focusing on format alone to determine sustainability strategy and benefits, organisations instead need to consider how different approaches perform in specific use cases.
In some scenarios, for example, the continuous energy demands of digital delivery may outweigh the one-off impact of print, particularly where information is accessed repeatedly or stored over long periods. In others, digital will clearly offer advantages, especially where distribution scale or accessibility is the primary requirement.
Outcomes are shaped by delivery
Whatever situation applies, the key to making good sustainability choices is to recognise that outcomes are shaped by how information is delivered and used over time, not by the medium itself. This shift in thinking also aligns with broader moves towards lifecycle-based assessment, where environmental impact is evaluated across the full span of use rather than at a single point in time.
The approach is already being formalised, with the EU’s Ecodesign for Sustainable Products Regulation (ESPR) establishing a framework law that sets strict rules on sustainability, durability, and repairability for goods sold in the EU to promote a circular economy. EU rules also require that large companies publish regular reports on the social and environmental risks they face, and on how their activities impact people and the environment.
The underlying point is that the core arguments that form the digital/print debate are now much more nuanced than they were 10 or 20 years ago. Organisations need to strike the right balance based on their operational needs and sustainability obligations, not just to protect the environment but also to identify the most business-efficient processes in which digital and/or print must play a role.
Satish Thiagarajan, founder of Brysa, a Salesforce and data consultancy based in the UK, explains why high quality data is the foundation for using AI successfully.
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AI is everywhere in business right now, and for good reason. It offers the potential for better visibility across operations, fewer surprises, and more efficient use of resources. Most businesses have run a pilot to test that. Fewer have made it past one.
The stall point is consistent. Projects start well, attract investment, generate interest, and then stop delivering. The technology rarely gets the blame internally, but it tends to take it publicly. The real problem is almost always the data behind it.
Why data decides whether AI works
Business data systems weren’t designed to tell the whole story. They were each added over time to solve specific problems. One for finance, one for sales, another for HR, and a few more for marketing, support, and operations. Individually, they do the job for which they were intended, but they don’t really connect. And that’s fine, until you try to apply AI.
AI doesn’t think in terms of individual systems. It looks for patterns across everything, from customers and revenue to pipeline activity and service history. When that information is split across systems that don’t line up, those patterns break down, and what you’re left with is data that doesn’t quite agree with itself: records that don’t match, account data that conflicts with billing history, customer activity that looks different depending on where you check.
At that point, the problem isn’t a lack of data. It’s that the data doesn’t hold together. And if the data doesn’t hold together, the output won’t either.
What “AI-ready” actually looks like
Before AI can do anything useful, the data has to make sense on its own. Without that, AI is, effectively, guessing.
Context matters just as much. Data only becomes useful when it carries the relationships behind it. A customer record on its own doesn’t say much. Connect it to purchases, support history, and engagement activity, and you start to see why things happened, and that’s what AI needs to work with.
Timing forms another pressure point. Business moves quickly, but the data often doesn’t. If updates are delayed, or stitched together after the fact, AI will always be working from an outdated version of events. When data flows in real time, it reflects what’s actually happening, not what happened last week.
Then there’s continuity. When past performance connects directly to current activity, AI has something to learn from. Without that link, every decision starts from scratch. To get to that point, data needs to be consolidated in one place, and that’s where a CRM comes in.
Bringing it together in one place
Used properly, a CRM becomes more than a system for managing contacts. It acts as a central hub for accounts, opportunities, cases, campaigns, and service activity. AI doesn’t need perfectly clean data, but it does need to understand how work actually happens, and a CRM gives it that. Business data is constantly changing, and it needs to scale across teams, regions, and functions. Role-based access, audit trails, and clear permissions aren’t just nice-to-haves, they keep data usable as it grows.
Building a usable data foundation
The goal when faced with fragmented systems isn’t to replace everything, but to connect what’s already there. Customer data, comprising account histories, contact records, and interaction activity, is standardised and can be used across sales, marketing, and service, reducing duplication and avoiding inconsistency.
Workflows matter as well. If data quality depends on someone fixing issues later, it won’t hold. When validation happens at the point of entry, and updates flow automatically across systems, accuracy is built in, rather than an afterthought. When the data is reliable and connected, AI can support things like demand forecasting, lead prioritisation, or churn prediction, and good governance ties it all together.
AI doesn’t fail because the models aren’t capable. When the underlying data is fragmented, AI reflects that fragmentation. When the data is coherent and connected, AI has something solid to work with. That’s the difference between systems that generate outputs and systems that actually support decisions.
Satish Thiagarajan is the founder of Brysa, a Salesforce and data consultancy based in the UK. His company advises media, industrial, and services clients on using Data Cloud and Agentforce to turn signals into action. His work focuses on closing the loop between insight and execution in sales, marketing, and service.
Chris Derham, Business Development Director at Alcatel-Lucent Enterprise talks to us about the buildings of the future and how they can help us reach net zero.
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Buildings and their operations sit among the biggest climate challenges of our era, but they also offer one of the most impactful levers for emissions reduction.
When we look at the UK, data shows that direct and indirect emissions from the buildings sector in the UK account for 27.7% and 9.1% of total energy-related CO2 emissions, respectively. Significantly, per capita emissions from the buildings sector in the UK are 1.2 times the G20 average, suggesting that there is an opportunity to reduce this impact.
If net zero is the destination, effective management of the built environment is one of the most important routes to get there.
From gadgets to digital ecosystems
For years, “smart building” meant a collection of clever devices, from automated blinds to motion sensors. Today, that model is outdated.
Modern smart buildings function more like digital organisms. Instead of isolated systems operating independently, a central orchestration layer brings them together, aggregating and coordinating multiple sub-systems through a unified digital framework. Lighting, HVAC, occupancy monitoring, and security systems now communicate through shared data frameworks, adjusting in real time to how a space is actually used.
Artificial intelligence sits at the core of this shift as it can analyse usage patterns, forecast demand, and make autonomous adjustments. For example, a meeting room that typically fills at 10 am can be air-conditioned just in time, or lights on an underused floor of the building can be powered down before energy is wasted.
None of this works without high-performance connectivity. Advanced networking technologies such as Wi-Fi 7 and private 5G are being deployed to ensure low latency, high capacity, and airtight security. These networks form the invisible nervous system of the building, carrying the data streams that enable continuous optimisation.
Across the Channel
In many EU countries, smart buildings are increasingly treated as essential infrastructure, rather than an optional innovation.
Countries such as France and Germany have embedded automation and monitoring requirements into climate legislation, and digital capability is becoming a matter of compliance, not just a competitive differentiator.
At the centre of this transformation is the Energy Performance of Buildings Directive. This legislation requires all new buildings to be zero-emission by 2030 and existing stock to follow by 2050. Achieving that at scale without digital systems that continuously measure and optimise performance would be nearly impossible, meaning that as member states translate the directive into national law from 2026 onwards, investment is expected to intensify.
France provides a concrete example through its Decree BACS, mandating building automation and control systems in larger non-residential properties. By 2027, any such building with output above 70kW must comply with the legislation.
Progress in the UK
The UK presents a more fragmented picture. Innovation is not the problem. Manchester’s Triangulum initiative is a standout example of smart, low-carbon urban development. By integrating energy-efficient technologies, IoT sensors, and renewable energy systems, it demonstrates how coordinated digital infrastructure can reduce emissions and create more sustainable, liveable city spaces.
The difference lies in consistency. The UK lacks a comprehensive, national framework that mandates or systematically incentivises smart building adoption at scale. Instead, progress tends to occur on a project-by-project basis.
One lesson from continental Europe is that well-designed regulation does not stifle innovation, it often accelerates it.
A strategic framework in the UK could:
• Define common standards for smart buildings and energy efficiency • Support interoperability across regions and technologies • Encourage investment in digital infrastructure upgrades
The next opportunity lies in coordination. A national standard for smart buildings and smart cities could provide clarity for investors and developers, while also allowing for local flexibility.
The UK’s move towards net-zero
The good news is that although the UK still lacks an overarching framework on smart buildings and cities, many existing regulations are being adapted and modernised to help reach the goal of net-zero by 2030.
For example, the Minimum Energy Efficiency Standards (MEES) currently require commercial and private rented domestic properties to have an Energy Performance Certificate (EPC) rating of at least E. The government is currently consulting on proposals to raise this standard, which would potentially require all rented commercial buildings to achieve EPC B by 2030 to remain legally lettable.
In practice, this means significant upgrades for the UK’s commercial building stock. Investment in building fabric materials, LED lighting and controls, HVAC replacement, building management systems, and smart energy monitoring will be instrumental in achieving this standard and reducing environmental impact.
Other regulatory changes, such as reform of the Energy Performance of Buildings (EPB) Regime, will also play a key role when it comes to improved data collection, new EPC metrics that better reflect operational performance, and quality assurance for EPC assessments.
Taken together, this legislation is likely to require the installation of smart technologies across UK buildings.
Smart buildings: An important opportunity
Smart buildings are a powerful tool for cutting carbon emissions. By using real-time monitoring, automation, and AI, they reduce energy waste and optimise heating, cooling, and lighting. Beyond efficiency, they provide the data and control needed to achieve large-scale emissions reductions.
Effective regulation is key to driving adoption and creating a low-carbon, sustainable built environment. If the UK is to accelerate toward net zero, smart buildings must move from isolated examples of best practice to the standard for how we design, operate, and upgrade our spaces.
Martin Jakobsen, Managing Director at Cybanetix, on why SOC training and progression will be vital to meet the challenge of AI-driven cyber attacks
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The accepted wisdom in cybersecurity is that the Security Operations Centre (SOC) has become overwhelmed. There’s some truth in this. Yes, the time taken to detect and remediate has grown, with IBM stating this now stands at 241 days. Yes, alert fatigue remains an issue, with SOC analysts snowed under 10,000 alerts per day leading to confirmation bias whereby positive alerts are discounted. And yes, alert volumes are rocketing due to a thriving black-market economy in attack kits and services, not to mention the emergence of AI-enabled attacks. Yet the SOC can adjust to these challenges and move with a rising tide if it adopts a paranoid posture.
One of the key attack trends over the past year is for threat actors to gain and maintain access legitimately. It’s for this reason we’ve seen a rise in credential theft (with an 800% increase in 1H2025) and the use of living off the land techniques (LotL). The attacker can log-in and use legitimate, trusted tools to evade detection and move laterally across the network to escalate those privileges. But the very fact these attacks don’t leave telltale footprints can make them much harder to detect. The SOC needs to rely on tools such as endpoint detection and response (EDR) and monitor tool usage to look for anomalies and that means listening to the less noisy network activity and low-severity alerts.
SOC: Selective Hearing
However, most SOCs focus on the high-severity alerts to such an extent that they even measure their success against the resolution of these incidents. SOC service level agreements typically specify a mean time to detection (MTTD) of 30 minutes and a mean time to respond (MTTR) of 15 minutes but the small print will often reveal this only applies critical alerts. Medium level alerts will typically be responded to within 1-2 hours and those low-level alerts that could indicate a LotL attack? Those are relegated to a window of 12 hours or more.
To capture this range of alerts will require the SOC to process ten times the usual volume of events. This presents the SOC with a quandary. How do you increase the monitoring and the ingest of alerts without submerging a SOC team who may already be drowning? For that to happen, the SOC must stop being selective and instead become more efficient.
To begin with, automation must be extended. Many teams will already be using Security Orchestration Automation and Response (SOAR) which can be configured to automatically remediate and close cases. But there are numerous other processes that can also benefit from automation. These can see the application of threat intelligence, automatic threat hunting and telemetry gathering, artificial testing, correlation with other alerts, and entity mapping, all of which can be used to enrich cases to the point where the SOC analyst doesn’t need to gather any further information when picking up the case.
Recovering from Cybersecurity Incidents
If we take the pre-defined playbooks that contain the recipe for how to detect, contain, eradicate and recover from specific cybersecurity incidents, for example, these can be automated to respond in a cascading effect. This sees one playbook used to trigger another depending on what the first has discerned, so that sub-playbooks iterate through lists of entities for each part of the case. Assuming 4,000 alerts coming into the SOC, triggering 100 playbooks per alert, with each playbook performing around ten actions such as enrichment lookups, correlation queries and containment steps, that’s equivalent to over four million triggered automations being executed per day before these cases are passed to a human analyst.
AI and the Analyst
AI, too, has a role to play. It currently enables the translation of free text questions into syntactical queries of Security Incident and Event Management (SIEM) and EDR data and can also be used to explain alerts, investigations and findings using human-friendly language and to summarise cases. It also lends itself to detection engineering, facilitating the faster creation of playbooks through the creation of code and detection syntax. With many detections sharing the same remedial actions, using AI to recommend a course of action makes sense, reducing analyst workloads substantially. And looking to the future, we can expect it to be used to optimise SOC operations by building playbooks on the fly and through the use of predictive investigative outcomes.
Applying these methods of automation enables any alert to be dealt with much more efficiently. The alert will initially be put through a process of enrichment, with threat intelligence used to compare the alert with known threats. SIEM and EDR searches will then correlate information, after which any associated alerts pertaining to the same entities (i.e. IPs, users, accounts, devices etc.) are linked to the case for the analyst to review. Using these processes, it’s possible to automate 65-70% of all SOC activity, dramatically reducing case workloads and allowing the SOC to process those massive alert volumes.
Human in the Loop
Yet, while automation is critical to adopting a paranoid posture capable of responding to evolving threats, it’s no substitute for the skills of the SOC analyst. Human expertise is invaluable in evaluating, verifying and deciding upon the best course of action and the likelihood is that those skills will become even more pertinent as AI becomes more widely used. This is because the technology can become so goal-driven that it becomes blinkered and can make incorrect deductions. In one instance, an AI agent went on to misinterpret a threat and produce a fictitious kill chain and mitigation advice, revealing the need for a human in the loop (HITL) and traceability in AI.
Paranoid monitoring does require the generation of more alerts for investigation. But we do have the tools and automation capabilities to handle those volumes so that this uptick needn’t equate to a massive increase in alert fatigue. What it does mean is that the role of the analyst will subtly change. They will be augmented by these processes and need to develop additional skillsets associated with validating these outputs, so the SOC will need to continue to invest in continuous training and progression, particularly if they want to hang on to that talent which remains in short supply. But unless we make these changes, the SOC won’t be able to keep pace with emerging threat patterns and will almost certainly fail to meet the challenge of AI-driven attacks.
Jean-Philippe Avelange, CIO at Expereo, on why network resilience must be front of mind to drive digital transformation
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Digital transformation has become fluent in the language of applications. Boards are asking for AI, cloud migration, automation, better customer experiences and more real-time data. Teams are being asked to modernise faster, operate more efficiently, and make digital investment show measurable returns. But what many enterprises are still learning is that the bottleneck is not always the application, the data, or the platform team. It is often the network underneath them.
For years, connectivity has been treated as little more than plumbing. Something to procure, renew and occasionally upgrade when a site opens or a contract ends. That assumption held up reasonably well when enterprise technology was slower, more centralised and more predictable. But it has become harder to defend now that applications are distributed, users are everywhere, data moves constantly between environments, and businesses expect digital services to perform in real time.
Expereo’s Enterprise Horizons 2025 research found that only half of organisations believe their networks are ready to support new technology initiatives. This is an issue for any organisation expecting transformation to move from a programme plan to something employees and customers can depend on every day. Once new tools scale across sites, providers, clouds and regions, the network either becomes an enabler of change or the place where momentum starts to slow.
The same research found that more than half of companies had experienced financial impact from network downtime or poor performance in the previous 12 months. That is lost productivity, lost revenue and lost confidence in the digital services that a business is trying to build around.
Resilience is not the same everywhere
The instinct, when faced with a fragile network, is often to add more – more bandwidth, more redundancy, another circuit. This creates the appearance of resilience while driving up costs and doing little to improve the experience where it actually matters. At the same time, most organisations still treat every location as equally important. But a headquarters, a manufacturing site, a contact centre and a small regional office are fundamentally different in how they operate and the risk they carry. Yet they are often supported by similar connectivity models.
Resilience needs to reflect that reality. The network should be designed around the role each site plays in the business. Some locations need diverse fibre paths or wireless failover to maintain continuous operations. Others need strong performance guarantees and rapid remediation. Others require a simpler, reliable and cost-appropriate baseline.
The goal is not to make every site identical – it is to make every site fit for purpose.
Standardisation still plays a role, but not in forcing every location into the same architecture. The more effective approach is to define clear site categories, each with a pre-defined level of resilience. That turns expansion into a repeatable process, rather than a constant redesign exercise.
Seeing where failures actually happen
Another gap sits in visibility. Most IT teams monitor applications closely, but far fewer have a clear view of the network paths on which those applications depend. When issues arise, teams are often troubleshooting without knowing whether the problem sits with the user, the site, the provider or the cloud environment. By the time the cause is identified, the impact has already been felt.
Failures rarely occur in isolation. They happen across the path between users, sites, providers and cloud platforms. Without visibility into those paths, problems are misdiagnosed, escalated slowly or incorrectly attributed to the application itself. Network observability changes this dynamic. It provides early warning rather than post-incident analysis, showing where performance is degrading, where traffic is being routed inefficiently and where user experience is being shaped by infrastructure rather than software. This visibility is also critical for data sovereignty. As organisations adopt cloud, AI and third-party services, understanding how data moves becomes as important as knowing where it is stored. In many cases, the network is the only place where the view exists.
From network to advantage
As digital transformation becomes embedded in day-to-day operations, connectivity moves from a background concern to a business-critical capability. The question is no longer whether the network matters, but whether investment in it is aligned with business risk. Adding more bandwidth or blanket resilience does not solve the problem – being more precise does. Resilience needs to be applied where it matters most, observability needs to be built into the network layer and design decisions need to reflect how each part of the organisation actually operates.
Connectivity has long been treated as plumbing, but in reality, it underpins digital transformation. It determines whether applications perform consistently, whether users trust the tools they are given, and whether organisations can adapt without repeatedly rebuilding their foundations. The organisations pulling ahead are not treating the network as an afterthought. They are designing resilience into the transformation from the start.
U.S. Merit Systems Protection Board: Driving Operational Exellence
Interface revisits the important work of the U.S. Merit Systems Protection Board – an independent, quasi-judicial agency in the Executive branch that serves as the guardian of Federal merit systems. CIOCraig Thomas, explains the strategy behind the completion of Phase II of its case management journey, application stabilisation challenges and the deliberate rollout of secure artificial intelligence tools.
“At MSPB we field IT that is necessary, useful, cost-effective, manageable and scalable. If the technology doesn’t add value, doesn’t help us meet our mandate, I don’t want it… We see the active deployment phase as an incubator for support methodology, data and reporting strategy, and road-mapping the next five years of your application – use the active deployment phase, don’t just firefight.”
Morgan Street Holdings: Cybersecurity for Strategic Operations
Morgan Street Holdings is a privately owned investment and operating company whose portfolio includes global supply chain specialist HAVI, marketing and sourcing firm tms, consumer products brand Stanley, and hospitality and vending business Continental Services. Collectively, the organisation employs more 10,000+ people globally across more than 50 countries. Business Information Security Officer, Douglas Darden, talks building cyber resilience to enable the business and deliver cybersecurity for strategic operations.
“It’s not in us as a cyber team to just say no. Give us the opportunity to conduct a risk assessment and the cybersecurity function can become a business enabler.”
Also in this issue, we hear from Confluent on why AI is changing what data privacy means; learn from Kore.ai on how unmonitored AI agents are becoming enterprise AI’s biggest risk; and Xsolla explain why the real AI debate in video games isn’t about jobs, it’s about creativity.
Gareth Hewitt, Founder of LemonEdge, on why the real lesson from DORA is that resilience has to run through the whole operating model, from the infrastructure underneath it to the controls and workflows used every day
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The EU’s DORA regulation has exposed how firms operating in private markets face a set of risks that is not purely about IT.
Designed to reduce financial sector reliance on a small number of infrastructure vendors, the regulation came into force last year. Since implementation it continues to throw a spotlight on risks arising from continued use of manual methods and over-reliance on individual employees’ subject matter expertise.
The regulation is forcing firms to examine how their operating models work under pressure and where risk resides inside workflows.
A private equity or private credit manager may sit on robust cloud infrastructure at one end of its technology stack, while still relying on spreadsheets, manual handoffs and offline approvals at the other. In that kind of environment, resilience is only as strong as the least controlled part of the workflow.
The real risk often sits inside the workflow
This is where risk accumulates in an organisation – in processes that are not properly systemised. This is amplified when they rely on manual intervention or a small number of people who know how to make them work.
A month-end close supported by spreadsheets and a sequence of offline steps may function well enough in normal conditions. However, it looks far less resilient when deadlines tighten, a key individual is unavailable or an investor query lands at exactly the wrong moment.
DORA, in effect, acts as a pressure test on whether resilience has been built into the operating model or simply assumed. Private markets firms have lived with this kind of exposure for years, often because experienced teams compensate for process weaknesses. Regulation leaves no room for that comfort. The question now is whether the workflow holds up under strain.
With DORA, accountability has moved to the top
One of the clearest shifts under DORA is the level at which accountability now sits. Historically, operational resilience could be treated as a technology matter and delegated accordingly. If a firm had a CTO, responsibility was often there. If it did not, it shifted into finance or operations. DORA has since changed that dynamic. Responsibility now sits with the management body, which is held accountable for the ICT risk management framework. It means resilience is now a governance issue with clear ownership at the top of the business.
That changes the conversation both inside firms and with suppliers. Firms increasingly want hard evidence from their providers. They want to understand incident processes, failover arrangements, access controls and recovery expectations in practical terms. They also want to know when documentation was last reviewed, whether controls have been tested – and what would happen if a system failed.
The weakest point is often internal
For many private markets firms, however, the central issue is not whether a major external provider is resilient in principle. It is whether the firm’s own workflows can withstand increased pressure.
Key-person risk is at the heart of this issue. Many firms have built effective processes around capable individuals who know every workaround and hidden dependency. That may keep the machine running, but it is not the same as resilience. If knowledge is not captured and supported by the underlying platform, the process is weaker than it appears, severely increasing dangers when individuals leave or are unavailable.
The same applies once essential work starts moving outside the core platform into spreadsheets, email chains or offline approvals. Control weakens, visibility drops, auditability becomes harder and recovery becomes more uncertain. In private markets, where reporting expectations are high and investor scrutiny remains intense, that is not a side issue. It goes to the heart of whether the operating model is fit for purpose.
That matters particularly in fund accounting, where complexity has only increased. Reporting expectations are higher, structures are more demanding, and firms need stronger control across workflows. A system built for a different era often pushes work outside the main platform at exactly the point where clarity and control matter most. Once reporting becomes a scramble and key numbers are being pieced together manually, the workflow has already become more fragile than it should be.
DORA is the prompt, not the end goal
Operational resilience has often been treated too narrowly as a compliance cost. In practice, stronger resilience usually brings clearer process ownership, better visibility across workflows and faster responses when investors, auditors or regulators ask harder questions. It also reduces key-person risk and makes growth easier to support because the process does not have to be rebuilt every time complexity increases.
DORA will not solve every vulnerability in private markets operations, nor was it meant to. What it does is raise the bar for accountability, testing and supplier oversight. It shines a harsher light on brittle processes that have survived largely through habit and human intervention. It also makes clear that operational resilience depends not just on policies and providers, but on whether the underlying systems and platforms are strong enough to support controlled, auditable workflows under pressure.
That is the real wake-up call. Resilience has to run through the whole operating model, from the infrastructure underneath it to the controls and workflows used every day. That’s the real underlying lesson of DORA that private markets firms need to heed.
Craig Gravina, CTO at Semarchy, on why successful AI at scale requites the transparency and trust only proper governance foundations can deliver
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Across the globe, organisations are aggressively approving AI budgets, hiring teams, and deploying models, yet the promised returns remain elusive for many. AI investments continue to grow, but measurable business value is not keeping pace with the level of spend.
The numbers tell a striking story. Semarchy’s 2026 research of C-suite executives reveals that 99% of UK organisations claim AI readiness – with 69% saying they’re completely ready. Yet 56% making significant investments cite data management as their top challenge, while only 33% are prioritizing it for investment. This 23-point gap reveals the fundamental issue: organisations are building AI applications whilst underfunding the data infrastructure those applications require.
Globally, fewer than 2% of enterprises successfully avoid data quality problems, even though 74% planned to increase AI spending in 2025.
This isn’t a failure of technology talent or algorithms; it’s a governance breakdown. The path to faster AI ROI doesn’t run through better models, but through better governance and transparency, embedded at the center of every AI initiative from the outset.
The Hidden Cost of Ungoverned AI
When AI operates without governance, the primary risk shifts from technical to reputational. Whereas technical failures are recoverable, reputational damage is far harder to restore. Consider consequential AI decisions: credit denials, medical recommendations, hiring shortlists. When these go wrong publicly, the fallout extends far beyond the technical team. When regulators or customers ask how they make their decisions, organisations without governance have no credible answers.
The regulatory pressure only amplifies this risk. Global frameworks such as the EU AI Act, emerging UK regulations, and sector-specific rules increasingly require explainability and traceability. Companies that cannot show how AI reached its conclusions risk fines, restrictions, and forced remediation.
Public misfires, such as biased outputs or visible system breakdowns like Grok AI’s high-profile failure on X last year, can rapidly erode customer trust and brand equity. For consumer tech brands especially, reputational cost can exceed technical cost exponentially. Internally, unexplained or unreliable AI outputs erode confidence, resulting in disengaged business users, stalled initiatives, and data leaders losing credibility.
These aren’t exceptional cases. They’re the predictable result of deploying AI without governance infrastructure.
The Governance Misconception
Many organisations still treat AI governance as a compliance checkpoint, bolted on just before deployment to satisfy legal or risk requirements. This narrow interpretation is exactly what makes governance feel like an obstacle. Organisations feel forced into a false choice: move fast and bypass governance or be compliant and accept delays.
In this scenario, projects slow to a crawl. Data teams spend months preparing ‘clean’ datasets specifically for AI, only to sit in approval queues. By the time governance clears, business conditions have changed or stakeholders have moved on to new priorities.
The answer isn’t less governance; it’s different governance. Governance should be intrinsic to how data is defined, managed, and delivered. When governance “travels with the data,” models consume information that already carries quality checks, lineage, access controls, and semantic context already present. AI initiatives don’t wait for approval gates – they consume governed data from the start. There’s nothing to retrofit or remediate later, because the controls were in place from day one.
This shift from governance-as-gate to governance-as-infrastructure is the key divide between organisations that struggle to realise AI ROI and those that achieve it.
Transparency as a Strategic Asset
Leadership often frames transparency as a compliance requirement, but in AI, it’s just as critical for development speed. When data lineage is clear, AI teams don’t have to spend weeks figuring out where data came from, how it was transformed, or whether they can trust it. They can focus on building and refining models instead of investigating data provenance, shifting effort from detective work to value creation.
Transparency also removes technical friction. With explicit semantic context, models interpret data correctly without layers of custom preprocessing or extensive feature engineering. Consistent access controls across data sources prevent last minute security reviews from stalling projects at critical milestones.
Transparency enables continuous improvement cycles. When you can see exactly which data influenced a decision, you can diagnose errors with precision rather than guesswork. You can identify which specific data sources introduce noise or bias into model outputs, and measure whether data quality improvements affect AI performance in production, creating feedback loops.
Organisations that try to reconstruct this visibility only during audits pay for it repeatedly in delays, extended debugging, and failed deployments. By contrast, those that build transparency from the start move faster through development, testing, deployment, monitoring, and iteration. Transparency then becomes a competitive advantage rather than compliance burden.
What Real AI Success Looks Like
Real AI success isn’t a single breakthrough model. It’s the ability to deliver value repeatedly and at scale. Successful organisations move from proof of concept to production without major rework or last-minute governance scrambles.
In these organisations, AI consumes the same governed data as everyone else. Agents and models access data through shared interfaces and policies, alongside business users and operational systems. There’s no special ‘AI data prep’ phase, no separate pipelines to maintain, and no governance gap to close before go‑live. AI is simply another consumer of trusted data.
Explainability comes by default. Because lineage, transformations, and quality metrics are already present in the data, teams can trace any decision without forensic effort. When governance is built into data flows, AI teams can retrain on fresh data without re-running compliance reviews, keeping models current as business conditions change. Iteration cycles shorten from months to weeks or days.
This foundation also enables decentralised experimentation with centralised trust. Teams can launch AI initiatives against shared, governed data products without creating shadow pipelines.
Getting There: Three Practical Shifts
Reaching this future state doesn’t require a multi-year overhaul or new tech stack. It needs a focused effort in how data is delivered to every consumer, including AI, with governance built in rather than added later.
First, stop treating AI data preparation as a separate workstream. If AI teams need specially cleaned and packaged data, you’ve created handoffs that introduce delay and governance risk. Instead, provide data that all consumers can trust and use immediately.
Second, embed semantic context with the data. AI needs business context and meaning, not just schemas. What does ‘customer’ mean in this specific context – prospect, active user, former customer? What business rules apply, and what relationships matter for decision making? This semantic layer enables AI to interpret data correctly without custom workarounds.
Third, make lineage and quality observable by default. When lineage, quality scores, and transformation history are always available, debugging, compliance, and continuous improvement happen without emergency efforts.
Yet our research reveals the challenge: whilst 56% of UK organisations cite data as their top AI challenge, only 33% are prioritising investment in it. This misalignment between stated priorities and actual investment is precisely why AI initiatives continue to struggle, regardless of confidence levels.
The ROI Equation
The companies that achieve AI ROI faster aren’t the ones with the biggest budgets or the most sophisticated models – they’re the ones that eliminated the friction between data and AI consumption through proper governance infrastructure.
When governance is intrinsic, projects don’t wait for approval gates. With built-in transparency, debugging is fast, and audits are painless. The result? Shorter time to value, lower risk of public failure, reduced regulatory exposure, and AI investments that deliver measurable impact. These aren’t abstract benefits – they show up in project timelines, deployment success rates, and business KPIs.
The technology is ready. The question is whether your data governance is ready to support AI at scale. Success requires the transparency and trust that only proper governance foundations can provide.
Simon Pamplin, CTO at Certes, on how Quantum computing will eventually force a reckoning with the cryptographic assumptions on which the financial system is built.
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Financial institutions hold some of the most sensitive and long-lived data of any sector. Customer identities, decades of transaction records, credit histories, and proprietary trading information must be kept confidential, not just today, but far into the future. The cryptographic systems guarding that data, however, were built for a different era; one in which quantum computing was purely theoretical. That era is ending.
Recent guidance from both the G7 Cyber Group and the UK’s National Cyber Security Centre has made the stakes explicit: financial organisations should complete their transition to post-quantum cryptography by 2035. For institutions managing sprawling, decades-old technology estates, that deadline is less reassuring than it might first appear. Ten years sounds like breathing room. In practice, for organisations of this complexity, it is barely enough.
Quantum Risk: The Threat Doesn’t Wait for the Technology
The most common mistake in discussions about quantum risk is treating it as a problem for tomorrow. The assumption is that until a quantum computer powerful enough to crack modern encryption actually exists, there is no immediate danger. That assumption is dangerously flawed.
Sophisticated adversaries are already operating on a longer time horizon. The strategy, widely referred to as “harvest now, decrypt later,” involves systematically collecting encrypted data today and storing it until quantum computing capabilities catch up. No quantum computer is needed to execute this phase of the attack, only patience and storage.
For the financial sector, the implications are particularly serious. The data being harvested now, customer records, transaction histories, and commercially sensitive communications, could have a useful life measured in decades. By the time it is decrypted, the individuals and organisations it concerns will still be very much affected by its exposure. This is not a theoretical future liability. It is a risk quietly accumulating in the background of every financial institution that has not yet begun to act on it.
Why Updating Financial Systems Is So Hard
The cryptographic methods underpinning most financial infrastructure today, primarily RSA and elliptic curve cryptography, derive their security from mathematical problems that are extraordinarily difficult for conventional computers to solve. Quantum computing threatens to render those problems tractable, potentially dismantling encryption that currently appears robust.
Responding to that threat, however, means working through some of the most technically complex environments in any industry. Core banking platforms were often built 20, 30, or 40 years ago. Cryptographic functions are frequently embedded deep within application logic, firmware, or hardware, in payment terminals, ATMs, and proprietary systems that were never designed with replaceability in mind.
Replacing or updating these components is not a software patch. It can mean recertifying devices, replacing physical infrastructure, or undertaking large-scale application rewrites, all while maintaining continuous service to customers and satisfying stringent regulatory requirements. Progress is possible, but it is measured in years, not quarters.
Rethinking Security from the Data Outward
The quantum threat is also accelerating a broader rethink of how financial institutions approach security architecture. Perimeter-based defences, firewalls, VPNs, and network segmentation have consistently shown their limitations when attackers can move laterally through systems using legitimate credentials or compromised access. Relying on the boundary to keep data safe has a poor track record.
A more resilient approach centres protection on the data itself. By applying strong controls directly to information as it moves across systems, organisations can maintain security even within legacy environments that cannot be immediately upgraded. Sensitive data remains protected regardless of where it travels or which network it traverses.
Alongside this, crypto agility, the ability to swap out cryptographic algorithms and rotate keys without overhauling entire systems, is becoming a fundamental requirement rather than a nice-to-have. The transition to post-quantum standards will not be a one-time event. Cryptographic best practice will continue to evolve, and institutions that have built flexibility into their architecture will be far better positioned to keep pace.
The Cost of Inaction
The financial sector has a well-established capacity to absorb and adapt to technological change. It has navigated the transition to digital banking, the rise of real-time payments, and successive waves of cybersecurity threats. The quantum challenge is different in one important respect: the timeline for harm is already running.
Regulatory expectations are being set now. Adversaries are collecting encrypted data now. And the internal processes required to modernise a major financial institution’s cryptographic infrastructure take years to complete. The gap between when action is needed and when it can realistically be delivered is not wide, and it is narrowing.
Preparation does not demand panic or the immediate replacement of every system. It demands a clear-eyed audit of where sensitive data lives, an honest assessment of which information carries long-term confidentiality requirements, and a commitment to building security architectures that can evolve as the threat landscape does.
Financial institutions that move early will not simply reduce their quantum exposure. They will emerge with stronger, more adaptable security postures and with the trust of customers, regulators, and partners intact.
Quantum computing will eventually force a reckoning with the cryptographic assumptions on which the financial system is built. The question is no longer whether that reckoning is coming. It is whether institutions will be ready when it arrives.
Peter Pugh-Jones, EMEA Field Chief Data Officer at Confluent, on why the challenge for companies will not be building AI systems but standing behind the decisions those systems make
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For years conversations about data privacy have centred on conventional dangers, like breaches from outside, or leaks from within. The assumption has been that the biggest risk lies in information either being inadequately protected or improperly handled.
As we move deeper into the AI era, that picture is shifting. A more complex privacy challenge that we’re now faced with comes from how data is used once it sits inside an organisation.
AI is a crucial part of everyday business operations. It automates processes and shapes decisions. Data is no longer simply stored or shared; it’s interpreted and acted on at incredible speed, in ways that are difficult to trace or explain.
Decision-makers recognise the importance of accessing this data. 80% of business decision makers say without up-to-date data, businesses can’t be fully confident in decisions.
As such, the systems and rules that dictate how AI is used have never been more important. Business leaders need to be able to understand and explain how automated decisions are reached and the data that informed it.
Governance has to sit at the centre of the privacy conversation — not as a compliance exercise, but as the framework for the responsible application of AI. Without that foundation, organisations are likely to expose themselves to regulatory and reputation risk that they’re simply not equipped to avoid.
Privacy Now Depends On Explanation
Governments worldwide recognise the need for these AI frameworks. Europe’s AI Act has drawn the most attention, but equivalent regulatory approaches are appearing in markets from South Korea and the UK.
The result is that companies deploying AI systems are held to higher standards than ever when it comes to demonstrating that they use AI in a lawful, appropriate manner. As such, many businesses are discovering a gap between deploying AI and understanding it.
Implementing a model that produces useful outputs is relatively straightforward. Explaining how those outputs were created and which data shaped them is much harder. Where that clarity is missing, privacy becomes an operational problem.
Organisations may need to pause or redesign systems already in production because they cannot explain how those systems reached their conclusions. Some companies may even find themselves withdrawing products already released into the market.
So: what challenges are these organisations facing?
The Segmentation Challenge AI Introduces
One significant obstacle is segmentation. Companies need to understand who their systems interact with and which rules apply to each, and this isn’t always clear.
Businesses have historically segmented audiences by geography, demographics or behaviours. AI creates a more demanding requirement in that the systems using it must recognise when different safeguards should apply to different groups of people.
Regulation is pushing this further especially around children and vulnerable users. Content recommendations and automated responses that are acceptable for one group can become inappropriate for another.
The difficulty is that many AI systems are trained on broad datasets gathered across the internet. That breadth makes it harder to understand whether information came from a reliable source, or whether it should appear in a particular context. Without stronger segmentation, organisations risk losing control over how AI behaves in real interactions — and if that AI behaves inappropriately, it’s likely to lead to a breach of regulation.
Why Governance Cannot Be An Afterthought
Another mistake appears repeatedly in businesses deploying AI and modern data platforms. Governance is treated as something that can be dealt with later once systems are already running, with isolated but exciting pilots running well on smaller data sets often leading businesses to try and run before they can walk.
The challenge is even sharper in real time environments where data moves constantly between applications and teams. When governance is not designed into those flows from the beginning it quickly becomes a bottleneck.
In practice, the most effective point to govern data is when it first enters the business. Once information is already moving through systems, feeding models and generating outputs introducing controls becomes far more complex.
Many companies only realise months later that they’re lacking certain controls needed to manage risk. If they were never properly built in, it’s an expensive, time-consuming, incredibly nuanced task to put the genie back in the bottle.
The Shared Responsibility For AI Decisions
As with any cybersecurity approach, the human link can also be the weakest in the chain.
Responsibility for AI risk is often treated as if it sits neatly with one team. In many companies the assumption is that specialists are handling it, whether that is data scientists, a compliance function or a single executive role. The underlying thought is: “this is not my problem — someone else is dealing with it.”
That assumption creates problems. AI systems are trained on vast datasets and their behaviour is not always easy to predict without close scrutiny. When governance is treated as a delegated task, important questions can slip through the cracks unanswered.
Decisions informed by AI still sit with the business using the technology and ultimately with its leadership. Without senior oversight and a clear understanding of how systems are built, trained and governed privacy risks tend to surface long after those systems have become part of everyday operations.
The Question Organisations Should Be Asking
Organisations have the capability to build powerful AI systems. The harder question is whether those systems can stand up to scrutiny.
That means understanding where data originates, recognising differences between users and putting governance in place before automation begins to scale. It’s not enough to just co-opt an impressive new platform and give it access to your data.
In an AI driven environment privacy does not sit somewhere at the end of the process. It shapes how systems are designed, deployed and managed from the beginning.
In the years ahead, the challenge for companies will not be building AI systems. The challenge will be standing behind the decisions those systems make.
Berkley Egenes, Chief Marketing & Growth Officer at Xsolla, on why the real AI debate is about creativity and ensuring that machines support human expression, rather than replace it
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The conversation around artificial intelligence (AI) in video games has quickly zeroed in on jobs. Headlines warn of artists, writers, and designers being displaced by tools that can generate concept art at the click of a button, produce dialogue on demand, or compose background music in seconds. That fear is understandable; we’ve seen similar concerns in journalism, marketing, and content production, but it’s also limiting. Because when we focus primarily on economic displacement, we miss the far deeper challenge: what happens to creativity when generative AI begins to produce the art, dialogue, music, and even mechanics that shape a game’s identity?
The real debate isn’t jobs. It’s creativity.
From Efficiency Tools to Artistic Authors
In 2024, a survey by the Game Developer Conference (GDC) found that nearly half of game developers were already experimenting with generative AI tools for writing, art, or code. Industry analysts estimate that by 2030, up to 70% of mid-sized and large studios will integrate AI into their asset pipelines. These numbers signal rapid adoption, but they also risk setting expectations that AI is first and foremost an efficiency multiplier.
And it is, at least on the surface. Game development is famously deadline-driven and resource-constrained. Developers often spend years polishing art assets, scripting dialogue trees, and composing music suites. Generative AI promises dramatic productivity gains: conceptual environments in minutes, ambient soundscapes generated automatically, even procedurally expanded quests.
But under the hood of that promise is something more complex. Creativity in games isn’t just about completing tasks faster. It’s about voice, intention, and authorship.
When Enhancement Changes the Creative Equation
This is where the idea of job enhancement becomes more complicated than it first appears.
Generative AI unquestionably enhances creative roles. It can allow a single environment artist to produce in days what previously took weeks. It can enable a narrative designer to draft and iterate on branching dialogue trees at unprecedented speed. In pure productivity terms, enhancement looks like empowerment: the same people, equipped with better tools, producing more ambitious worlds.
But enhancement is not neutral. When AI dramatically increases output capacity, it changes the nature of the job itself.
Imagine a studio with ten environment artists. Before generative AI, they produced a carefully curated set of handcrafted scenes over two years. With generative AI tools, the same team might produce twice as many environments in half the time. That is job enhancement in its clearest form: no layoffs, no replacements, just expanded capacity.
But creative identity does not scale linearly with asset count. More backgrounds do not automatically mean a stronger artistic vision. In fact, abundance can dilute intentionality.
As AI enhances production, the human role often shifts from originating every element to curating, refining, and selecting from machine-generated options. The artist becomes part creator, part editor. The writer becomes part storyteller, part prompt engineer. The designer becomes part world-builder, part systems orchestrator. That shift is subtle, but profound.
When creators move from author to editor, the center of gravity in the creative process changes. Enhancement increases capability, but it can also redistribute authorship. The critical question is now whether AI makes creatives more productive. It does. The question is whether enhanced productivity deepens creative vision, or gradually distances humans from the expressive core of the work.
Why Creativity Matters More Than Efficiency
People care deeply about the emotional resonance of games. A compelling narrative arc, a haunting melody, a dialogue choice that feels meaningful – these aren’t just outputs, they’re expressive decisions. They reflect human imagination and carry cultural and artistic weight.
Creativity in games operates at multiple levels, like visual storytelling, narrative voice, mechanics design, and audio identity. Generative AI tools can do all of these. Large-language models can produce thousands of lines of dialogue in seconds; image synthesis tools can generate environments, characters, and textures from prompts; music AI can compose adaptive scores that fit different gameplay contexts.
The Limits of Machine Creativity
When AI generates a piece of music, art, or a story beat, it fundamentally recombines patterns learned from human-created data. There is no subjective inspiration, no lived experience, no intentional aesthetic choice behind the work, only statistical inference. That distinction is more than philosophical. It affects the game’s identity.
Consider two hypothetical scenarios:
A studio uses AI to generate placeholder environment concept art that artists later refine
A studio uses AI to generate final environment assets with minimal human input
In the first scenario, AI accelerates workflow, but human creativity still sets the artistic direction. In the second, the machine’s biases, training data limitations, and opaque generative patterns increasingly define visual identity, potentially diluting the studio’s artistic voice.
This pattern repeats across other domains. AI-generated dialogue might be serviceable, but will it capture the nuance of lived human experience in a way that players recognize as authentic? These are not questions with easy answers, but they are central to the cultural value of games.
The False Comfort of Economic Framing
Much public discourse has focused on job displacement. Partly because economic arguments are easier to quantify. People can point to employment numbers, wages, and productivity curves.
Creative impact, on the other hand, is harder to measure. When we frame the AI debate primarily in terms of jobs, we implicitly assume that creative work is fungible, that one person’s artistic contribution is interchangeable with another’s, including a machine’s. But in the arts, identity matters. Players choose games not just because they work well, but because they express something unique – a vision, a style, a tone. AI might replicate style, but it can’t originate meaning.
Redefining Roles, Not Replacing Them
That’s not to say generative AI has no place in game development. If used thoughtfully, it can be a powerful collaborator, a brainstorming partner, a rapid prototyping tool, and a way to push creative boundaries.
For example, writers using AI to generate dozens of narrative alternatives in seconds may help them explore more possibilities before committing. Whereas level designers using AI to test countless iterations of mechanics can see what feels most engaging.
In these cases, AI augments human creativity, not replaces it. It expands the sandbox in which creators play. But this requires deliberate choices. Studios need creative leadership that understands when AI is a tool and when it’s overreaching. There must be clear boundaries around authorship and safeguards to ensure that AI outputs serve the human vision, not obscure or subsume it.
Creativity as a Competitive Advantage
There’s another economic point that circles back to creativity: in a crowded market, artistic distinction is a competitive advantage. According to industry analysis, the global video game market is projected to exceed $300 billion by 2027, but growth is slowing in core segments, leading studios to compete fiercely on creative differentiation rather than sheer production volume.
In a world where everyone has access to the same AI tools, technical efficiency alone won’t distinguish one game from another. Games that lean too heavily on generic, AI-generated material risk becoming indistinguishable.
So the paradox emerges: AI might make game creation easier, but that very ease could erode the uniqueness that makes games worth playing.
The Future of AI in Games Should Be Artistic, Not Automatic
We should absolutely have conversations about job training, economic transition, and the ethics of data usage. But those debates should not eclipse the most important question: how do humans and machines collaborate to create meaning?
Creativity is not an economic output. It’s a human act of expression. In video games, where storytelling, mechanics, visuals, and sound converge, that act of expression is the beating heart of the medium.
If we allow AI to take over the mechanics of creation without guarding the human spark that animates it, we risk more than job shifts; we risk a homogenized cultural future where games lose their soul.
The real AI debate is about creativity and ensuring that machines support human expression, rather than replace it.
Chris Tredwell, Chief Operating Officer and Charis Thomas, Chief Product Officer at Aqilla, on why the question is no longer whether to adopt AI, but whether processes, governance structures and training pathways are ready for the workforce
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Have you ever got into an old car with a Gen-Zer? If they were driving, chances are you wouldn’t have got very far. A recent survey has found that 39% of 14–29-year-olds couldn’t identify an ignition key. Proof, if it were needed, that once technology advances, old ideas are quickly forgotten. This isn’t just happening in cars. The internet and social media have produced their own native generations – people who have never known a world without those technologies.
The same pattern is starting to emerge with AI. That means Gen Z and Millennials are about to experience a similar shift. The first wave of true AI natives will soon enter the workforce – a cohort that has never known a world without AI.
AI- The New Normal
People’s reactions will largely depend on their experience with AI. But one thing is certain: these graduate and entry-level employees won’t need to be convinced of its value. They’ve already seen what it can do, so if it’s missing, disbelief – or frustration – is likely to follow. It’s a bit like broadband. Here in the UK, it’s simply the standard we all expect. We don’t stop to think about how that connectivity reshaped our lives, helped us work from home or allowed us to stream high-definition media.
Many organisations are still in the early or experimental phases of AI adoption. They might be using the technology to automate basic email inbox management and take meeting minutes. Meanwhile, those further ahead of the curve are exploring more advanced tools and assessing where automation can be safely deployed, particularly for reporting and analysis.
But AI natives won’t see these use cases as experimental. In fact, they probably wouldn’t even refer to them as use cases. It’s just normal, like using a search engine rather than visiting a library to carry out research.
Prompting New Behaviour
Perhaps the biggest difference, however, is where organisations may integrate AI into their existing workflows, AI natives are more likely to structure work around it from the outset.
For them, work tends to start within an AI system, defining the objective clearly, setting constraints, and effectively “briefing” it, before iterating quickly and refining outputs as they go. For AI natives, this kind of prompt-based mindset isn’t a specialist skill; it’s simply how they approach tasks.
This is a fundamental shift. For AI natives, the question isn’t “Should we use AI here?” It’s “Why can’t I use it for this piece of work?” When their expectations collide with more cautious, process-led environments, friction is almost inevitable. Not because one approach is right and the other is wrong, but because both sides are starting from completely different assumptions.
Skills Transfer and Mentoring
But how does the need for AI natives to understand and work through basic manual processes coexist with intuitive prompt-based thinking? Should AI use come with experience-based restrictions in the finance sector? For example, do your three years first, and then you can use the tools.
It’s probably not what AI natives want to hear, but there is logic behind the approach. Learning the manual processes behind automation will enable new recruits to apply the necessary checks and balances to system outputs — putting them in a position to verify data rather than passively accept it.
Without taking this step, there’s a real risk that people will lose the ability to question the outputs they’re working with. That, in turn, has implications for how people are taught. Whether in an educational setting or on the job, that training needs to help AI natives understand the logic behind the systems they’ll be working with.
Lurking in the Shadows
If AI natives encounter friction when trying to use the technology, there’s a risk they’ll seek informal workarounds. Organisations have seen similar patterns before with personal devices or early cloud adoption. With AI, the risks are more focused on data, traceability, and accountability than on system access and security, though these remain important considerations.
Rather than restricting AI use, organisations are already beginning to reshape it by building oversight into how systems are used. That might mean making the AI’s working assumptions more visible and requiring humans to validate outputs. It might also require AI systems to signal their confidence in those outputs and to request manual checks. Over time, this reduces risk and creates an environment where people can work confidently with AI without losing sight of who is responsible.
This approach also challenges a common narrative. Much of the current discussion around AI focuses on job displacement, but the reality is more nuanced. The issue isn’t a simple replacement of human intuition and experience, but how those qualities evolve alongside increasingly capable systems.
Rather than removing the need for people, this managed shift reinforces it. Greater emphasis is placed on human-in-the-loop models, in which individuals with a deep understanding of AI can interrogate, challenge, and interpret system outputs.
A different starting point
So, what happens next? AI tool adoption, for sure. But it goes far deeper than that. Getting ready for AI natives means shifting to a different starting point – and learning to “live in the prompt”.
As AI natives begin entering the workforce and eventually move into leadership roles, the expectation won’t be that AI is introduced; it will be that it is already there. That shift reshapes how people think, learn, and approach tasks from the outset. It will also change how tasks are conceived, carried out and reviewed. The ability to configure, interrogate and challenge systems will become as important as the ability to interpret their outputs.
For organisations, the question is no longer whether to adopt AI, but whether their processes, governance structures and training pathways are ready for a workforce that already assumes it – and will expect to work that way from day one.
This month’s cover star, Marcus Johnston, deploys a leadership philosophy that blends empathy, operational discipline and pragmatic innovation as Precisely scales cyber solutions to meet the demands of regulation and accelerating digital risk. Learn how this CISO is reframing Cybersecurity for the AI era.“I view the role of InfoSec as a trusted partner advisor in the goals of the company to innovate, to introduce new technology, new platforms, to constantly be on the watch for changes in the threat environment.”
Ireland Department of Agriculture: Growing a Culture of IT Transformation
Louise McKeever, former Chief Information Officer and Head of Operations at Ireland Department of Agriculture, discusses the changes she drove at the agency and how a culture of IT transformation has gone on to thrive. ““My vision is that the Department’s data has consistency, is securely accessible, understood, and trusted… We have modernised our technology landscape, strengthened our capabilities, and most importantly, made a real difference in how we serve the Department and the sector.”
Washington State Dept of Natural Resources: Building Trust & Enabling Transformation
Washington State’s Department of Natural Resources (DNR) has been on a journey of building trust to enable transformation. We go inside that technology journey with CIO Liz Lewis-Lee on a mission to deliver reliable, effective technology. “At the DNR, all of our technology has to work to support all of the people all of the time, both in the office and out in the field.”
Virginia SCC: Building a New Cybersecurity Landscape
Glendon Schmitz, Chief Information Security and Privacy Officer at Virginia State Corporate Commission (SCC), discusses the exciting challenges of building a successful cybersecurity function. ““If everything’s a priority, nothing is. So understanding one’s lack of resources from a funding perspective and also the human side is important.”
Redefining Technology Leadership Through People, Culture and Business Outcomes
From the Music Industry to the Boardroom, IT leader Angie Fyke has blazed a trail for women in tech – she tells Interface her story of redefining technology leadership through people, culture and business outcomes from telcos to retail and today at Ontario Medical Supply. “The feedback I value most is when teams say they’re clearer, more confident, and able to move faster – that’s when you know change is working.”
Also in this issue, we learn from Claroty why critical infrastructure can’t afford to bolt on resilience; hear from NetApp on why defending against AI-powered cyberattacks requires AI-powered defence; and OVHcloud explain why Blockchain is crucial for the future of trust in AI.
Rob Demain, CEO at e2e-assure, on why the clock is ticking when it comes to IT/OT convergence for Critical National Infrastructure (CNI) and associated organisations
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Many critical national infrastructure (CNI) operators lack the ability to protect their infrastructure despite the UK being subjected to daily sub-threshold cybersecurity attacks, according to the Strategic Defence Review 2025. It’s a situation that the Network and Information Systems (NIS) regulations, introduced back in 2018, sought to prevent. But since its inception, just over half of the operators of essential services have updated or strengthened their existing policies and processes, leaving many woefully unprotected.
In desperate need of reform, NIS is set to be superseded by the Cyber Security and Resilience Bill (CSRB), which is expected become law later this year, at which point a consultation on implementation proposals will commence followed by secondary legislation and an adjustment period for stakeholders. The bill will broaden the scope to include other organisations deemed critical to the national economy i.e. data centres, Managed Service Providers (MSPs) and critical suppliers. Plus, the government reserves the right to extend those categories still further as part of its ‘future proofing’, which will enable changes to be made to the act to accommodate emerging threats and potential targets.
New Demands
All of these new entities will need to comply with the Cyber Assessment Framework (CAF), which lays out expected cybersecurity and resilience outcomes. First published in 2018 to support NIS, it has undergone a number of revisions since, with v4.0 released in August 2025. This version places a far greater emphasis on proactive security and decision making based on real threat intelligence. As well as adding new contributing outcomes on understanding threats and secure software development and support, it also expands the sections on security monitoring and response and recovery, while an entirely new category has been added on threat hunting.
All of this points to a far greater emphasis on being able to demonstrate assurance and proactively monitor all aspects of CNI infrastructure and that means more scrutiny of both IT and Operational Technology (OT). Until recently, securing OT wasn’t seen as a priority. These systems were chiefly concerned with maintaining system availability and minimising downtime. But their increased integration with IT systems to connect with the industrial Internet of Things (IIoT) and deliver real-time monitoring, for example, are exposing these systems to attack, with threat actors able to move laterally from one environment to the other.
The threat posed by IT/OT convergence is well known, but it continues to be the Achilles heel of CNI, as revealed by the Volt Typhoon attack. This saw Chinese nation state actors maintain persistence across CNI in the USA since at least 2021 through the use of Living off the Land techniques, illustrating just how insidious and sustained these cybersecurity attacks can be.
Securing IT/OT Systems
It’s these types of threat the CAF addresses through its risk and asset management requirements. Organisations must risk assess systems with respect to their dependencies and interactions with other systems such as IT/OT, and document and understand those dependencies. But other complementary frameworks can also be used to map IT/OT system security, such as the ISMS within ISO27001 from an IT perspective and IEC 62443 from the OT side, in addition to ISO/IEC 27019 for process control systems.
Being able to follow these frameworks will require organisations to increase their security monitoring of both IT and OT and the transparency of their processes. They will need to transition from being reactive to proactive, and become resilient and risk informed, which will mean many will have to change their approach. These are really the only options available to them in this respect if they are to move the resilience needle.
The first is to decentralise and harden OT systems while keeping them segregated from IT. However, hardening alone can’t keep pace with digital transformation. Many OT assets cannot support multi-factor authentication (MFA) or accommodate rapid patching because they are downtime sensitive. So, surface hardening alone won’t confer the resilience needed long term.
The second option is to manage IT and OT together by giving everything an identity in a converged environment, but to do that you need to move the monitoring of OT into the Security Operations Centre (SOC). Centralised monitoring allows threats to be detected across both IT and OT networks, for teams to monitor east-west traffic, and to correlate alerts that might otherwise appear unrelated. And it’s this centralised management that will provide the visibility and control needed to improve IT/OT resilience.
Converged Cybersecurity
Such a converged SOC doesn’t just offer continuous visibility over IT, industrial control systems (ICS), OT and cloud environs, but also the real-time triage of critical alerts. These might include unauthorised PLC logic changes, unsafe set-point writes, abnormal OT protocol behaviour, lateral movement in ICS DMZs, OT malware,or unauthorised remote access into OT environments. These alerts are then grouped by operational impact, such as whether they present a safety critical risk or could lead to service degradation, so that they can be prioritised. Weekly threat hunts and detection surface validation over distributed environments provide the threat hunting capabilities needed to meet the CAF requirements and the SOC evidences and provides that all important audit-ready compliance mapping to meet the demands of other frameworks too such as IEC 62443, and ISO/IEC 27019.
Whether standing up a converged SOC internally or outsourcing, this capability is the most efficient way to adapt to the tightening regulations, particularly as we can expect ‘future proofing’ to lead to yet more demands. The emphasis is now firmly focused on the proactive monitoring of both IT and OT systems together, given their growing dependencies, so it makes sense for those organisations in scope – as well as those who could soon be – to begin to move their OT monitoring from the plant and into the all-seeing all-knowing enclave of the SOC.
Adnan Patka, Enterprise Manager – Blockchain, AI and Web3 at OVHcloud, on why the convergence of blockchain and AI heralds a brighter future for both
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Anthropic’s Mythos team recently assessed various LLM technologies, scoring ChatGPT against Gemini, Grok, Claude and others. The metrics included trustworthiness, but also user deception, sycophancy, encouragement of user delusion and co-operation with human misuse.
Clearly, there’s no doubt that AI can be an enormously positive transformational force: the development of AlphaFold, whose founders won the Nobel Prize, showed us that very clearly. But when AI is being assessed for encouraging ‘user delusion’, it’s clear that it still has a PR problem.
In fact, AI has more than just a PR problem: research from McKinsey highlighted that although almost two thirds (64%) of decision-makers reported that AI was accelerating innovation within their organisation, less than half (39%) could actually report positive financial impact on the business as a result.
The AI Trust Gap
AI doesn’t exist in a vacuum, and the interplay of AI with other technologies is beginning to come into focus. We see that blockchain has great potential to complement AI, providing the transparency and trustworthiness that it needs. In a recent study of Web3 professionals, almost three-quarters (70%) said that blockchain had the potential to fill AI’s trust gaps.
But where else are these issues coming from?
It’s overly glib to say that people and businesses don’t always trust AI. What our research told us was that 32% of Web3 experts believe that privacy is AI’s main challenge. Historically, AI systems have been shown to be biased, and data has often been collected by AI systems for training or other uses – sometimes without user permission. One in seven (14%) of the study also reported that they believed AI needed more transparency to be trustworthy.
Blockchain’s Potential for Supporting AI
Blockchain is well-placed to help tackle these issues. Blockchain was originally created as a database with clear traceable links between items, without the need for a single governing authority.
For example, consider an AI system which optimises food supply chains, allowing a supermarket to maintain lower prices. In an environment where people may distrust AI, they may suspect that the system is simply buying lower-quality stock and shipping it more affordably, potentially meaning shorter shelf-lives and less tasty tomatoes! However, blockchain systems can help to track the provenance of these items, proving where the tomatoes were grown, when, by who, and the subsequent shipping and treatment of them, all in a publicly accessible ledger.
Blockchain systems also automatically check the validity of transactions and link them together in a way that makes fraud very difficult. Changing one transaction generally requires changing the entire ‘course of history’ or having significant control (specifically, controlling over half of the nodes) of an entire blockchain, which is usually unfeasible in most large, public blockchains today.
Delivering Benefits with Blockchain
There are also a number of cases where blockchain can bring functionality benefits to AI systems. For example, as we saw, privacy is a significant concern for AI users, but blockchain systems are able to authenticate securely without exposing user credentials, through self-sovereign identity. This is especially useful where AI systems need to interface with other tools that might not be as trustworthy as the core system.
Blockchain principles can also support data exchange in federated learning systems, where data is shared between different machine learning platforms. Blockchain can establish the validity of this data while still preserving its integrity and user privacy. This means that AI can be trained on data that is consistent and robust – without breaking trust.
There are a huge number of applications for this kind of technology, but unfortunately, it’s not all plain sailing.
Blockchain’s Challenges
The industry is undergoing a huge change today. Interest in stablecoins – a crypto asset which is attached to the value of a more stable asset like a traditional (fiat) currency or other physical commodity – has quadrupled since October 2025. Large, well-established organisations are considering what private and public blockchains can do for them, which could ultimately have a positive and stabilising impact on the regular bear and bull cycle that the crypto market experiences.
However, some more negative parts of blockchain’s legacy persist. Almost two thirds (61%) of our research sample said that concerns about blockchain’s credibility were having an impact on its integration into the enterprise ecosystem. This includes blockchain’s links with the more unsavoury side of cryptocurrency, including cybercriminal activity. Over half (54%) simply said that there wasn’t enough understanding about blockchain’s capabilities and what it could really do, holding IT decision-makers back from making the most of it.
At the same time, this isn’t a one-way street. AI’s capabilities – in particular, automated, agentic AI – can carry out blockchain activities without needing user input. For example, AI can issue transactions or analyse data and summarise it for monitoring systems. There is tremendous potential for AI to support many different parts of the blockchain ecosystem, summarising trends, automatically carrying out tasks, or executing smart contracts without human intervention.
A Mutually Beneficial Relationship
Blockchain and AI have enormous potential to support each other. There are some organisations already starting to integrate blockchain into AI and vice versa, but it will still be a number of years before the relationship is mature. That said, two-thirds of the Web3 experts we surveyed (67%) believed that it’d take roughly one to four years, with only eight percent saying that it might take five to six years.
Indeed, given the enormous benefits that blockchain can bring to AI, not to mention the rapidly increasing acceptance of blockchain technologies across the financial sector in particular, the convergence of these two technologies is almost inevitable. If we can push past the challenges, the future is bright for both blockchain and AI.
Adam Gale, Field CTO for AI & Cybersecurity at NetApp, on why cybersecurity in the AI era will depend on two capabilities: detecting abnormal behaviour as early as possible and ensuring trusted data can always be restored
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How can we not talk about cyberattacks when talking about AI? Barely a week passes without another story on AI-generated scams, deepfake voice fraud or ransomware becoming more sophisticated. Security teams are starting to see the effects in their own environments too. In many organisations, the first sign is simply the number of alerts appearing in security dashboards each morning.
Generative AI tools are lowering the technical barriers that once limited cybercrime. Cybercriminals can use it to generate convincing phishing emails in almost any language, code malware variants in minutes, or automate the process of scanning infrastructure for vulnerabilities. In fact, cyberattacks are now being generated at industrial scale. The good news is that AI can be an equally powerful tool for organisations in defending against this deluge.
When threats multiply faster than defences
It’s important to understand how quickly – and how far – Ransomware-as-a-Service has come in recent years. Large language models (LLMs) can now generate convincing phishing campaigns tailored to specific roles or individuals. Threat actors are already using them to scrape publicly available data and craft highly personalised emails that mimic internal communications. Malware authors are experimenting with AI to produce polymorphic code that changes its behaviour between executions, making signature-based detection far less effective.
Voice cloning is another rapidly emerging risk. In several reported cases, help desks and IT support teams have been persuaded to reset credentials after receiving calls from voices that sounded identical to employees or senior executives. What previously required careful social engineering can now be automated and scaled.
Many of these incidents succeed because cybersecurity platforms were built around a fundamental assumption: threats evolve incrementally and can therefore be detected by identifying known patterns. These include signature-based detection, rule-based alerting and static threat indicators. However, the problem is that this model breaks down quickly when cybercriminals can generate new variations faster than those signatures can be updated.
Additionally, monitoring tools generate huge volumes of warnings, many of which turn out to be harmless, but IT security teams still need to investigate them. When hundreds of alerts appear each day, this creates a risk of alert fatigue which may see genuine threats hidden in a sea of false alarms. As a result, malicious actors are now operating at machine scale while many defensive processes still rely on human triage, and this mismatch is becoming one of the defining problems in modern cybersecurity.
Fighting AI with AI
On the bright side, all that AI-powered automation can also be used for defence – not just offence. For example, AI can strengthen cybersecurity by examining activity across systems and data and identifying behaviour that deviates from normal operations.
Instead of relying only on known hacking techniques, AI-driven systems can monitor how data is accessed and modified across environments. If behaviour changes unexpectedly, systems can raise alerts or trigger automated responses. Detecting anomalies early matters even more as breaches become more automated, because the earlier suspicious activity is identified, the easier it is to contain the impact.
Automation also reduces the burden on security teams. Analysts spend less time reviewing routine alerts and focus more on investigating genuine threats. As organisations increasingly rely on AI systems, protecting the data those systems depend on becomes central to cybersecurity strategy.
This is especially crucial today, as modern enterprise data environments are highly distributed. Data is constantly moving between on-premises systems, cloud platforms, analytics pipelines and AI training environments. In turn, every transfer, replication process or API connection creates another potential attack surface.
This also means that storage plays an elevated role in supporting cyber resilience. Capabilities such as storage-level anomaly detection, autonomous ransomware protection and immutable snapshots allow organisations to identify suspicious data activity and preserve trusted recovery points. If systems are compromised, clean versions of data can be restored quickly without paying ransoms or rebuilding environments from scratch.
Building Confidence in AI Environments
AI is rapidly industrialising cybercrime. Malicious actors can now generate new techniques, test them and deploy them at a pace that traditional security operations struggle to match. Therefore, defence strategies must adapt accordingly. That means shifting from signature-based detection to behavioural analysis and from manual investigation to automated response. In other words, defending against AI-powered threats will increasingly require AI-powered security.
Ultimately, cybersecurity in the AI era will depend on two capabilities: detecting abnormal behaviour as early as possible and ensuring trusted data can always be restored. In a world where attackers can generate new threats in minutes, organisations that cannot protect and recover their data quickly will struggle to trust their systems at all – including the AI tools they increasingly rely on.
Nick Haan, Field CTO at Claroty, on how resilience will define which organisations stay operational when the next wave of disruptive attacks hits
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In October last year, Spain experienced one of the most dramatic infrastructure failures in modern European history. A sudden collapse in grid frequency left more than 50 million people without power, grounded flights, halted trains, and shut down businesses across the Iberian Peninsula. Fortunately, it was down to a technical issue known as an overvoltage event, not a hostile act by threat actors.
But the incident still delivers an important lesson: when critical infrastructure fails, the consequences will quickly cascade.
Geopolitical tensions are running high and state-sponsored actors increasingly target operational technology environments directly. The conditions for a similarly disruptive incident – this time deliberate – are building.
Withstanding these disruptive incidents requires building resilience into critical infrastructure at a foundational level. Not bolting it on as an afterthought. But with so many facilities designed and built for a different age, where do operators start?
The infrastructure threat is no longer theoretical
State-sponsored threat actors are no longer simply probing IT networks for data – they are targeting the operational technology that controls physical processes, including energy generation, water treatment, transport systems, and manufacturing.
The list of targets is expanding too, as critical infrastructure now encompasses airports, telecoms networks, hospitals, and commercial data centres. All of these areas are under increased cyber threat, and that makes it even more important that operators get on top of it now.
Data centres in particular will be a growing concern. Modern hyperscale facilities consume enormous amounts of power, making them uniquely dangerous nodes on the grid. If you bring a data centre down in one go, the impact on the grid will be immense.
Taking a centre offline creates a spike in one direction, while bringing it back up creates another. A coordinated cyberattack targeting multiple facilities simultaneously wouldn’t just take those sites offline, but could also destabilise the wider grid they draw from.
The problem with bolting security on
Most infrastructure operators are well aware of the increasing cyber threat, but it competes with many other challenges for resources.
A core difficulty facing most operators is that they are not starting from a blank page. The systems that control physical operations were built for reliability and longevity, not security. Many have been running for decades, and some predate the internet entirely.
Replacing them wholesale is not a realistic option, and even widespread retrofitting may not be possible where taking a system offline could interrupt critical services.
But that doesn’t mean that nothing can be done. The real opportunity in retrofit scenarios lies not in the operational technology (OT) assets themselves but in the infrastructure that surrounds them. Replacing a complete factory won’t happen – some of those components will remain old. But the switches, the firewalls, the IT-type infrastructure that underpins OT operations: that is what needs replacement.
Without modernising that network layer, even strong security tooling cannot do its job. If you know you need to do segmentation but haven’t got the switches to enforce it, what are you going to do with the information?
This is where resilience-by-design comes in. Organisations that treat cybersecurity as something to be addressed after the operational priorities are settled will find themselves permanently catching up – technically constrained, financially stretched, and exposed.
Resilience by design in practice
For organisations building new infrastructure, the opportunity to get this right exists – but only if security is treated as a design requirement from the earliest stages. The architectural choices, the network topology, the equipment specifications: these need to account for cybersecurity years before the first brick is laid, not at commissioning when the options have already narrowed.
But inbuilt resilience is still achievable for existing operators. The starting point is understanding what you actually have. An up-to-date asset inventory is the foundation of everything else, because you cannot protect what you cannot see.
From there, the question that should drive every security investment decision is simple: which systems would cause the greatest disruption if they stopped working? Security programmes built around that question will always outperform those built around compliance checklists.
Organisational structure matters too. Bringing IT and OT under a single point of security responsibility is essential – one person accountable across both domains, with the authority and tenure to make decisions that outlast their own role. Security decisions made by people who know they are moving on in two years tend to reflect that horizon.
Simplify, don’t accumulate
Most critical infrastructure domains tend to operate at a slow pace, where changes are big but take time to build momentum. This is a poor fit for the fast-paced and increasingly hostile nature of the cyber threat landscape.
However, there are immediate steps that operators can take now, without a major investment programme. Launching a programme to reduce redundancy and overlap is a quick win, especially for remote access systems.
Over time, most operational environments accumulate technology in layers. Each new vendor relationship, each maintenance contract, each operational requirement brings its own tools and its own access pathways. In one customer environment, we found 80 different remote access solutions in active use.
Reducing that to say, five or 10, is already a major security improvement – the complexity cost of those 80 solutions, in monitoring burden, policy management, and sheer number of potential entry points, far outweighs any operational convenience they provide.
The principle is straightforward: stop adding more and start strengthening what you already have. Vendors naturally tend to push their own tools and access requirements, but organisations need to push back. Prioritise resilience, simplify the ecosystem, and eliminate the fragility that attackers are counting on.
Preparing for the next wave of digital risk
The Iberian Blackout may not have been a hostile act, but it demonstrated what happens when critical infrastructure proves more fragile than anyone anticipated. The threat environment is not getting easier, and the interconnected systems that underpin daily life – energy, transport, communications – leave little margin for complacency.
Those that have built security in from the foundation will be better placed to withstand incidents, recover faster, and continue serving the people and industries that depend on them. Those who haven’t will find that bolting it on after the fact is slower, more expensive, and less effective than doing it right from the start. In the year ahead, resilience won’t just protect systems – it will define which organisations stay operational when the next wave of disruptive attacks hits.
Dave Silke, Managing Director, EMEA & APAC at Centripetal, on reframing cybersecurity as a leadership discipline
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Cyber resilience is no longer a technology problem; it’s a leadership one. For many executives, cybersecurity risk has become background noise. It’s ever-present and, fair to say, it’s routinely acknowledged, but it’s rarely confronted with the urgency it demands. Breaches appear in the news with unsettling regularity, followed by familiar language such as “sophisticated attackers” and “unprecedented scale”. But once the moment passes, business for most continues as normal.
This quiet normalisation of cyber incidents is not resilience. It is inertia, and it is costing organisations far more than balance sheets can show. The average global cost of a data breach, recorded by IBM, reached $4.44 million in 2025. This was driven primarily by operational disruption, lost business and recovery costs, but broken customer trust is harder to quantify and plays a significant role.
Yet despite the scale of impact, many boards still treat cybersecurity as a technical line item. Something to insure against or react to when needed. It is viewed as a risk to manage rather than a capability to lead. That mindset is the real vulnerability.
Inertia in the C‑suite
Leadership inertia rarely comes from ignorance. It often emerges from success. Many organisations have spent decades refining governance, compliance, and audit processes that worked well in a slower, more predictable world. But today’s threat landscape is shaped by automation, AI, and global cybercrime‑as‑a‑service, and those same mechanisms can quietly hold organisations back.
We remain deeply comfortable analysing failure. Forensic investigations, root cause reports and post‑incident reviews feel constructive, like we’re doing something about it. But in cybersecurity, understanding the last breach rarely prevents the next one. Attackers do not repeat themselves for our benefit, they adapt, and with AI, they now move faster than any human response cycle can match.
Forensic investigations are simply about giving shape to chaos. But what if we didn’t need to let the chaos in in the first place?
The Imbalance Between Speed and Focus
Modern cyber threats have scaled and ransomware groups now operate like businesses. Initial access brokers sell compromised credentials and AI and ransomware-as-a-service lowers the barrier to entry. At the same time, leadership attention is finite; CIOs and CTOs are balancing cloud migrations, regulatory change, AI adoption, supply chain risk and workforce transformation often while CISOs and security teams drown in alerts that they cannot realistically action.
The result is a dangerous disparity between leadership and attackers who operate at machine speed. We ask security teams to “do more” with dashboards overflowing with indicators, logs and alerts. But intelligence without application is noise, and noise breeds complacency.
Intelligence was Once a Government Privilege
For decades, threat intelligence was the domain of governments and military organisations. It relied on classified sources, cross‑agency collaboration, and the ability to process vast volumes of data in real time. That gap has now closed, and enterprises can now access the same categories of intelligence – from strategic, operational and tactical – previously reserved for nation states. Platforms enriched by AI and machine learning can ingest billions of indicators, correlate them at wire speed, and apply protections instantly across networks, cloud environments and endpoints.
This matters because over 99% of exploited vulnerabilities are already known at the time of attack. Security AI and automation now demonstrably change outcomes. Yet, despite availability, intelligence‑driven security is still framed by many leaders as “advanced”, “complex” or “future‑state”. That framing is itself a symptom of inertia.
Cultural resistance plays a significant role here. Research consistently shows that organisations reward risk avoidance over proactive change – even when data shows the cost of inaction is greater. The World Economic Forum’s Global Cybersecurity Outlook 2026 reporthighlights that organisational readiness and culture gaps are a major weakness in cyber security.
Leadership signals matter. When cyber risk is discussed only after incidents, teams learn that defence is reactive by design. When budget cycles plan for recovery rather than prevention, attackers are given implicit permission to succeed.
On the other hand, boards that treat intelligence as a strategic asset rather than a defensive afterthought consistently outperform peers in resilience and recovery. McKinsey’s 2025 report ‘Competitive advantage through cybersecurity’ shows that organisations embedding cyber security into strategic decision‑making achieve stronger long‑term performance and faster incident containment.
Leaving the “When, Not If” Era Behind
The phrase “it’s not if but when” has done more harm than good, as it removes agency. It tells leaders that breaches are inevitable, regardless of the level of effort or investment.
That is no longer true. Threat intelligence can prevent 99.99% of breaches. Threat‑informed security allows organisations to see hostile infrastructure before it is weaponised, block known threats before they touch production systems, and reduce noise so that human teams can focus on what truly matters.
For senior technology leaders, the challenge is not adopting another platform; rather, it is reframing cyber security as a leadership discipline. Every generation of leaders is defined by the risks it chooses not to accept, and today’s leaders are navigating a moment where intelligence – both human and technological – offers genuine leverage against an overwhelming threat landscape.
Choosing to remain reactive is no longer prudent. It is a decision with consequences that ripple through employees, customers, communities and markets.
Andrea Babayan, Demand Growth Strategist at Ipsotek (an Eviden business), on why the real competitive advantage will not belong to the hub with the most advanced analytics stack but the one that can demonstrate proportionality, resilience and clarity of purpose
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Transportation hubs are not simply adopting new technologies. They are reconfiguring how they operate. Digital identity systems, AI-driven video analytics, environmental sensors, drones and upgraded communications platforms are converging into core processes.
What was once framed as incremental innovation is now embedded in passenger throughput, dispatch coordination, platform management and perimeter oversight. Modernisation is no longer an upgrade cycle. It is a redesign of the operating model.
The more difficult question is not what these systems can detect, but whether institutions are evolving with equal deliberation.
Identity Border Systems as Throughput Infrastructure
Border modernisation makes the shift explicit. Europe’s Entry/Exit System (EES) illustrates how biometric identity is no longer merely a security control. It is a flow determinant. When enrolment, verification and exception handling are integrated into primary processing lanes, identity becomes inseparable from capacity planning and operational resilience.
The expansion of touchless identity verification in US airports reflects the same structural move. Identity confirmation now shapes staffing equations, lane geometry and peak-period modelling.
When these systems perform, throughput improves. When they stall, queues lengthen – and confidence declines.
Not all identity applications carry equivalent risk. Verification within controlled checkpoints differs materially from open-ended identification in public space. Proportionality must therefore be embedded at design stage. Governance is not a constraint imposed after deployment; it defines the parameters within which identity systems can scale without undermining trust.
In jurisdictions such as the European Union, where the AI Act establishes a formal framework for high-risk systems, institutional readiness must include formal risk assessment, auditability and transparent oversight mechanisms as foundational design requirements – not retrospective safeguards.
Border digitisation is not merely technological enhancement. It is throughput engineering under regulatory and operational accountability.
Sensor Convergence and Institutional Responsibility
Beyond borders, transport networks are integrating AI-powered video analytics with environmental sensors, access control systems and communications infrastructure. The objective is coordinated situational awareness – not visibility for its own sake.
Crowd density analysis can inform service adjustments. Platform anomalies can trigger structured escalation. Perimeter events can be validated through multiple inputs before operational response.
This convergence strengthens detection capability. It also expands institutional responsibility. As data streams intersect, purpose limitation, retention discipline, interoperability standards and escalation protocols must be clear. Integration increases capability – and scrutiny.
Governance is not a brake on innovation. It is the framework that allows it to scale responsibly. Alert volume creates noise. Decision quality creates advantage.
The Operational Decision Core
Modernisation is increasingly coalescing into centralised operational environments – decision cores that synthesise data across security, passenger flow, maintenance, access control and communications.
This direction aligns with the formalisation of collaborative operational models such as the Airport Operations Centre (APOC), which positions airport coordination as a structured, cross-stakeholder decision environment rather than a collection of siloed control rooms.
What was once compartmentalised becomes interconnected. The value lies not in dashboards, but in how insights shape staffing allocation, capital prioritisation, service recovery and commercial performance. Yet greater visibility does not eliminate boundaries. Cross-functional insight should improve coordination, not dilute accountability. Rich operational data must remain tied to defined purposes.
As AI systems transition from pilot to operational dependency, resilience becomes decisive. Designing for stress is therefore as important as designing for efficiency. Compliance cannot be retrofitted. Interoperability cannot be improvised. Institutional maturity cannot be assumed.
What Comes Next
Transportation hubs are becoming decision environments embedded within physical infrastructure. Cameras function as sensors; identity shapes throughput; and analytics informs operational judgement. But the defining difference over the next decade will not be technological sophistication; it will be institutional discipline.
In my view, the real competitive advantage will not belong to the hub with the most advanced analytics stack. It will belong to the one that can demonstrate proportionality, resilience and clarity of purpose – consistently, transparently and under pressure. Smarter systems are inevitable. Smarter institutions are a choice.
How Sonata Software is driving CPL Aromas’s technology transformation
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When CPL Aromas needed a software partner with deep technical expertise to guide its transformation, it chose Sonata Software. Theirs is a relationship that’s been going strong for eight years and counting – since Alfred Muthunathan, CIO at CPL, joined the team. “He was looking to transform the IT landscape,” says Uttam Hazari, Head of UKI & Europe at Sonata Software. “But before he could embark on that journey, it was important to ensure that the foundation was stable first.”
The goal was very simple: to ensure CPL could continually strengthen its system performance and improve reliability across its global operations. “It was growing at a rapid pace,” says Hazari. “However, the systems and data weren’t well integrated. It was important for us to work collaboratively with CPL to not only analyse the processes, but also stabilise the systems and the applications, and allow the company to regain its confidence.”
This early engagement reflects Sonata’s Frontier Firm approach – combining deep engineering expertise with business-aligned transformation to create resilient digital foundations.
A transformational relationship
Alongside the ERP support, Sonata partnered with CPL Aromas to develop its first B2B customer portal, enabling users to securely access orders and shipment information, thereby improving transparency and reducing manual interactions. “The early successes formed the foundation for a long-term digital transformation partnership built on trust, responsiveness, and delivery excellence,” Hazari adds.
This momentum reflects Sonata’s broader approach to building long-term, value-driven digital partnerships.
“Sonata Software is committed to building strategic partnerships that help organisations accelerate their digital transformation journeys. Today, our clients are looking for initiatives that move faster, reduce risk, and deliver clear, measurable business impact. As a Microsoft Frontier Partner, we bring deep expertise in translating advanced Cloud and AI capabilities into tangible outcomes. Our expansion across the UK and Europe marks an exciting phase of growth for Sonata, and our transformation journey with CPL Aromas is a key pillar of that strategy. We are privileged to have CPL Aromas as both a valued customer and a trusted partner.” – Anthony Lange, Chief Revenue Officer at Sonata Software
What began as a simple collaboration has evolved into a multi-phase, enterprise-wide transformation journey over the past eight years. A couple of years in, Sonata’s role expanded. “As part of that, we helped CPL rebuild and transform their core infrastructure,” says Hazari. “We also helped to implement Azure Site Recovery, stabilise IMS operations, strengthen identity and endpoint security, and establish modern monitoring with Azure Sentinel. And this is just the beginning.”
From ERP to infrastructure management to full enterprise modernisation, Sonata has been with CPL every step of the way, including the end-to-end global migration from the legacy ERP platform to Microsoft Dynamics 365 across multiple legal entities. “As we speak, the engagement has matured into a data-driven, AI-first innovation spanning across Dynamics 365 and the customer engagement platform, RPA automation, and agentic development,” says Hazari.
AI-first
Developing an AI-first approach is at the core of CPL’s current and ongoing focus, and it’s an area where Sonata has played a major role. “Sonata has been working very closely with CPL Aromas in its AI-first evolution – not just technically, but strategically as well,” says Hazari.
One of the key contributions to this has been building a modern digital core through the Dynamics 365 ERP program, enabling real-time visibility, standardised processes, and scalable operations. “These things are a prerequisite for effective AI deployment,” says Hazari. “Without that, you can’t just bring in AI to do the magic. Data is the most important ingredient. If the data isn’t right, the AI won’t be either. Then came automation at scale through RPA initiatives, which reduced the manual workload and increased process efficiency.”
More recently, Sonata has been working with CPL to pioneer its agentic AI adoption. “One of the recently deployed agents is a custom planner agent, which is designed to automate one of CPL’s most complex manufacturing processes,” Hazari explains. “This represents a major leap towards AI-driven decision intelligence across operations. Together, these initiatives have established the technology, data, and automation foundation for CPL Aromas’ AI-first strategy.”
These capabilities exemplify how Frontier Firms operationalise AI – embedding intelligence into core processes to drive real-time, autonomous decision-making.
The four pillars
Sonata is now helping CPL deliver value across four strategic dimensions. These consist of:
Operational resilience and security
Standardisation of global processes and transparency
Enterprise-wide data platform
Agentic AI-driven decision-making
“Bringing these initiatives together is transforming CPL into a digitally agile and AI-ready enterprise,” says Hazari. “That’s the value we’ve been able to deliver.”
The goal is for this relationship to continue for many more years. Sonata will continue to contribute towards CPL’s incredible growth, and as this collaboration progresses, it will be centred on CPL’s AI-first operating model.
“Scaling agentic AI beyond the initial successes is very important,” says Hazari. “That’s across all business functions, whether it’s finance, quality control, demand forecasting, supply chain optimisation, and even customer engagement. The idea is to help CPL in democratising AI across business functions, to reach a state where they’re able to create their own workflows and generate their own agents.”
As well as this, it’s about continuous automation and expansion to further reduce manual effort wherever possible from current processes. “Lastly, we’re working on enhancing digital sustainability,” says Hazari. “This includes ensuring that systems remain scalable, secure, and ready for emerging AI technologies. Technology is changing; AI is changing very rapidly. It’s extremely important for Sonata, as the strategic partner, to make sure we’re able to keep CPL Aromas one step ahead in this journey.”
Appian: Why AI is Putting Better Business Within Every Organisation’s Reach
Our cover story highlights how AI is putting better business within everyone’s reach.Mark Talbot, Director – CS AI Initiatives at Appian, reasons that as organisations grow more capable with AI, the challenge shifts from proving its value to expanding access to it. “Instead of concentrating control and decision rights in a small, central group, modern AI tools give more agency to the people closest to the work. They can see what is not working, imagine better approaches, and use AI to help redesign and improve the processes they rely on every day.”
CPL Aromas: How a Leading Fragrance House is Using AI to Amplify Creativity
In the world of retail, a leading fragrance house uses AI to amplify creativity. Alfred Muthunathan, CIO at CPL Aromas, explains how the family-owned business is using AI as a strategic capability to support creativity and accelerate innovation. “We didn’t bolt AI onto our systems; we redesigned the organisation, so AI is native to how we operate… Our new system takes away the workload from perfumers and has allowed us to create something that always keeps the nuances of our industry at its core.”
Vibrant Capital: Scaling AI on Main Street
Shadman Zafar, Founder & CEO of Vibrant Capital, is building a CIO-led model for enterprise transformation. Vibrant Capital is an operator-led investment and company-building platform focused on scaling AI in the real economy. “We don’t spray investments across hundreds of AI startups. We curate a portfolio with purpose – selecting companies that solve the real mission-critical problems CIOs face in scaling AI adoption.”
Also in this issue, we learn about the supply chain transformation journey at Swiss sportswear brand On, unpack the latest AI readiness research from Snowflake and hear from Hitachi Vantara about the importance of strong data foundations for the best utilisation of AI.
Snowflake’s UK research reveals that while many continue to invest in artificial intelligence (AI), the country’s businesses are in the early stages of finding productivity gains at scale
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UK productivity remains a longstanding economic challenge, with policymakers consistently positioning AI as a key lever for growth and competitiveness.
Snowflake’s findings show AI investment and experimentation amongst businesses though impact so far is varied. 45% of UK organisations say AI is delivering early gains or in specific use cases, though 23% are already seeing it delivering productivity improvements at scale. Buoyed by this thought, most organisations expect AI investment to increase over the next 12 to 24 months, with just 1% planning to decrease spend. Businesses continue to back thetechnology as a strategic priority, demonstrating confidence that productivity breakthroughs will come.
The UK AI Report
Conducted by YouGov on behalf of Snowflake, the report surveyed 500 senior decision-makers including CEOs & CFOs from large UK organisations, spanning key industries including public sector, manufacturing and financial services. These industries are seen as being vital to the Government’s AI and productivity ambitions. Its 2025 AI Opportunities Action Plan aims to boost the UK economy by £47 billion annually, estimating that widespread AI adoption could increase national productivity by up to 1.5% each year.
Dr Fabian Stephany, Economist & Departmental Research Lecturer at the Oxford Internet Institute (OII), University of Oxford commented: “I am encouraged to see early evidence that AI is beginning to generate measurable productivity gains for UK firms. Since the introduction of generative AI, many observers have been asking when these gains would materialise, and the findings suggest that this moment may now be arriving. This is consistent with what research would predict: technological breakthroughs rarely translate immediately into productivity improvements, as organisations need time to adapt their workflows, governance structures and capabilities.“
From AI Promise to Productivity Reality
The data suggests that while belief in AI’s potential is strong, execution at scale is proving more complex. Findings indicate that the primary obstacles to AI-led productivity are not technological. Instead, organisations point to structural and operational barriers as factors slowing the move from pilots to enterprise-wide transformation.
Top barriers include a lack of skilled workforce, poor data quality, organisational silos and unclear leadership or strategic direction. Technology itself ranks below many of these internal challenges, cited by just 19% of respondents. Responsibility for AI governance is also often fragmented across executive, technology, data and business leaders. While executive leadership typically holds responsibility for investment, there is no clear governance owner, limiting accountability and slowing decision-making.
This suggests that many UK organisations are pursuing AI at a measured pace, building progress through smaller, targeted use cases while strengthening internal structures, with broader productivity gains likely to follow as foundations mature.
In debates about national productivity, AI is positioned as a growth engine. For business leaders, these gains will manifest themselves at both their top and bottom line with cost reduction as a clear goal. Nearly half (44%) say that cost reduction matters most as a key measure of success, while 26% say the same of revenue growth.
The Executive Confidence Gap
The research also reveals cautious confidence on AI deployments among senior leaders. Only 24% of organisations say AI initiatives are identified and prioritised using a rigorous framework aligned to business objectives. Meanwhile, 40% expect AI to take two years or more to materially improve productivity.
Around 60% say ethics and safety concerns influence their decisions to adopt and scale AI. This reflects a responsible approach to deployment, particularly in regulated and risk-sensitive sectors.
Jennifer Belissent, Principal Data Strategist, Snowflake, said: “UK organisations clearly believe in AI’s long-term potential, and continued investment runs parallel to this belief. This research shows, however, that belief alone is not enough. Productivity gains require clear ownership, strong data foundations and alignment between AI initiatives and measurable business objectives. AI has the potential to be a real driver of UK productivity and economic growth. But unlocking that potential depends on getting the fundamentals right – governance, data and clear accountability.”
A Varied Industry Picture
The research highlights clear differences in AI maturity and confidence across key UK industries, although productivity gains remain uneven.
Financial services is more advanced on governance and strategic alignment, but regulatory and reputational concerns are slowing the move from structure to scale.
Manufacturing shows strong belief in AI’s long-term productivity potential, yet expects slower returns due to skills gaps and integration challenges.
Retail lags on confidence and delivery, with AI often confined to isolated use cases amid persistent data quality issues and fragmented ownership.
In the public sector, organisations are the most risk-aware and governance-led, but also anticipate longer timelines before productivity gains are realised.
53% cite safety & reliability of AI outputs as the top concern affecting confidence in AI.
Two thirds (66%) say ethics and safety significantly shape adoption decisions.
52% say AI will not materially improve productivity for at least two years.
While this cautious approach prioritises trust and accountability, it may mean productivity gains take longer to come to fruition.
Turning Point for UK Enterprise AI
Across industries, many are still realising how best to drive AI productivity at scale and the skills needed to make this a reality. While levels of governance maturity and risk appetite differ, the journey to broader productivity gains is shared.
Dr Stephany added: “The report’s finding that skills shortages are a key barrier to adoption strongly resonates with findings from my research group (SkillScale) at the Oxford Internet Institute, University of Oxford. AI systems are only as powerful as the people who develop, maintain, apply and govern them. In SkillScale’s research, we find that workers with AI-related skills command a wage premium of around 23% in the UK, have higher chances of finding a job, and are more likely to receive additional job benefits. These patterns reflect the strong and growing demand for talent capable of working with artificial intelligence. Expanding access to AI skills and training will therefore be critical if organisations want to sustain and scale these productivity gains and ensure that the benefits of AI are broadly shared.”
Jennifer Belissent concluded: “The research paints a clear picture. The foundations for AI success in the UK are in place. Organisations are investing, experimenting and strengthening governance frameworks. However, to close the gap between ambition and measurable productivity gains, businesses need stronger alignment, clearer ownership and more robust data foundations. If AI is to play the transformative role policymakers and business leaders expect, the focus must now shift from experimentation to disciplined execution.”
Methodology
The research was conducted by YouGov on behalf of Snowflake among 500 senior decision-makers from large UK organisations with 250 or more employees across manufacturing, financial services, retail, the public sector and other industries. Fieldwork was conducted in January 2026.
Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 13,300 customers around the globe, including hundreds of the world’s largest companies, use Snowflake’s AI Data Cloud to build, use and share data, applications and AI. With Snowflake, data and AI are transformative for everyone.
Asia’s FinTech ecosystem reached new heights with breakthrough announcements and industry-defining moments that will reshape the region’s financial landscape
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Money20/20, the world’s leading FinTech show and the place where money does business, concluded three days of industry‑shaping conversations. High‑impact networking, and packed stages were seen across three days from April 21–23 at the Queen Sirikit National Convention Center (QSNCC) in Bangkok, Thailand.
Money20/20 Asia – 2026
This year’s show welcomed over 4,500 attendees, a 40% increase in its third year. With over 360 speakers delivering over 100 hours of content across four stages. A very busy Money Hall show floor brought together delegates, sponsors and exhibitors from 90 countries. Across the show floor, companies reported a surge in commercial activity, with hundreds of partnership meetings, product demos, and investor conversations driving tangible deal‑flow throughout the three days.
“Money20/20 Asia is where Asia does business. The record attendance we’re seeing, combined with our relentless focus on quality – of audience, conversations, content, and experience – is translating into real partnerships and outcomes for the leaders shaping the future of financial services in the region. It’s why we are firmly established as Asia’s #1 quality FinTech show.” Danny Levy, Money20/20’s Executive Vice President & Managing Director for Money20/20 Asia and Middle East.
Headline Sessions
AI, cross‑border payments, digital banking, and the accelerating rise of digital assets, including stablecoins, tokenisation, and CBDCs shaped the headline sessions at Money20/20 Asia. Leaders from global banks, FinTechs, and regulators unpacked these themes across discussions on trust in banking, invisible finance, intelligent infrastructure, the future of digital banks, and ASEAN’s sustainability transition.
“Our goal is not just to digitise finance, but to humanise it,” said Daranee Saeju, Assistant Governor, Bank of Thailand, reinforcing the event’s focus on people‑centred innovation and trusted digital ecosystems.
These themes came to life across the agenda’s most talked about sessions. On Day 1, Technology, Trust and the Future of Banking in Asia brought together Scarlett Sieber of Money20/20 and Kattiya Indaravijaya of KASIKORNBANK to explore how modern infrastructure and AI‑driven intelligence are redefining trust and resilience in banking. “Uncertainty is a new normal. Banking will exist, but the way banks have to do the business will totally change,” said CEO Indaravijaya, Chief Executive Officer.
Day 2 spotlighted the rapid evolution of digital assets with The Rise of Blockchain and Stablecoin Payment Rails, featuring leaders from Uquid, Pantera Capital, VelaFi, and Trace Finance in a forward looking discussion on next‑generation cross‑border payment rails.
On Day 3, The New Paradigm of Cross‑Border Money Flows and International Expansion saw speakers from Money20/20, TenPay Global (Tencent), Fiserv, and Ant International unpack how Asia’s payment giants are building interoperable, multi‑rail systems to power global expansion.
Three Days of Expert Inisghts
Along with KASIKORNBANK, the programme saw strong participation from leading global and regional banks, with senior executives from Standard Chartered, Deutsche Bank, J.P. Morgan, Citi, and DBS Bank present across the three days.
FXC Intelligence and Money20/20 presented new findings from The New Era of Asia’s Cross‑Border Payments, underscoring Asia’s rapid growth, rising interoperability, and the convergence of key technologies shaping cross‑border finance. The Press Lunch additionally marked the debut of Money20/20’s new book, The New Intersection of Money – Where TradFi and DeFi Converge, exploring how traditional and decentralised finance are now co‑creating the future of financial services.
Money20/20 Asia spotlighted five rising startups Boost Capital, TrustPlus AI, Continuum, Eazy Digital, and zkMe, Money20/20’s Startup pitch winner during its Startup Media Panel. The show also hosted the Startup and Investor Park, where APAC startups met global investors and competed for a Golden Ticket to the 2026 Startupbootcamp Sustainability Singapore Accelerator. The program supports founders with pitching opportunities, investor access, and pathways to scale across Asia’s fast-growing fintech markets.
Policy20at Money20/20 Asia 2026 brought together more than 80 of Asia’s top policymakers, regulators, and industry leaders to address the rise of sovereign intelligence in global finance. In a closed-door Governors’ and Chairs’ Roundtable, participants aligned on three priorities: embedding regional values into global standards, building harmonised but sovereignty‑respecting cross‑border rails, and advancing intelligence‑led governance through AI and real‑time data.
After a highly successful third year in Bangkok, Money20/20 Asia has confirmed its return to the Queen Sirikit National Convention Center next year from 27-29 April 2027.
Andrew Power, Head of UK&I at Tricentis, on why the right approach to AI can deliver the foundation for more resilient, predictable systems
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Artificial intelligence is reshaping software delivery in financial services. Code that once took teams weeks to develop can now be generated and deployed in a matter of hours. This isn’t just about faster delivery; it changes the fundamentals of how software is built and how it behaves in production.
Financial institutions have moved quickly to integrate AI across core systems, from customer operations to anti-money laundering (AML) and software development to capture efficiency and innovation gains. UK parliamentary evidence shows adoption is already widespread, with the majority of firms using AI, and more planning to follow.
But as adoption spreads and becomes more embedded within key systems, so does exposure. Risk is no longer confined to individual defects, but shaped by how quickly those defects can spread across interconnected environments.
AI has removed the limits on how quickly software can be created, but not on how confidently it can be trusted, and financial institutions can now generate and deploy code faster than they can safely validate it.
This creates a new paradox: AI is both accelerating the pace of software change and increasing the speed and scale at which failures can materialise.
Machine-Speed Failure
AI-driven development shortens the distance between change and consequence. Software updates can move through the pipeline from creation to production with significantly less friction. However, this also reduces the time available to identify, flag and contain any issues before they have an impact.
AI-driven software changes don’t just move fast, they scale fast. Unlike traditional failures, these are systemic risks. A single misstep in an AI-generated update can propagate unpredictably.
For financial services, this is especially significant when key systems are deeply interconnected, spanning complex layers of infrastructure, integrations, and third-party services. Even a minor defect can propagate quickly across systems, amplifying its impact.
What would once have been contained can now escalate, cascading across systems and causing wider disruption that affects customers, operations and, in some cases, market activity. In financial services, this is not just a technical issue but a business risk with direct implications for customer trust, regulatory compliance and financial stability. The challenge is no longer simply identifying defects but maintaining confidence in what is being deployed.
This risk is already being felt across the sector. Institutions are accelerating delivery to meet customer expectations and competitive pressures, but often without corresponding advances in validation. Tricentis’ research shows 68% of financial services organisations anticipate outages or serious incidents due to poor software quality.
Regulatory Pressure for AI is Increasing
The issue is also drawing attention from regulators. Earlier this year, the UK Treasury Committee warned that current approaches to AI in financial services are inadequate and could expose customers and the wider system to “serious harm”, highlighting the need for stronger guardrails, clearer accountability and more robust oversight to deploy it safely.
Traditional resilience frameworks were never designed for systems evolving in real time, and AI can no longer be treated as a marginal technology risk. It must become central to how organisations manage and assess resilience.
This marks a shift from software quality being an engineering concern to a board-level issue of operational resilience. If machine-speed change is the new operational hazard, then failure to address it becomes a strategic issue rather than a technical one. With that in mind, financial leaders must acknowledge AI’s dual role as both a driver of risk and a mechanism for preventing it.
AI as Both a Safeguard & Source of Risk
AI also offers the most effective and scalable way to manage the risks it introduces. Advanced AI-driven validation, continuous monitoring and risk-prioritised testing can identify issues earlier than any manual process, helping reduce the likelihood they reach production.
In effect, the same AI that accelerates software creation must now be applied to validation and governance – operating at the same speed and scale.
The same capabilities that facilitate rapid software production can be applied to validation and governance, continuously evaluating system behaviour, detecting anomalies and prioritising testing based on potential business impact, rather than volume. This allows organisations to move beyond rigid approaches and towards more adaptive, responsive quality models that more accurately reflect the way AI behaves.
Instead of relying on standard periodic testing cycles, systems can be validated on an ongoing basis. This enables earlier intervention before issues escalate.
AI can also help organisations better understand the complexity of their own systems. By analysing dependencies across applications and infrastructure, it becomes possible to identify which processes are most critical and where failures would have the greatest impact.
From Acceleration to Control
There is a clear mismatch in how financial organisations approach AI. While many are leveraging AI to accelerate development, far fewer are evolving their validation and governance to keep pace, and it’s in this gap that risk emerges.
This is the “confidence gap”, where organisations can create software faster than they can safely deploy it.
To address this imbalance, firms must treat software quality as a core component of their AI strategy. Development and validation must move forward together. Governance must adapt to continuous, AI-driven change. This requires a move from static testing and coverage metrics to continuous, risk-based validation, where software is assessed in real time based on potential business impact.
If AI is the engine driving software creation, validation must act as the braking system – built in, not bolted on at the end. At machine speed, gaps in control become points of failure. The aim is not to slow innovation, but to ensure it progresses in a way that is sustainable and safe. When validation keeps pace with development, firms can move quickly and competitively, whilst maintaining control over how risk is introduced and managed.
This is a change we are seeing across large enterprises adopting AI-driven quality approaches, where validation, monitoring and governance are increasingly orchestrated together rather than treated as separate processes.
Preventing the Next Outage
The financial sector has already seen how quickly failures can escalate in complex, interconnected environments. In March, an IT error at Lloyds Banking Group exposed the private financial information of nearly half a million customers, prompting the bank to issue £139,000 in compensation.
Such incidents aren’t isolated: over the last two years, more than 33 days of unplanned banking outages have been reported to Parliament, underlining the scale of the issue.
As AI increases the velocity of change, it also raises the stakes for getting it wrong. But the irony is that it also provides the tools needed to prevent these failures from happening in the first place. AI is both contributing to the risk of outages and becoming the most effective way to prevent them.
By applying AI to continuous validation, monitoring and risk detection, organisations can spot issues earlier, understand their potential impact and intervene before disruption occurs. This shifts the focus from reacting to outages to preventing them, and it’s where the paradox becomes constructive. AI doesn’t have to be a source of instability.
With the right approach, it can become the foundation for more resilient, predictable systems. Those that fail risk trading innovation for instability. In the AI era, speed without confidence is simply another form of risk.
Peer-reviewed Physical Review Research paper shows efficient preparation of financial distributions on quantum hardware
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Haiqu, a leading developer of quantum middleware, has announced the publication of joint research with HSBC in Physical Review Research demonstrating an efficient approach to encoding real-world probability distributions into quantum circuits.
Quantum State Preparation
Quantum state preparation, the process of encoding classical data into quantum states, is widely recognised as a major bottleneck when implementing many algorithms on hardware. This challenge is particularly relevant for applications such as financial risk modelling and simulation, where complex probability distributions must be loaded onto quantum devices.
The research uses matrix product state (MPS) methods to construct shallow circuits that encode smooth functions, including probability distributions, directly into quantum states. It also introduces a sampling-based workflow that avoids storing the full discretised dataset in classical memory, enabling larger encoding circuits to be generated.
The approach was validated on finance-relevant models including heavy-tailed Lévy distributions, commonly used to capture extreme market events.
On IBM quantum hardware, circuits up to 25 qubits produced samples that passed standard statistical tests, showing the method can accurately reproduce the probability distributions these models rely on in practice.
Sampling-Based Workflow
Using the sampling-based workflow, the researchers also executed circuits up to 64 qubits, reproducing qualitative features of the target distributions under realistic device noise and demonstrating feasibility at larger scales. Similar behavior was observed in simulations up to 156 qubits, indicating the approach can extend to substantially larger problem sizes.
“Preparing complex probability distributions efficiently is a key step in many quantum algorithms,” said Dr. Philip Intallura, Group Head of Quantum Technologies at HSBC. “This work shows how they can be implemented with much shallower circuits, bringing practical applications such as financial risk modelling closer.”
“One of the biggest practical barriers is getting realistic financial data onto today’s quantum hardware. This work shows a scalable path around that barrier and helps move quantum finance workflows from theory toward execution.” Mykola Maksymenko, Co-founder & CTO, Haiqu
Haiqu is an emerging leader in quantum software that supports the notion that near-term, commercially viable applications are achievable with the right software, even on current hardware. Haiqu’s hardware-agnostic software can run applications with up to 100x more operations on current devices compared to competitors. Headquartered in New York City in the United States, Haiqu’s expert team operates from US, Canada, Ukraine, UK, EU, and Singapore, contributing to the company’s mission to make quantum computing practical as soon as possible.
ZeroThreat co-founder Dharmesh Acharya on why the only way to know if your defences actually hold is to challenge them with continuous penetration testing and exploit validation
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Your security dashboard is green. No alerts. No critical flags. Everything looks fine. That feeling of calm is exactly what you should be worried about. A clean dashboard does not mean your application is secure. It often means you are measuring the wrong things.
If a threat operates outside those parameters, it stays invisible. Your logs look normal, your vulnerability scanner reads low risk and your compliance status says passing. And somewhere in your environment, an attacker could be moving quietly through systems your dashboard never touches.
Let’s take a look at why green dashboards can be misleading, what they are not showing you, and what real security validation actually looks like.
The False Comfort of a Green Dashboard
There is something deeply reassuring about a green dashboard. No alerts. No red flags. And no critical vulnerabilities screaming for attention. For most security teams, that view signals control. It signals safety. But here is the uncomfortable truth: a clean security dashboard does not mean your environment is secure. It often just means your tools are not seeing the full picture.
Most monitoring systems only report what they are configured to detect. If a threat operates outside those parameters, it stays invisible. Your SIEM logs look normal. Your vulnerability scanner shows low risk and your compliance status reads “passing.” Meanwhile, an attacker could be sitting inside your network, moving quietly, and your dashboard would never know.
According to IBM’s Cost of a Data Breach Report, the average breach takes 168 days to identify and 51 days to contain it in the finance industry. That is over six months of green dashboards while real damage is being done. False confidence in security metrics is not a minor issue. It is one of the most exploited gaps in enterprise security posture today.
5 Problems with Traditional Security Metrics
Traditional security metrics were built for a different era. They measure what is easy to measure, not what actually matters. And when security decisions are based on incomplete or misleading data, the entire security program becomes vulnerable, even when everything looks fine on paper.
1. Visibility Without Context
Knowing that 10,000 events were logged means nothing without understanding what those events represent. Traditional metrics track volume, not relevance. Security teams end up drowning in data while the actual threats, the ones that matter, go unnoticed. Coverage without context is just noise.
2. Compliance Masking Risk
Passing a compliance audit does not mean you are secure. It means you met a checklist. Many organizations confuse regulatory compliance with actual cyber resilience. Attackers do not care about your audit results. They look for gaps, and compliance-focused metrics rarely surface those gaps in time.
3. Perimeter-Focused Thinking
Most traditional security metrics are built around the perimeter. But the perimeter does not exist the way it once did. Remote work, cloud environments, and third-party integrations have dissolved those boundaries. Metrics that still prioritize perimeter health give a dangerously narrow view of your actual attack surface.
4. Lagging Indicator Dependency
Traditional metrics tend to be reactive. They tell you what already happened, not what is happening right now. Mean time to detect, incident counts, patch rates, these are all lagging indicators. By the time they show a problem, the damage is often already in motion. Real security needs leading indicators too.
5. Ignoring Unknown Assets
You cannot protect what you cannot see. Shadow IT, unmanaged endpoints, forgotten cloud instances, these assets rarely show up in traditional security dashboards. Yet they are among the most targeted entry points for attackers. Metrics that only account for known assets create a false sense of complete coverage.
Hidden Risks Your Dashboard Doesn’t Show
Your dashboard reflects what your tools are configured to monitor. Nothing more. Unmanaged devices, misconfigured cloud storage, dormant user accounts with excessive privileges, these risks exist outside the monitoring boundary. They do not trigger alerts. They do not show up in reports. But they are real, and attackers know exactly how to find them.
Lateral movement is one of the most dangerous and least detected attack behaviors. Once an attacker gains initial access, they move quietly across your environment using legitimate credentials and trusted pathways. Traditional security monitoring tools rarely flag this activity because it does not look like an attack. It looks like normal user behavior. That is precisely what makes it so effective.
Third-party risk is another blind spot most dashboards completely ignore. According to Verizon’s Data Breach Investigations Report, 15% of breaches involve a third party. Vendor access, supply chain integrations, and API connections create exposure points that sit entirely outside your visibility. If your dashboard is not showing you that, it is not showing you everything.
What a Genuinely Healthy Security Posture Looks Like
A healthy security posture is not about having zero alerts. It is about having full visibility, fast response capability, and continuous validation. Organisations with mature security programs do not chase green dashboards. They build systems that surface the right information at the right time.
According to IBM, organizations with a fully deployed security AI and automation program contained breaches 108 days faster than those without. Speed of detection and response is one of the clearest indicators of a strong security posture. That cannot be measured by looking at how calm your dashboard appears.
Real security health includes knowing your complete asset inventory, including cloud workloads, third-party connections, and unmanaged endpoints. It means having continuous monitoring that goes beyond compliance checkboxes. It means your team runs regular adversarial testing to find gaps before attackers do.
And it also means your security metrics are tied to business risk, not just technical thresholds. When a CISO can clearly explain what is protected, what is exposed, and why, that is what a genuinely healthy security posture actually looks like.
How to Ensure Real Security: Exploit Validation
Knowing you have vulnerabilities is not enough. You need to know which ones can actually be exploited, and how far an attacker could get if they tried. That is what continuous exploit validation delivers. It moves security testing from a scheduled event to an ongoing process that reflects your real-world risk exposure.
AI-driven automated penetration testing makes this possible at scale. Instead of waiting for an annual pentest, these tools continuously simulate real attacker behavior across your environment. They test your controls, validate your detections, and surface exploitable paths before a real threat actor finds them. Your security team gets evidence, not assumptions.
The result is a security program that is grounded in reality. You stop relying on what your dashboard says and start relying on what has actually been tested and verified. Continuous exploit validation closes the gap between perceived security and actual security, and that gap is exactly where breaches happen.
Conclusion: Stop Trusting Your Dashboards and Start Validating
A green dashboard does not mean you are secure. It means nothing alarming has been detected within the boundaries your tools are configured to monitor. That is a very different thing. Real security is not about how calm your dashboard looks. It is about how thoroughly your environment has been tested and validated.
The only way to know if your defences actually hold is to challenge them. Continuous penetration testing and exploit validation give you evidence, not assumptions. They show you what an attacker would find before an attacker actually finds it. That shift, from monitoring to validating, is what separates a false sense of security from a real one.
By Dvir Hoffman, CEO at CommBox on why organisations that will lead in the next phase of digital transformation are those that treat AI not as a feature, but as a production capability
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Enterprise AI has entered a new phase. The experimentation cycle that defined the past few years, full of proofs of concept, innovation labs, and sandbox deployments, is giving way to a harder question: how do we operationalise AI at scale, safely and measurably?
Nowhere is this tension more visible than in customer service voice environments. Voice remains the most complex, emotionally nuanced and operationally demanding channel. It is also where AI has the potential to unlock some of the greatest value.
Recent research from McKinsey highlights that organisations embedding generative AI directly into customer operations are seeing productivity improvements of 30 to 45 percent when deployment is integrated into workflows rather than layered on top. The distinction is critical. AI succeeds not because it sounds intelligent, but because it is embedded into systems, governance and business metrics.
For technology leaders, the path from pilot to production is less about enthusiasm for AI and more about discipline in execution.
Why AI Voice Often Stalls Before Scale
The majority of AI initiatives do not fail because the technology underperforms. They stall because the surrounding enterprise architecture is not aligned.
In controlled pilots, AI voice agents can demonstrate impressive conversational capability. They answer FAQs, interpret intent and simulate human dialogue convincingly. But production environments are not defined by conversation quality alone. They are defined by operational depth.
When a customer calls a healthcare provider, an insurer or a retailer, the AI must do more than talk. It must: Authenticate identity securely. Retrieve and update records in real time. Execute transactions, escalate appropriately and comply with regulatory frameworks. Without direct integration into CRM systems, billing platforms, policy databases or electronic health records, AI remains superficial.
This is where many organisations hit friction. Production requires orchestration across telephony infrastructure, data platforms, compliance frameworks and human workflows.
Governance becomes another inflection point. Voice interactions carry legal and reputational weight, particularly in regulated sectors. Disclosure requirements, audit trails, escalation protocols and data protection controls cannot be retrofitted after deployment. The World Economic Forum’s 2024 work on responsible AI underscores that governance must be embedded into AI systems by design, particularly where customer trust and compliance are at stake.
When governance is treated as an afterthought, scaling slows dramatically.
There is also a measurement problem. Too many pilots are judged by narrow metrics such as intent recognition accuracy or conversation duration. Production environments are judged by business impact: containment rates, reduction in average handling time, cost-to-serve, regulatory adherence and customer satisfaction. If AI is not connected to those outcomes from the outset, executive momentum fades.
The shift from pilot to production requires organisations to think less about model performance and more about operational alignment.
Automation Without Eroding Trust
A common concern among executives is whether AI voice will erode customer trust. The answer depends entirely on how it is deployed.
Voice remains deeply human. Customers call when they want clarity, reassurance or resolution. In emotionally charged situations, such as reporting an accident, disputing a claim, or querying medical results, the experience must feel competent and controlled.
The most effective AI voice deployments do not attempt to automate everything. They focus on high-volume, structured interactions where resolution paths are clear and compliance rules can be embedded confidently. Appointment scheduling, policy updates, payment processing and order tracking are examples where end-to-end automation can meaningfully reduce friction.
In live enterprise environments, we are seeing organisations safely automate a significant proportion of inbound calls when the AI agent has direct access to real-time data and defined escalation thresholds. Customers benefit from immediate resolution, while human agents are freed to handle complex and emotionally sensitive cases.
Equally important is what happens when escalation occurs. AI should not disappear at the point of handoff. Instead, it should transfer context, summarise the conversation and provide agents with relevant data and next-best-action prompts. This augmentation model aligns with Gartner’s 2024 analysis of customer service technology trends, which emphasises that the greatest gains come from combining automation with agent enablement rather than pursuing full replacement.
Trust is reinforced when customers feel they are being served efficiently and responsibly. That requires transparency about when AI is involved, clear pathways to human support and systems that operate within strict compliance guardrails.
In regulated industries, explainability is no longer optional. Enterprises must be able to demonstrate how decisions were made, how data was handled and how customers can escalate concerns. When these safeguards are engineered into the platform, AI voice becomes a tool for strengthening trust rather than compromising it.
Where Enterprise Leaders Should Focus
As AI investment accelerates, CIOs and CDOs face pressure to deliver measurable value while maintaining governance standards. The lesson from organisations successfully scaling AI voice is that integration and oversight matter more than experimentation.
AI should be treated as infrastructure. That means prioritising deep integration with core enterprise systems from the outset. An AI voice agent that cannot execute transactions securely or access accurate, real-time data will struggle to deliver meaningful business outcomes.
Governance must also be operational, not theoretical. Clear escalation pathways, role-based permissions, audit capabilities and sector-specific compliance frameworks need to be embedded within the technology layer. When risk management is part of the architecture, deployment accelerates rather than slows.
Finally, measurement must be tied directly to business performance. Containment rates, resolution times, operational cost reductions and customer satisfaction metrics should be defined before rollout. McKinsey’s 2024 research reinforces that organisations capturing the most value from generative AI are those embedding it deeply into workflows with explicit performance targets.¹ AI that operates alongside business KPIs, rather than parallel to them, is far more likely to achieve sustained executive backing.
The broader transformation taking place across enterprise technology is not about AI replacing human capability. It is about rearchitecting customer engagement so that automation, data and people operate in synchrony.
Meeting AI Voice Demands
Voice remains one of the most demanding channels to modernise precisely because it sits at the intersection of emotion, compliance and operational complexity. Yet that is also why it offers such strategic value. When AI voice is integrated into core systems, governed rigorously and measured against real business outcomes, it moves from being an innovation experiment to becoming a structural advantage.
The organisations that will lead in this next phase of digital transformation are those that treat AI not as a feature, but as a production capability. Moving from pilot to production is not simply a technical milestone. It is a cultural one, signalling that AI is no longer an experiment on the edge of the enterprise, but a trusted component at its core.
The Innovate Finance Global Summit (IFGS) once again set the tone for London FinTech Week, transforming the historic Guildhall into…
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The Innovate Finance Global Summit (IFGS) once again set the tone for London FinTech Week, transforming the historic Guildhall into the beating heart of global financial innovation on Tuesday April 21st 2026. As the flagship event of the week-long programme, IFGS brought together more than 1,500 senior leaders from over 70 countries. Cementing its reputation as one of the most influential gatherings in the FinTech calendar.
A mix of founders, regulators, policymakers, investors and financial institutions filled the venue’s grand halls, all drawn by a shared ambition: to shape the future of financial services. IFGS has long positioned itself as “where decision-makers meet,” and in 2026 that promise felt particularly tangible.
A Global Stage for a Rapidly Evolving Industry
The summit’s scale and structure reflected the complexity of today’s FinTech ecosystem. Across four stages and more than 100 sessions, attendees were immersed in a dense programme of keynote speeches, panel discussions and live demonstrations.
What distinguishes IFGS from many industry events is its ability to convene not just innovators, but the entire value chain. Fom early-stage startups to global banks, Big Tech firms and regulators. Companies such as Google Cloud, Amazon Web Services and Microsoft were prominent throughout the programme, reflecting the growing convergence of financial services and cloud infrastructure. Where policy meets practice and innovation meets implementation.
The agenda in 2026 was firmly aligned with the industry’s most pressing challenges and opportunities. Themes ranged from AI in financial services and open finance to stablecoins, fraud prevention and financial inclusion. Not juts abstract talking points, but the battlegrounds on which the future of finance will be decided.
Opening Momentum: Optimism with a Call for Action
The day began with a keynote from Innovate Finance CEO Janine Hirt, who set a confident yet pragmatic tone.
“We have built one of the most dynamic fintech ecosystems in the world here in the UK,” she said. “But leadership is not guaranteed. It requires constant innovation, investment and collaboration.”
Hirt highlighted the UK’s continued strength in areas such as open banking, while stressing the need to accelerate progress in digital assets, fraud prevention and global competitiveness.
A recorded address from Chancellor Rachel Reeves reinforced this narrative, positioning fintech as a cornerstone of the UK economy.
“Fintech is not just a success story—it is a strategic priority,” Reeves noted. “We will continue to back innovation, support digital assets development and ensure the UK remains a global hub for financial services.”
The political backing on display underlined fintech’s growing importance—not just as a sector, but as a driver of national economic growth.
AI, Data and the Next Wave of Innovation
Unsurprisingly, artificial intelligence dominated much of the conversation. Across multiple sessions, speakers from firms including NVIDIA, IBM and Accenture explored how AI is reshaping everything from customer onboarding to fraud detection and credit decisioning.
What stood out was the shift in tone. The discussion has moved beyond hype to implementation.
“We’re past the experimentation phase,” said a senior executive from Mastercard during a panel on AI in payments. “The focus now is on scaling responsibly. Embedding AI into core systems while maintaining trust and transparency.”
Similarly, Revolut’s leadership team pointed to AI-driven personalisation as a key differentiator in the next generation of digital banking. “Customers increasingly expect financial services to anticipate their needs. AI enables us to deliver that, but only if it’s built on strong data foundations.”
Closely linked to AI was the continued evolution of open banking into open finance and ‘smart data’. Speakers from the Financial Conduct Authority (FCA) and firms such as Plaid and TrueLayer emphasised the importance of interoperability and regulatory clarity.
“Open finance is the natural next step,” said an FCA representative. “The challenge is ensuring it delivers real value to consumers while maintaining robust safeguards.”
Meanwhile, stablecoins and tokenisation emerged as key themes in the context of global competition. Circle, Ripple and several UK-based digital asset firms contributed to discussions around the future of programmable money.
“The question is no longer if tokenisation will reshape markets, but how quickly,” said a Ripple executive during a digital assets panel.
The Exhibition Floor: Innovation in Action
Beyond the stages, the expo hall offered a tangible view of FinTech’s evolution. Established players such as Lloyds Banking Group, NatWest and Santander UK showcased innovation initiatives alongside emerging startups presenting solutions in regtech, embedded finance and payments.
Fintech scale-ups including Checkout.com and Adyen demonstrated new capabilities in cross-border payments and merchant services, while regtech firms, such as Entrust, highlighted advances in compliance automation and fraud detection.
This blend of established and emerging companies is one of IFGS’s defining strengths. It creates an environment where partnerships can form organically. Whether between a startup seeking scale or an incumbent looking to innovate.
The presence of regulators, notably the FCA, added another layer of value. Initiatives such as onsite ‘office hours’ enabled direct engagement between FinTech firms and regulators.
“Dialogue is essential,” one FCA official commented. “Events like IFGS give us the opportunity to hear directly from industry and shape regulation that supports innovation.”
Networking: Where Deals and Ideas Converge
If content is the backbone of IFGS, networking is its lifeblood. The summit’s design – from curated meetings to informal discussions in the Guildhall’s historic spaces – encouraged meaningful interaction.
With thousands of attendees and a high concentration of C-level executives, the event offered unparalleled access to decision-makers. Conversations between banks, FinTechs and investors were constant, with many attendees citing partnership discussions as a key outcome.
Even external challenges—such as a London Tube strike on the day—did little to dampen participation. If anything, it reinforced the determination of attendees to be part of the conversation.
“Nothing was going to keep people away,” remarked one venture investor. “IFGS is where the industry sets its agenda for the year.”
Key Takeaways: Collaboration, Competition and Confidence
Several clear themes emerged from IFGS 2026.
First, collaboration remains critical. The UK’s fintech success is built on strong relationships between startups, incumbents and regulators.
Second, global competition is intensifying. Whether in AI, digital assets or open finance, the race to lead the next phase of financial innovation is well underway.
Third, there is a growing sense of confidence in fintech’s role as an economic driver.
“Fintech is no longer a disruptor, it is the foundation of modern financial services,” said a senior executive from HSBC during a closing session.
Conclusion: A Catalyst for the Year Ahead
IFGS 2026 delivered on its promise as the centrepiece of London FinTech Week. By bringing together the full spectrum of the FinTech ecosystem in a single venue, it created a powerful platform for dialogue, collaboration and innovation.
More than just a conference, IFGS serves as a barometer for the industry’s direction. The conversations held within the Guildhall’s walls will shape strategies, partnerships and policies in the months and years ahead.
As FinTech continues to evolve at pace, events like IFGS are not just important; they are essential. They provide the space for ideas to collide, for relationships to form and for the future of financial services to be defined.
In 2026, IFGS once again proved why London remains at the forefront of global FinTech. And why the world continues to look to the UK for leadership in shaping what comes next.
Lee Nolan, GM UK&I at Hitachi Vantara, on why AI will not be defined by the sophistication of the models being deployed but the strength, consistency and reliability of the data that sits behind them
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Spend five minutes in any boardroom and AI will come up. Strategies are being signed off, budgets are being released and pilots are already underway, giving the impression that momentum is building at pace. Yet beneath that surface is a more uncomfortable reality, one that is becoming harder to ignore as organisations move beyond experimentation and into delivery.
Most organisations are trying to build AI on foundations that were never designed for it. The ambition is clear and well-funded, but the underlying data infrastructure has not kept up. That gap between intent and readiness is now becoming visible, particularly as organisations look to scale beyond isolated use cases and deliver outcomes that are consistent and commercially meaningful.
Recent research into UK businesses reinforces this point. While adoption continues to move forward, only a small number of organisations are genuinely set up to support AI at scale. The issue is not tools or talent, but the condition of the data at the core of the business.
AI Exposes What Businesses Would Rather Ignore
AI is often described as a layer that can be applied to existing systems to unlock value. In practice it does the opposite. It brings complexity into sharp focus, exposing inconsistencies and inefficiencies that may have been tolerated for years.
That is why data quality has moved to the centre of the conversation. Around 67% of UK organisations now cite it as the primary driver of AI success. The shift reflects a growing awareness that no level of investment in AI can compensate for weak or unreliable inputs.
For many organisations, data has evolved without a consistent approach to governance. In fact, Gartner estimates that 80% of organisations attempting to scale digital initiatives will fail due to weaknesses in data and analytics governance. Systems have been added over time, ownership is unclear and definitions vary. The result is a fragmented environment where the same metric can mean different things across the business. When AI is introduced, it does not resolve those inconsistencies, it amplifies them.
The Hype Cycle is Giving Way to Reality
Over the past year, there has been a shift in how organisations approach AI. The early phase was driven by urgency, with businesses keen to move quickly and demonstrate progress. That momentum remains, but it is now being balanced by a more realistic perspective.
There is a greater focus on outcomes, with more scrutiny on how AI is delivering value. Many organisations have realised that quick wins are harder to achieve when the underlying data is not fit for purpose, and that scaling AI requires a level of operational discipline that cannot be bypassed.
What was initially framed as a technology challenge is now understood as a business challenge, spanning processes, ownership and governance as much as platforms and tools.
Confidence is High but Capability is Uneven
Confidence across organisations remains high, but it often does not reflect reality.
While many businesses consider their data infrastructure to be mature, progress is often uneven. Some teams may be working with well governed data, while others are still reliant on manual processes and disconnected systems. This creates a situation where parts of the business are ready to move forward, while others are not, a challenge reflected in wider industry research from McKinsey & Company, which highlights siloed data as one of the biggest barriers to scaling AI.
That inconsistency is where problems begin. AI depends on trust in the data If that trust is not consistent across the organisation, outputs become unreliable and adoption slows. From the outside, many organisations appear ready, but internally the foundations are still being stabilised.
Control vs Convenience
There is also a growing emphasis on control, particularly around where data is stored and how it is managed. Data sovereignty is now playing a central role in decision making, with around 85% of UK organisations saying it directly influences how they deploy AI.
This reflects a broader recognition that data is both a critical asset and a potential point of risk. As organisations become more reliant on it, they are also becoming more deliberate in how it is governed and protected.
At the same time, the expectation that everything should be built in-house is fading. Many organisations are turning to external partners to accelerate progress, while retaining control over their data and strategic direction. This balance allows them to move faster without losing oversight.
Vague AI Strategies
One of the most persistent challenges is the lack of clarity around what AI is meant to deliver. Too many initiatives begin with broad ambition and little definition of success, resulting in activity that is difficult to measure and even harder to scale. This is reflected in wider industry trends, with Gartner noting that only 53% of AI projects make it from prototype into production.
The organisations making progress are far more structured. They define clear objectives, establish measurable outcomes and maintain a focus on value throughout. In the UK, a growing majority are now putting formal KPIs in place for their AI initiatives.
This shifts AI from being an experiment to something that can be managed, evaluated and improved over time.
AI Will not Wait for Organisations to Catch Up
AI will continue to evolve at pace, and the pressure on organisations to keep up is unlikely to diminish. What is changing is the nature of the conversation. It is becoming less about what AI can do in theory, and more about what organisations are actually capable of delivering.
Most are still in the process of building the foundations required to support AI effectively. That is not a failure, but it does define the scale of the challenge ahead.
Because ultimately, AI will not be defined by the sophistication of the models being deployed. It will be defined by the strength, consistency and reliability of the data that sits behind them.
Mark Talbot, Director, CS AI Initiatives at Appian, reasons that as organisations grow more capable with AI, the challenge shifts from proving its value to expanding access to it
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Many organisations have long treated improvement as something that arrives as a top-down effort, not something built with the people doing the work. Specialists designed new processes, discussed them in formal forums, and introduced them through large change programmes that often felt detached from daily work. For most employees, ‘transformation’ meant being asked to follow new rules, rather than designing better ways of working.
AI is starting to reverse that pattern. Instead of concentrating control and decision rights in a small, central group, modern AI tools give more agency to the people closest to the work. They can see what is not working, imagine better approaches, and use AI to help redesign and improve the processes they rely on every day. This shift – which can be described as the democratisation of AI – changes who participates in improving the business. However, it is worth remembering that this shift only works at scale when AI is embedded within a platform that maintains governance, visibility and control.
Process Improvement in the Hands of Many
Until recently, fixing a broken process often meant filing tickets, waiting for a slot on an IT roadmap, or hoping that a specialist team would eventually address the issue. Creating applications, building automations or redesigning workflows were seen as highly technical tasks. For most employees, waste and inefficiency were things to work around, not things they had the tools or authority to change.
That obstacle is now deteriorating, as long as organizations don’t lose sight of the fact that governance remains essential, particularly in highly regulated environments
AI agents, generative AI and conversational interfaces allow people across the business to shape how work is structured. Within this model, someone in operations can describe an outcome in plain language and have an AI system propose and embed the steps within existing processes. Within a governed platform, non-technical users can adapt existing solutions and automate repetitive tasks without waiting months for central support. At the same time, process insights give developers visibility into what is being built, enabling them to refine, standardise and scale applications more quickly across the organisation.
Data is opening up as well. Data fabrics and related architectures connect scattered information sources into governed layers that a wider audience can access safely. Instead of waiting on static reports, people can access relevant, trusted data when they need it, and use AI to interpret and apply it to their decisions.
When process insight and data access reach this level, best practices move beyond documentation or occasional training. Tools and workflows embed them into daily work, improving performance across the organisation.
Scaling Improvement Across the Organisation
As more individuals understand how their work connects to broader outcomes, organisations unlock a powerful driver of change. Process improvement no longer depends only on a small group of specialists. Employees can recognise when processes are inefficient or risky and have the means to address them at scale, inside an AI platform.
By encoding domain knowledge into AI assistants and digital coworkers within an enterprise-grade AI platform, organisations can share expertise across roles and levels. These AI-powered helpers do not replace professional judgment. They strengthen it. They surface options, highlight inconsistencies and provide context, while humans make the final decision. Over time, each interaction becomes both a learning moment and a new piece of institutional knowledge that organisations can capture and reuse.
In this model, process improvement is no longer episodic or confined to formal transformation projects. It becomes part of everyday work, inside a platform with AI tools that provide real-time feedback and recommendations.
AI, Noise Reduction, and Better Oversight
This shift raises a key question: if AI platforms make analysis, decision support, and process design more accessible, what happens to deep expertise?
There is a concern that easy access to AI advice might weaken people’s understanding. If answers are always a prompt away, will teams still develop the knowledge that comes from working through complexity? If people follow AI suggestions without grasping the logic, how meaningful can human oversight really be?
Over-reliance on instant guidance can create only surface-level competence. People may treat AI outputs as instructions rather than as inputs to their own reasoning.
On the other hand, used well, AI can create more room for expertise, not less.
By handling repetitive tasks and routine decisions, AI reduces the volume of low-value work that consumes people’s time. Teams can then focus on exceptions and refine how they make decisions. Instead of dealing with every routine request themselves, they can focus on work where context and experience matter most.
When AI removes more of the routine burden, teams have more capacity to focus on judgement, process design and oversight. That helps build expertise while keeping improvement connected to the wider goals and governance of the business.
Shaping AI, Not Just Living With It
As organisations grow more capable with AI, the challenge shifts from proving its value to expanding access to it. AI is moving from something that happens to the workforce to AI being something that is built and refined with the workforce.
Organisations should treat people as partners in shaping AI, rather than as operators of automated systems. When AI platforms can be combined with process visibility and human judgement, employees can have an outsized effect on the systems around them. They can influence how work is structured and how decisions are made. In that sense, AI redistributes who participates in designing better ways of working, and creates an opportunity to anchor that shift in thoughtful design and human expertise.
Daniel Ehnhage, Head of AI Transformation at Unit4, on why those that put people and capability at the centre of their AI strategy will unlock far greater and more sustainable value than those led by technology alone.
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As the head of AI transformation, it might sound counterintuitive to suggest that artificial intelligence is not the most important part of my work. It makes a significant contribution to the radical change we are looking to achieve, but the technology itself is only about 10% of the solution. A significant part of the planning and investment must be based around addressing issues like the integration of siloed information systems, the building of the organisational capability required to adopt AI safely and finding the right business case. The key is to understand that adopting AI is not only about improving existing processes – it’s about gradually reshaping how we work in a sustainable way. The goal should be phased, practical improvements that build maturity over time.
This can be daunting for any organisation that has well-established operating practices. It requires a deliberate shift from problem‑solving to rethinking how value is created across the organisation. AI is far more capable and can empower your teams to find new solutions such as gathering more intelligence about market opportunities to improve productivity and decision making. The focus should be on enabling internal teams to work smarter through safe, responsible AI adoption. If your organisation is prepared to embark on such change, you must recognise AI becomes most powerful when you bring the right data together. Today, many organisations, including ours, are still maturing in this area. Successful adopters of AI prioritise building data readiness step by step so AI can create real value without overpromising.
Obviously, the role of AI transformation then becomes much broader with the added challenge of having to implement change without disrupting existing business performance. Consequently, there are some key areas where organisations must focus their attention, beyond ensuring they pick the right AI tool…
Structural Change – Put the AI Board in Place
AI transformation evolves how organisations work. It does not replace everything we humans do today. The goal is to focus on practical, high‑value use cases that improve productivity, quality, and employee experience without creating disruption. A widely debated expression of this change is the concern that AI will replace human employees. Personally, I think this lacks imagination around the positive impact that AI can have on a workplace. Yes, it may reduce the number of repetitive, mundane tasks, but more importantly it will create new ways of working and collaborating.
However, given how rapidly the technology is moving it is critical your organisation puts the right safeguards in place and agrees policies about ethical usage. That requires adoption of a cross-functional AI Board to provide a framework for embracing AI which will manage the impact of the structural change. This provides focus for your organisation’s approach to AI. The goal should be to agree which tools offer the most benefit for your teams and concentrate on exploiting use cases that will deliver the most benefit.
The AI Board should be responsible for establishing the governance structure to help the IT and cybersecurity teams to ensure the use of AI is not creating new vulnerabilities. It should provide clarity and safeguards so employees can use AI confidently and responsibly. Our goal is to enable safe experimentation – not restrict innovation.
People Change – Enabling Collaboration and Experimentation
The ambition should be to get employees excited about the potential of AI to open up new ways of working that can lead to rewarding opportunities and exciting new challenges. Indeed, it is widely accepted that helping your people to accommodate the change is the biggest challenge you will face, taking up about 70% of the time required to implement the technology. This is because successful implementations depend on collaboration between distinct teams, which in turn depends on breaking down barriers, both for individuals and teams.
For example, imagine being able to use AI to analyse data from diverse systems such as customer service, product development and marketing to identify new opportunities to support customers.
Integrating these data sources could be seen as interfering with distinct job functions, so for all employees it is critical to educate them on what will be expected of them and a good start point is explaining how they will be measured. It could include simple measures such as demonstrating usage of AI tools, but if an organisation wants employees to adopt the technology it is also important to empower them through training.
With the right support, employees will want to experiment, which should also enable them to understand use cases for AI in their work and the competencies they need to develop. This can be achieved through opportunities for cross-functional teams to explore new ways of working and innovating and should be encouraged by senior leaders. It is crucial they set the right tone, support initiatives, celebrate successes and listen to employee feedback.
Business Change – Building the Right Business Case
The business case is not just about saving money to solve a specific problem. It is too easy to look at the saved hours and productivity gains from adopting AI as the sum total of the investment costs you must deal with. There are a number of internally focused requirements that you must build into your thinking about AI transformation. There will be costs around the integration work to enable AI to access data from disparate systems. Competence development must be a top priority. Time must also be allocated to the process of change management and how it may disrupt existing business processes. Security must be a top consideration. These are all internally focused tasks, but you must look at them if you are to capitalise effectively on your AI investment.
It is tempting to become overly excited by the potential of AI as a technology, and certainly it will bring dramatic change to organisations in the years to come, but having experienced the factors necessary for successful transformations, it is absolutely critical senior leadership teams approach AI-enabled change with cool heads and clarity on what they want to achieve. Above all, they must remember success is not dependent on the implementation of the technology, but predominantly on bringing employees with them on the journey. Many commentators talk about the rise of AI-first organisations. Those that put people and capability at the centre of their AI strategy will unlock far greater and more sustainable value than those led by technology alone.
Vincent Guillevic, Director of Fraud Labs at Entrust, argues companies that treat identity as a continuous thread rather than a single checkpoint will be better positioned to reduce losses and protect customers
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Identity verification and tackling fraud began as a face-to-face process, built on human trust. Opening a bank account involved meeting a banker in person and from there, trust was established because both parties could see and interact with each other directly in branch.
Fast forward to the digital age and a lot of services have moved online. Identity verification has therefore shifted from in-person checks to remote identity verification. Today, we’re in an era where identity is now central to every interaction we have online.
Fraud has followed the same trajectory. Much like a burglar would test every possible entry point rather than just the front door, fraudsters probe every stage of the customer journey. They look for weaknesses at onboarding, during login, and throughout ongoing transactions and data requests.
That challenge has intensified in recent years. AI has given fraudsters faster, sophisticated and scalable tools. Deepfakes can bypass checks, AI‑generated documents can appear real, and phishing and impersonation attacks can now be automated at scale.
Once a fraudster gains access to a legitimate account, the damage escalates quickly. Global losses from account takeover (ATO) fraud were projected to reach $17 billion in 2025, up from $13 billion in 2024. While the underlying intent of fraudsters seeking the weakest point of entry, the breadth, speed and sophistication of modern attacks have.
Identity Fraud Patterns Across the Customer Lifecycle
Fraud can occur at any stage of the customer journey. From verifying identity at onboarding to securing connections and fighting fraud in everyday transactions. Each stage introduces its own risks, and attackers adapt their tactics based on where value can be extracted most efficiently.
In 2025, patterns showed a clear distinction between industries targeted for new account fraud and those targeted for account takeover fraud. Businesses that offer immediate incentives such as promotional offers or sign-up bonuses are primarily targeted for new account fraud. In contrast, businesses where accounts accumulate long-term financial or data value face higher levels of ATO.
Industries built around sign-up incentives or instance access experience most fraud at onboarding. For instance, in crypto, 67% of fraud attempts occur during account creation, largely driven by sign-up incentives. Vehicle rental follows a similar pattern, with 67% of fraud taking place at onboarding as attackers use fake identities to gain short-term access to high-value assets. In these sectors, low-friction onboarding creates opportunities to harvest incentives or establish accounts that later become avenues for future money laundering.
Account takeover fraud reflects a different strategy. Rather than creating fake accounts, attackers focus on compromising established accounts using tactics such as stolen credentials, phishing, malware, or social engineering. Entrust data shows this is most common in industries where accounts hold enduring value. In payments, 82% of fraud attempts occur after onboarding, while in professional services the figure is 62%. High-value, long-standing accounts are attractive because they enable fund transfers, loans, and access to identity-rich data, making them more valuable than newly created accounts.
These patterns highlight two critical realities. First, organisations can no longer optimise for one type of risk at the expense of another. Defending a single point in the journey inevitably leaves gaps elsewhere. Second, fraud has become highly professionalised. Modern fraud operations are organised, strategic, and adaptive, moving toward the highest rewards and the weakest controls.
Prevention Must Span the Entire Journey
If fraud can occur at any stage, prevention must operate at every stage. Organisations that implement robust, lifecycle-wide identity strategies save an average of $8 million per year in fraud-related costs. These savings come from detecting threats earlier, more accurately, and beyond a single checkpoint.
There are three areas where that lifecycle approach needs to be strongest.
Get onboarding right
Onboarding is the first opportunity to establish genuine trust. Strong Know Your Customer (KYC) or Know Your Employee (KYE) processes combine document verification with biometric checks such as face recognition or fingerprint scanning to confirm that the person applying is who they claim to be. Liveness detection adds a further layer by distinguishing real users from synthetic identities and deepfakes, which are linked to approximately one in five biometric fraud attempts.
With strong identity verification at onboarding not only reduces immediate fraud, but also limits the downstream damage caused with fraudulent accounts.
Secure existing accounts with continuous authentication
Verifying identity once is no longer sufficient. Continuous authentication, combining multi-factor authentication with biometric re-verification like facial recognition, allows businesses to protect established accounts without creating unnecessary friction for legitimate users.
Crucially, it enables authentication requirements to adapt dynamically as risk levels change, rather than applying the same static check regardless of context. In payments businesses, where most fraud targets the authentication process itself, this adaptability is key to mitigating attacks before losses occur.
Monitor behaviour in real time, not just identity
Device intelligence and behavioural signals make it possible to assess risk based on how users interact with services, flagging unusual login patterns, device anomalies, or out-of-character transactions.
As AI-driven fraud becomes more sophisticated and convincing, behavioural indicators provide another layer of ongoing fraud detection. Focusing monitoring on high-risk actions, rather than only high-risk identities closes a critical gap in traditional defences.
The Window of Opportunity
Fraud has always followed the customer journey. What has changed is the availability of advanced technology capable of tracking, analysing, and responding to threats at every stage. The key question for organisations is whether these capabilities are deployed as a connected strategy or left as isolated controls with gaps in between.
Companies that treat identity as a continuous thread rather than a single checkpoint will be better positioned to reduce losses and protect customers, and preserve the trust that underpins long-term digital relationships.
Andrew McLernon, CEO and co-founder at Interlink, on why culture is the real disruptor
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For much of modern business history, disruption has been framed as something external. An emerging technology or a competitor rewriting the rules. Often, markets shift faster than organisations can respond and leaders are told to move quicker, work harder and implement more systems to keep up.
Today, AI has become the latest catalyst for this narrative, with every week seeming to bring another promise of productivity gains or automation breakthroughs. Yet as AI accelerates, many organisations are responding in surprisingly familiar ways: longer hours, stricter oversight, everyone back to the office mandates and layers of new processes built on outdated foundations.
In my experience, this is the wrong response. The real disruption of the AI era isn’t technological. It’s cultural. And leaders who fail to recognise that, risk solving tomorrow’s challenges with yesterday’s assumptions.
The Illusion of Productivity
When economic pressure rises, organisations often default to visibility as a proxy for performance. Leaders want to see people working, whether that means more time in the office, more meetings or more activity. But activity isn’t the same as effectiveness.
AI is already capable of performing many routine tasks faster than humans, a fact that should lead us to rethink how work is structured. Instead, many businesses are doubling down on models that were designed for a different era, treating time spent on tasks as the primary measure of contribution, rather than outcomes achieved.
The irony is that this approach undermines the very productivity gains leaders say they want. People become busier but not necessarily more effective. Creativity declines, decision-making slows and, ultimately, innovation suffers because teams are exhausted rather than energised.
True productivity in an AI-enabled world comes from clarity and focus, not from squeezing more hours out of people.
Culture Before Performance
At Interlink, we’ve learned that performance rarely improves by targeting performance alone. It improves when culture enables people to do their best work.
Culture isn’t slogans or perks; it’s the operating system behind every decision. It determines whether people feel trusted or controlled, whether ideas are encouraged or suppressed and whether change is embraced or resisted.
As we scaled a profitable, AI-powered business across multiple continents, we discovered that culture has to scale before performance can. If it doesn’t, growth amplifies dysfunction. That realisation changed how we approached leadership. Instead of asking, “How do we get more output?” we began asking, “What conditions allow people to produce their best work consistently?”
The answers were not technological; they were human.
Redesigning Work Rather Than Reinforcing Old Models
One of the biggest leadership mistakes I see today is adding complexity to existing systems instead of redesigning them. Organisations introduce new tools without changing behaviours. They add layers of management without simplifying decision-making. They enforce policies intended to restore control rather than building trust.
For us, introducing a four-day working week was not about doing less; it was about focusing on what truly matters. Compressing time sharpened our priorities, improved decision-making and encouraged greater ownership of outcomes by everyone across the business. The result was counterintuitive for some observers: productivity rose, retention strengthened and creative thinking accelerated. When time had clearer boundaries, focus sharpened and accountability deepened.
Flexible and hybrid working emerged from the same philosophy. Instead of designing work around physical presence, we designed it around contribution and trust replaced oversight as the foundation of accountability.
These changes weren’t always comfortable and they absolutely required leaders to relinquish some traditional forms of control. But they reinforced a principle that has become increasingly clear: autonomy drives engagement and engagement drives performance.
The Tension Between ‘Back to the Office’ and the Future of Work
The current push for universal office returns reflects a deeper anxiety about how work is evolving. For some leaders, visibility feels like certainty. If people are physically present, it feels easier to manage performance. But this perspective risks confusing familiarity with effectiveness.
The future of work is unlikely to be defined by a single model. People’s roles, responsibilities and life circumstances vary too widely for one-size-fits-all solutions. Organisations that impose rigid structures in pursuit of control may find themselves losing talented individuals who value flexibility and trust.
That doesn’t mean offices are irrelevant. Physical spaces remain powerful for collaboration, learning and connection. The challenge is not choosing between remote or office-based work but designing environments that genuinely enhance productivity rather than simply recreating old habits.
The businesses that succeed will be those that treat flexibility as a strategic tool rather than a concession.
AI as an Amplifier of Leadership, not a Replacement
Because our business operates in AI-powered demand generation, we spend a great deal of time thinking about the relationship between automation and human expertise. AI excels at pattern recognition, scale and speed but what it lacks is context, empathy and strategic judgement.
The danger for leaders is assuming that technology alone can drive transformation. AI amplifies whatever culture already exists. In organisations built on trust and curiosity, it accelerates innovation; in environments dominated by fear or rigidity, it often automates inefficiency.
The competitive advantage lies not in whether a company uses AI (most soon will) but in how leaders integrate it into a culture that values learning and experimentation.
Simplicity as a Leadership Discipline
Another lesson from scaling is that complexity grows naturally. As businesses expand, processes multiply; communication becomes fragmented, and decision-making slows because too many layers intervene between ideas and action.
We’ve learned to treat simplicity as a leadership discipline. That means regularly rebuilding systems that no longer serve us, even when they once worked well. It also means resisting the temptation to add new structures simply because growth makes things feel messy. As well, simplicity requires intentional effort. Leaders must continually ask which processes genuinely add value and which exist only because they always have.
Leadership for an Uncertain Future
Perhaps the most important shift leaders must make is moving from control to clarity. In a world where technology evolves faster than organisational structures, certainty is increasingly rare. What teams need is not rigid instruction but clear purpose, shared values and the autonomy to adapt.
Leadership becomes less about directing tasks and more about shaping environments where people can thrive. That includes prioritising wellbeing not as a perk but as a strategic requirement. Burnout may produce short-term output, but it erodes long-term capability and the organisations that will define the next era of business are unlikely to be those that simply adopt the latest technology fastest. They will be the ones that rethink how work itself is designed, aligning technology with human potential rather than attempting to replace it.
Culture as the Ultimate Competitive Advantage
As AI becomes ubiquitous, technological differentiation will narrow. Tools that once seemed revolutionary will become standard. But what will remain distinctive is culture.
Culture determines how quickly teams learn, how openly they challenge assumptions and how resilient they are during uncertainty. It shapes whether innovation is encouraged or quietly resisted. And, in that sense, culture is not a soft concept; it is a strategic asset.
The real disruption of the AI age is not automation, it’s the opportunity to redesign leadership around trust, simplicity and human potential. Leaders who embrace that shift will find that technology accelerates their progress. Those who cling to outdated models may discover that even the most advanced tools cannot compensate for disengaged people.
Disruption isn’t about changing the industry first; it’s about changing how we lead.
Our cover star Shadman Zafar, Founder & CEO of Vibrant Capital, is building a CIO-led model for enterprise transformation. Vibrant Capital is an operator-led investment and company-building platform focused on scaling AI in the real economy. “We don’t spray investments across hundreds of AI startups. We curate a portfolio with purpose – selecting companies that solve the real mission-critical problems CIOs face in scaling AI adoption.”
FNB: Redefining Data Science in Commercial Banking
We also hear from Yudhvir Seetharam, Chief Analytics Officer at South Africa’s First National Bank (FNB) on a data science journey characterised by curiosity, culture and the drive for a competitive edge. “Ours is a holistic approach focusing on the customer,” he explains. “Understanding the context of each customer journey and then using that context so that when we interact with you, we’re able to drive the right conversation with the right customer, at the right time, through the right channel and for the right reason. These ‘five rights’ make our interactions with clients more impactful.”
Virginia Farm Bureau: An Enterprise CIO’s Journey
Shifting focus to the world of insurance at the Virginia Farm Bureau, we spoke withan Enterprise CIO at a complex mission-driven organisation. As he approaches retirement, Patrick (Pat) Caine reflects on his career as a CIO and the centennial of an organisation renowned for resiliency, collaboration, commitment to a greater cause, diversity and service to its members. “In my role as CIO, I’ve always been that person who connects the dots between business needs and technology execution. Virginia Farm Bureau is digitally relevant, collaborative, and well‑positioned for the future.”
Mastercard: Protecting Trust in the Digital Economy
Michele Centemero, EVP Services at Mastercard Europe explains why promoting awareness, stronger collaboration and data-sharing, and continued innovation of payments ecosystems, will be critical in reducing the impact of scams and protecting trust in the digital economy. “The combination of AI, robust identity controls and open banking can help protect consumers from scams, whether across card and account‑to‑account payments or in fraudulent account openings.”
Thales on AI Security: How FinServ’s Budget Priorities Signal a Boardroom Shift
Todd Moore, Global VP – Data Security Products at Thales, reveals why making AI security a boardroom priority today, will help firms position themselves to capture competitive advantage, safeguard customer confidence, and define the future of secure innovation. “Balancing AI’s opportunity and risk means embedding security at every stage, from design to deployment and ongoing monitoring.”
Paymentology: The First Live AI-Agent Payment Is a Test for Credit Infrastructure
Thomas Benjaminsen Normann, Product Director at Paymentology, dissects the future for agentic payments and the progress still to be made. “Agentic payments demand something more granular: a clearer account of who or what acted, under what limits, and with what right to create a liability on the customer’s behalf.”
Also in this issue, we hear from Publicis Sapient, on why asset managers must redesign their enterprise for AI-driven decision intelligence; learn from Bitpace why the most resilient payments infrastructure will be the one with the most adaptability; rank the AI maturity of 12 of the largest payments networks in the latest Evident AI Index; and round up the key FinTech events and conferences across the globe.
Michele Centemero, EVP Services, Mastercard Europe on why promoting awareness, stronger collaboration and data-sharing, and continued innovation of payments ecosystems, will be critical in reducing the impact of scams and protecting trust in the digital economy
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As our world becomes faster, smarter and more interconnected, scammers are evolving in parallel, developing increasingly sophisticated ways to exploit people’s trust. By harnessing new technologies and behavioural insights, they are refining their methods to appear ever more credible and convincing.
While attacks on systems continue, today’s fraudsters are increasingly targeting people, often relying on psychological manipulation to achieve their goals.
Understanding Social Engineering
Many modern scams fall under the umbrella of social engineering,which isthe use of deception and emotional manipulation to influence a person’s behaviour.
In the digital world, cybercriminals use these tactics to build false trust, create urgency or fear, and ultimately trick people into sharing confidential information or taking actions that can cause financial harm to themselves or their employer.
Recent European industry data indicates that social engineering-related fraud and authorised push payments (APPs) – where victims are tricked into sending money to fraudsters posing as legitimate payees – now account for a growing share of overall scam losses[1].
This is directly impacting a growing number of consumers, with the majority of people saying they’ve experienced some form of scam or fraudulent attempt to capture their personal information highlighting why awareness and vigilance are critical for people of all ages.
Education is the First Line of Defence
Protecting consumers and businesses from malicious activity is a priority, and it starts with awareness. When people understand how scams work, they’re more likely to spot the warning signs before it’s too late and be empowered to protect themselves against fraudsters.
Three of the most common social engineering scams to watch out for are:
Imposter fraud – Criminals pose as trusted organisations (such as banks, retailers, or government bodies) to pressure victims into sharing personal or financial details. Research indicates over half (53%) of European consumers have been targeted via phone or voice call scams, with social media scams affecting around two in five people, and tech support impersonation tricking roughly one in three.*
Phishing – Fraudulent emails, texts, or messages that are designed to look legitimate, often urging immediate action like clicking a link or resetting a password, leading victims to disclose sensitive information or install malicious software. Nearly three in five (58%) have received phishing emails or fraudulent text messages (63%) and QR code scams are on the rise, impacting nearly a quarter of Europeans.*
Romance or honeypot scams – Scammers build emotional relationships over time, gaining trust before exploiting it for financial gain. These types of attacks are also widespread, with one in four people (24%) encountering fake profiles, requests for money, or online relationships that lead to financial exploitation. These scams hit younger generations hardest, with 40% of Gen Z and 35% of Millennials affected, compared with 21% of Gen X and 11% of Boomers.*
How Businesses Can Protect Consumers from Scams
With fraudsters increasingly using AI to commit more sophisticated, larger scale attacks, businesses and banks should also consider how they deploy technology to protect customers from bad actors.
The combination of AI, robust identity controls and open banking can help protect consumers from scams, whether across card and account‑to‑account payments or in fraudulent account openings.
Looking at identity controls specifically – take the example of continuous identity verification, a fraud prevention measure that verifies the user is who they claim to be throughout the entire lifecycle journey. This helps to prevent scammers from opening or taking over accounts to apply for credit, create ‘mule’ accounts or impersonate others.
Behavioural biometric data is often used as part of this and can be used to analyse how a user interacts with their device – from typing patterns to on‑screen movements – to flag unusual behaviour.
More in depth, AI powered transaction analysis can also help banks and financial institutions to stay ahead of payment threats. It provides banks with the intelligence needed to detect and stop payments to scammers, using AI and a network-level view of account‑to‑account transactions to enable intervention before funds leave an account.
Staying Ahead of an Ever-Evolving Threat
As social engineering tactics continue to evolve, staying ahead requires a combination of intelligent technology, consumer education, and proactive action from businesses and financial institutions.
While no single measure can eliminate risk entirely, greater awareness, stronger collaboration and data-sharing, and continued innovation of payments ecosystems will be critical in reducing the impact of scams and protecting trust in the digital economy.
*Source: This study was conducted by The Harris Poll on behalf of Mastercard from September 8 to September 25, 2025, among 5000+ consumers in the following European markets: EUR: France (n=1,005), Germany (n=1,002), Italy (n=1,016), Spain (n=1,005), UK (n=1,004)
Mastercard: Transforming the Fight Against Scams
Innovation – Our advanced AI-powered Identity insights examine digital footprints and assess unique patterns to detect risk and flag suspicious activity indicative of scams.
Collaboration – We collaborate across industries, partners and organizations worldwide to secure the digital ecosystem, ensuring payments are safe for all. Combating the growing threat of scams demands a collective effort.
Education – We work with and through our collaborators to provide knowledge and tools that help people protect themselves and their loved ones from scams, while also working to destigmatise the experience of being a victim.
$12.5bn in losses from U.S. consumer reported online scams in 2023
$486bn in global losses from scams and bank fraud schemes in 2023
22% YoY growth in U.S. consumer scam losses suffered in 2023
From sender to recipient, we vigilantly monitor accounts and transactions for any elevated scam risk
Identity insights – Provides actionable identity insights and risk scores for businesses to improve identifying their good customers from the scammers creating “mule” accounts or impersonating someone else with a false identity.
Transaction patterns – Flags suspicious activity across the money movement flow to prevent payments to scammers before it is sent through the real-time analysis of transaction elements.
Account confirmation – Enables account validation to confirm account ownership and validate identity details in real-time through our open banking capability, which draws on the safe exchange of consumer-permissioned data to facilitate frictionless and secure payments.
Todd Moore, Global Vice President, Data Security Products at Thales, on why making AI security a boardroom priority today, will help firms position themselves to capture competitive advantage, safeguard customer confidence, and define the future of secure innovation
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Financial Services organisations are responsible for some of the biggest growth in the global economy. Equally, they’re some of the most vulnerable. Like many other sectors, they’re racing to embrace AI, but with adoption comes new security risks.
According to Thales’ Data Threat Report: Financial Services Edition 81% of FinServ organisations are now investing in GenAI-specific security tools, with nearly a quarter using newly allocated budget. This surge in funding marks a turning point: AI security has moved from being an IT concern to a boardroom priority.
The fact that new budget lines are being carved out specifically for AI security signals a fundamental shift in corporate strategy. Boards increasingly recognise that protecting AI systems is as critical as safeguarding payment rails or core banking infrastructure. For an industry built on trust, resilience, and regulatory compliance, this investment wave shows how central AI has become to both risk management and competitive growth.
Balancing AI Innovation and Security
While FinServ organisations are aware of the security risks AI poses, they’re also seizing upon the opportunities it presents. The report has found that in 2024, FinServ businesses outpaced the broader market in AI deployment, leading in enabling employees to use AI and ahead in AI integration, which has continued into 2025. Additionally, 45% say they’re in the ‘integration’ or ‘transformation’ phases of their GenAI journey, compared to just 33% across wider industries.
AI’s ability to accelerate services, automate processes, and analyse data at scale makes it an exciting prospect, especially in the financial sector. This makes securing AI systems a priority for FinServ organisations, with increased GenAI integration reflecting developing organisational maturity and progress beyond experimentation.
The Risk
Yet the scale of opportunity is matched by the scale of challenge. AI systems require vast amounts of structured and unstructured data to conduct analysis and make recommendations.
For FinServ organisations, this often includes highly sensitive customer and transactional information, proprietary algorithms, and records bound by strict regulatory oversight. The risk is not only about whether AI systems themselves are secure, but whether the data they’re working from is accurate, as well as whether their adoption inadvertently creates new routes to data exposure and exfiltration.
Businesses need a clear strategy to fully understand how AI models are operating within their IT infrastructure, the applications they’re interacting with, and the data they’re accessing and pulling from.
The Response
Balancing AI’s opportunity and risk means embedding security at every stage, from design to deployment and ongoing monitoring. Newly allocated budgets for AI security, with nearly a quarter of FinServ firms making such investments, show how central AI has become to board-level strategy. These investments move firms beyond reactive fixes to proactive frameworks that evolve with the technology. AI security is no longer just an IT concern, it’s a strategic priority requiring collaboration between security, compliance, and business leaders. By factoring risk into early planning, organisations can align innovation with responsibility and build resilience for the long term.
Pioneering AI Security
Building on investment in AI-specific security is only the beginning. As scrutiny intensifies, the firms that will lead are those that treat AI security as integral to business strategy, not a bolt-on layer. Success will require visibility into how models behave, continuous validation against emerging risks, and adaptive controls that evolve with the threat landscape.
The financial services organisations that embed these safeguards into their core infrastructure will protect sensitive data as well as setting a benchmark for resilience and trust in an AI-driven economy. By making AI security a boardroom priority today, these firms position themselves to capture competitive advantage, safeguard customer confidence, and define the future of secure innovation.
Thales: AI is the New Insider Threat
Thales 2026 Data Threat Report Finds 70% of Organisations Rank AI as Top Data Security Risk
Data security has taken centre stage as the success of enterprise AI initiatives increasingly hinges on consistent, controlled access to proprietary organisational data sources. The 2026 Thales Data Threat Reportexamines the complex calculus that organizations must undertake to enable innovation while securing their most valuable asset – their data.
This research was based on a global survey of 3,120 respondents fielded via web survey with targeted populations for each country, aimed at professionals in security and IT management.
Lee Fredricks, Director – Solutions Consulting, EMEA at PagerDuty, on why technology leaders should see 2026 as a time for operational resilience to shift from ambition to accountability
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Technology leaders should see 2026 as a time for operational resilience to shift from ambition to accountability. In 2025, too many cloud services outages and disruptions took place across the public and private sectors, and now regulatory, technological and cultural pressures are converging to say that enough is enough.
Outages often translate into broader repercussions for the organisation, including revenue impact, customer churn, share price pressure and potentially regulatory reporting obligations. Operational metrics must now be discussed alongside financial KPIs at the board level. C-suite leaders understand accountability, especially within the very regulated financial sector.
DORA’s First Birthday
It’s now been one year since the implementation of the Digital Operational Resilience Act, or DORA, introduced by the EU to strengthen the digital resilience of financial institutions. By now, organisations have had time to consider moving from mere compliance to creating a competitive edge from their investments.
Enterprise tech leaders are in the middle of a balancing act. They’re managing ongoing modernisation and transformation initiatives while navigating multi-jurisdictional regulatory scrutiny. At the same time, they face constant pressure from the board and must meet evolving customer needs—all competing for immediate attention. The stakes have never been higher. Operations teams are no longer viewed as a back-office IT function. Their success in keeping the organisation running and driving revenue is now a board-level concern.
For organisations today, IT is business delivery.
A year of DORA has seen organisations make the shift from focusing solely on mere compliance to setting meaningful demonstrable testing, third-party risk visibility and strictly mandated incident reporting timelines. Financial firms have lessened their exposure to risky situations. Payments providers aren’t only reliant on a single cloud region or SaaS supplier, or unable to provide evidence of real time incident response efforts and auditable logs after a disruption.
One benefit of these overall systemic improvements is enhanced supply chain accountability. Financial institutions and their technology partners are both liable for potential penalties and reputational risk, which makes it highly critical that they can prove their resilience capabilities.
Nevertheless, operational resilience is a continuous discipline. A fragmented incident response can expose firms to regulatory and reputational risk again and again if not addressed systemically. As such, many organisations are looking toward AI agents as part of a move towards ‘no-touch’ operations.
From Autonomy to Self-Healing
Under set policies, autonomous agents can handle incident response and operational tasks, such as detection, triage and remediation. AI agents deployed in operations may become the backbone of L1 (first contact) and L2 (more skilled) support. Contrast this with the traditional, reactive, ticket-driven model of IT. The industry can move much faster and with a higher successful close rate. Leveraging intelligent automation reduces mean time to detection/resolution and KPIs around lower incident volumes reaching L3. Additionally, it can lead to improved service availability percentages. Well integrated agents that actually support existing operations teams also help manage the issues around talent shortages faced by many organisations.
A typical incident lifecycle with agentic processes includes several stages depending on the model, but can be summarised as: Anomaly detected, correlated with recent deployment, a remediation script triggered and a human notified if set thresholds were breached. Such no-touch operations are golden in any sector, but particularly with industries such as digital banking and retail, where peak traffic periods demand near-instant response and poor customer experience is a powerful motivator for users to instantly change providers.
IT Standardisation
In addition, consider standardisation as part of strategic infrastructure best practices. There is a role for central operations clouds and operational ‘golden paths’ as solid foundations for reliable operational scale and dependability. Standardisation enables consistent, scalable operational excellence especially across large, distributed enterprises. ‘There is one way and it is the right way’ can be a great time and stress saver for operational teams – particularly if a regulatory notification and clear evidence is required.
For example, a global bank might define a single golden path for deploying customer-facing applications with pre-approved monitoring, incident response workflows, and regulatory reporting templates built in. In an outage, teams follow the same process and automatically capture the evidence required for regulators, avoiding confusion, delays, and compliance risk.
All of these possibilities take us to an exciting new place for an evolved set of developer and operational roles. When organisations enable AI to reshape daily engineering work away from manual firefighting and low-value work it frees headspace and time for developers and engineers to move into more architectural thinking and intelligent oversight of automated systems. These augmented teams will be empowered to manage simple situations instantly and devote more time and attention to the more difficult issues – the edge cases and the strategic necessities.
Enabling Agentic AI
Using another lens, businesses with agentic IT operations capabilities support their current talent, extending their reach and the speed of their response. The winning organisations will be those who deploy agents strategically, freeing up humans for that higher-value work – i.e. L3 expert support – and setting new standards for operational excellence that customers can rely on. Ideally this means making commensurate investment in existing people, training and organisational change management. A culture of continual upskilling and forecasting that points humans to where they make the best impact will be just as important as the autonomous tech tools working alongside them.
Autonomous agents allow many new services, and one of those can be described as self-healing operations. This evolution of the operations world is where predictive detection, automated remediation and embedded resilience all coalesce. With an autonomous process of testing, maintenance and remediation, organisations can focus on finely measuring improved customer trust. They can also enjoy the productivity and revenue benefits of high business continuity and availability.
AI is still a new technology, and many are legitimately concerned with the concept of autonomous agents. There is a need for clear guardrails, audit trails and explainability in automated remediation, and many technology partners have invested in their ability to support across these areas. Moreover, firms must maintain direction with policy-driven automation rather than uncontrolled autonomy, particularly in regulated industries.
Mandate Operational Excellence
This year is very likely to reward organisations that treat operational resilience as core to their business strategy. Those investing in automation, standardisation and governance will set the pace for their industries in an AI-enabled and increasingly autonomous world.
Regulators are already expanding their scrutiny and reliability expectations beyond financial services firms. Across the world, jurisdictions are increasingly looking to strengthen their economies and digital services in particular through resilience and cybersecurity measures. At the same time, agentic operations, and the organisational performance benefits they support, will rapidly become table stakes technology in all sectors. Inevitably, customers will judge brands on digital reliability as much as price or product features when evidence of outages are a click or a headline search away.
Start now. Audit internal incident response maturity, review the potentially complex web of third-party IT dependencies and identify where automation makes clear business sense. While resilience is an investment in compliance, it is also critical to ensure customer trust and future stability.
With growth in data centre power demand, driven by AI and other power-hungry applications, could microgrids hold the key? Rolf Bienert, Technical & Managing Director of global industry body, the OpenADR Alliance discusses the potential for microgrids in providing flexibility and clean energy
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Generating enough power for the demands of artificial intelligence (AI), cryptocurrency and other power-hungry applications, is one of the biggest challenges facing data centres right now. With a power grid already under pressure and in the process of trying to modernise and flex to cope with the huge demands placed on it, the industry needs to rethink the way it adapts to these challenges.
Data Centres
According to figures from the International Energy Agency (IEA), data centres today account for around 1% of global electricity consumption. But this is changing with the growth in large hyperscale data centres with power demands of 100 MW or more. And an annual electricity consumption equivalent to the electricity demand from around 350,000 to 400,000 electric vehicles.
With the rise of AI and expectation of what it can deliver, the next few years are likely to see a significant rise in the number and size of data centres. This has serious consequences for the energy sector. While, technology firms are under growing pressure to make data centres more sustainable.
Microgrids – The Opportunities
Microgrids could be the answer in providing a more sustainable and efficient energy supply for data centres. While the concept of a microgrid can vary depending on how they are used, they can be defined as small-scale, localised electrical grids that can operate independently or in conjunction with the main power grid. They can range in size from a university to a single home.As a global ecosystem, we’re seeing them used in different scenarios, from residential to large campuses.One interesting use case is MCE, a California Community Choice Aggregator, which has established a standardised setup for residential virtual powers plants (VPPs) with OpenADR used as the utility connection to manage the prices and consumption.
The feasibility and suitability of microgrids depends on factors like the specific requirements of the data centre, regulatory environment and the long-term goals for sustainability, resilience and cost-efficiency.
The real value is in helping overcome grid constraints and improving reliability by managing consumption and maintaining power during grid issues. For data centres that require uninterrupted operation, this ability to deliver resilience is critical.
Sustainability is another important advantage. By integrating renewable energy sources, such as solar or wind power, and energy storage, microgrids can significantly reduce carbon footprint. While in terms of cost savings, they can reduce operational costs by utilising local power generation and demand-response strategies.
Microgrids are modular, which means they can grow as the data centre’s needs evolve. Plus, when it comes to regulation, they face fewer regulatory hurdles compared to other options, like nuclear power, because they can operate mostly ‘net zero’ on the grid connection.
Microgrids – The Challenges
For data centre operators and investors trying to address power supply and stability issues, the use of microgrids can also mean challenges.The first of these is the start-up costs. While we talk about a reduction in operational costs once up and running, set-up costs for microgrids can be high, requiring significant capital investment especially for larger data centres, so important to bear in mind.
Sustainability may be a big plus point, but the use of renewables like solar and wind depend on the weather – and the weather can be fickle. This necessitates robust storage solutions, backup power or large grid connections to ensure reliability and stability at all times. It’s also important to stress that the effective integration of these various distributed energy sources and systems can be technically challenging, so working with good integrators and partners is paramount.
When it comes to powering data centres, microgrids are not the only option being considered. Alternatives like small modular nuclear reactors (SMRs) are also be touted as potential power sources. In my mind, SMRs are not in competition with microgrids but could become an important baseline component of them.
In their favour, SMRs provide a constant, high-capacity output, ideal for 24/7 operation, and a zero-emissions power source. Once operational, they offer stable costs over decades. But they also face challenges like stringent regulation and public opposition to development, while a nuclear plant, even a small-scale one, involves substantial upfront investment. This is aside from the risks around nuclear waste and safety.
Bottom line is that the data centres are going to need a very high continuous supply of power and microgrids offer options for a more resilient and responsive energy infrastructure. Decentralised power through a network of microgrids could help dynamically manage power loads and optimise renewable energy sources – especially as demands on the grid grow as we march onwards towards an AI-powered future.
Jamil Jiva, Global Head of Asset Management at Linedata, on why the next chapter of AI-driven finance will be shaped not just by technology, but by creativity
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Beyond Data: Where AI Finds Unexpected Inspiration
The discussion about training AI largely focuses on concerns that accessible, human-generated data is limited and may soon run out completely. If this is the case, how can technology that depends on a seemingly endless stream of inputs to iterate, test, and adapt deliver the results we expect? AI relies on structured, high-quality data to thrive, but what happens when we run out of spreadsheets and financial models to train AI? We need new data sources to ensure it continues to learn, adapt, and deliver accurate insights. Video games stand out as offering some of the richest, most expansive, and complex environments for AI training.
At first glance, video games and financial operations seem to belong to entirely separate worlds. However, AI connects these domains, with models leveraging virtual-world training to tackle real-world financial tasks. Financial documents such as credit agreements and tax returns are often convoluted, unstructured, and labour-intensive to process. Therefore, AI designed to interpret such data must possess strategic reasoning, real-time adaptability, and advanced pattern recognition. So, could video games be the ideal training ground?
Contrary to popular belief, gameplay can significantly improve how people think, learn, and solve problems. The abilities required to excel at video games closely reflect the skills AI systems must acquire today.
Levelling Up: What Virtual Worlds Teach Machines
Practice leads to proficiency, a principle that applies to both humans and AI. Interestingly, many of the most significant advances in AI development have emerged not from conventional data training, but from taking creative approaches. Games push AI to emulate human thinking and sharpen its statistical intuition.
These game-trained models are neither expensive nor heavily reliant on resources, and they sidestep the issue of data scarcity. As a result, they are actively shaping the future of financial intelligence. The examples below offer a clear demonstration of the potential of gameplay.
Virtual Economies: Lessons from World of Warcraft
World of Warcraft, with millions of players interacting in an immersive and dynamic world, features an economy that closely mirrors real-world financial systems, complete with inflation, supply and demand cycles, and fraud risks. The game even inspired one of the most renowned epidemiological studies: when the in-game ‘Corrupted Blood’ plague spread unpredictably, scientists used it as a model for real-world pandemic simulations.
Financial models depend on vast, interconnected data networks, much like the economy in World of Warcraft. Organisations employ AI to continuously monitor patterns, detect anomalies such as fraud or misstatements, and optimise data extraction for financial reporting, mirroring the way AI analyses virtual economies.
Urban Chaos: GTA V and Real-World Simulation
While Grand Theft Auto (GTA) V is famous for its open-world chaos, researchers have leveraged its traffic systems and non-player character behaviours to train AI for applications such as self-driving cars, crime pattern recognition, and urban planning. At its heart, GTA provides a platform for AI to process vast amounts of unstructured data in real time.
Similarly, financial institutions manage millions of data points from a wide range of sources. Their AI tools must automatically extract insights, classify information, and normalise complex formats. GTA serves as a controlled yet intricate environment for simulating scenarios, enabling AI to optimise for real-world tasks through ongoing feedback loops.
Sandbox Creativity: Minecraft and Adaptive Thinking
Minecraft provides a sandbox environment where AI learns through exploration. OpenAI even trained an AI to play Minecraft by watching YouTube tutorials, closely mimicking the way humans learn. Similarly, any AI used by financial institutions must be able to self-learn from new document types and structures, adapting just as a Minecraft AI learns to survive.
Reinforcement learning, where AI improves based on feedback, is a key element of intelligent document processing. Thanks to its vast scalability and dynamic, hierarchical environments, Minecraft serves as an ideal setting for navigation and repeated feedback loops, helping models develop domain-flexible reasoning.
Multiplayer Mayhem: Dota 2 and the Art of Teamwork
Dota 2 stands out as one of the most complex competitive games ever created, presenting AI with challenges in real-time decision-making, strategic coordination, and adaptability. OpenAI Five, trained on the equivalent of 45,000 years of gameplay within just 10 months, managed to defeat renowned, professional human teams. As anyone who has mastered StarCraft knows, tactical adaptability is essential for gaining the upper hand.
Financial institutions operate in environments that are just as dynamic as the shifting levels of a video game. Market conditions, regulations, and data formats are in constant flux. AI must be able to adjust to new document structures, handle missing information, and navigate edge cases, much like AlphaStar adapts to an opponent’s unpredictable strategies.
From Pixels to Profits: Bringing Game Logic to Finance
Whether to streamline operations, mitigate risks, or make informed decisions in today’s data-intensive financial landscape, AI has the potential to fundamentally transform financial offerings, delivering personalised and evolving experiences that foster understanding and combine seamlessness with regulatory compliance.
Yet AI does not simply require more data from which to learn; it needs better data. Video games offer near limitless, pre-built, highly complex digital worlds where AI can test hypotheses, simulate scenarios, and refine decision-making models. By utilising these unique environments, AI is challenged to enhance its speed, accuracy, and efficiency.
The world of video games has many lessons we can learn when building AI, and given AI’s remarkable ability for transferable learning, it makes sense to leverage these pre-trained models to power essential financial workflows. It is more than just document processing; it is thinking, and the same intelligence that enables AI to defeat world champions in Dota 2 is now driving the next generation of financial AI solutions.
The next chapter of AI-driven finance will be shaped not just by technology, but by creativity. By embracing unconventional data sources such as the immersive complexity of video games, industry leaders will unlock new possibilities for personalisation, security, and customer engagement.
Richard Doherty, Head of Wealth & Asset Management, Publicis Sapient, on how asset managers must redesign their enterprise for AI-driven decision intelligence
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The asset management industry is entering a structural inflexion point. The first wave of AI focused on improving productivity through copilots and automation. The next wave will fundamentally reshape how decisions are made, executed, and governed across the enterprise. This is not a technology upgrade. It is an operating model shift.
Despite significant investment, many firms remain trapped in fragmented AI experimentation. A majority are yet to realise meaningful economic returns from AI, not due to lack of capability, but due to a failure to redesign how intelligence is applied across the organisation. The gap between ambition and outcome is not a technology problem. It is a structural one.
From Automation to Decision Intelligence
The industry conversation has evolved. The question is no longer whether to adopt AI, but how to scale it across the enterprise. However, most firms are still approaching this challenge through the lens of automation, identifying tasks that can be executed faster or at lower cost. This delivers incremental value, but does not address the underlying constraint: the structure of decision-making within the organisation.
Traditional operating models are built around sequential workflows. Work moves from function to function: research, compliance, operations, and distribution, each dependent on the previous stage. This creates latency, duplication, and fragmentation. Agentic operating models shift the focus from tasks to decisions.
Instead of asking “Which processes can we automate?”, leading firms are asking: “Which decisions can be augmented or owned by intelligent systems?”
This shift enables organisations to move from sequential workflows to parallel decision systems; from human-led analysis to AI-assisted reasoning; from periodic insight to continuous intelligence. The result is not a marginal improvement. It is a step-change in how the enterprise operates.
The Pressures Driving Change
This transformation is not happening in a vacuum. Asset managers face mounting structural pressures: margin compression driven by fee pressure and passive competition; rising operational complexity from regulation and product proliferation; and advisor capacity constraints that limit scalable growth. Agentic operating models directly address all three.
By automating complex workflows, rather than individual tasks, firms can significantly increase advisor and analyst capacity without proportional cost increases. Parallel decision systems reduce the time required to launch products, respond to market events, and deliver client insights. This compresses cycles from months to days. Continuous monitoring of guidelines, portfolios, and operational processes reduces exposure to regulatory breaches and operational failures.
These are not theoretical benefits. They represent measurable improvements in cost-to-serve, time-to-market, and operational resilience.
Not all Intelligence is the Same
To scale AI effectively, organisations must recognise that not all problems require the same type of intelligence. Enterprise AI operates across three distinct layers, and conflating them is one of the primary reasons AI initiatives fail to scale.
Deterministic systems execute predefined rules with complete consistency. They are essential for functions where there is zero tolerance for error, trade validation, settlement processing, and regulatory reporting. If a business outcome must be identical every time, deterministic logic remains the correct approach.
Predictive systems use historical data to forecast outcomes. Applied in areas such as portfolio risk modelling, fraud detection, and client churn prediction, they generate probabilities and insights, but they do not interpret context or make decisions independently.
Agentic systems operate where problems require interpretation, judgment, and contextual understanding, investment guideline interpretation, regulatory document analysis, portfolio insights, and client communication. These systems can reason across complex information, generate insights, and take action within defined boundaries.
The ‘Different but Valid’ Dilemma
A critical challenge in adopting agentic systems is understanding how they behave. Traditional software produces identical outputs. Agentic systems produce reasoned outputs.
This introduces what I call the ‘different but valid’ dilemma. An agent may take a different reasoning path from a human and arrive at a different, but still correct, conclusion. This variability is not an error. It is inherent to reasoning systems.
The real risk lies in hallucination, outputs that are not grounded in data or evidence. Managing this requires organisations to clearly define where variability is acceptable. All AI-driven processes sit on a spectrum: deterministic actions with no variability (trade execution), predictive actions with controlled variability (risk scoring), and agentic actions with higher variability (investment insights).
Leading firms design systems where agents perform reasoning, deterministic systems enforce execution, and humans retain oversight on high-consequence decisions. This balance enables both flexibility and control.
The Operating Model Shift
The most significant change is not technological; it is organisational. Traditional models are built on functional workflows. Agentic models are built on coordinated decision systems.
Consider what launching a new investment product looks like under each model. In a traditional model, it involves sequential handoffs between teams, compliance reviews the guidelines, operations configures the systems, and distribution drafts the client narrative. Each stage waits for the last.
In an agentic model, intelligent systems operate in parallel: compliance agents interpret guidelines, operations agents configure constraints, distribution agents generate client narratives, and governance agents validate outputs. This orchestration compresses timelines, reduces friction, and enables continuous decision-making. It represents a fundamental redesign of how work is performed.
Governance: the Foundation for Trust
Trust is the prerequisite for scaling AI. Without it, adoption stalls, not because the technology fails, but because the organisation cannot adequately explain or defend the decisions it makes.
Leading firms implement governance models built on three principles. First, explainability: every decision must be traceable and auditable. Second, authority boundaries: agents operate within clearly defined limits. Third, human oversight: high-consequence decisions remain under human control.
Regulatory expectations will continue to evolve, but one principle remains constant: organisations must be able to explain how decisions are made.
Scaling AI is a Leadership Challenge
Executives must take a deliberate approach across four areas:
Define the intelligence model: map business problems to deterministic, predictive, or agentic systems.
Build the foundation: invest in data, infrastructure, and orchestration capabilities.
Redesign the operating model: shift from workflows to decision systems.
Implement governance to ensure transparency, control, and compliance.
Start with high-value use cases and expand rapidly across the enterprise. The firms that act now will establish a structural advantage in cost, speed, and decision quality. Those that do not risk being constrained by legacy operating models that cannot scale with the demands of modern markets.
The Question is not if, it is Who
The industry is not simply adopting new technology. It is redefining how decisions are made. The firms that succeed will not be those that deploy AI tools in isolation. They will be those who design the right form of intelligence for each problem, redesign their operating models around intelligent systems, and scale agentic capabilities across the enterprise.
This shift is already underway. The question is no longer whether it will happen. The question is which firms will lead, and which will be forced to follow.
Sanofi: Supporting the World’s Health Through Data
This month’s cover story spotlights Sanofi, one of the world’s largest pharmaceutical companies. For an organisation that puts the end-user – the patient – first, this requires an unwavering focus on R&D and continuous improvement. For the sake of the world’s health; every patient counts. So, when opportunities arose to improve services through data and advanced technology like AI, Sanofi brought in experts to steer and develop the journey.
Snehal Patel, Head of Global Data and AI Platform, takes a deep dive with Interface… “These innovations have fundamentally transformed Sanofi’s data and AI value chain,” says Patel. “It’s enabled scalable and efficient development across the organisation. We now have a far more agile development environment that supports the broader AI initiatives at Sanofi.”
Anson Cho, Director of Information Security & Data Protection at Langham Hospitality Group, discusses the pandemic’s silver lining and the development of a proprietary matrix to embed security into the heart of operational excellence.
“Our strategy wasn’t about over-engineering our systems to match the spend of a global financial institution; it was about increasing our defensive maturity so we are never an easy mark,” says Cho. “In cybersecurity, you want to ensure your barriers are sophisticated enough that attackers move on. We focus on staying ahead of the curve and continuously evolving so that our security posture remains a formidable deterrent.”
FNB: Redefining Data Science in Commercial Banking
Yudhvir Seetharam, Chief Analytics Officer at South Africa’s First National Bank (FNB) on a data science journey characterised by curiosity, culture and the drive for a competitive edge.
“Ours is a holistic approach focusing on the customer,” he explains. “Understanding the context of each customer journey and then using that context so that when we interact with you, we’re able to drive the right conversation with the right customer, at the right time, through the right channel and for the right reason. These ‘five rights’ make our interactions with clients more impactful than a spray and pray approach.”
Ian Franklyn, Chief Revenue Officer at Mainstreaming, on why delivering exceptional streaming experiences won’t require just technology, but also collaboration and synergy
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Streaming video has firmly established itself as the dominant force shaping global internet traffic. From premium live sports and breaking news to on-demand entertainment libraries, audiences now expect seamless, high-quality viewing experiences on any device, at any time. For leaders across media, telecoms, and technology, the challenge is no longer about enabling streaming. It is about sustaining it at scale preserving reliability, efficiency and profitability.
Yet, despite the central role video plays in today’s digital economy, the underlying delivery model remains fundamentally fragmented.
Many broadcasters and OTT platforms still rely heavily on centralised, third-party content delivery networks (CDNs). These operate largely outside internet service provider (ISP) infrastructures. This model has supported the growth of streaming over the past decade. However, it is increasingly misaligned with current demand patterns, especially during large-scale live events.
The result is a structural inefficiency that affects every stakeholder in the ecosystem. And the industry can no longer ignore it.
The Growing Cost of Disconnection
When millions of viewers tune in simultaneously, vast volumes of video data must travel across multiple interconnected networks before reaching end users. This often means duplicating the same streams across long-haul routes, placing unnecessary strain on transit links and core infrastructure.
For ISPs, this translates into rising traffic volumes without proportional financial return. Networks become congested, costs increase, and visibility into traffic flows remains limited.
Broadcasters and OTT platforms face a different but equally critical challenge. With limited control over last-mile delivery, performance becomes unpredictable at precisely the moments that matter most. Buffering, latency, and degraded video quality directly impact user experience, driving churn and damaging brand reputation.
Ultimately, the end user bears all the consequences. Even minor disruptions during peak events can cause frustration and dissatisfaction. This consequently erodes trust, impacting both service providers and content owners in an increasingly competitive market.
Rethinking Delivery: Moving Closer to the Edge
Addressing these challenges requires a fundamental rethink of where and how video is delivered.
Rather than relying solely on centralised infrastructure, delivery capacity can be deployed directly within ISP networks, closer to the end user. This edge-based approach localises traffic, reducing the distance data must travel and fundamentally improving efficiency.
The benefits are immediate. By placing content within ISP networks, duplicated traffic across transit routes is minimised, congestion in core networks decreases, and latency is reduced. At the same time, both ISPs and content providers gain greater visibility and control over performance.
This model is particularly valuable for live streaming, where demand is highly concentrated and unpredictable. Traditional CDN architectures, designed for distributed but relatively predictable traffic patterns, are simply not built to handle sudden spikes in concurrent viewership.
Edge delivery networks purpose-built for video, by contrast, enable capacity to be positioned dynamically where it is needed most. This ensures that even the largest live events can be delivered with consistency, reliability, and low latency.
From Delivery Burden to Shared Value Creation
The evolution toward edge-based video delivery represents a fundamental shift for both ISPs, and broadcasters and OTT platforms.
For ISPs, streaming has long been treated as a cost centre. A growing source of bandwidth consumption that drives infrastructure investment without directly contributing to revenue. As traffic volumes continue to rise, this model becomes increasingly unsustainable both economically and operationally.
At the same time, broadcasters face a different challenge. How can they efficiently manage highly variable demand? Particularly during large-scale live events where audience peaks are both massive and unpredictable. And where failure is not an option.
Embedding video delivery capabilities within ISP networks changes this dynamic for both sides.
For ISPs, localising traffic reduces reliance on upstream transit. This alleviates pressure on core infrastructure, enabling more efficient use of existing capacity. It also opens new monetisation opportunities, allowing them to move beyond being passive carriers and play an active role in delivering premium streaming experiences.
For broadcasters and OTT platforms, the benefits are equally strategic. Edge-based delivery enables them to scale live events more efficiently. Activating capacity where and when it is needed rather than overprovisioning for peak demand. This results in more predictable performance, consistent quality of experience, and improved cost efficiency.
In this shared model, video delivery is no longer a burden for one side or a risk for the other. It becomes a coordinated effort, aligning incentives and generating value for all the stakeholders involved.
An Ecosystem that Works in Synergy
Realising this opportunity requires more than technology. It demands a shift toward a more collaborative operating model: a true ‘Better Together’ approach.
This means deeper alignment across the ecosystem, bringing together ISPs, broadcasters, OTT platforms, and technology providers around shared objectives. Instead of operating in silos, each stakeholder contributes to a unified delivery framework designed to meet the demands of modern streaming.
In practical terms, this approach increases transparency, improves performance, and aligns both technical and commercial incentives. Integrating delivery capacity within ISP networks creates a stronger foundation for long-term growth, enabling more efficient scaling as demand continues to rise.
The result is a more resilient and adaptable ecosystem. One capable of supporting increasingly complex and large-scale streaming experiences, and responding dynamically to future demand.
Building the Next Generation of Streaming Infrastructure
The misalignment between how video is consumed and how it is delivered is no longer sustainable, and delaying a change will only amplify the problem
As streaming evolves, new formats such as ultra-high-definition video and low-latency interactive services will place even greater demands on network infrastructure. At the same time, audience expectations will continue to rise, leaving little tolerance for disruption.
Meeting these challenges requires a shift toward integrated, edge-driven architectures supported by strong ecosystem partnerships.
By bringing video delivery closer to the viewer, the industry has an opportunity to redefine both the economics and performance of streaming. More importantly, it can move beyond the limitations of fragmented models toward a more efficient and scalable future. Ultimately, delivering exceptional streaming experiences won’t require just technology, but also collaboration and synergy, aligning the entire ecosystem to operate as one.
Martijn Gribnauis, Chief Customer Success Officer at Quant, on why Agentic AI will redefine financial services
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A recent Google Cloud survey showed that only 13% of finance organisations are currently using agentic artificial intelligence. This number needs to, and will rise when you consider that 88% of financial leaders are seeing ROI from generative AI already. Agentic is the next and most advanced evolution of artificial intelligence the world has ever seen.
Agentic AI is not on the way. It is here and already reshaping how forward-leaning financial institutions operate. In 2026, for IT and finance leaders to build an insurmountable competitive lead they must deploy agentic AI in every area where it can safely and effectively create value. The institutions that hesitate will find their business models under threat from familiar competitors and newcomers alike.
Reinvention of Core Processes
Agentic AI is poised to reinvent core financial processes. Bookkeeping, record maintenance, and period-end close are nearing complete automation. Month-end processes that once required late-night, stress-filled marathons will evolve into continuous, largely automated cycles. IT teams will no longer spend evenings on high alert waiting for failures.
This shift also frees IT leaders, finance teams, and operations functions from monotonous repetitive tasks. Instead of focusing on system uptime and manual reconciliation, they will collaborate with the C-suite on strategic initiatives that drive growth and revenue.
Understanding Why Adoption Is So Low
Despite the promise of Agentic AI, there is understandable caution. Some 80% of organisations have reported ‘risky behaviour’ from AI agents, and in the world of finance that is an alarming number. Finance is one of the most regulated, risk-averse sectors in the world. The fear of losing control remains the primary reason so few in the industry have embraced Agentic AI.
Loss of control and fear of catastrophic error
Financial leaders fear that an autonomous system could go ‘off script’, mis-route payments, misinterpret rules, or inadvertently cause compliance breaches. In finance, even small errors can trigger major financial or regulatory consequences.
Security and data privacy concerns
Large AI models require huge quantities of sensitive data. Organisations worry about breaches, cyber-attacks, or manipulation. An AI agent with improperly configured permissions could, in theory, execute fraudulent transactions or expose confidential customer information.
Bias and fairness risks
If AI agents make decisions using incomplete or fragmented data, they risk perpetuating or amplifying bias. At scale, biased decision-making can undermine customer trust and expose firms to legal and regulatory challenges.
Regulatory ambiguity and audit difficulty
Regulators are still determining how to govern agentic AI. Some organisations fear that early adoption could unintentionally violate rules or create future audit vulnerabilities.
These fears are legitimate, but not insurmountable.
Tackling the Adoption Barriers: A Practical Blueprint for Finance Leaders
To capitalise on Agentic AI’s immense potential, leaders must take a structured approach grounded in business value, security, and trust.
1. Start With Clear, Measurable ROI and Efficiency Gains
In finance, adoption accelerates when decision-makers see proof of value.
Start by automating repetitive processes. Agentic AI can handle tasks like data entry, reconciliation, invoice matching, and initial fraud checks faster and more accurately than humans. This leads to reduced operational overhead as automation lowers labour costs, shortens processing times, and reduces error rates. Demonstrating these savings through case studies or internal pilots is critical to changing minds.
AI agents can enable revenue growth by analysing huge data sets to identify new investment opportunities, optimise trading strategies, and generate personalised product recommendations. Each of these capabilities directly impacts top-line growth.
2. Strengthen Risk Management and Compliance Through AI
Agentic AI will improve risk management when deployed responsibly. This starts with real-time fraud detection. AI agents can monitor transactions continuously, identifying patterns that suggest fraud long before traditional systems would detect an anomaly.
Continuous monitoring is also incredibly helpful when it comes to compliance. AI agents excel at ensuring adherence to KYC and AML regulations. They can automatically maintain audit trails, identify missing documentation, flag anomalies, and escalate issues instantly.
Enhanced stress testing and scenario modelling can both be completed via Agentic AI. It can simulate complex market environments more dynamically than legacy tools, providing deeper insights into vulnerabilities and improving resilience. When showcased and presented in this context, agentic AI becomes a risk-reduction tool in the eyes of decision makers.
3. Directly Address Security and Trust Concerns
Trust is the cornerstone of adoption. Implement enterprise-grade security architecture that includes encryption, secure APIs, strict access controls, and continuous monitoring of agent behaviour. And, use explainable and transparent AI systems (XAI) so your finance teams understand the reasoning behind decisions. XAI helps provide interpretable outputs that support auditability and regulatory compliance.
Start small with a controlled, low-risk pilot. A proof-of-concept in a non-critical workflow helps teams understand the technology, gather evidence, and build internal support before scaling. Produce numbers based reporting that speaks the language of the people who make the decisions. Show, don’t just tell them how agentic will move the business forward.
4. Highlight the Competitive Advantage
Agentic AI adoption is not just an efficiency upgrade. It is a competitive imperative. AI agents create faster innovation cycles by accelerating product development, service delivery, and operational improvements.
They also provide superior customer experience. From instant account servicing to personalised financial recommendations, Agentic AI delivers the speed, personalisation, and convenience customers expect. Plus, it scales exponentially. No matter how many people call in at the same time, an agentic agent will answer immediately. Agentic AI reduces up to 86% of time spent in complex workflows that were traditionally handled only by people. This will be huge in getting ahead of your competition.
5. Build Momentum Through Internal Champions
Adoption increases when respected leaders advocate from within. Mid-level managers, AI-literate staff, or members of the C-suite who understand the technology can serve as champions. Use them and their beliefs to drive alignment, communicate benefits, and counter misconceptions. The more people from different departments and levels of the organisation that talk up the technology, the more likely you are to get buy-in.
Your Time is Now
Agentic AI will redefine financial services. The organisations that act today will build capabilities, insights, and competitive advantages that late adopters will not be able to replicate. Finance leaders must begin asking where agentic AI can support their business, where it can remove friction, where it can unlock growth, and where it can transform operations. The firms that act now will lead the industry. Those that hesitate will not get the chance to catch up.
The only remaining question for finance organisations is not whether agentic AI will change the industry, but how quickly they choose to deploy it.
Richard Ford, Chief Technology Officer at Integrity360, on why cybersecurity must move beyond control and embrace trust
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Cybersecurity has long been focused on building walls, but the biggest threat is already inside. Today, insider risk accounts for nearly half of all data breaches. This isn’t just about malicious actors, it’s about regular employees and trusted contractors who make simple, costly mistakes.
Remote and hybrid working has only intensified the problem. With teams distributed and work happening across cloud platforms and collaboration tools, it’s harder than ever to track what’s happening, let alone why. Although AI tools promise efficiency, they also introduce new vulnerabilities. Employees pasting code into chatbots or bypassing corporate tools to meet deadlines. All seemingly innocent, but highly risky.
Insider Risk
Ransomware gangs know this and are now skipping the technical breach altogether and going straight to the source – a company’s insiders. Whether through bribery or social engineering, attackers are finding that humans can be the weakest link in even the most well-defended environments. Despite this, most security budgets still focus outward.
Traditional tools like data loss prevention (DLP) struggle to keep up with today’s dynamic and unpredictable user behaviour. Meanwhile, simulated phishing tests and punitive training schemes often breed resentment, not resilience. It’s time to rethink the model.
Human Error, Human Fix
We need to stop treating employees as the problem and start making them part of the solution. Enter Human Risk Management (HRM), a behavioural approach to cybersecurity that recognises the complexity of modern work. HRM tools monitor real-world user behaviour, detect anomalies in context, and deliver just-in-time nudges to prevent risky actions before they happen. Instead of punishing mistakes, they help users avoid them in the first place.
Of course, technology alone won’t fix the issue, culture is key. Leadership must champion security as a shared responsibility, not an IT rulebook. Success should be measured by how quickly employees improve, not how often they slip up. Awareness campaigns need to be practical and rooted in real-world behaviour.
Organisations also need to understand how digital transformation has changed the risk landscape. Shadow IT is no longer a fringe issue, it’s how work gets done. Whether it’s a developer using an AI plugin or a marketer sharing files via a personal drive, employees will always find the fastest path to productivity. Security must meet them there, not block the way.
Cybersecurity Built on Trust
The smartest businesses are those that treat identity like infrastructure, and behaviour like a vital data stream. They invest in tools that adapt to people, not the other way around. This means a move away from a surveillance approach and embracing the nuance of human error and design systems that support.
In a world where threats are increasingly internal and AI is both a risk and a tool, cybersecurity can no longer be about control. It must be about trust, and that starts with understanding the humans behind the keyboards.
Pierre Noel, Field Chief Information Security Officer at Expel, on why security with community-based governance is a key business pillar that better positions organisations to become more resilient and target growth
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It’s been a particularly rocky start to 2026 for the global cybersecurity landscape. From the Substack data breach to PayPal credential-stuffing attacks in February, we are not looking at IT failures alone. These attacks are balance-sheet events: direct assaults on business value, triggering remediation costs and long-term impacts on financial health. Compounded with the conflict with Iran, leading to potential ramifications in the cyber realm, it’s more important than ever for the C-suite to be aligned on cybersecurity priorities.
Despite this, a glaring disconnect remains in planning and execution. Expel’s research found that while 85% of finance leaders view cybersecurity as a key component of business planning, only 40% express full confidence in security’s ability to align with business strategy. To bridge this gap, CISOs must move from reporting on activity and start reporting on resilience and unit cost.
Translating Alert Volume Into Unit Cost
CISOs must change how they present the value of their operations. CFOs are largely indifferent to technical metrics like the ‘millions of blocks pings’ or ‘SOC alert volume’ – to a finance leader, an alert is simply another form of disruption to daily operations.
To fix this, CISOs should introduce the ‘unit of cost protection’. By breaking down security spend into the cost required for a single transaction or business unit, CFOs can understand and manage it from experience. A tiered approach works best here: high-risk business units justify higher protection costs than low-risk ones. This allows CFOs to treat security as a scalable operational expense rather than a black hole of additional tooling – the kind of framing that also resonates in a boardroom.
Mapping Investment to Business Risk Exposure
Expel’s research shows that while 43% of finance decision-makers are confident that security can prioritise investments based on risk, only 46% are confident that security can deliver cost-efficient solutions. To move in the right direction, CISOs should shift from ‘vulnerability management’ to thinking about ‘business risk exposure’, requiring a different view of how threats unfold over time.
It’s all about asking the right questions. Instead of requesting more firewalls to protect a specific timeframe, start asking for the cost of securing diverse digital ecosystems across an extended risk window. The 2026 Winter Olympics is a good example: Russian-led cyber campaigns began raising concerns months before a single athlete arrived in Italy, proving that risk isn’t a one-day event but an ongoing operational cost.
For European organisations, this framing is increasingly non-negotiable. While NIS2 and DORA help make the cost of under-investment concrete and quantifiable, the upcoming Cyber Resilience Act (CRA), with key reporting requirements starting in September 2026, extends this pressure to anyone manufacturing or selling digital products in the EU. Even for purely domestic UK entities, the new UK Cyber Security and Resilience Bill is moving the goalposts toward these same high standards. Ultimately, CFOs must understand that cybersecurity isn’t just about preventing loss; it’s a prerequisite for safe and secure growth.
The Reputational Multiplier
So those are the questions to ask, but how do CISOs deal with the ‘unknown unknowns’, specifically long-term brand damage? While compliance fines under NIS2 or DORA may be straightforward (and important) to model, they rarely represent the full scope of the potential damage. In such scenarios, CISOs should propose a reputation multiplier: a framework for quantifying the financial fallout of brand damage in a language CFOs know and trust, looking past immediate recovery costs to factor in the long-term implications of re-establishing market trust.
The 2026 CarGurus breach illustrates this well. Impacting 12 million users, the cost wasn’t purely technical; it also came from the stock price dip and marketing spend required to repair the brand. For UK companies, where regulatory scrutiny is heightened, that multiplier effect is even more pronounced. This is the language of a CFO, and it helps CISOs better translate the urgency and relevance of a strong cybersecurity posture.
Standardising the Language of ROI
Closing the gap between CFOs and CISOs needs more than just better data; it needs a shared vocabulary. By standardising the language of ROI, CISOs transform cybersecurity from a vague insurance policy into a transparent value driver fully trusted by finance teams. Move away from complicated defensive jargon toward a unified framework of unit costs, and the gap between the CISO and CFO starts to close.
Security has become a key pillar of business operations, and in the current threat environment, it’s genuinely a community-based governance issue. The organisations that get this right aren’t just more resilient. They’re better positioned to grow.
Dr. Yvonne Bernard, CTO at Hornetsecurity, on meeting the challenge of managing the speed of AI adoption and harnessing its defensive capabilities while mitigating the risk of uncontrolled adoption
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The past year has been defined by acceleration. Threat actors rapidly embraced automation, AI, and social engineering. Scaling their tactics at unprecedented speed, while defenders raced to keep pace. Historically, defensive resilience evolves in step with attacker innovation, but in 2025 that balance began to falter.
In an analysis of over 6 billion monthly emails, Hornetsecurity’s Security Labs found that the volume of sophisticated threats grew faster than most security teams could adapt to. Malware-infected emails soared by 131%, scams increased by nearly 35%, and phishing attempts – powered by access to advanced AI – rose by 21% from the previous year.
Typically, attacks, even at volume, are easily filtered by good firewalls and secure email gateways. But the sophistication and AI-led nature of 2025’s boom made it even harder for organisations to defend themselves. The question now is: can security teams and businesses wrestle back control?
Evolving Cyberattack Landscape
AI enhances efficiency and precision. As such, cybercriminals use it to launch faster, more convincing and adaptive attacks, ranging from deepfakes to credential stuffing. As an example, there is a concerning trend of attackers increasingly using ‘MFA bypass kits’ to create deceptive login pages. These pages capture not only the user’s credentials but also have logic built in to handle MFA prompts as well. The unsuspecting user is then passed to the real login page for the target service and meanwhile the ‘kit’ grabs a copy of the user’s session token. This allows the attacker to impersonate the person and access their data.
Examples of such kits include Evilginx (open source) and the W3LL panel. Protecting against these attacks can be challenging, as they are adept at bypassing MFA safeguards. Threat actors often use compromised LinkedIn accounts, for example, to gain access to substantial information and connections. This enables them to impersonate trusted business connections. Paired with the weaponisation of Agentic AI, this will magnify existing vulnerabilities within an organisation, while introducing new ones that defy traditional containment models.
As it stands, the lack of oversight within organisations on the extent of AI’s adoption by cybercriminals has enabled the emergence of ‘Ransomware 3.0.’ Ransomware has evolved past simple encryption and exfiltration, with this next phase focusing on LLM-driven orchestration and a shift to data integrity manipulation.
To counter AI-accelerated compromises and ‘Ransomware 3.0’ in 2026, organisations must adopt a Zero Trust-based cyber resiliency strategy. This requires businesses to implement strong, non-phishable machine authentication, strict least-privilege access, and constant monitoring to protect the integrity of the data that users and AI agents can access. It should become the baseline expectations rather than aspirational goals for this year.
The Secret Value of ‘Least Privilege’ Access
Another strategy to proactively improve cybersecurity defences in 2026 is to enforce the principle of ‘least privilege’ access. This tactic grants users access only to the data that’s needed for their role. Limiting excessive access is important for preventing the potential for widespread data exposure and damage in the case of an account compromise.
Businesses, however, must strike a balance over access; if it’s too strict, it can hinder productivity and lead to shadow IT issues. Getting this balance right when it comes to privileged access is where sophisticated permission managers are invaluable tools to work with. They streamline the process and remove the guessing game of who and what to grant access to, thereby ensuring, in the case of an attack, that the entire organisation won’t be brought to its knees.
How CISOs are Adopting ‘Resilience, not Perfection’
The rate at which AI is advancing means not every organisation will be equipped with the tools or the know-how to tackle every AI-inspired attack. But as the saying goes, ‘prevention is better than cure’. It’s better to create a strong security culture than to continually chase after the next best tool.
Organisations can’t strengthen their resilience without involving every single person under their umbrella. That’s why CISOs must continue to invest in cybersecurity awareness programs.
These should include simulated AI-phishing attacks (phishing remains the number one attack vector) to test users and enable them to apply learnings from the modules.
If any user clicks on a phishing email, they should receive additional training at that very moment, to cement the learning. Over time, a good training system should automatically identify users who rarely fall for such attacks and reduce the training they receive while making the simulations they do receive more difficult. Conversely, giving persistent offenders additional bite-sized training and simulations can help improve security outcomes over time.
The key challenge for 2026 is managing the speed of AI adoption and harnessing its defensive capabilities while mitigating the risk of uncontrolled adoption. But with excellent training, cyberattack practice runs, and the adoption of Zero Trust principles, organisations will find themselves in a strong position.
About Dr. Yvonne Bernard
Dr. Yvonne Bernard is the CTO of Hornetsecurity by Proofpoint, Proofpoint’s business unit leveraging the Hornetsecurity product suite dedicated to managed service providers (MSPs) and small to mid-sized businesses (SMBs), providing next-generation cloud-based security, compliance, backup, and security awareness solutions that help companies and organisations of all sizes around the world.
Dr Megha Kumar, Chief Product Officer and Head of Geopolitical Risk at CyXcel, on whether our risk and regulatory frameworks and institutional cultures can keep pace with Agentic AI
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Within the next couple of years, Agentic AI is likely to progress from early stages of operation to be fully embedded within systems. Its expansion will be subtle rather than spectacular. It will integrate steadily into enterprise platforms, logistics networks, compliance workflows, cybersecurity operations centres and executive decision-support tools. Processes will move faster, operating expenses will decline and performance indicators will trend upward.
Yet these visible improvements mask a deeper challenge. The regulatory exposure, data governance pressures and erosion-of-trust risks associated with Agentic AI are being misjudged.
Unlike earlier AI applications designed primarily to generate outputs – whether text, imagery, or predictive insights – agentic systems are built to act. They sequence decisions, draw from multiple data environments, initiate consequential processes and function at scale with differing levels of human supervision. In sandbox environments this can seem contained and controllable. Over extended periods in live environments, however, sustained oversight, traceability and effective governance become significantly more complex.
Evolving Operational Complexity
There are two key challenges that businesses must address.
First, how do organisations monitor what agentic systems are doing once deployed? These systems evolve through updates, integrations and retraining and they interact with new data environments.
Second, how do you ensure responsible behaviour throughout the lifecycle? Regulators, policymakers and customers will likely expect firms to shift from compliance assurance to risk assurance and demonstrable evidence of trust and transparency.
The prevailing assumption is that human oversight will mitigate these risks. Human in the loop or human over the loop has become the default reassurance. In practice, however, that assumption breaks down far faster than many anticipate.
When a system works 95 per cent of the time, human reviewers limit their scrutiny. Behavioural science tells us that automation bias and complacency occur when automated systems are high-performing. Employees often become validators of AI outputs rather than critical examiners. The diligence gap widens gradually and then suddenly.
Facing Up to Difficult Questions
How do you incentivise employees to remain diligent checkers when the system mostly ‘works’? And how much time does effective oversight actually require? True review is not a cursory glance at a dashboard. It involves interrogating assumptions, validating inputs, checking context and assessing downstream consequences. In many cases, meaningful oversight may take nearly as long as performing the original task manually. When checking becomes more costly than doing the job yourself, pressure to ‘trust the system’ intensifies.
And what happens to accountability when oversight exists on paper but not in practice? Governance documentation may show layered review structures, escalation pathways and audit processes. Yet if humans are functionally disengaged, responsibility becomes dispersed. When errors surface, organisations may struggle to attribute fault – was it the model design, the data, the integrator, the operator or the reviewer who signed off without fully scrutinising?
Regulators are only beginning to grapple with these realities. In jurisdictions such as the European Union, the EU AI Act introduces risk-based obligations, documentation requirements and human oversight provisions. These are important steps, however, the operationalisation of those requirements in dynamic, agentic environments remain untested at scale. Compliance on paper will not automatically translate into resilient governance in practice.
Addressing the Trust Challenge
Beyond regulatory exposure, there is a broader trust challenge emerging.
As Agentic AI systems scale across industries, they will generate vast volumes of automated outputs – reports, communications, risk assessments, content, decisions and transactions. If errors or manipulations spread through interconnected systems, confidence in digital outputs may erode.
In geopolitically sensitive contexts, this has profound implications. Agentic systems interacting with external data sources could amplify disinformation, introduce biased datasets or make decisions based on manipulated inputs. The speed of automation may outpace the speed of verification. Trust, once diluted, is difficult to restore.
Data protection risks will also intensify. Agentic systems frequently require broad access privileges to perform tasks effectively. They may access internal databases and personal data and interact with third-party platforms. Each interaction creates potential exposure points. A single misconfiguration or prompt injection attack could trigger cascading consequences across systems.
The next phase of AI adoption will not simply amplify productivity: it will amplify regulatory, legal and reputational risk. This moment therefore demands serious scrutiny before agentic AI becomes deeply embedded in business infrastructure.
The Moment for Action has Arrived
So, what should organisations be doing now?
To begin with, organisations need to look past superficial, tick-box compliance. Effective governance cannot live solely in policy documents – it must function in day-to-day operations. This means investing in continuous monitoring capabilities, robust audit trails and real-time anomaly detection tailored specifically to Agentic AI behaviours.
In parallel, incentive structures should be redesigned. Meaningful human oversight will not happen if it is treated as secondary to speed or output. If employees are expected to provide meaningful review, organisations must allocate time, training and authority accordingly. Performance metrics should reflect risk management responsibilities, not just output rate.
Clear lines of accountability are equally important. Senior leadership and boards should determine who carries ultimate responsibility for outcomes produced by agents. Where third-party vendors are involved, responsibilities must be contractually and operationally defined. Incident response mechanisms should be rehearsed in advance, rather than presumed to work when pressure is high.
Expertise must also be integrated across functions. Legal, risk, compliance, cybersecurity, data protection and operational teams should be engaged from the outset. Deploying Agentic AI is not simply a technical upgrade – it reshapes the organisation’s risk profile.
Finally, resilience demands deliberate stress-testing. Leaders should examine not only pathways to success but how models fail at scale. How would the organisation respond if a system update embedded systemic bias, if an integration vulnerability enabled unauthorised activity or if automated actions eroded customer confidence? Rigorous scenario exercises, however uncomfortable, are essential to building genuine preparedness.
As Agentic AI advances, Risk Management Should Match its Pace
None of this is an argument against adoption. Agentic AI presents meaningful productivity improvements and the potential for sustained competitive differentiation. Organisations that deploy it with discipline and foresight may secure a measurable advantage. The danger lies not in adoption itself, but in pursuing acceleration without knowing the risks and putting the right guardrails in place.
The coming two years are critical for businesses. Before these systems become deeply embedded in core processes, organisations have an opportunity to shape the control environment around them. However, once agentic systems are fully embedded, retrofitting controls will be far more difficult and costly. Leaders must therefore treat this period as a design phase for oversight, not merely a race for competitive advantage.
Agentic AI is advancing rapidly. The defining question is whether our risk and regulatory frameworks and institutional cultures can evolve just as quickly.
As companies pour billions into developing their own AI tools, Fayola-Maria Jack, Founder and CEO of Resolutiion, argues that many are forgetting what worked well in the early tech era, confusing ownership with innovation
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Back in the very early days of computing, organisations rarely hesitated to buy the hardware and software they needed to modernise. Now we’re deep into the AI age. Many organisations are deciding the best approach to adopting the technology is to take building it into their own hands.
Many of the more traditional companies, like big banks, have publicly stated that they’re developing their own AI tools in house. Meanwhile, corporate investment in AI reached £191 billion ($252.3 billion) in 2024 and is only likely to have risen since..
Yet, the challenges of internal AI development are becoming abundantly clear. A recent report from MIT found that 95% of AI pilot projects failed to deliver any discernible financial savings or uplift in profits. It also found companies purchasing AI tools succeed about 67% of the time. Meanwhile, internal builds succeed only one-third as often.
Why do companies feel they need to build their own AI tools?
Those statistics alone show buying AI from specialised vendors and building partnerships is often the wiser choice. But, with a handful of traditional businesses deciding to lean the other way, it begs the question: why are these companies not only initially choosing the in-house route, but also persisting with it despite low success rates?
The instinct to ‘build’ is rooted in legacy thinking – and to some extent, a naivety around what makes AI solutions special. Traditional enterprises have long equated ownership with control: control over systems, data, and perceived competitive advantage.
When AI entered the scene, many executives applied that same logic, assuming that building in-house equated to ownership, at the heart of innovation. But this overlooks a fundamental truth that is unique to AI – AI isn’t another IT system you can own and stabilise. It evolves exponentially, not linearly. It demands constant retraining, rapid iteration, and deep specialisation – all at odds with the traditional corporate IT environment, which is built for stability and compliance, not experimentation and speed.
Are companies really investing in innovation?
Another common belief is that buying is seen as conceding leadership to outsiders. While building feels safer politically, signalling ‘we’re investing in innovation’. Ironically, though, that safety is often an illusion that leads to slower progress and higher long-term cost. But again, there is deep irony if talent is outsourced to India, or another foreign jurisdiction, on the basis of cheap labour.
The exact same dynamic plays out internally, too. AI initiatives are career-defining projects for senior technology leaders and they attract budget, visibility, and prestige. Once a build programme is launched, it’s politically difficult to pivot, even in the face of poor performance. As a result, the build strategy often survives by narrative rather than by evidence.
Underpinning all of this is the institutional belief that ‘our data is unique’ – that their data will deliver proprietary insight and competitive advantage. In reality, most internal data is messy, siloed, and outdated. It reflects years of practices that are often misaligned with best practice, and therefore should never be used to train AI. Instead of building capability, many organisations end up building complexity.
Increased Caution in Regulated Sectors
Alongside these misbeliefs, regulatory caution and data residency also play into the decision to build in-house; especially in regulated sectors like finance, healthcare, and government. Here, enterprises typically believe that adopting third-party AI tools may expose sensitive data to external environments they cannot fully control. Perhaps this is because data protection laws have created a heightened sensitivity to where data is processed and how it’s used to train models.
Take banks as an example – historically they have viewed data as a fortress, a core asset to be guarded. Their culture of confidentiality and regulation makes them instinctively cautious about sharing information externally. Add to this the fact that large banks already have substantial internal technology infrastructures and budgets, and building seems logical on paper. The truth, however, is that building internally doesn’t eliminate compliance risk, but often amplifies it. This is because companies take on the burden of securing systems, updating controls, and managing ethical frameworks themselves.
On the other hand, buying from specialist providers means adopting a system that’s been engineered for compliance at scale. Purchasing doesn’t dilute compliance, it accelerates it, because you inherit the expertise and validation of teams who do this. In fact, most reputable AI vendors now far exceed enterprise compliance standards, designing privacy-preserving architectures that mitigate these risks far more effectively than in-house teams can, full-time.
Competitive Edge
The financial sector’s competitive edge increasingly lies not in owning the algorithms, but in applying them better and faster. Challenger banks and fintechs have embraced this: they buy tools (whereby anti-money-laundering and fraud detection platforms are incorporated into model-risk management protocols aligned with regulatory expectations), they integrate, and they move rapidly. Traditional banks, by contrast, are still in a transitional mindset, modernising legacy systems while trying to preserve control. That’s why their build programmes are often more about transformation theatre than tangible AI capability, and will ultimately see them fall further behind.
Underestimation of AI’s Lifecycle Cost
Beyond the issues of legacy thinking, poor data quality and compliance risk, companies attempting to build in-house also face a number of additional challenges when it comes to the talent, time, and technical debt needed.
Talent: True AI expertise is scarce and expensive. Competing with the open market for top data scientists and ML engineers is unsustainable for most enterprises.
Time: AI doesn’t stop evolving while your internal team builds. By the time a prototype is ready, the underlying technology stack may have already advanced.
Technical debt: Maintaining models, retraining on new data, and ensuring explainability and auditability over time all demand continuous investment.
Most companies underestimate this lifecycle cost by an order of magnitude. Add to that the reputational risk of bias or error (especially when deploying AI in customer-facing contexts) and the true cost of internal builds can spiral quickly.
A Change in Mindset is Needed
As more of these challenges surface, we should see an uptick in companies moving towards buying AI rather than building it – and it’s a pattern that’s thankfully already emerging. As AI becomes infrastructure, not novelty, enterprises will mirror the software evolution of the 1990s and 2000s: moving from bespoke builds to modular adoption.
The early adopters that buy today will pull ahead dramatically because they can focus on application and differentiation, not on maintenance. In time, the ‘build’ approach will be seen much like writing your own word processor in 1995: a costly distraction from real innovation.
Organisations need to shift from ownership to orchestration. This requires humility, recognising that innovation now happens outside corporate walls, and confidence – trusting that your value lies in how intelligently you deploy technology, not in whether you wrote its source code. Culturally, companies need to redefine ‘strategic advantage’ as agility plus insight, not possession plus control. AI isn’t an asset you own; it’s a capability you cultivate.
In simpler terms, the companies that thrive in the AI age will be those that treat AI as an ecosystem, not an ‘ego system’.
Chris Larsen, Chief Technical Officer – atNorth, on shaping ecosystems that support both digital progress and the preservation of our natural environment for future generations
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The AI industry continues to grow seemingly exponentially. With 92% of companies planning to increase their AI investments in the next three years, demand for the high density digital infrastructure required to support these types of workloads is unsurprisingly at an all time high.
Data centres have always needed a significant amount of electricity to power and cool their computer equipment. Yet the sheer quantity of data to be processed for AI and other high performance computing – such as financial trading calculations and simulation technologies – necessitates a colossal amount of energy. For example, a report from the International Energy Agency states that data centres will use 945 terawatt-hours (TWh) in 2030, roughly equivalent to the current annual electricity consumption of Japan.
At the same time, there is growing pressure for all organisations to comply with ESG frameworks. The introduction of regulations such as the EU’s Corporate Sustainability Reporting Directive (CSRD), mandates the publication of carbon footprint disclosures. This leaves many businesses with a difficult conundrum to solve – how to balance digital advancement whilst mitigating environmental impact?
Once a consideration for local IT teams, the choice of a data centre partner is now at the forefront of balancing these two critical trends and is beginning to garner boardroom attention.
Data centres that are designed with environmental responsibility and community integration in mind can act as the central hub of a thriving society, an ‘ecosystem’ that supports long-term sustainability and regional economic development.
Location and Design
Where a data centre is built, and how, is fundamental to its efficiency and sustainability. AI-ready facilities often require rapid scaling in line with customer demand. Access to ample suitable land is essential. Modular designs allow for faster builds and easier adaptation to new innovations in cooling and hardware technologies,
Power and connectivity are also critical. Many regions struggle to offer the necessary renewable energy and high-speed network capacity. In contrast, the Nordics provide an ideal environment. An abundance of renewable energy, a cool natural climate that enables more energy efficient cooling techniques and excellent connectivity.
As a result, the presence of data centres can promote local investment in power, connectivity and electrical infrastructure that benefits the whole community. For example, atNorth’s ICE03 data centre in Akureyri, Iceland, facilitated the development of a new point of presence (PoP) for Farice, which operates submarine cables linking Iceland to mainland Europe. This enhances telecom reliability and strengthens digital infrastructure across the region.
Data centres can also support the stability of local power through grid balancing services. Something that is integral to the future design of atNorth’s data centres.
Decarbonisation and Circular Partnerships
Data centres are incredibly energy-intensive, and so many operators are investing in ways to reduce their carbon footprint. These include utilising the most efficient infrastructure and cooling technologies.
atNorth goes one step further and has committed to sourcing heat reuse partnerships for all of its new data centre campuses. This means that waste heat generated during the infrastructure cooling processes can be captured and redirected to support nearby businesses and homes. In Finland, for example, a partnership has been formed with Kesko Corporation that will utilise waste heat from atNorth’s new FIN02 campus to heat a neighbouring branch of one of its stores.
These types of initiatives essentially enable data centres to act as a decarbonisation platform for their clients’ IT workloads, helping them meet environmental targets and reducing running costs too. Something that is a key differentiator for businesses such as atNorth client and partner, Nokia, that has complex technical requirements and stringent sustainability goals.
Responsible Operations
Beyond environmental responsibility, data centres can be a positive force in the communities in which they operate. They create skilled jobs, drive improvements in local infrastructure, and often spark growth in hospitality, retail, and leisure services. At atNorth, we prioritise hiring locally and actively support education, charitable, and community initiatives in the regions we operate.
Similarly, a care for the natural surroundings is pivotal to promoting a successful, data centre ecosystem integration. For example, atNorth has set aside part of its DEN02 site in Denmark for biodiversity efforts, installing insect monitors to track changes in insect abundance and diversity throughout the site’s development.
As digital demand continues to grow, so does the need for responsible and sustainable development. High-performance computing can, and should, advance without compromising environmental integrity. By partnering with data centres that prioritise environmental stewardship and social responsibility, we can help shape ecosystems that support both digital progress and the preservation of our natural environment for future generations.
Nicole Reader, Head of Technology Solutions & Delivery at The Bunker (part of the Cyberfort Group), on finding a measured path forward for the future of cloud
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For more than two decades, UK organisations have embraced the cloud as the default model for digital growth. Hyperscale platforms have offered flexibility, speed and a route to innovation that would once have required years of capital investment. Cloud first became the business mantra. Cloud native became the ambition. Few stopped to ask what this meant for long term control. Today that question is becoming unavoidable.
Geopolitical relationships are shifting at pace. Trade tensions, regulatory divergence and new data access laws are reshaping the digital landscape as quickly as any technological change. At the same time, businesses are generating and storing more information than ever before. AI tools, collaboration platforms and SaaS applications are accelerating data creation at a rate that is testing infrastructures, supply chains and budgets alike.
In that context, many UK organisations are starting to ask a difficult question. When we moved to the cloud, did we quietly export more control over our data than we realised? The uncomfortable answer in many cases is yes.
The Assumption of Cloud Control
A significant proportion of UK businesses rely on global services, whether hyperscalers such as Amazon Web Services and Microsoft Azure or SaaS platforms headquartered overseas. These providers are sophisticated, resilient and often highly secure. However, their global footprint means that data is frequently stored, processed or managed beyond UK borders.
The challenge is that many boards assume that if data is accessible from the UK, or if a provider has a UK presence, it remains firmly under UK control. This assumption is often incorrect.
There is a crucial difference between data location and legal jurisdiction. Data residency refers to where data is physically stored. Data sovereignty refers to which who ultimately governs access to that data. Those two concepts are not interchangeable.
Legislation such as the US Cloud Act demonstrates why this matters. Under certain circumstances, US authorities can compel US headquartered providers to provide access to data, even if that data is stored outside the United States. The geographic location of a data centre does not automatically determine who can lawfully demand access.
Boards often conflate these terms, believing that selecting a UK service resolves sovereignty concerns. In reality, the corporate structure of the provider, contractual arrangements and cross border processing activities can all shape the legal framework that applies.
This is not an abstract legal debate. It is a question of operational control, regulatory exposure and risk appetite.
The Convenience Compromise
The rise of public cloud was driven by many compelling advantages. Flexibility, scalability and rapid deployment transformed how businesses launched products and expanded into new markets. For many organisations, the cost of building and maintaining their own infrastructure was prohibitive and the hyperscalers offered an attractive alternative at a great price.
However, that convenience came with trade-offs that were not always fully understood at the time. Cloud contracts can be complex. Consumption based pricing models include ingress and egress charges. Including API calls and a range of ancillary costs that can quickly exceed initial forecasts. It is not uncommon for organisations to reach the midpoint of their financial year and discover their cloud budget has already been used.
Meanwhile, operational design decisions made years ago may not have been stress tested against today’s regulatory expectations or geopolitical realities. Many mid-market IT teams have spent the past decade maintaining estates rather than redesigning them. In some cases, institutional knowledge has not kept pace with the evolution of cloud services and their associated risks.
The result is a landscape in which data has been distributed widely, often for operational reasons, but without a holistic understanding of the sovereignty implications.
Repatriation is Not a Silver Bullet
In response, there has been a growing push towards data return and sovereign cloud offerings. European initiatives are seeking to create regional alternatives to US dominated platforms. In the UK, there have been calls by government to expand domestic data centre capacity to retain greater control over national data assets.
The instinct is understandable, particularly for government, defence and heavily regulated sectors where sovereignty can become a non-negotiable requirement. However, it would be naïve to assume that bringing data back to the UK automatically makes it secure or resilient.
Local does not necessarily mean safe. High profile breaches over the past year have affected organisations across multiple jurisdictions, regardless of where their infrastructure is hosted. Security is not guaranteed by postcode.
There are also practical constraints. Data volumes are expanding rapidly, fuelled by AI workloads and increasing digitalisation. Hardware supply chains are under pressure, with significant demand driven by hyperscale AI investments. Price volatility is already evident, with some organisations seeing substantial cost increases within weeks.
Simply building more UK data centres does not eliminate capacity constraints or environmental considerations, particularly around power and cooling.
Furthermore, many businesses rely on global platforms to serve international customers and partners. A purely national approach can undermine interoperability and performance. For most organisations, the right answer will involve a hybrid strategy rather than wholesale repatriation.
From Technical Detail to Board Level Risk
What has changed is not simply the technology, but the level at which these decisions must be made.
Data sovereignty is no longer a technical footnote for the IT department. It is a board level risk issue. Directors must understand where critical data is stored, where it is processed and which legal regimes can assert authority over it. They must assess whether current arrangements align with the organisation’s risk appetite and regulatory obligations.
This is particularly acute in sectors such as financial services, healthcare and defence, where the sensitivity of data and the scrutiny of regulators are intensifying. For these organisations, sovereignty and security are intertwined. Compromises made for convenience or short-term cost savings can carry significant long-term consequences.
Security itself must be treated as a foundational approach rather than an add on. Too often, security controls are bolted on after operational decisions have been made. Minimum standards are implemented, arbitrary certificates are obtained and compliance boxes are ticked. While certifications can provide useful benchmarks, they do not replace rigorous design and ongoing validation.
If data is brought back onshore, but not properly segregated, monitored and protected, the sovereignty objective is completely undermined. There is little value in regaining geographic control if the underlying environment remains vulnerable.
The Business Case Reality
It would be unrealistic to ignore commercial pressures. For many mid-market organisations, cost remains a primary driver of decision making. Risk appetite is frequently calibrated against budget constraints. The perfect solution is rarely affordable.
That is why compromise becomes central. The critical question is not whether to compromise, but where. Does an organisation prioritise flexibility over jurisdictional control? Does it accept higher costs to secure local hosting? Does it rely on hyperscale security capabilities while accepting overseas governance frameworks?
There is no universal answer. The correct balance depends on the nature of the data, the regulatory environment and the strategic objectives of the business. A small retail operation will have different requirements from a growing fintech or a defence contractor. Supplier selection must reflect that risk profile. Not all cloud or data centre providers are equal in capability, assurance or sector expertise.
Boards should therefore ask their providers some direct questions. Where exactly is our data stored and where is it processed? Which legal jurisdictions apply, and under what circumstances could external authorities demand access? Who within your organisation has access to data, and how is it segregated from other customers? What is the exit plan, and how do we ensure data is fully returned and deleted at the end of a contract?
These are not confrontational questions. They are governance essentials.
A Measured Path Forward
As a result the UK should not retreat from global cloud ecosystems, nor should it blindly assume that everything must be deported. The objective is not isolation, but informed control.
Where sovereignty is genuinely critical, particularly in government and national security contexts, local hosting and specialist providers may be essential. In other scenarios, public cloud may remain the most effective platform, provided its legal and operational implications are fully understood and managed.
The most significant risk today is not that UK businesses have embraced the cloud. It is that many have done so without fully mapping the sovereignty, jurisdictional and security consequences that come with relinquishing control of data.
As data volumes grow and geopolitical uncertainty continues, that gap in understanding becomes a strategic vulnerability. The cloud has delivered extraordinary value. Now all these years later, it demands a more mature conversation.
Convenience built the digital economy. Control will define its resilience.
Leonardo Boscaro, EMEA Sales Leader at Nutanix Database, on why sovereignty requires repeatable, compliant database operations and recovery across hybrid multicloud environments
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In conversations with customers, infrastructure leaders are being asked to deliver more control with the same people. Stronger compliance with less tolerance for error. And higher resilience in environments that are objectively more heterogeneous than they were even a few years ago. Expectations continue to rise, but the operating models used to run critical systems haven’t kept up.
This pressure shows up first at the database layer because they sit at the centre of mission-critical services. While still being managed through manual processes, fragmented tooling, and a heavy reliance on specialist knowledge. In many organisations, when availability, security and compliance are under scrutiny, this combination creates exposure very quickly.
Database-Dedicated Platforms
The shift we now see in regulated organisations is toward database-dedicated platforms. Where the operating model is standardised through approved templates, guardrails, automated workflows, and built-in auditability. In practice, this means treating database workloads as a dedicated domain, with infrastructure and lifecycle operations designed together rather than as an add-on to a general-purpose environment. This approach depends on having a standardised operational layer for database lifecycle management and recovery that works consistently across hybrid and multicloud environments.
And in regulated environments, what matters is not only being compliant, but also being able to demonstrate it repeatedly. When provisioning, patching, and recovery depend on tickets, tribal knowledge, and one-off scripts, controls become hard to test. Furthermore, audit trails are incomplete, and resilience turns into a matter of confidence rather than capability.
How Complexity Crept In
Most enterprise database estates grew through sensible decisions made at different points in time. A platform was added to meet a new requirement, a legacy system could not be moved, or a new tool solved a specific operational gap. Each step made sense in isolation. Over time, however, teams found themselves managing dozens or hundreds of databases across multiple engines and environments. Each with its own processes for provisioning, patching, recovery and monitoring.
What they face now is inefficiency and operational fragility. Databases are where control, auditability and resilience intersect. So, when processes are manual or inconsistent, the risk surface expands quickly. In regulated industries, this shows up in audit pressure, long recovery times and an uncomfortable dependency on a small number of specialists.
Why Databases Expose the Cracks First
Many infrastructure leaders we speak to ask why databases should be their concern at all. Traditionally, databases belonged to DBA teams, while infrastructure focused on platforms and capacity. Unfortunately, it’s not that simple anymore.
Today, infrastructure and security leaders are under constant pressure to improve compliance, reduce risk exposure and maintain availability with fewer people and less tolerance for error. Databases sit directly in that line of responsibility. Patching windows, backup failures or untested recovery plans are operational risks with business consequences.
What becomes clear very quickly is that automation alone does not solve this. Many organisations have invested heavily in scripts and bespoke workflows to manage database lifecycles. While these efforts reduce pressure in specific areas, they often create new complexity elsewhere. Particularly when people change roles or environments scale.
Standardisation, Not Scripting, is the Real Shift
The real breakthrough comes when organisations move from automating tasks to standardising the operating model itself. This means treating database operations as a productised capability, with approved templates, guardrails and repeatable workflows built in from the start.
When provisioning, patching, cloning, and recovery follow a consistent model, compliance becomes part of the process rather than something validated afterwards. Human error is reduced because the system guides operations rather than relying on memory or documentation. And audit readiness improves because actions are traceable and predictable.
This is why many organisations are moving away from bespoke automation and toward standardised operating models, where infrastructure, lifecycle, and governance are designed together.
Recoverability Turns Theory Into Reality
Recoverability is the stage at which operating models are tested under pressure. Many organisations technically have disaster recovery in place, but testing it is complex, disruptive and often avoided altogether.
For mission-critical services, particularly in financial services or the public sector, this is not acceptable. Recovery needs to be a standard operational capability, not a specialist exercise dependent on a few experts and fragile runbooks.
By embedding recovery workflows into the same platform used for everyday database operations, testing becomes simpler and more frequent. Switchovers, failovers and restores can be executed through guided processes, with far less room for error. This is not about faster failover, but about confidence, credibility, and the ability to demonstrate control.
Sovereignty is Becoming Operational Autonomy
We all know how important sovereignty is, yet it’s often discussed in terms of data location instead of dependency and control, beyond just geography. Real sovereignty must factor in where the data resides, who ultimately controls the operating model and under which jurisdiction that control sits.
In this context, hybrid strategies work but only if they preserve consistency. Running databases across on-premise and cloud environments without a common operating model simply moves complexity from one place to another. True autonomy comes from having one set of standards, workflows and controls that travel with the workload, regardless of where it runs.
Our customers want the freedom to adapt to regulatory, geopolitical or commercial change. And without rebuilding governance and operational processes each time. This has made portability and consistency critical.
A Database-Dedicated Platform, Not Just Infrastructure
What emerges from all of this is a shift in how database platforms are defined. Beyond running databases on infrastructure, databases must now be delivered through a dedicated platform experience. One where lifecycle automation, governance and recoverability are baked in, not added later.
When you take a platform approach, you can support multiple database engines, span hybrid environments and provide a single operational plane for teams. This allows infrastructure leaders to move beyond firefighting and towards standardised, compliant operations that scale.
Independent economic analysis from Forrester’s Total Economic Impact study supports what many organisations are already seeing in practice. When database operations are standardised, the benefits show up quickly. Faster delivery, less manual effort, and more consistent controls reduce day-to-day operational friction and lower risk. Often generating measurable returns earlier than traditional infrastructure-only programmes.
The modern mandate for infrastructure leaders
For today’s CIOs, CTOs and CISOs, the challenge is no longer where databases should run, but whether they are governed, recoverable and consistent by design. As digital services expand, AI initiatives place new demands on data, and regulatory scrutiny increases. Operational discipline becomes a leadership responsibility. In regulated environments, credibility is earned through evidence, with regulators and customers, and in the public sector it is earned with citizens.
The Index shows industry stalwarts Visa and Mastercard outpacing their peers and delivering tangible AI outcomes thanks to early investments in talent and innovation.
Behind them, PayPal (3rd), American Express (4th), Stripe (5th) and Block (6th) emerge as the challengers. They outperformed the Index average, but are yet to match the leaders’ scale of deployment and outcome disclosure.
AI Moving from Experimentation to Deployment
Over the past two years, the 12 payments companies in the Index have publicly documented nearly 100 AI use cases. Underscoring how rapidly AI has moved from experimentation to deployment across core payment workflows. It’s a landscape defined by constantly evolving fraud threats and rising customer expectations for faultless, high-speed processing. Evident notes that nearly a third of these use cases disclose measurable outcomes, including efficiency gains, risk reduction and revenue uplift.
“Payments firms adopted AI out of necessity long before many other industries – their business models demanded it. Companies who invested early – like Visa and Mastercard – have gained a clear advantage over their peers, both in AI capabilities and the value their deployments are realising.” Alexandra Mousavizadeh, Co-Founder and Co-CEO of Evident.
Talent, Innovation, Leadership and Transparency
The Evident AI Index for Payments provides the most comprehensive independent benchmark of AI maturity across the industry. It is based on publicly available data around four pillars critical to successful AI deployment: Talent, Innovation, Leadership and Transparency.
According to Evident, Visa’s lead is based on consistent performance across the four pillars. And because it demonstrates the clearest evidence that AI is institutionalised across its core transaction network. Visa and Mastercard show maturity in areas such as fraud detection, cybersecurity and network-level risk reduction. Visa stands out for the scale and measurable impact of a handful of large, multi-year deployments focused on the integrity and security of its entire ecosystem.
“Mastercard shows strong evidence of scaled deployment and quantified performance improvements. Particularly in areas like fraud detection and AML tracing,” continued Mousavizadeh. “But what sets Visa apart is the degree to which the company is demonstrating impact at scale over multiple years. From applications of AI across its operations and network. It signals a shift from individual use cases to AI as institutional capability.
“What the Index also reveals is the importance of consistent innovation to maintain competitive advantage. With relatively nascent industry players like Stripe and Block performing well – and showing their AI potential reflected in their valuations – the Index leaders cannot afford to drop off the pace.”
AI Impact on Show, but ROI Reporting Scarce
Firms in the top half of the Index account for nearly 80% of use case disclosures (with the top three providing a significant 54%). Highlighting the link between AI maturity and the ability to scale deployment.
Visa performed strongly in this regard. For instance, its latest threat report disclosed advanced AI/ML blocked nearly 85% more fraud compared to one year prior. Similarly, when Mastercard incorporated Gen AI technology into its Decision Intelligence solution, initial modelling showed AI enhancements improved fraud detection rates from an average of 20% to as high as 300% in some instances.
However, Evident notes that no payments company has disclosed realised or projected ROI across all enterprise or group-wide AI activities.
“The Index leaders are locked in a tight race at a point when the thinking around corporate AI adoption is shifting – away from chasing the biggest models to building technologies that solve real operational problems efficiently,” commented Annabel Ayles, Co-Founder and Co-CEO of Evident. “Against this backdrop, the absence of ROI disclosure – or any group targets for AI ROI – is increasingly conspicuous. Currently, 1-in-5 banks now report on group-level AI returns. However, payments firms have yet to quantify the aggregate impact of their AI investments. To keep justifying this expenditure, the market will sooner or later demand clearer evidence of value.”
A Hotbed of AI Talent
The Index also reveals that the average payments company has over 30% more AI-focused workers than other financial institutions, despite substantially smaller employee numbers.
The three major card networks – Visa, Mastercard and American Express – account for nearly half (48%) of the payments industry’s AI talent stack. PayPal is currently the biggest employer, accounting for nearly a fifth (18%) of that AI talent.
PayPal’s AI talent has allowed it to build proprietary models tightly integrated with its data and workflows. Consequently, it accounts for nearly a quarter (24%) of the 98 AI use cases documented by its peers over the past two years – 1.7x as many AI applications as detailed by Visa or Mastercard.
“AI maturity is no longer defined by talent volume alone, and the Index leaders combine AI development, data engineering and product capabilities in ways that allow them to move rapidly from model experimentation to production deployment,” concluded Ayles.
The Evident AI Index Methodology
The Evident AI Payments Index ranks the AI maturity of 12 of the largest payment networks and processors across the globe. These 12 entities were chosen by aggregating the largest payment companies, with a minimum of $2B in annual revenue.
It is an independent, ‘outside-in’ assessment based exclusively on publicly available information. Each company was assessed against 60+ individual indicators, organised into four pillars critical to successful AI deployment at scale: Talent (45% weighting), Innovation (30%), Leadership (15%) and Transparency of Responsible AI activity (10%).
Data is gathered through a combination of extensive manual research and proprietary machine learning tools that extract key data points from company reporting and public disclosures (including press releases, investor relations materials, group-level website pages, group-level social media accounts, and media interviews with senior leadership), as well as a range of third-party data platforms.
Further information on the methodology of the Index can be found at evidentinsights.com
Adam Spearing, VP of AI GTM EMEA at ServiceNow, on why those that invest in AI foundations now will shape their operating models on their own terms
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Much of the debate around AI still centres on pilots: which tools to test, which use cases to prioritise, which risks to manage. Executive teams commission proofs of concept, establish governance forums and assess compliance exposure. Far less scrutiny is applied to the consequences of waiting.
Traditional technical debt is familiar territory for CIOs. It stems from shortcuts, ageing platforms and deferred upgrades. It builds over time and is eventually addressed through structured modernisation programmes. Visible in legacy code, brittle integrations and manual workarounds. It appears on risk registers and capital plans. Leaders know how to describe it and, in principle, how to resolve it.
Forward-looking technical debt is different. It arises when organisations postpone the foundational changes needed for new ways of working. It is not created by past expediency, but by present hesitation. And it accumulates faster.
AI Adoption
In the context of AI, the effects are already emerging. Each quarter spent debating readiness instead of building it increases the distance between legacy operating models and AI-enabled competitors. As models improve and user expectations shift, that distance widens, reshaping competitive baselines. What begins as a modest capability gap can harden into structural disadvantage.
While companies debate whether to adopt AI, the margin for strategic choice narrows. Many organisations frame AI adoption as a binary decision: adopt now or wait until the technology matures further. In practice, the room for discretion is smaller than it appears. Time spent stalled in pilots or governance loops increases the gap between internal capability and market expectation.
More than 75% of organisations are expected to face moderate to severe AI-related technical debt in 2026, predicts Forrester. The issue will not simply be missed efficiency gains. It will be structural misalignment between how their systems operate and how work is increasingly done.
This misalignment often appears gradually. Teams rely on manual data preparation because underlying systems cannot support automation. AI tools are layered onto fragmented architectures and deliver inconsistent outputs. Employees experiment with external tools because internal platforms cannot provide the functionality they need. Each workaround creates further fragmentation.
Over time, these patterns compound. Integration backlogs expand. Security and risk teams struggle to enforce consistent controls across proliferating tools. Data governance becomes reactive rather than designed. What began as caution begins to constrain strategic options.
The AI Paradox
Here’s the paradox: organisations are either rushing into unsuccessful AI pilots that create immediate technical debt, or they’re avoiding AI entirely and creating forward-looking debt through inaction. Both paths lead to the same place – systems that can’t support the future of work.
AI isn’t just another technology layer to bolt onto existing infrastructure. It’s fundamentally changing how people interact with systems and how work gets done. Increasingly, AI becomes an interface through which employees access information, execute tasks and navigate processes. When AI becomes the interface – not just for customers but for employees navigating their daily tasks – organisations without AI-ready foundations will find themselves unable to compete on speed, efficiency, or experience.
The companies that hesitate aren’t just missing out on automation benefits today. They’re building a deficit that grows exponentially as AI capabilities advance. Each new model release, each competitor’s successful implementation, each customer expectation shift adds to the debt. Each significant model improvement raises the performance benchmark across the market. Unlike legacy systems that degrade slowly, this gap accelerates.
From Avoidance to Advantage
Breaking free from forward-looking technical debt requires a fundamental mindset shift. This isn’t about buying more technology or launching more AI pilots. It’s about creating the conditions for sustainable AI adoption that builds capability rather than complexity.
The organisations succeeding with AI aren’t the ones with the biggest budgets or the most aggressive rollouts. They’re the ones that took a deliberate, phased approach to ensuring their data, systems, and culture could support AI at scale. They treated readiness as an operational discipline rather than an innovation side project. They understood that AI adoption isn’t a destination, it’s a continuous capability that requires solid foundations.
This starts with honest visibility into current technology estates. Leaders must understand what systems can realistically support AI workloads, where data quality creates barriers, and which processes are ready for automation. Only then can organisations introduce AI incrementally, modernising systems where necessary rather than forcing new capabilities onto brittle foundations. Without that clarity, AI risks being layered onto structural weaknesses.
Modernisation therefore becomes targeted. Consolidating fragmented workflows, standardising data models and reducing unnecessary integration points increase the feasibility of scaling AI across multiple use cases. Early deployments focused on well-defined processes with clear data lineage can build internal confidence while strengthening governance practices.
Clear Debt to Stay Competitive
Forward-looking technical debt does not appear on a balance sheet. It shows up in slower product cycles, manual workarounds, integration backlogs and frustrated employees. It surfaces when competitors deliver AI-assisted services as standard and customers begin to expect the same everywhere. By the time these symptoms are visible, the underlying gap has already widened.
Timing therefore becomes a strategic variable. AI capability builds cumulatively: early investment in clean data, modern workflows and interoperable systems creates a base for continuous improvement. Each iteration becomes easier, faster and more reliable. Those that delay face the opposite trajectory: increasing complexity, rising retrofit costs and shrinking room for strategic choice.
The real issue is not adoption in principle. It is whether leadership teams are prepared to treat readiness as urgent rather than optional.
Reducing forward-looking technical debt requires acting before competitive pressure dictates terms, aligning technology modernisation with operating model reform, and accepting that disciplined progress now is less risky than accelerated catch-up later.
AI adoption will continue irrespective of individual organisational hesitation. Vendors will continue to refine their offerings. Regulators will clarify expectations. Customers and employees will adjust their behaviours. Those that invest in foundations now will shape their operating models on their own terms. Those that delay risk reacting to a competitive gap that is already commercially significant.
Chris Gunner, vCSO at Thrive – a leading NextGen MSP/MSSP, delivering global AI, cybersecurity, cloud, compliance, and digital transformation managed services – on how CISOs can position their cyber strategy to to become part of how a business navigates uncertainty
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Quantification of cyber risk is a growing trend. While this can be genuinely useful, in practice it is often misunderstood or over-applied by security leaders. It can range from an arbitrary figure to attempting to model every possible risk on the register in a Monte Carlo simulation. The focus can fall on the mechanics of quantification, rather than how financial decision-makers actually use the information.
Think of the CFO – they don’t walk through every penny in the budget. Instead, they usually focus on the board-level levers that can materially affect the business. These often include three key areas: strategic optionality, removing friction from capital events and avoiding shocks and smoothing operating costs. Security conversations should be anchored the same way.
The Importance of Strategic Optionality
If faced with a credible one-year growth plan, CFOs may recommend a one-year office lease despite a 20% premium. This is because it maintains the option later of moving or re-contracting once the growth trajectory becomes more visible. Like most strategic decisions, it is about preserving flexibility in the face of uncertainty, even if that flexibility comes at a short-term cost.
If we apply this to a cyber context, there are often businesses that have taken a calculated gamble with their existing business strategies. While the plan is sound, there is a chance it might not land as expected. When they require security services, the choice between a ‘standard’ and ‘premium’ SOC frames the decision as one of optionality rather than security spend. Paying more now to preserve the ability to adapt later down the line. A simple illustration is incident response. An on-call retainer with defined response times can look more expensive than ad hoc support. Until an incident occurs and procurement becomes the bottleneck. In those moments, flexibility is often far more valuable than marginal savings achieved earlier.
Removing Friction from Capital Events
For CFOs, especially those operating in the alternative investment space, the focus is on structuring capital events. As opposed to managing day-to-day operational costs. One of the most painful points in that process is due diligence. The careful exchange between acquirer and target that aims to provide enough information for each to price risk, without giving the entire game away.
CISOs can materially influence how smooth or painful that process becomes. The most effective support often comes from understanding upfront what the diligence process will look like and preparing accordingly.
For example, they might develop executive-level ‘Security at ACME’ overviews to sit alongside more detailed trust centre or technical reports. Being available to diligence teams for interviews, and for example clearly articulating which services are outsourced to an MSSP, and why, builds credibility between those executive teams.
Decision-makers often don’t look at penetration test reports at a deal level. They are assessing whether the organisation understands its own control environment. A well-prepared CISO who can clearly explain why certain controls exist acts as a trust amplifier during transactions.
It is often the difference between a diligence process that closes cleanly and one that drifts. Two organisations can have similar maturity. Yet the one that can respond within a day with clear, consistent evidence reduces follow-up questions, avoids uncertainty premiums in pricing discussions and prevents security from becoming a late-stage negotiation point.
Avoiding Shocks and Smoothing Operating Costs
For any individual who has worked with a finance partner to define a departmental budget will know that predictability often takes precedence over absolute cost. Contract value can be secondary to payment terms, renewal timing or the ability to forecast spend with confidence.
CISOs can align with this by looking to reduce unplanned operating expenditure. In addition to understanding the cost structure of their controls by communicating with the technical pre-sales engineer, procurement and account teams.
A good example is cyber insurance. While often purchased directly by finance teams, many policies are relatively off-the-shelf and provide access to services the security team already operates or has under contract. Other policies include notable exclusions for the events most likely to occur. Such as a ransomware incident without business interruption cover. In many cases, these gaps can be addressed in-policy with a flat fee or a more predictable cost model.
The value here extends beyond risk transfer and into more predictable costs: replacing reactive spend with planned expenditure.
Aligning Cyber Conversations to Board Priorities
Across all of the above examples, the common thread is that the board is rarely asking security to prove its value in isolation, and is surprisingly comfortable with uncertainty. But they are asking whether the cyber papers support better decisions, fewer constraints and more predictable outcomes for the business as a whole.
CISOs who frame their priorities in those terms will find their conversations move away from justifying individual controls and towards understanding how security choices shape the organisation’s ability to respond to change. In that context, cyber becomes part of how the business navigates uncertainty, rather than a specialist function defending its budget. Speaking the board’s language, ultimately, is less about converting cyber risk into pounds and pence. It is more about understanding which levers matter at that level and showing how security choices influence them.
Adonis Celestine, Senior Director – Global Automation Practice Lead at Applause, on the rise of AI and why In a world of autonomous systems, trust is the ultimate competitive advantage
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Every generation of technology has its defining disruptor – the force that rises above the rest and reshapes its environment. In the mid-2000s, Marc Andreessen captured the moment when digital systems began transforming entire industries with his famous line: “software is eating the world”. At the time, software was the apex predator of technology, defining how value was created and delivered. Today, that hierarchy has shifted. Artificial Intelligence (AI) has reached the top of the technology food chain. Not just accelerating software, but fundamentally reimagining how it’s created, tested, and deployed.
AI is no longer just a tool; it is a co-creator. Developers now rely on AI daily to translate high-level intentions into working code. A practice sometimes known as ‘vibe coding’. Tasks that once took months can now be delivered in weeks, days, or even minutes. The pace is exhilarating, but it introduces challenges that traditional quality assurance (QA) practices were never designed to meet. And if QA cannot keep up, speed will come at the cost of reliability and trust.
When AI Outpaces QA
Conventional QA depends on predictability. Features are defined, code is written, and test cases verify the expected behaviour. However, AI disrupts this traditional model. Generative and Agentic AI systems don’t simply follow instructions; they interpret them. These systems adapt to context, learn from data, and can produce different outputs from the same prompt, influenced by factors such as training, temperature settings, and the model’s probabilistic nature. With development cycles now measured in minutes, traditional QA handoffs are often impossible.
This has led to a growing gap between speed and certainty. Teams can ship products faster than ever, yet it’s becoming much more difficult to ensure consistent, ethical, or safe behaviour in real-world conditions. Enterprises are already experiencing AI-powered features that fail in ways conventional testing could not anticipate, undermining trust and creating new risks.
Hidden Risks in Autonomous AI Workflows
AI-driven development introduces blind spots that traditional QA often struggles to detect. One key issue is context drift. This occurs when AI performs well in controlled testing environments but behaves unpredictably when faced with edge cases, cultural differences, or ambiguous inputs. For example, a customer-facing chatbot might pass functional tests but produce biased or misleading responses when deployed on a global scale.
Another challenge is compound autonomy. When multiple AI agents are involved in code generation, testing, and deployment, the system may begin to validate its own processes. Without human oversight, errors can propagate unnoticed. An AI agent might ‘approve’ certain behaviours because they statistically align with previous outputs. Rather than meeting user or business expectations.
Invisible change also complicates QA efforts. AI models continuously evolve through processes like retraining, prompt tuning, or data updates. A feature that worked flawlessly last week may function differently today. Traditional regression testing often fails to capture these subtle but significant shifts.
Most critically, AI workflows blur the lines of accountability. When failures occur, it can be unclear whether the issue lies with the model, the data, the prompt, the integration, or the deployment pipeline. QA teams must continuously validate not only the outputs but also the decision-making processes behind them.
Redefining Quality and Trust in an AI World
Slowing AI development is neither practical nor beneficial. Organisations must redefine quality in a probabilistic, AI-driven environment. Quality now extends beyond just correctness. It involves ensuring that systems operate reliably in real-world scenarios. This shift requires moving from static test cases to continuous, adaptive validation.
QA teams must evolve into ‘quality intelligence’ teams, broadening their responsibilities from simply detecting defects to actively fostering trust in AI systems. AI-assisted testing is crucial in this process. It can automatically generate extensive test cases by analysing requirements and code patterns. It can predict defects using machine learning. Detect visual inconsistencies across devices, and produce realistic, privacy-compliant synthetic test data. Additionally, Agentic AI can autonomously maintain and self-heal test scripts, adjusting their logic as underlying code or user interfaces change.
Furthermore, AI systems themselves need rigorous evaluation. Techniques such as red teaming, rainbow teaming, benchmarking, bias and ethics checks, and drift monitoring are essential to help promote AI’s reliability, fairness, and alignment with business objectives.
Human oversight is critical. While AI can scale testing and automate numerous tasks, critical thinking, risk assessment, and judgment cannot be fully delegated. Humans must guide, validate, and refine AI outputs to maintain both quality and trust.
Emerging Roles and Responsibilities
AI is reshaping professional roles. Developers are increasingly using AI by instructing machines through natural language rather than traditional programming methods. This shift has led to the emergence of new roles such as AI agent orchestrators, prompt engineers, QA specialists for autonomous systems, and governance leads who ensure ethical and auditable AI practices.
These roles are essential for maintaining human oversight. Developers and testers must experiment, validate, and continuously refine AI outputs while being cautious not to rely too heavily on AI.
Trust in the Age of the Apex Predator
As with any apex predator, AI has changed the rules of the game. Software once “ate the world” by making systems programmable. Today, AI “eats software” by making it autonomous, capable of creating, modifying, and deploying autonomously. In this new environment, speed is no longer the ultimate measure of success; trust is. Systems may move fast, but without rigorous QA, ethical oversight, and human judgment, they may not be reliable, accurate or ethical.
The new apex predator demands adaptation. Organisations navigating this AI-driven era must embrace automation and innovation, but pair it with strong quality practices, governance, and continual human oversight. Only by combining these elements can companies ensure their AI systems are not only fast and efficient but also dependable and aligned with business objectives. In a world of autonomous systems, trust is the ultimate competitive advantage.
Tom Lanaway is Head of Innovation at Connective3, a global brand & performance marketing agency. He leads a team building AI-powered marketing measurement and marketing intelligence tools.
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Most businesses are asking the wrong question about AI. They’re asking, ‘Which AI tool should we use?’ They should be asking: ‘Can our people actually think with AI?’
I run an innovation team at a marketing agency. We’ve spent the last two years building AI into everything we do, including measurement, content, strategy, and automation. We’ve got lots of tools, 18 different products to be precise.
Below is what I’ve learned. But the tools aren’t always the bottleneck; sometimes the skills are.
The Tennis Racket Problem
A colleague put it perfectly recently: “AI is a tool. Think of it as if you’ve got a smart assistant sat there. But it’s saying, I’m going to give you the best tennis racket, now go and play in a Grand Slam.”
That metaphor stuck with me because it captures something the artificial intelligence hype cycle keeps missing. We’ve convinced ourselves it democratises everything. That anyone can now do anything. That the barrier to entry has collapsed. And there’s truth in that, but it’s incomplete. The barrier to access has collapsed, but the barrier to effectiveness hasn’t. Give someone GPT-4, and they can generate text. Give them the best tennis racket, and they can hit a ball. But the gap between hitting a ball and playing at Wimbledon is still vast. Most organisations are stuck in that gap, wondering why their AI investments aren’t transforming anything.
Three Skills That Aren’t Always Present
When I look at where teams struggle and where I see the same patterns across other businesses, three specific competencies keep showing up as gaps:
1. Problem Decomposition
Not everyone knows how to break down complex work into chunks that AI can help with. This sounds simple, but it isn’t. Most people approach AI with whole tasks such as ‘Write me a marketing strategy’, ‘Analyse this data’ Or ‘Create a campaign’. AI will then produce something, but it’s usually mediocre, because the person hasn’t done the harder work of understanding which specific parts of that task AI is good at, and which parts need human judgment. The skill isn’t using AI; it’s knowing what to give it. Someone who is brilliant at their job but can’t decompose problems will get worse results from AI than someone more junior who understands how to break work into the right pieces.
2. Output Assessment
How do you know if what AI gives you is good? This is where intuition becomes essential and it’s also where the ‘AI replaces expertise’ narrative falls apart. You need domain knowledge to evaluate AI output. You need enough experience to feel when something’s off, even if you can’t immediately articulate why. You need the pattern recognition that comes from years of doing the actual work. Artificial Intelligence doesn’t replace that intuition; it requires it. The best AI users I’ve observed aren’t the most technical; they’re the ones who’ve built up enough expertise in their field to quickly assess whether AI output is useful, directionally correct, or completely off base. They know what good looks like, so they can recognise it when they see it, or notice when it’s missing.
3. Articulation
Can you clearly express what you really want? This is the unglamorous core of the whole thing. Some people struggle to articulate their requirements to other humans, let alone to AI. We’ve all sat in meetings where someone spends 20 minutes explaining what they need, and you’re still not sure what they want. AI makes that problem worse. The skill isn’t ‘prompt engineering’ in the technical sense; it’s the much older skill of clear thinking and clear communication. If you can’t articulate what you want specifically, precisely, with the right context and constraints, you won’t get useful output from AI or from anyone else.
The Uncomfortable Implication
Here’s what this means for how businesses should think about AI investment:
Stop leading with tools: Most organisations have tool fatigue already. Another platform, another integration, another training session on which buttons to click. It’s not working.
Start with the human work: Before asking ‘What AI should we use?’, ask ‘Can our people break down problems, assess output, and articulate requirements?’ If they can’t do those things well without AI, they won’t do them well with AI either.
Invest in the skills, not just the access: This doesn’t mean AI prompt engineering courses; it means developing clearer thinking, better problem decomposition, and sharper articulation. These are old skills, applied to new tools.
Accept that expertise still matters: The people who’ll use AI best are the ones who already know their domain deeply. AI amplifies competence; it doesn’t create it.
Connected Intelligence Isn’t About Connected Systems
I’ve spent a lot of time thinking about how different marketing channels and data sources connect and how you build intelligence across systems rather than in silos.
But I’ve come to think the more important connection isn’t between systems, it’s between human judgment and AI capability. The integration layer that matters most is the one between the person and the tool.
Get that wrong, and it doesn’t matter how sophisticated your AI stack is. Get it right, and even basic tools become powerful.
Hampshire Trust Bank (HTB) is using artificial intelligence (AI) to act faster on customer concerns. It is empowering its teams…
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Hampshire Trust Bank (HTB) is using artificial intelligence (AI) to act faster on customer concerns. It is empowering its teams to identify and respond quickly, whilst also meeting regulatory timeframes for handling complaints and supporting vulnerable customers.
Netcall: AI-Powered Sentiment
The specialist bank has worked with Netcall to deploy AI-powered sentiment analysis using Netcall’s Liberty Create platform. The solution reduces manual effort and improves operational efficiency by bringing customer emails from multiple mailboxes into a single interface. Incoming messages are automatically analysed to identify dissatisfaction, highlighting cases that may require faster intervention. This allows urgent cases to be prioritised, helping HTB to resolve issues before they escalate and improve the customer experience.
“Our AI-powered sentiment analysis solution rapidly processes vast amounts of email data. Its efficiency allows our team to focus on resolving customer enquiries and issues rather than sorting priorities. The streamlined process ensures swifter responses and better customer outcomes, upholding our reputation for exceptional customer service.” Ed Eames, Head of Customer Savings Operations at Hampshire Trust Bank.
The application was built by the Hampshire Trust Bank development team using Liberty Create. It worked closely with Netcall to integrate AI sentiment analysis into existing processes. Customer-facing teams were involved throughout to ensure the solution aligned with established workflows and regulatory requirements.
Customer Service Control
A key benefit of the approach is the level of control it gives internal teams. Keywords, sentiment thresholds, and classifications can be adjusted directly. This allows rapid refinement as customer behaviour changes or new regulatory considerations emerge, without waiting for development cycles.
“Liberty Create has enabled my development team to work with remarkable agility. The ability to rapidly create and refine applications to meet ever-evolving business needs has significantly enhanced our efficiency. This allows us to deliver a wealth of new features to end users and customers with speed. With the integration of AI, we’ve been able to advance our processes while ensuring exceptional customer service. Our Sentiment Analysis application launch is a prime example of this.” Trina Burnett, Head of Engineering at Hampshire Trust Bank.
The sentiment analysis system also supports automated and ad-hoc reporting. This provides a single source of insight into customer interactions and actions taken. This helps reduce manual effort, supports audit and compliance activity, and enables teams to continuously improve customer service operations.
“As scrutiny around customer experience and accountability increases across UK financial services, the ability to listen, adapt and respond at pace is becoming a defining capability for banks seeking to maintain trust and service standards,” said Alex Ballingall, Key Account Manager at Netcall.
“HTB’s approach shows how banks can use AI-driven insight practically. Turning customer communications into faster action without adding operational complexity,” Ballingall concluded.
About Netcall
Netcall is a leading provider of low-code and customer engagement solutions. A UK company quoted on the AIM market of the London Stock Exchange. By enabling customer-facing and IT talent to collaborate, Netcall takes the pain out of big change projects. It helps businesses dramatically improve the customer experience, while lowering costs. Over 600 organisations in financial services, insurance, local government and healthcare use the Netcall Liberty platform to make life easier for the people they serve. Netcall aims to help organisations radically improve customer experience through collaborative CX.
Patrick Cooney, CFO at Version 1, on why, in an AI-driven operating environment, financial discipline is more important than ever
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Over the last decade, digital transformation has become part of the CFO’s remit. As organisations invested in automation, cloud and data platforms, finance leaders were well placed to oversee spend, drive efficiency and ensure technology investments delivered measurable returns. As artificial intelligence (AI) moves from experimentation into the core of how organisations operate, that model is beginning to evolve. Primarily because AI-scale transformation demands a different balance of expertise.
A recent move by Coca-Cola illustrates this shift. The decision to take digital strategy out of CFO John Murphy’s remit and appoint Sedef Salingan Sahin as the company’s first Chief Digital Officer is not a rejection of finance-led transformation. It reflects a practical reality. While strong financial discipline remains essential, the architectural complexity and technical depth required to embed AI across an enterprise now go beyond traditional finance capabilities alone.
In all industries, AI is no longer confined to innovation labs or isolated pilots. It is increasingly embedded in how organisations operate, make decisions and manage risk. At Version 1, our earliest focus on AI was external: helping partners use AI to transform their own businesses. We have quickly turned the lens inward. Over the past quarter, we have accelerated the use of AI across our own finance and operational functions, implementing a wide range of practical use cases that fundamentally change how work gets done.
Some of these are relatively simple but have had a significant impact. Using AI to summarise documents, generate meeting notes or surface insights from large volumes of information has become normal and is already saving time across the organisation. Others are more structural. In finance, we are applying AI to areas such as accounts payable, accounts receivable and general ledger reconciliations, where large datasets and repetitive processes create natural opportunities for automation and acceleration.
We are also rethinking reporting itself. Rather than manually producing variance analyses each month, we are developing standardised prompts that allow AI to highlight key trends, explain deviations from budget and surface insights that would traditionally take hours to compile. These are not abstract efficiencies. Rather, they directly affect the speed, quality and value of financial decision-making.
What is striking though is the pace of change. Even over the past few months, usage has increased exponentially as people find new ways to integrate AI into their daily work. This is no longer an optional experiment. AI is reshaping how organisations function from the inside out.
Modern CFOs Deliver Stewardship and Governance
One of the biggest challenges CFOs face with AI is that traditional ROI models struggle to capture its true impact. Unlike earlier waves of digital transformation, AI does not deliver value solely through cost reduction or headcount optimisation. Increasingly, its value lies in better planning, faster decision-making, improved risk management and higher-quality outputs.
I see this clearly in how we use AI for planning. Recently, we fed a combination of internal data, previous plans and external consultancy material into a large language model and spent time crafting a detailed prompt. The output was a first-pass design for a major simplification programme (including workstreams, resourcing requirements and sequencing) that would previously have taken weeks to develop.
It is worth noting that this new process didn’t replace human judgement – it dramatically accelerated it. We are using similar approaches to shape annual finance priorities, drawing on historic plans and organisational context to generate structured, actionable starting points. This kind of value is real, but it does not always show up neatly in short-term financial metrics.
At the same time, the risks associated with AI are increasing. Model drift, regulatory scrutiny, data security and vendor dependency all carry financial implications. This is why governance matters as much as innovation. At Version 1, we have put formal structures in place, including an AI oversight committee that reviews and approves new tools, ensures appropriate controls are in place and sets clear boundaries around responsible use. We tightly manage which platforms can be used and how data is protected, recognising that public, uncontrolled tools pose unacceptable risks in an enterprise environment.
This combination of accelerating value and growing risk is precisely why ownership models are changing. Many CFOs continue to play a leading role in digital transformation, with research showing that around three-quarters of finance leaders now prioritise digital strategies at the highest levels of the organisation.
People Remain at the Heart of AI Adoption
As AI scales, the CFO’s role is shifting from delivery ownership to strategic stewardship. Finance leaders are uniquely positioned to connect technology ambition with financial reality, ensuring AI investments are governed properly, aligned to business outcomes and measured over time.
This aligns closely with how we think about our own operating model at Version 1. We use what we call a ‘strength in balance’ business model, built around three equally important pillars: customers, people and a strong organisation. That final pillar includes financial performance, risk management, cybersecurity and governance, all areas that become more critical, not less, as AI adoption accelerates.
People are central to this conversation. AI inevitably raises questions about job impact and cost optimisation, and organisations have a responsibility to approach this responsibly. That means clear communication, strong change management and treating people fairly where roles evolve. It also means investing in training and enablement. We have rolled out organisation-wide AI training focused on responsible use, and we are developing a network of AI champions with deeper skills who can identify and build use cases without relying solely on central teams.
The most effective model I see emerging is a shared one. Specialist digital leaders focus on building and embedding AI capabilities at scale. CFOs retain accountability for financial discipline, data governance and value realisation. When these roles work in partnership, organisations are far more likely to capture the value they expect from AI.
Financially Guided Value Delivery
As AI becomes a baseline capability rather than a differentiator, debates about who ‘owns’ digital strategy are becoming less relevant. The more important question is how organisations ensure AI investments deliver measurable, sustainable value. For CFOs, AI is now undeniably a balance sheet issue.
Investment in the latest technology affects cost structures, risk exposure, governance and long-term resilience. Those who engage proactively, shape governance and demand disciplined value creation will help their organisations unlock lasting advantage. Those who remain passive risk inheriting complexity, cost and compliance challenges that are far harder to unwind later.
In an AI-driven operating environment, financial discipline is not diminished. It is more important than ever.
In the world of MedTech, innovation does not happen in isolation. It relies on deeply interconnected digital ecosystems that span research and development, manufacturing, clinical environments and global corporate operations. For Olympus, a global medical technology company with 30,000 employees operating across multiple regions and regulatory environments, cybersecurity has become a foundational enabler of trust, resilience and patient safety.
At the centre of this transformation is Ryan Larsen, Global Head of IT Security at Olympus, whose role sits at the intersection of technology, leadership and mission-driven purpose. His mandate is clear: ensure that Olympus’ global digital and operational environments remain secure, reliable, and able to support innovation at scale.
“In practical terms, I’m responsible for the cyber defence and digital resilience of Olympus as a global MedTech company,” Ryan explains. “That means ensuring our systems, data and people are protected so innovation can move quickly, safely and with trust across R&D, manufacturing and corporate operations worldwide.”
Virginia Farm Bureau: An Enterprise CIO’s Journey
Virginia Farm Bureau is an organisation renowned for resiliency, collaboration, commitment to a greater cause, diversity and service to its members. For outgoing CIO Patrick (Pat) Caine leadership at Virginia Farm Bureau has never been about technology for technology’s sake. After 18 years as CIO, his role evolved into what he describes as that of an “enterprise technology leader,” responsible for supporting a uniquely complex organisation whose mission stretches far beyond insurance or IT.
“I’m responsible for all aspects of enterprise IT,” he explains. “Founded in 1926, Virginia Farm Bureau is a diverse membership organisation with four major business entities and multiple companies that provide agricultural advocacy and related agricultural business support services, healthcare insurance sales and administration, P&C Insurance, and a large entertainment property that hosts the State Fair of Virginia.”
Gowling WLG: Implementing Human Centred AI
When we talk about AI finding its feet within a business, the obvious challenge is change management. How do you ensure your team is on board with the change? What if they have technical questions? How does a business address their fears and concerns? This is where having a people-focused leader and a technology-focused leader forming a united front is incredibly valuable.
Kelly Davis is the Chief People Officer at international law firm Gowling WLG. Al Hounsell is the Senior Director, AI Innovation & Knowledge. Davis has been in HR leadership roles for most of her career. During that time, she has been very intentional about the way she has moved between industries.
Hounsell started his career as an entrepreneur. He then went to business school and law school, before ending up in a large global firm. There, he fell in love with the nascent legal technology ecosystem. He joined Gowling WLG over a year ago. His goal is to reimagine the practice of law by infusing it with technology.
New research from Appian shows strong optimism among public sector workers about artificial intelligence (AI) transforming public services. However, awareness among the public remains limited,…
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New research from Appian shows strong optimism among public sector workers about artificial intelligence (AI) transforming public services. However, awareness among the public remains limited, with 75% of surveyed UK adults aged 18+ (representing approximately 41 million people*) unable to name a single way in which the public sector currently uses AI.
The 2026 UK Public Sector AI Adoption Outlook report surveyed 1,000 public sector workers and 1,000 UK citizens. It reveals a clear divide between those tasked with delivering AI-enabled services and those who use them. While two thirds (67%) of public servants believe it will improve public services over the next five years – rising to 87% among director-level leaders – only 44% of citizens share this optimism. Afigure closely mirrored by workers in administrative roles (40%).
This disconnect could be explained by the way AI is currently being deployed inside government. Nearly half (45%) of initiatives operate as bolt-on experiments or standalone tools rather than being embedded into core service workflows. Many applications remain invisible to citizens – limiting public awareness of where and how artificial intelligence is already in use.
“Too much AI in the public sector is still being used as a personal productivity tool rather than embedded into the processes that actually run services. When AI is treated as a bolt-on experiment or standalone tool, it struggles to deliver meaningful impact – our research shows nearly half of government’s application of AI falls into that trap. If organisations want AI to move beyond pilots and produce real value, it has to be integrated into core processes from the start.”
Peter Corpe, Industry Lead UK Public Sector at Appian
Public Trust in AI Remains Limited
Public trust in responsible AI use remains low across much of government. Fewer than half of UK citizens trust central government (39%) or local government (44%) to use it responsibly – placing government behind retailers (60%), banks (55%) and consumer technology companies (54%). The clear exception is the NHS, which commands a 63% net trust rating, making it the most trusted organisation for AI use across both public and private sectors.
Regarding AI making decisions without human oversight, 67% of public sector workers are comfortable with the technology selecting cases for tax or benefits compliance checks compared with 40% of citizens, while 56% of public sector workers support its use in analysing NHS scans versus 40% of citizens. Concerns about AI also extend beyond individual decisions, with the majority of the public worried about implications around data security and privacy (67%), job losses (63%), auditability of decisions (61%) and ethical oversight and bias (59%).
Fixing Processes Should Come Before Delivering AI at Scale
Inside government, enthusiasm for AI is tempered by concerns about execution. Less than a third (29%) of public sector workers say their organisation or department is delivering on most of its commitments. A similar proportion say they are moving slower than planned (27%), while a quarter (25%) identify a significant gap between AI strategy and delivery.
One year on from the AI Opportunities Action Plan, where the Government allocated £2bn to implement research and resources, the new research findings point to a growing disconnect between strategic ambition and service delivery reality. Nearly 9 in 10 public sector workers (89%) say their organisation is not fully able to leverage AI.
This delivery challenge is widely recognised by both public sector workers and citizens. A majority of public sector workers (55%) and citizens (56%) agree that existing processes must be fixed before new technologies are introduced, prioritising process improvement over deploying new AI tools.
“AI is only as good as the work you give it,” said Corpe. “This research shows strong belief in AI’s potential, but also a clear warning: without fixing the underlying processes first, it will struggle to deliver on its promise. Serious AI is not about experimentation or standalone tools – it’s about applying intelligence to the core processes that keep public services running.”
Different Priorities, Same End Goal
While both citizens and public sector workers agree that existing processes must be fixed as a priority, the research reveals contrasting expectations of what AI should deliver. Citizens want AI investment to deliver faster services (35%), improved public safety and fraud prevention (27%) and easier-to-use digital services (26%).
By contrast, public sector workers are more focused on efficiency gains (47%) and cost savings (41%), highlighting that citizens focus on outcomes they directly experience and public sector workers focus on how those outcomes are delivered.
The 2026 UK Public Sector AI Adoption Outlook was commissioned by Appian and conducted independently by Censuswide. The study surveyed 1,000 UK public sector workers, including 250 director-level respondents or above, and 1,000 UK citizens aged 18+.
Dr. George Papamargaritis & Dr. Konstantia Barmpatsalou
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Obrela’s Dr. George Papamargaritis (EVP MSS) and Dr. Konstantia Barmpatsalou, (Blue Team Support Manager) on why embracing a risk-led cybersecurity model will leave financial organisations better positioned not just to meet regulatory requirements but to strengthen resilience, protect customers and uphold the trust that is so essential to the future of financial systems
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Cybersecurity in the financial sector was once viewed as a compliance-driven discipline. But as attackers have increasingly targeted institutions with sophisticated, persistent and often internally driven campaigns, it has become a strategic priority.
According to the Digital Universe Report H1 2025, financial services were the second most targeted industry globally, accounting for 19% of all observed cyberattacks. This reflects both the sector’s value to adversaries and the complexity of the digital ecosystems it now operates within.
Regulatory frameworks such as the FCA and PRA’s operational resilience rules, the EU’s Digital Operational Resilience Act (DORA) and NIS2 have strengthened baseline protections. However, the report’s findings demonstrate that regulation alone cannot deliver true cyber resilience. Institutions must adopt a strategic, risk-led approach that looks beyond compliance to understand real threats, behaviours and operational dependencies.
Tailored, Internal and Stealthier Threats
One of the most striking insights from the report is how targeted financial sector attacks have become. Industry-specific security risks now represent 32% of all incidents in the sector. This is an indication that adversaries are designing attacks using detailed knowledge of financial operations, from trading workflows to payment systems.
Internal activity is also a major concern. Suspicious internal activity accounts for 26% of detections across financial services, reflecting the frequency of compromised accounts, misused privileges and lateral movement. For a sector historically focused on defending the perimeter, this shift highlights the need for deeper visibility into user behaviour and identity-driven risks.
The wider threat landscape reveals adversaries are moving away from overt, signature-based attacks. In H1 2025, brute force activity made up 27% of global alerts, while vulnerability scanning accounted for 22% and known malicious indicators for 20%. Notably, direct malware payloads dropped to 0% of trending alerts, replaced by fileless techniques and living-off-the-land methods that bypass traditional defences.
For financial institutions, this is a challenge. Many compliance requirements still centre on endpoint protection, patching and malware controls. These will of course, remain important, but they cannot address threats that are increasingly behavioural, stealth-driven and identity-focused.
Operational Complexity
The financial sector’s cyber risk is intensified by its expanding operational footprint. Cloud adoption, open banking, digital identity models and extensive third-party ecosystems have all created new points of exposure. Financial services operate within a global digital infrastructure that is both vast and increasingly interconnected. This level of complexity cannot be effectively protected through compliance checklists alone.
Regulators are recognising these realities. DORA’s emphasis on ICT third-party risk, operational resilience testing and continuous oversight reflects the need for more proactive, intelligence-driven approaches. But DORA still only sets a minimum standard. True resilience requires institutions to move beyond regulatory expectations and embed cybersecurity into broader business strategy.
Strategic, Risk-Led Cybersecurity
A risk-led approach begins with understanding the threats that pose the greatest risk to operations and customers. Financial institutions remain priority targets for groups such as FIN7, TA505, Cobalt Group and various state-backed actors. Their tactics, such as credential harvesting, remote access tools, web-injection frameworks and lateral movement, are specifically designed to exploit the digital fabric of financial services.
This evolving threat profile puts identity and behaviour at the heart of cyber defence. With credential-driven and internal threats so prevalent, institutions must prioritise behavioural analytics, continuous authentication and zero-trust models that verify users and devices contextually rather than relying on static controls.
Strategic cyber resilience also needs to have continuous assurance. Traditional audits, annual testing and scheduled penetration exercises cannot keep pace with rapidly evolving threats. Leading institutions are shifting toward continuous control monitoring, automated attack simulation and persistent adversarial testing. These practices align with the Bank of England’s CBEST framework and demonstrate a sector-wide move toward ongoing, intelligence-led assurance.
Crucially, cyber risk must be treated as an operational issue, not just a technical one. Embedding cybersecurity into enterprise risk management, financial planning, product development and board oversight is essential. This integrated approach also mirrors the direction of FCA and PRA regulation, which increasingly emphasises governance, accountability, and resilience across the entire organisation.
Beyond Compliance
Financial services underpin national economies and public confidence. As digital ecosystems grow and adversaries become more sophisticated, the sector faces a dual challenge: meeting rising regulatory expectations while defending against complex, targeted attacks. It is clear that cybersecurity must evolve from compliance-driven activity to a strategic capability built on intelligence, continuous assurance and behavioural insight.
Institutions that embrace this risk-led model will be better positioned not just to meet regulatory requirements but to strengthen resilience, protect customers and uphold the trust that is so essential to the future of financial systems.
Children’s Mental Health Week 2026 spotlights the theme ‘This is My Place’. Tech charity founder James Tweed is calling on…
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Children’s Mental Health Week 2026 spotlights the theme ‘This is My Place’. Tech charity founder James Tweed is calling on the UK’s IT departments to donate surplus laptops and devices to help some of the country’s most overlooked vulnerable children.
Rebooted
Tweed founded Rebooted to support the children of prisoners and provides laptops so they can learn at home.
“Having a parent in prison can be traumatic and often leads to a child struggling at school,” says Tweed. “If that child then falls behind digitally or is excluded from education, their long-term prospects narrow dramatically. It’s a vicious circle and we need to break it early.
“For many of these children, school is already unstable. If they also lack access to reliable technology at home, they’re starting from behind. In 2026, digital access isn’t a luxury, it’s foundational.”
A Practical Solution
With businesses refreshing hardware on regular cycles, Tweed believes IT leaders are sitting on a practical solution.
“Across the UK, thousands of perfectly usable laptops are sitting in storage cupboards or heading for recycling. Those devices could transform a child’s ability to learn, revise and stay connected to school.”
Crucially for IT heads, data security is central to the model. All donated devices are securely wiped and processed by Rebooted’s technology partner, GeTech, using certified data erasure procedures.
“Security is non-negotiable,” assures Tweed. “Every device is professionally wiped to recognised standards before it’s redeployed. IT teams can donate with complete confidence.”
Children’s Mental Health Week
Children’s Mental Health Week, launched in 2015, focuses this year on belonging and ensuring young people feel they have a place in their communities. Tweed argues that digital access plays a direct role in that sense of inclusion.
“We talk a lot about wellbeing and belonging,” he says. “But if a child can’t access homework platforms, revision tools or basic digital resources, they quickly feel excluded. Technology can either widen the gap — or help close it.”
Rebooted is now urging CIOs, IT directors and managed service providers to review surplus stock and consider structured donation programmes as part of their ESG and sustainability strategies.
“This is practical, measurable impact,” Tweed adds. “Instead of gathering dust, those devices can help ensure a vulnerable child can genuinely say, ‘This is my place.’”
IT leaders interested in donating surplus equipment can find more information at:rebooted.me
Gregory Mostyn, CEO and co-founder of Wexler, on why the era of generalist AI tools is over, and how the future will focus on high-precision AI designed for specific industries
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For decades, the UK’s professional services sector, including areas such as Law, Insurance, and Wealth Management, has argued that its business value is locked in its access to proprietary data and the specialised labour required to navigate it. Investors, lured by the moat of institutional knowledge, priced these companies accordingly. However, the first quarter of 2026 has seen significant AI disruption within the professional services market. The catalyst wasn’t a single event, but rather a move by foundational model providers that turned the industry’s most defensible assets into commodities.
When Anthropic launched its specialised legal AI plugin, OpenAI integrated a real-time insurance underwriting engine directly into its interface, and Alturist Corp automated bespoke tax strategies, the market reacted harshly. As professional services titans such as RELX, MoneySuperMarket, and St James’s Place saw their share prices decline by more than 10% in a matter of hours, the message became clear: the era of treating AI as a ‘future risk’ is over.
The market has been awoken to the fact that foundational AI models are no longer just plugins or nice ‘add-on’ tools; they are competitors. The move by foundation-model providers into professional services – like the legal sector – is not a one-off shock, but rather an inevitability.
The Proliferation of Information
Historically, a law firm’s competitive advantage was its access to information – repositories of case law, proprietary research, and historical contracts. Investors and clients valued these companies on the assumption that this data constituted an impenetrable barrier to competitors. Before AI entered the mainstream, the cost of extracting actionable information from thousands of pages of data required a small army of junior associates and hundreds of billable hours.
In 2026, that moat has mostly evaporated. Recent benchmarks show that frontier models now achieve 80% accuracy on complex documents, compared with the 71% average of a human associate. More importantly, they do it at a fraction of the cost. It is now estimated that the inference cost for a system at the level of GPT-3.5 dropped by more than 280-fold between November 2022 and October 2024. It’s predicted that UK law firms will reduce their chargeable hours by 16% through the implementation of AI.
The narrative that AI would be able to handle only ‘low-level’ tasks, such as NDAs or simple contract summaries, has all but evaporated. Anthropic’s move into high-stakes litigation support validates this trend.
AI – From Swiss Army Knives to Scalpels
An error made by many law firms when AI became entrenched within the market was to treat it as a ‘plug-in’, a nice-to-have built onto existing internal software. Many adopted general-purpose tools, often referred to as ‘Swiss Army knife’ solutions, that covered the breadth of legal work but lacked the precision, jurisdictional nuance, and risk-weighted requirements for high-stakes professional services.
The 2026 market reaction highlighted the needs of a ‘scalpel’ approach – those that go deep in a specialised vertical within a legal workflow. For example, instead of a junior associate spending billable hours searching through case files to establish the facts of a case, they could use a ‘fact intelligence’ platform that can automate that process into minutes, whilst increasing accuracy by 95% versus 78% for human reviewers and up to 90% savings in large-scale litigation. The market is no longer rewarding firms for having information. Rather, it rewards those who can apply it at the lowest possible cost and friction.
Reallocating Capital Across Professional Services
We’re already seeing investors withdrawing from the traditional software market and reallocating that capital into specialised AI firms. However, the risk for legacy players is that they are being disrupted from both ends. From the bottom, they are losing the efficiency game to generalist foundation models from companies such as OpenAI and Google, which are commoditising the ‘knowledge’ aspect of professional services, including basic advice and contract drafting. At the top, they are losing the expertise game to specialised firms that use AI as a precision instrument; their overhead would be lower than that of a traditional Magic Circle firm, allowing them to undercut prices while maintaining profit margins.
The result is a massive reallocation of capital. Investments into vertical AI (AI built for one specific industry) are expected to surge to $115 billion by 2034. The market no longer bets on labour with tools, but on autonomous workflows. Investors have realised that the value lies in the middle layer – the software that sits between a general foundation model and a specific industry’s needs.
Innovation or Obsolescence
So far, the first market fluctuation of 2026 has taught us that you cannot outrun new technologies. To survive, firms must stop treating AI as an add-on and treat it as a foundation for their core business infrastructure.
For UK professional services, the choice is no longer whether to adopt AI, but whether they can evolve quickly enough to avoid becoming the training data for companies building foundational models. The firms that remain in 2030 will recognise that the competitive landscape has changed. You’re not just competing with your peers, but with the compute cycles of the world’s most powerful AI labs.
The era of generalist AI tools is over, and the future will focus on high-precision AI designed for specific industries.
Jack Bingham, Regional Director of Digital Native UK, Ireland & South Africa, Confluent on how data, treated properly, compounds in value to drive digital disruption
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When I talk to founders and tech leaders, one question seems to consistently come up: what separates today’s disruptors from the last decade’s? In 2010, being cloud-first was what made investors sit up and take note. In 2026, it will be streaming-first.
I’ve spent the last year or so working closely with companies that are, quite literally, building their businesses in real time. For them, real-time capability isn’t a department or a layer that supports the business. It is the business. The acid test is simple: how quickly can you capture a critical event – a payment, a login, a failed delivery – and respond with the next best action? That focus shapes how they build products, structure teams, and think about innovation.
Here’s what I’ve learned from them:
Lesson 1: Data is a Product, Not a By-Product
Many traditional companies still treat data as something to collect, store, and analyse later. The new generation of businesses, on the other hand, treats it as a reusable, governed product that everyone can access. When it’s built and shared this way, teams stop rebuilding the same foundations for every new use case. They move faster because they’re working from a single, trusted view of the truth, shortening product cycles, speeding up iteration, and spending more time solving problems that matter.
That mindset, rather than the size of the tech stack or the number of engineers, is what sets disruptive businesses apart. In these organisations, technology, data, and business strategy move in lockstep. Decisions aren’t passed up and down hierarchies, they’re made by teams who understand both the data and the customer problem in front of them.
When you can trust your data and respond in real time, innovation stops being a department. It becomes a reflex.
Lesson 2: Real-Time isn’t a Feature, it’s a Foundation
A few years ago, one of the world’s largest supermarket chains realised it didn’t have a single real-time view of its inventory. Without that visibility, omnichannel experiences were impossible. Once it shifted to a streaming architecture, every transaction became a live event that updated stock, triggered supply chains, and even made it possible to get your groceries delivered straight to your kitchen fridge – coordinated through live inventory data, smart home devices, and real-time security feeds.
That’s the practical power of streaming: it connects what happens in your business to what should happen next so you can provide products and services that take customer satisfaction to a whole other level. Real-time data stops being a reporting tool and becomes the foundation of every decision, interaction, and innovation.
I often ask businesses what they would do differently, if they knew the state of every event in their organisation. The most forward-thinking companies already have the answer. They’re using streaming to turn business events into reusable building blocks, creating new experiences by connecting the data they already have in smarter ways.
Lesson 3: Culture is the Multiplier
Being streaming-first is only half about architecture. The other half is attitude. The best digital enterprises don’t wait for permission to experiment. They map their most important business events, align teams around them, and empower people at every level to react fast and learn faster.
And the difference is visible. Feedback loops are shorter. Structures are flatter. Failure is treated as information. This culture of continuous experimentation is why these companies can move at the pace they do.
We often run ‘Event Storming’ workshops with teams to map their critical business events. The idea is to create alignment – getting people from engineering, product, and operations to agree on what really matters and how those moments connect. That process reveals a lot.
Digital disruptors go beyond simply deploying streaming architectures. They build streaming mindsets. Leadership plays a crucial role here: data must be treated as a strategic asset. If it isn’t up top, it won’t be anywhere else in the organisation either.
Lesson 4: Streaming and AI will Converge
AI is only as good as the data you feed it. Unfortunately, most enterprises are still feeding it yesterday’s data. Streaming-first companies already know this. They’re building intelligent data pipelines that give AI the context it needs to make decisions in real time.
That’s how the next generation of innovators will pull ahead: not by having bigger models, but by having cleaner, faster, more connected data. Streaming is what will let AI move from reactive to predictive… and from predictive to autonomous.
Too many organisations are cutting investment in data while pouring money into AI projects. But AI without quality data is just expensive guesswork. The companies doing this well understand that data has to be a product in its own right. And when business and technology teams design around that shared understanding, innovation follows naturally.
Lesson 5: The Mindset of the Next Disruptors
If I were starting a company tomorrow, I’d look closely at the critical events that run my business. I’d then make sure I had a way to capture those in the stream, make them reusable, and build every product and process around them.
When your business can see and act on what’s happening in the moment, you gain something no traditional architecture can give you: time. And in the next wave of disruption, that’s the only advantage that really matters.
If we look to who we can learn from in the coming months, it’s financial services and healthcare that are moving the fastest. Real-time fraud detection, patient monitoring, and risk management are becoming operational necessities – and these industries will set the benchmark for real-time data excellence.
Looking Ahead to 2026
By 2026, I don’t think we’ll talk about ‘real-time’ as a differentiator. It will simply be how modern businesses operate. Batch systems won’t disappear, but they’ll coexist within a single, streaming-first platform that delivers data whenever it’s needed.
Once every process can react instantly, the question then becomes: can it anticipate? Can it learn? That’s where AI and streaming meet and where we move from reactive to autonomous enterprises that not only respond to the present but adapt to what’s coming next.
Data, treated properly, compounds in value. The decisions you make with it become faster, sharper, and more confident. The companies that understand this will be the ones still leading when today’s titans look like yesterday’s news.
Jonny Combe, President and Chief Executive Officer, PayByPhone on how urban mobility is evolving from car-centric to multimodal and the opportunity the parking industry has to play a central role by integrating payment infrastructures that support a more connected, flexible mobility ecosystem
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The journey has changed. Over the past few years, the mobility industry has undergone seismic shifts toward more digital experiences. Cash payments continue to disappear and in the US made up only about 14% of all payments in 2024. Over half of the US adult population make use of mobile wallets and many companies provide payment opportunities via apps for their services. While this has made some processes more efficient and streamlined, it has also resulted in very fragmented data streams.
Consider this scenario: a commuter drives an Electric Vehicle (EV) to a rural or suburban transit hub where they park and charge, then boards a train into the city. The final mile is completed on an e-scooter, shared bike or another mode of public transport to reach their destination. One journey, four separate payment interactions across four different apps.
This is the daily reality for millions of commuters, and it exposes a fundamental challenge that not only the parking industry, but also the mobility industry as a whole must confront. Continuing to build payment infrastructure for journeys that end at the curb, is no longer enough; we should be facilitating one system for these evolved modern journeys.
City Centres Reimagined
A substantial amount of land in city centers has traditionally been dedicated to parking, but there is a growing trend where we see city centers worldwide redesigning their urban space. On-street parking is giving way to pedestrian zones and cycle lanes. Traditional car parks are transforming into multimodal hubs that are integrating EV charging, micro-mobility stations, and last-mile logistics. Technologies like automatic number plate recognition are helping to eliminate friction at entry and exit points. However, backend complexity of the redesign of urban mobility has grown exponentially.
Local authorities now juggle relationships with cashless payment providers, meter operators, EV charging networks, micro-mobility vendors, and logistics partners. Each bring their own payment rails, reconciliation requirements, and data formats. For many municipalities, simply reconciling payments between a meter provider and a digital parking platform already strains finance teams. Adding multiple mobility partners brings a significant extra load to existing operational capacity and the operational burden is only part of the equation.
The Hidden Cost of Fragmentation
The more critical issue is strategic: fragmented payment systems can create fragmented data, and fragmented data can undermine intelligent policy.
When payment information sits in siloed systems across multiple vendors, authorities lack the consolidated view needed to answer essential questions:
How does parking behavior correlate with public transit usage?
What pricing strategies would optimize utilization across the entire mobility network?
Where should we invest in EV infrastructure based on actual demand patterns?
How do we measure progress toward carbon reduction targets?
Without integrated payment and usage data, cities are making significant capital infrastructure decisions with an incomplete picture.
The Payment Layer as Strategic Infrastructure
Forward-thinking cities are, however, beginning to recognize payment infrastructure not as back-office plumbing, but as strategic architecture for the mobility ecosystem.
The solution lies in centralized payment platforms that serve as a unifying layer – ‘super apps’ as they are called in other industries. The backend of these apps should be able to consolidate transactions across multiple mobility services, automate complex multi-party reconciliations, and create unified data lakes that enable AI-driven insights.
This approach can deliver immediate operational relief: finance teams spend less time manually reconciling disparate systems, and the strategic value compounds over time. With consolidated data, authorities can model the true economics of mobility transitions, identify underutilized assets, dynamically price services to manage demand, and measure environmental impact with precision.
Building for What Comes Next
The parking industry has always been about managing physical space, yet the future is about orchestrating mobility experiences. The question for industry leaders isn’t whether parking will integrate with broader mobility systems but whether parking operators will architect that integration intentionally.
Doing so requires a fundamental rethink of the role parking payment providers play in the payment value chain, while investing and building the technology and the payment infrastructure that makes seamless, sustainable urban mobility possible.
The infrastructure we build today will determine whether cities can deliver on their mobility and sustainability commitments tomorrow. For parking industry leaders, this is both a challenge and an opportunity: to evolve from transaction processors into the essential connective layer of urban mobility. Those with the vision, and the technological ability to rise to that challenge, have a real opportunity to lead the next generation of multimodal mobility payments.
About PayByPhone
PayByPhone is a global leader in mobile parking payments. We simplify journeys for millions of UK drivers with smart, intuitive technology and user-focused features. In addition to fast, secure parking payments, drivers can also locate nearby fuel stations and EV chargers – and pay for EV charging – all in the PayByPhone app. We work with over 1,300 cities and operators across the UK, North America, France, Germany, and Switzerland. More than 110 million drivers worldwide have downloaded the PayByPhone app to simplify their parking and vehicle payments to date. To discover how our products and services can elevate your driving experience.
Adrian Wood, Strategic Business Development & Offer Marketing Director at DELMIA
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The era of trial-and-error manufacturing is over. By integrating NVIDIA’s Physical AI into DELMIA’s Virtual Twin technology, Dassault Systèmes is moving the industry from static automation to autonomous software-defined systems that “learn” the laws of physics before the first part is made.
Revolutionising Manufacturing with Agile AI-Driven Production
Manufacturing is reaching a breaking point. Rigid production and logistics systems slow setup, ramp-up and scaling. Meanwhile deterministic automation struggles with real-world change, from new variants to unplanned constraints. The future is agile, software-defined production built on modular autonomous equipment, proven virtually and deployed with confidence.
Dassault Systèmes and NVIDIA are building the industrial AI foundation to make that future real. DELMIA contributes the virtual twin of production systems. A semantically rich model of production that connects design intent to real-world execution across engineering, manufacturing and supply chain. NVIDIA contributes physical AI and accelerated computing to simulate robotics-grade physics and perception at scale. Together, we can virtualise and orchestrate autonomous production systems. Then manufacturers can prove changes virtually and make them real faster, with less risk and rework.
This collaboration establishes a shared industrial AI architecture. This grounds artificial intelligence in the laws of physics and validated scientific knowledge. The integration of NVIDIA Omniverse physical AI libraries into the DELMIA Virtual Twin of global production systems represents a major step forward. It allows manufacturers to design, simulate and operate complex systems with a new level of confidence and precision. Not just incremental improvements; this partnership establishes a mission-critical system of record for industrial AI that powers a new way of working.
Virtual Twins: The Cornerstone of Modern Manufacturing
For years, manufacturers have optimised production lines in the physical world. While effective, this approach is often slow, resource-intensive and constrained by the cost of experimentation in live operations. Virtual twin technology changes this dynamic. A virtual twin is a science-based model of a system that goes beyond visualisation, enabling realistic validation of how operations should run before changes are made in the real world.
DELMIA empowers companies to create comprehensive virtual twins of their entire operational ecosystem. This includes everything from individual machines and robotic workcells to full factory floor layouts and global supply chains. Within this virtual environment, manufacturers can:
Simulate and validate production processes before a single piece of equipment is installed.
Optimise workflows for maximum throughput and efficiency.
Identify potential bottlenecks and safety hazards without disrupting ongoing operations.
Train operators and maintenance crews in a risk-free setting.
The virtual twin orchestrates design, engineering, production and supply chain in one environment so decisions can be tested, trusted and reused. This capability alone delivers significant value, but its impact grows when combined with physical AI.
Integrating AI for Autonomous Production
The partnership with NVIDIA brings physical AI into DELMIA virtual twins. NVIDIA Omniverse provides a platform for developing and operating 3D simulations and industrial digitalisation applications using OpenUSD-based interoperability. Combined with DELMIA’s production semantics, manufacturers can test autonomous behaviour in realistic conditions before deployment.
This is the shift from ‘mirroring reality’ to ‘proving change’. AI models accelerated by NVIDIA computing can evaluate scenarios across production constraints, resources and variability. They can help teams reduce commissioning surprises, improve flow and validate how production should respond to change, from new variants to disruptions.
The result is the emergence of software-defined production systems. These are factories and operations where decisions remain human-led, but are continuously supported by AI that recommends, tests and validates options in the virtual twin before changes are deployed. This creates a feedback loop where the virtual world is used to validate better outcomes for the real world.
A Practical Application: The OMRON Collaboration with DELMIA & NVIDIA Drive Real-World Success
To understand the real-world impact of this technology, consider the collaboration with OMRON, a global leader in industrial automation. OMRON recognizes that addressing the growing complexity of modern manufacturing requires a move toward fully autonomous and digitally validated production systems.
By combining DELMIA’s Virtual Twin of Production Systems, NVIDIA physical AI, and OMRON automation technologies, manufacturers can move from design to deployment with greater confidence. When a manufacturer introduces a new product variant or packaging change, automation often fails in small but costly ways, such as automation-grasping reliability, orientation on conveyors or downstream flow stability. Instead of trial-and-error changes on the line, teams can validate process logic, layout constraints and operating rules in the DELMIA virtual twin, then simulate realistic robot and material behaviour using NVIDIA’s AI before deployment. The result is faster adaptation and less physical rework.
The Top 3 Broader Impacts on Manufacturing
This fusion of virtual twin technology and industrial AI has far-reaching implications for the entire manufacturing sector including:
Unlocking New Efficiencies: Software-defined production systems can continuously identify operational improvements that are difficult to see through manual oversight alone, improving throughput, uptime and overall performance while reducing avoidable losses.
Advancing Sustainability Goals: By simulating processes in the virtual world, companies can minimize physical prototyping and reduce waste. AI-driven optimization within the DELMIA virtual twin helps manufacturers fine-tune their operations to consume less energy and use fewer raw materials, directly contributing to their sustainability commitments.
Fostering Continuous Innovation: When the risk and cost associated with testing new ideas are lowered, innovation flourishes. Manufacturers can experiment with novel factory layouts, new automation strategies and different production workflows within the safety of the virtual twin. This agility allows them to adapt quickly to changing market demands and stay ahead of the competition.
The partnership between Dassault Systèmes and NVIDIA is about more than just combining two powerful technologies. It’s about establishing a new, scientifically validated foundation for industrial AI. By integrating NVIDIA’s physical AI libraries into DELMIA, we are empowering manufacturers to build the autonomous, efficient and sustainable factories of tomorrow, today.
Trilliam Jeong, CEO at WealthBlock on why pairing credit discipline with real-time reporting will deliver a better position to hold onto investor confidence
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There’s no shortage of noise around the direct lending market right now. On one hand, deal activity remains strong, capital continues to flow in and investor appetite hasn’t wavered. On the other, competition is fierce, rates are edging down and macro conditions are less forgiving than they were a year ago.
But strip out the headlines and the fundamentals still look solid. The demand is there, both from borrowers looking for speed and flexibility and from investors chasing yield and consistency. That puts direct lenders in a strong position, provided they’re prepared to adapt.
Operational Shift
One of the most significant shifts underway is operational. We’re seeing real adoption of technology across the mid-market from AI-assisted onboarding to fully digitised investor dashboards. This isn’t just cosmetic. Faster processes and clearer visibility mean capital can move more quickly, investors stay better informed and managers have more room to protect margins, even in a tightening spread environment.
LP expectations are shifting too. Many now expect a consumer-grade digital experience from the platforms they commit capital to. They want real-time access to reports, frictionless communication and clarity around how their money is being deployed. That shift in expectations is accelerating the tech arms race across the mid-market. It’s no longer about who can show the best deck but rather can deliver the best infrastructure. And as investor sophistication grows, that infrastructure is becoming a non-negotiable.
Digital Infrastructure
That shift is also influencing how mandates are awarded. Institutional investors increasingly view digital infrastructure not as a bonus, but as a sign of long-term readiness. Questions that once focused solely on deal pipeline and past performance now extend to data availability, reporting cadence and system resilience. It’s not just about what a manager can deliver but how transparently and reliably they can do it. As more allocators run tighter operational due diligence processes, digital maturity is quietly becoming a competitive edge. Platforms that can demonstrate consistent, tech-enabled processes are better positioned to win, and keep, capital.
That matters, because rates may not stay where they are. Increased competition is already putting pressure on pricing. But firms with strong digital infrastructure are better placed to absorb it. Operational leverage, not just headline yield, is becoming a key differentiator.
Scaling Up
There’s also the issue of scale. Consolidation is real and it’s reshaping the market. The biggest managers are only getting bigger and their resources are hard to match. But size alone isn’t the whole story. Technology is giving smaller and mid-sized players a way to compete on experience even if not on balance sheet. A seamless, professional, tech-forward investor journey can carry real weight with LPs, particularly those who value speed and clarity over brand.
That’s especially relevant for new entrants. There’s no shortage of managers in direct lending and standing out requires more than just a different strategy. Yes, some are carving out a niche in NAV lending, venture debt or structured credit but what really earns attention is trust. That comes from clear communication, repeatable processes and a level of transparency that goes beyond the marketing deck.
The Outlook for Lending
The macro outlook is part of the equation too. With corporate defaults expected to rise, discipline is going to matter more than it has in recent years. Underwriting strength, sponsor alignment and proactive portfolio monitoring are back in focus. Investors will be watching for signals that managers are prepared for downside risk. The tougher the environment, the more exposed weaker systems become. Inconsistent reporting, vague valuation logic or delayed updates might have been tolerated in a bull market – but not now. Allocators want to know how a manager will behave under stress, not just how they perform when everything’s going to plan. That makes operational maturity as important as deal-level returns.
Firms that pair credit discipline with real-time reporting will be in a better position to hold onto investor confidence. Allocators are already asking more pointed questions and looking for managers who can back up claims with data. There’s still plenty of room to grow in direct lending, but it won’t be enough to rely on past performance or broad market tailwinds. The firms that outperform from here will need to be efficient, responsive and trusted. In a more competitive, more transparent and more regulated market, those are the traits that will endure.
Kevin Janzen, CEO of Gaming & EdTech AI Studio at Globant, on how AI will change the way games are made and expand the market
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Every major games studio is now experimenting with artificial intelligence. From generating NPC dialogue to automating animation and video assets. AI is promising to speed up production and lower costs for developers.
According to Boston Consulting Group (BCG), the gaming industry finds itself at a crossroads…. Looking to gain the momentum it felt between 2017 and 2021, where revenue surged from $131 billion to $211 billion. And AI could be at the forefront of this pivotal moment.
But as AI becomes central to how games are built, studios face a major challenge. Adopting automation without losing authenticity. For developers and retailers alike, this becomes a business concern that deserves close attention. Creativity sits at the heart of gaming, and the choices studios make today will influence what reaches players tomorrow. For the technology channel, this transformation means faster release cycles, broader product diversity, and a need for sharper forecasting.
A New Phase in Gaming’s Evolution
For most of gaming’s history, every era has been defined through visuals. Each generation has delivered stylistic, immersive worlds, such as the blocky charm of Minecraft to the cinematic realism of Red Dead Redemption 2.
Now, the real change is happening behind the scenes. AI is reshaping how games are built and experienced. Development teams are using AI to handle time-consuming tasks such as vast world-building creation and animation. This frees artists to focus on what players remember – the design and storytelling.
Players are already seeing the benefits in their gameplay. AI lets games adapt or adjust difficulty based on players’ skill levels, or change dialogue based on a player’s choices. This makes gaming worlds feel realistic, responsive and more personal.
With budgets continuing to climb for gaming studios, these new features matter. AI gives studios breathing room to experiment. Smaller teams can take creative risks, and established developers can experiment and test new ideas without derailing production. However, efficiency and costs aren’t the only gains as AI is creating space for developers to be more ambitious than ever before.
Automation and Artistry
For all its promise, AI also brings creative risk. Gamers notice when a quest feels repetitive or when dialogue sounds mechanical. And if AI is used carelessly, developers risk losing authenticity.
That sense of care is what keeps players invested. Whether it’s hand drawn detail, or play-driven choices. Games like this show what happens when technology supports vision rather than replacing it.
That’s why the industry’s embrace of AI is such a gamble. Used well, AI can help developers create richer, more personalised worlds. But used carelessly, it risks stripping away the artistry that makes games memorable.
The Ripple Effect Across the Supply Chain
As AI becomes a standard tool, development processes are speeding up and opening new creative possibilities. Independent studios now have access to the kind of production power once limited to major developers. That shift means faster pipelines and ultimately, more games reaching the market.
For retailers and resellers, this brings both opportunity and pressure. A consistent stream of releases can guarantee sales across the year, while lower production costs encourage more niche or experimental games that appeal to new audiences. Greater variety and volume benefits the market, but it also makes it harder to predict which games will break through.
Players are becoming more aware of how games are made and AI’s role in development. They’re starting to ask not only how a game plays, but also how it was built. Understanding the intent behind a studio’s use of AI – one that uses AI as a genuine creative tool and those that rely on it as a shortcut – will help retailers anticipate demand and spot the games with long-term potential.
The Right Way to Play the AI Game
The studios using AI most effectively have a few things in common. They keep AI in the background, using it to manage routine work, such as generating textures and landscapes, so creative teams can focus on narrative and emotional tone.
They also use AI to make experiences more personal. Thoughtful application of adaptive systems allows games to respond to individual play styles, adjusting difficulty and pacing to keep players engaged. This level of design deepens engagement and gives players a sense that the world responds to them personally.
Another area where AI is also making an impact is making games more inclusive. More than 400 million people around the world play with a disability, and new tools are expanding access – from adaptive controls to real-time translation that lets players connect across languages. As gaming becomes more diverse, the audience grows for everyone, including retailers, who can reach a larger, more engaged customer base.
When automation complements gaming artistry, it strengthens the relationship and trust between the developer and the player. Creativity becomes the main focus again, and that’s what keeps players loyal.
Balancing Innovation and Trust
AI is fast becoming integral to how games are conceived, built, and experienced — and that shift will reshape the entire value chain. For developers, success will come from balancing automation with artistry, ensuring that AI enhances creativity rather than replaces it.
For retailers, distributors, and partners, this transformation offers both opportunity and responsibility. A faster, more diverse release pipeline will bring fresh sales potential, but also greater complexity in forecasting and curation. The winners in this new phase of gaming will be those who can spot titles where AI adds genuine depth, inclusivity, and player connection — not just production speed.
Handled thoughtfully, AI won’t just change how games are made, it will expand the market for everyone involved in bringing those experiences to players. That’s a game worth playing for the entire tech channel.
JP Cavanna, Director of Cybersecurity at Six Degrees, on balancing the risks and benefits of AI in cyber defence strategies
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Undeniably, AI is here to stay. Having become part of day-to-day life, it’s hard to remember what life was like without it. But when it comes to cybersecurity, is it causing more harm than good?
Recent research outlines that 73% of organisations have already integrated AI into their security posture. The technology is clearly becoming a cornerstone of modern cybersecurity. Organisations are turning to AI not just as a tool, but as a partner in security operations, leveraging its capabilities to identify malicious activity faster, guide investigations, and automate repetitive tasks.
For it to be truly effective, though, AI must be paired with human expertise – but this is where organisations are starting to become complacent. Given the growing sophistication of cyber-attacks, and even AI-powered attacks, many are removing the human element while expecting AI tools to do all the work for them, leaving them even more vulnerable to threats. This overreliance risks creating blind spots, where critical thinking, contextual understanding, and instinct are overlooked. Without the balance of human judgement, AI can amplify mistakes at scale, turning efficiency into exposure.
The Cybersecurity Paradox
This situation puts many organisations in a potentially difficult position. On the one hand, AI can significantly improve the efficiency of security operations. In the typical SOC, for example, AI technologies can process alerts in around 10-15 minutes. This represents a significant improvement over human analysts, who can easily require twice as long for the same task.
Aside from the obvious efficiency gains, applying AI to these repetitive, time-pressured processes can also significantly reduce the scope for human error. And in turn, take considerable pressure off security analysts. Going some way to battling alert fatigue, an increasingly well-documented and persistent problem. In these circumstances, valuable human experience and specialist expertise can instead be more effectively applied to complex investigations, strategic decision-making, and other higher-value priorities.
On the flipside, however, AI remains prone to generating inaccurate or misleading insights, and users may not realise they are applying the wrong information to potentially serious security issues. Similarly, habitual blind trust in AI outputs can easily erode performance levels and even introduce new vulnerabilities. There is also scope for sensitive data to enter public environments, with the potential to cause compliance issues. This kind of information can also reappear in future versions of the AI model in question, therefore resulting in further data exposure risks.
Parallels with IoT Adoption
The situation mirrors that seen in the early days of IoT adoption, where the rush to innovate would often override security considerations. In this current context, therefore, human oversight and vigilance are extremely important. Clear governance frameworks, defined accountability, and continuous monitoring must underpin any AI deployment. Therefore ensuring that innovation does not outpace risk management or compromise long-term resilience.
A Growing Arms Race
If that wasn’t challenging enough, threat actors are also in on the AI boom in what has already been described as an ‘arms race’. In practical terms, AI tools are already widely used to create more convincing phishing attacks free from some of the more obvious traditional tell-tale signs of criminal intent, such as imperfect grammar or a suspicious tone.
Deepfake technology has also raised the stakes. We’ve all seen how convincing AI-generated video has already become. This is now finding its way into real-world examples, with one fake video reportedly causing a CFO to authorise a large financial transfer as a result.
At the same time, technology infrastructure is constantly under attack by AI-powered tools. They can be used to analyse defensive systems and identify weaknesses faster than humans. The net result of these developments is that defenders constantly play catch-up, as they can only respond to new attack vectors once discovered. The underlying takeaway is that at present, AI cannot be trusted to operate autonomously. Instead, human intuition, scepticism and contextual understanding remain essential to spotting emerging tactics.
As attackers refine their methods at machine speed, organisations need to resist the temptation to match automation with automation alone. They must double down on strategic thinking and continuous skills development.
Balancing Benefits and Risk
So, where does this leave security leaders who are looking to balance the benefits and risks? Firstly, and to underline a fundamental point, while AI offers scale and speed, it cannot replace critical human oversight. Organisations should view AI as an enhancer, not a replacer. Success lies in promoting partnership, not substitution.
Strong governance is vital. This should start with clear AI usage policies that define what can and cannot be shared with AI tools, while proper data classification and access control ensure that sensitive information is protected. In addition, regular validation of AI outputs can help to prevent inaccurate or misleading results from being unnecessarily acted upon.
Then there are the perennial challenges associated with employee awareness training, which is vital for avoiding complacency and understanding the limitations of generative AI tools. Cyber leaders should also monitor how AI is being used inside and outside the corporate environment, as staff often experiment with tools on personal devices.
Get this all right, and security teams can put themselves in a very strong position to embrace AI, safe in the knowledge that they have the guardrails and processes in place to balance innovation and efficiency with effective human-led oversight. Ultimately, success will depend not on how much AI is deployed, but on how intelligently it is governed and refined alongside the people responsible for securing an organisation.
A 2026 survey of nearly 1,000 C-suite executives found that 87% of companies now use AI in their core operations. However, AI errors and…
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A 2026 survey of nearly 1,000 C-suiteexecutives found that 87% of companiesnow use AI in their core operations. However, AI errors and rework continue to cost businesses over $67bn a year
Loopex Digital’s January 2026 analysis identified several common mistakes companies make when relying on AI.
1. Giving AI Too Much Control in HR
AI-led hiringfilters out 38% of top-level candidates before human review because it relies on keyword matching. Candidates respond by adjusting CVs to fit those words, often hiding real experience.
“When we started to use AI in our hiring process, we saw some strong candidates get rejected,” said Maria Harutyunyan, co-founder of Loopex Digital. “Out of 100 applicants, the 2 candidates that would’ve been hired didn’t make it because they used different wording instead of the exact keywords.”
How to fix this: “We simplified our job descriptions, removed buzzwords that didn’t matter, and limited AI to shortlisting. The quality of hires improved immediately,”said Maria.
2. Trusting AI Notes Without Review
AI note-takers often struggle with background noise and poor audio, leading to inaccurate notes. In many cases, up to 70% of summaries focus on side comments rather than decisions.
“We tested 10+ AI note-takers across50 of our regular meetings. Most of the main summaries ended up being jokes and half-finished sentences,” said Maria. “Key decisions were either unclear or missing entirely from the AI summary.”
How to fix this: “We limited AI notes to action points and decisions,” said Maria. “Everything else is filtered out or reviewed manually, cutting note clean-up from half an hour to minutes.”
3. Letting Artificial Intelligence Replace Your Customer Support Team
When customers realise they’re speaking to AI, call abandonment jumps from 4% to 25%. Even when customers stay on the line, AI tools can get policy and pricing details wrong, leading to confusion, complaints, refunds, and extra clean-up work for support teams.
How to fix this: Use AI only for simple FAQs, not complex cases. Define clear escalation rules for cancellations, complaints, and legal issues and route those to a human immediately. Restrict your AI from creative responses in support, only letting it use approved templates.
Maxio analysis of $40B+ in billings data shows vertical focus and AI innovation driving success, while growth inflection points emerge earlier than expected
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Analysis of $40B+ in billings data shows vertical focus and AI innovation driving success, while growth inflection points emerge earlier than expected
Growth remains strong for B2B SaaS and AI companies, but volatility is high, according to the B2B Growth Report by Maxio, a leading billing automation and revenue management platform. While the market is healthy overall, with the average company growing 18% year over year, more than 35% of companies experienced a decline, revealing an industry where growth increasingly depends on focus, discipline and execution rather than market momentum alone.
The report analyzed over $40 billion in billings data across 2,000+ companies from 2024-2025, revealing unexpected patterns in how growth varies by company size, business model, investment backing, and approach to AI. The findings challenge conventional assumptions about scaling thresholds, the universal benefits of AI adoption, and the predictability of growth trajectories.
“Growth didn’t disappear in 2025; it became harder to earn,” said Alan Taylor, Chief Operating Officer at Maxio. “The winners weren’t chasing every trend. Whether AI-native or traditional SaaS, the top performers stayed focused on solving real customer problems.”
Key Report Findings:
Growth is still the norm, but it’s not universal: Average company growth reached 18%, while aggregate market growth was closer to 13%, reflecting slower expansion among larger, more mature businesses. Nearly two-thirds of companies grew year over year, yet more than one-third declined. Down years remain common across all revenue bands.
Growth slows earlier than expected: The data revealed inflection points at around $5 million in billings with another slowdown beyond $25 million, not the typical $1 million, $10 million or $50 million marks, showing the operational challenges of scaling.
Vertical focus outperforms horizontal scale: Vertically focused companies grew faster than horizontal peers (20% vs 16%), reinforcing the value of specialization in competitive markets.
Capital helps, but doesn’t guarantee faster growth: Bootstrapped companies nearly matched VC-backed growth (20% vs. 22%), though scale differed dramatically with VC-funded companies nearly 4x larger. Private equity-backed companies focused more on profitability, growing 13% on average while skewing significantly larger than other cohorts.
AI accelerates, but only at the core: Truly AI-led companies, with AI central to product and positioning, grew fastest at 21%. However, AI-enhanced companies lagged at 16%, while non-AI companies quietly outperformed at 19%. This pattern suggests that AI adoption alone does not guarantee impact—AI implementation without clear value differentiation may not translate into competitive advantage.
“Average growth numbers only tell part of the story,” said Ray Rike, founder and CEO at Benchmarkit. “What stood out is how early growth friction shows up. Teams that identify where and why growth is accelerating will be best positioned to focus their resources on the market segments that provide faster growth.”
2026 Outlook
Despite a more competitive and complex environment, industry optimism is back and strong. Seventy-two percent of companies expect to grow faster in 2026 than 2025. However, leaders are entering the year with more measured expectations around buyer scrutiny, competition and the need for operational efficiency.
Sustainable growth is built, not assumed, the report found. Companies that understand their true growth levers, invest with intent, and maintain discipline as they scale will be best positioned to win in 2026.
Maxio is the billing and financial reporting platform trusted by over 2,000 SaaS, AI and subscription businesses worldwide. With $18B+ in billings under management, Maxio empowers finance teams to scale recurring revenue, automate quote-to-cash and deliver the insights needed to grow confidently.
Digital & Tech Head Soumya Mishra reveals how the group behind power brands like Sensodyne, Panadol and Centrum, broke away from GSK and transformed so successfully. Haleon is itself a large organisation so separating from a huge parent company was a big challenge… “It was the biggest deal of its kind and the first to happen in this industry,” Mishra adds. “We were separating to create simplification, but we had to work hard to achieve that. There were a lot of processes and policies that didn’t make sense and needed an overhaul. This had to be backed by a culture shift that was properly communicated.”
State of Montana: Cybersecurity Through A New Lens
State of Montana CISO, Chris Santucci, explains the organisation’s drastic shift towards security, and how his team has become a shining example within the wider IT centralisation sphere… “Fixing security vulnerabilities came down to having built enough social capital and trust to correct. I like to stay slightly uncomfortable as a CISO and as a human, to keep challenging myself to deliver better services and greater value. The mission is to ensure Montana citizens get the support they need while keeping services secure and protecting data.”
Publicis Sapient: Driving Banking Transformations with AI
Financial Services Director Arunkumar Gopalakrishnan reveals how Publicis Sapient is developing the playbook for delivering successful AI-led digital transformations across the financial services landscape. “Working with Generative AI today feels like standing on a new frontier. It keeps us on our toes, but it’s also what drives us – to stay relevant, deliver outcomes and connect both worlds of business and technology.”
Techcombank:
Chief Strategy & Transformation Officer, PC Chakravarti explores the operating model, Data & AI foundations, culture and talent playbook, and the partnerships turning ambition into market leading outcomes at Techcombank in Asia. “Tech is not the limiting factor – it’s about supporting people and talent to leverage capabilities to enhance business models.”
Oakland County:
Sunil Asija, Director of Human Resources at Oakland County, talks building trust with collaboration and becoming employer of choice. “To build trust the culture needs to change from top to bottom, and it needs everyone to join in that good fight.”
Lasse Fredslund, CMS Product Owner at Umbraco, examines the carbon footprint of our digital lives and offers advice on how to shrink it
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Our digital lives have a carbon footprint. The energy consumed to power and cool the data centres at the heart of ecommerce, online banking, social and streamed media, already emits as much greenhouse gas as the aviation industry. This is expected to increase to 8% of GHG emissions in 2025.
While hyperscale data centre operators, including Microsoft, Alphabet, and Amazon, have made big strides towards adopting renewable energy sources, they still need fossil fuel-powered backup systems to meet the 24×7 demand for power and cooling.
To meet the predicted 606 Terawatt hours of electricity needed to power datacentres by 2030, three mothballed nuclear plants have been recommissioned in the US, and major investment is going into building new nuclear plants. However, building will take years and until then, fossil fuel combustion will continue.
How Can we Shrink our Digital Carbon Footprint?
The good news is that we can all do our bit to lighten the load. Even turning off autoplay on our smartphones and turning down the screen brightness can contribute to an overall reduction in energy consumption on our digital devices. Web designers and developers can do even more: making multiple optimisations that reduce web page weight and lower energy consumption and associated GHG emissions.
For our own part, we’re focusing on ways to make our operations more sustainable and our software more energy-efficient. Running our CMS platform on Microsoft .NET9 has introduced features such as HybridCache that aid carbon-conscious web developers in building sites that load content more efficiently.
We’re also working closely with our global open-source community and digital agency partners to show how to reduce the CO2 emitted by business websites built on the Umbraco CMS platform. The Umbraco community Sustainability Team, formed in March 2023, has published documentation that provides practical steps for reducing web page weight and optimising data transmission.
Sharing Responsibility and Best Practices
By sharing sustainable best practices, and the measurable ROI that our partners’ clients have achieved as a result of carbon-conscious web design, we hope to amplify these changes across the industry. Together we can make a much bigger difference to our collective carbon footprint.
Prominent members of our open-source community Sustainability Team worked with us and implemented the Green Web Foundation’s CO2.js tool. We now have a Sustainability Dashboard, which helps businesses monitor and reduce the environmental impact of their websites running on Umbraco Cloud.
Ten tips to reduce Cloud Carbon Footprint
Members of the Umbraco Sustainability Team have published the following practical steps that organisations can take, and free tools that they can use, to measurably reduce the energy consumption and CO2 emissions of websites and digital experiences.
Lose weight
Just as the aviation industry has been introducing lighter aircraft to help reduce fuel consumption and emissions, carbon-conscious web designers can also help organisations to reduce web page weight.
The Sustainability Team recommends using tools such as www.Ecograder.com and www.Websitecarbon.com which show grams of CO2 emitted per web page. This is the simplest way to check a web page’s energy-efficiency, so that improvements can be made.
Neil Clark, Service Design Lead, at TPX Impact, observes, “Every piece of website software and code must minimise the data transfer it causes. We must start to consider data transfer as a constraint in all of our digital projects.”
Thomas Morris, Tech Lead at TPX Impact advises, “A useful first step is to set page weight budgets and stick to them. This helps to create a culture of optimisation with realistic targets. The HTTP Archive suggests a maximum of 1 Megabyte.”
Reduce Images
To reduce web page weight, Rick Butterfield, Lead Software Engineer at Wattle, emphasises, “Be ruthless about images. Make sure they’re sized well and avoid using stock images, which can sometimes be massive files.”
Thomas Morris agrees, “One of the biggest impacts you can have, with fairly minimal effort, is to use appropriately-sized images on your website, or consider whether images are needed at all. Using modern image compression formats, such as WebP, or AVIF helps reduce file sizes by up to 70% compared to JPEGs, without your users noticing any difference. Optimise images before upload, to reduce the extra compute effort of resizing images. Where appropriate, consider using SVG icons, logos or illustrations, since these often result in smaller image file sizes and also scale easily without compromising image quality.”
Compress fonts
Thomas Morris advises, “We suggest using system fonts to reduce extra server requests. If you do have to use custom fonts then compression tools, such as WOFF2, will help to minimise the data weight of those assets. WOFF2 is supported across all modern browsers.”
Minimising text assets, including HTML documents, JavaScript files and CSS files is a really good practice. Google’s Brotli is a lossless compression tool supported by 96% of browsers that makes this a lot easier and reduces text-based files by around two thirds.
Choose colours wisely
Rick Butterfield advises that web designers can even reduce carbon footprint by changing the colours selected for a website: “Blue shades use up more energy than reds and greens when they’re displayed on screens.”
Default to Dark Mode
“Dark mode is very simple to set up and can be built on incrementally,” enthuses Rick Butterfield. As with a lot of the best practices outlined by the Sustainability Team, these changes benefit end users too. “A university study found that switching from light mode to dark mode at 100% screen brightness can save an average of 40% battery power, so users don’t have to charge devices as often,” adds Rick.
Keep software updated
James Hobbs, Head of Technology at aer Studios, says, “Simply by keeping libraries, frameworks and the rest, up to date, your organisation is likely to benefit from enhanced efficiency, which means doing more work with the same or fewer resources, which is better for the planet. When Umbraco moved to .NET Core it made a massive difference to the efficiency of the CMS. Staying on top of this can deliver sustainability and efficiency benefits and an improved security posture.”
Load web content efficiently
To make data transfers of images, videos and iframes more efficient, the Sustainability Team recommends implementing lazy loading on clients’ sites. “Lazy loading limits what is loaded within the viewport and is supported in modern browsers,” explains Thomas Morris.
However, web designers should avoid applying lazy loading to hero images which are always visible at the top of a page, as this will cause the website to load slowly and impact user experience.
Make your Site Carbon-Aware
Rick Butterfield is a strong advocate for building carbon-aware websites. “The Green Software Foundation’s Carbon Aware software development kit allows developers to create software that does more when the electricity is from renewable sources and less when the electricity is from fossil fuels. Open APIs allow us to create this type of service for clients. Functionality of the site can be altered based on current grid usage, where your servers are located, or where your users are. As an example, images can be disabled if the server load is too high, or they could be stripped back to display illustrations instead.”
Choose carbon-efficient infrastructure
Andy Eva-Dale, CTO at Tangent, advises that running digital services from the cloud has both environmental and financial benefits for organisations, “All the major cloud providers have carbon commitments. Take advantage of PAAS features like auto-scaling, to ensure you’re only using and paying for the computing memory you need, and this is optimised for ‘business as usual’ traffic, from a carbon perspective. Then, when you have spikes in traffic, we can auto-scale those applications. Furthermore, when we start looking at microservice architecture, we can scale independently and set resource plans on individual services rather than whole applications, giving us more control.”
Andy Eva-Dale continues, “The next thing to consider is serving content geographically close to your audience. Hosting static files or caching your API responses on the edge can significantly reduce the amount of carbon your systems produce.”
Thomas Morris agrees, saying, “Serving static assets via a content delivery network (CDN) will ensure that requests are treated efficiently.”
Switch off after use
Andy Eva-Dale also advises turning off cloud-based resources after use, “When you’ve moved to a relatively stable business as usual cycle, turn off your non-production environment and turn them on only when you need to make a patch, or update a particular feature. If you’re in a continuous programme of work, look at switching off environments at weekends. Applications like Kubernetes give you increased control over that. An auto event-driven autoscaler was announced by The Cloud Native Computing Foundation that allows infrastructure to be adjusted, based on carbon metrics.”
Taking our own advice:
The Sustainability Team is committed to working with peers, clients and even competitors to share these best practices and collectively reduce the environmental impact of digital experiences. This includes Umbraco listening to our digital partners and making the necessary changes to our core CMS platform and website.
Neil Clark comments, “By having us as a Sustainability Team, we can really push change at all levels of Umbraco which means that the impact of those changes is going to be amplified and not restricted to a few developers or agencies changing the way that they work.”
This is not just a nice-to-have. Our digital agency partners tell us they are seeing more client briefs and RFPs that stipulate sustainable web design. In the face of new legislation such as the Corporate Sustainability Reporting Directive, there is an increasingly strong business case for carbon-conscious web design.”
Some Europe & Middle East CIOs anticipate up to 178% ROI on AI investments, with further efficiencies expected as Agentic AI scales
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Enterprises have moved decisively from AI pilots to scaled implementations, driven by proven benefits and expectations of significant financial returns, according to the Lenovo Europe & Middle East CIO Playbook 2026 with research insights by IDC. Nearly half (46%) of AI proof-of-concepts have already progressed into production, with organisations projecting average returns of $2.78 for every dollar invested.
The 2026 Lenovo CIO Playbook: The Race for Enterprise AI, draws on insights from 800 IT and business decision makers in Europe and the Middle East. It captures a regional inflection point and reinforces the value proposition for enterprise AI as both real and immediate. It calls on CIOs to act now to avoid lagging competitors. The research marks a clear shift from AI experimentation to measurable value creation, with nearly all (93%) of those surveyed planning to increase AI investments in the next 12 months. At an average spending growth rate of 10%, and 94% anticipating positive returns.
Enterprise AI Adoption in Europe and the Middle East
AI is now recognised as a core engine of business reinvention and competitive advantage. However, AI adoption in the markets is progressing at different speeds. Reflecting varying levels of digital maturity, regulatory readiness, and investment capacity, and there is a clear overconfidence problem among CIOs. While 57% of organisations in Europe and the Middle East are approaching or already in late-stage AI adoption, only 27% have a comprehensive AI governance framework. Further limitations in data quality, in-house expertise, integration complexity, and organisational alignment are causing a mismatch between ambition and readiness.
With Agentic AI overtaking Generative AI as the top priority for CIOs in 2026, these factors will prevent many organisations from fully capitalising on AI’s potential, leaving significant returns unrealised. Moreover, 65% of organisations are focused on scaling Agentic AI across their operations within 12 months, but only 16% report significant usage today, with the majority still piloting or actively exploring use cases.
More advanced markets such as Scandinavia, Italy, and the UK are moving beyond pilots, with a majority of organisations already systematically adopting AI and increasing focus on hybrid and edge deployments to support scale. In contrast, parts of Southern and Eastern Europe remain earlier in their AI journeys, with a higher proportion of organisations still in planning or early development stages. Meanwhile, the Middle East is emerging as a fast-moving growth market, showing strong adoption momentum and a sharp year-on-year increase in interest in advanced and Agentic AI.
Across the region, hybrid deployment models dominate as organisations balance innovation with data sovereignty and operational control. While interest in Agentic AI is accelerating. This signals a broader shift from experimentation toward more autonomous, production-ready AI use cases, even as readiness levels continue to vary by market.
“We’re now seeing clear returns from the AI pilots and proof-of-concepts organizations have invested in, with AI delivering measurable impact across the region. But many are not fully equipped with the skills, governance and readiness needed to scale AI to its full potential. As priorities shift toward Agentic AI, and compliance with regulation such as the EU AI Act becomes imperative, trust and scale must be built in from the start. Those who don’t, risk leaving tangible returns on the table.”
Matt Dobrodziej, President of Europe, Lenovo
Hybrid AI Now Preferred Enterprise Architecture
The research shows that real-world business and financial considerations are accelerating the shift toward hybrid AI. Factors such as data privacy, advanced security requirements, and the need to customise and optimise infrastructure are driving adoption of this model, which blends public cloud, private cloud, and on-premises compute. Nearly three out of five (58%) organisations now prefer hybrid as their primary AI deployment model.
Scalable, high-performing AI infrastructure is a critical enabler of enterprise AI success. Respondents in the region highlighted the importance of compute that is both cost- and energy-efficient. This factor ranked second overall, with many identifying it as key to moving AI from pilots into reliable production.
With AI PCs and edge endpoints central to an effective Hybrid AI strategy and securely running AI workloads locally, deploying AI-capable devices has emerged as the top IT investment priority for 2026.
“CIOs across the region are entering a decisive phase of AI adoption where agentic AI and enterprise-scale inferencing are moving from experimentation to core business priorities,” said Dobrodziej. “To unlock real value, organisations need strong foundations, including secure, energy-efficient infrastructure, flexible hybrid architectures, and AI-capable devices and edge endpoints that bring inference closer to where data is created, and work happens. When combined with the right governance and services, this end-to-end approach enables enterprises to innovate confidently, responsibly, and at scale.”
Lenovo recently introduced Lenovo Agentic AI, a full-lifecycle enterprise solution for creating, deploying, and managing AI agents, alongside Lenovo xIQ, a suite of AI-native platforms designed to simplify and operationalise AI across the enterprise. Built on the Lenovo Hybrid AI Advantage™, these offerings combine hybrid infrastructure, platforms, and services to address governance, integration, and performance from day one. Supported by the Lenovo AI Library of proven use cases, CIOs can reduce risk, accelerate time-to-value, and scale AI initiatives with greater confidence as they move beyond experimentation.
To further enable real-world deployment, Lenovo ThinkSystem and ThinkEdge inferencing servers help enterprises turn trained models into production-ready, low-latency AI applications across data center, cloud, and edge environments. By enabling faster, more efficient inference at scale, Lenovo helps CIOs bridge the gap between AI ambition and day-to-day business impact.
Building on this end-to-end AI foundation, Lenovo’s Smarter AI for All vision is focused on bringing AI to more people and businesses at scale, from enterprise infrastructure to AI PCs that deliver intelligent, personalised experiences directly to users. As outlined at Lenovo Tech World at CES 2026, Lenovo is advancing this vision across its AI PC and smartphone portfolio, with Lenovo and Motorola Qira representing one example of how personal AI can enhance productivity by understanding context across devices and helping users get things done.
Learn more about how enterprises can accelerate AI adoption with the right infrastructure, governance, and partnerships:Explore the full 2026 CIO Playbook report.
About the CIO Playbook Study
This is the third year of surveying CIOs in Europe and the Middle East, with Lenovo commissioning IDC which conducted research between 16th September 2025 and 17th October 2025. This year’s report draws on insights from 800 IT and business decision makers in Europe and the Middle East. Industries represented include: BFSI, Retail, Manufacturing, Telco/CSP, Healthcare, Government, Education and others.
About Lenovo
Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). To find out more visit https://www.lenovo.com, and read about the latest news via ourStoryHub.
Christina Mertens, vice president of business development, EMEA, at VIRTUS Data Centres on designing next gen digital infrastructure
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Europe’s digital infrastructure is entering a new phase of development. For more than a decade, growth was concentrated in a small number of metropolitan hubs. This was where connectivity, enterprise demand and financial services created natural centres of gravity for data centres. Cities such as London, Frankfurt, Amsterdam and Paris (FLAP markets) became the backbone of Europe’s cloud and colocation landscape.
That model is now under pressure. Computing power is surging in ways that surpass forecasts made even two years ago. AI training and inference, high performance computing (HPC), analytics and modernised public services all require significant and sustained energy and cooling capacity. McKinsey suggests that global demand for data centre capacity could more than triple by 2030. It’s clear Europe needs more digital infrastructure. However, it needs that infrastructure in places with the headroom and regulatory clarity to support long term expansion. And this is why what are referred to as second-tier locations are becoming critical to expanding Europe’s digital architecture.
In practical terms, second-tier locations are not secondary in importance. They are cities and regional areas outside the most constrained metropolitan centres, where there is greater headroom for power, land and long-term infrastructure planning. Across Europe, this includes parts of regional Germany and Italy, Iberia, the Nordics and areas of the UK outside of London. These locations are now playing a central role in how Europe expands its digital capacity.
Why the Digital Infrastructure Shift is Happening
The primary driver is power. Data centres require sustained, predictable electrical capacity over long periods, particularly as AI workloads increase baseline demand. In dense urban centres, electricity networks are often operating close to their limits, and upgrading them is complex, costly and slow. New substations are difficult to site, transmission upgrades can take many years, and competition for capacity from other sectors is intensifying.
Land availability compounds this challenge. Modern data centres are no longer single buildings inserted into existing industrial estates. They are increasingly campus-based developments, designed to accommodate multiple facilities, on-site substations and future expansion. Securing sites of that scale within major cities is difficult and expensive. And often incompatible with planning frameworks that prioritise mixed-use or residential development.
By contrast, regional and edge-of-city locations offer more physical space and greater flexibility. They make it possible to plan electrical infrastructure coherently from the outset, rather than retrofitting systems around urban constraints. For building services professionals, this changes the nature of both design and delivery.
Delivery Challenges in Regional Locations
While second-tier locations offer more space and flexibility, they are not without challenges. Securing grid capacity remains a critical path issue. It requires close collaboration with transmission and distribution network operators, regardless of geography. In some regions, new infrastructure or upgrades are required to support data centre demand. This can introduce complexity into delivery programmes.
Phased development is another defining characteristic. Many campuses are designed to be built out over several years, sometimes over a decade or more. Electrical and mechanical systems need to be designed and installed in a way that supports this staged approach, maintaining operational efficiency while allowing for expansion.
This places a premium on coordination between designers, contractors, operators and utilities. Clear documentation, consistent standards and long-term programme management become essential, particularly where different phases may be delivered by different teams over time.
Skills and Workforce Considerations
As data centre development spreads across a wider range of locations, skills availability becomes an important consideration. High-voltage electrical expertise, experience with resilient power systems and familiarity with data centre standards are already in demand, and that demand is unlikely to ease.
In regional locations where specialist labour pools may be smaller, there is increased focus on training, apprenticeships and long-term workforce development. From an operator and developer perspective, the ability of contractors and consultants to provide consistent quality across multiple phases is particularly valued on campus-scale projects.
This creates opportunities for building services firms that invest in people and develop repeatable delivery capability. Long-term relationships can be built where teams understand an operator’s standards and are involved across successive phases of development.
The Influence of AI and Higher-Density Workloads
AI is accelerating many of these trends. Training and inference workloads place sustained loads on electrical and cooling systems, increasing the importance of reliability and predictable performance. This reinforces the need for robust primary infrastructure and careful long-term planning.
Second-tier locations make it easier to accommodate these requirements because they allow for comprehensive system design at scale. Space for substations, cooling plant and future expansion can be planned into the site from the beginning, rather than being constrained by surrounding development.
From a building services perspective, this does not necessarily mean radically new technologies, but it does increase the importance of integration, resilience and accurate demand forecasting.
Why this Matters for the Built Environment Sector
The shift toward second-tier locations represents more than a geographical redistribution of data centres. It reflects a broader change in how digital infrastructure is planned, designed and delivered. Larger sites, longer programmes and greater emphasis on early-stage coordination place building services and electrical design at the centre of successful delivery.
For the built environment sector, this creates sustained opportunities across design, construction and operation. Campus developments require ongoing engagement rather than one-off interventions, and they rely on teams that can think beyond individual buildings to system-level performance over time.
Looking Ahead…
So, it’s clear that Europe’s digital infrastructure is becoming more distributed, and that trend is unlikely to reverse. Power constraints, planning pressures and rising digital demand all point toward continued development beyond traditional metropolitan hubs.
Second-tier locations are not a temporary solution. They are becoming a permanent and essential part of Europe’s digital landscape. For building services professionals, understanding how to design and deliver infrastructure at this scale, and over these time horizons, will be increasingly important.
As the next phase of development unfolds, success will depend on careful planning, strong collaboration and a clear understanding of how electrical and mechanical systems underpin the resilience and performance of Europe’s digital future.
Dan Nichols, Chief Technology Officer at virtualDCS, on why cloud resilience in the financial services sector hinges on shared accountability and an assume-breach philosophy
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A powerful catalyst for transformation, the cloud is reshaping how organisations compete in the financial services sector. Beyond significant cost savings and flexibility, leaders are eager to unlock the potential of AI-driven insights, intelligent automation, and real-time business modelling. And, in a space governed so strictly by data sovereignty and privacy policies, the cloud’s ability to localise, encrypt, and control data has made it a key enabler of compliance and customer confidence.
But as threats become more frequent and sophisticated – with attackers now targeting shared platforms and partner supply chains – organisations can no longer rely on their own defences alone. For true digital resilience, shared accountability, collective readiness, and clear governance across every cloud touchpoint are equally non-negotiable.
All Eyes on the Money
The industry sits at a valuable intersection of data, technology, and finance. A combination that makes it uniquely attractive to attackers. It holds some of the world’s most sensitive data, directly underpins the flow of global capital, and operates through deeply complex and interconnected systems. With every integration increasing the risk of exposure. Ultimately, the attack motivation is as simple and relentless as it is in most sectors: monetary gain. Cybercriminals target institutions precisely because of the value at stake and the speed at which disruption translates to loss.
How the Threat Landscape is Evolving
Ransomware groups may see insurers and payment providers as high-yield targets. They understand even seconds of downtime can induce multi-million pound losses. Under pressure to protect customer trust and avoid regulatory penalties, some firms may choose to pay in order to restore their service quickly. This dangerous perception only encourages repeat targeting and paves the way for damage to spread even further. Yet it remains a common response tactic among many.
At the same time, the rise of supply chain and third-party attacks has made it possible for criminals to bypass even the most well-defended cloud environments. By exploiting shared platforms, managed service providers, and cloud-hosted applications, perpetrators can move laterally across multiple organisations at once, amplifying both the reach and impact of their attacks. In other words, infiltrating one vendor’s weakness can cripple an entire network in one carefully coordinated strike. And, since some firms may overlook the cloud’s shared responsibility model – presuming end-to-end security sits solely with their cloud provider – multiple blind spots can inevitably emerge, creating easy openings to exploit.
In an environment where boundaries blur and dependencies multiply, traditional perimeter-based defences are no longer enough. Hybrid and multi-cloud infrastructures demand continuous visibility, faster detection, and coordinated response across every partner and provider. The goal is not simply to prevent breaches, but to withstand and recover from them collectively. It’s about recognising that in today’s ecosystem, no financial institution is secure in isolation.
Inside the Ransomware Economy
Evolving beyond the scattergun attacks of the past, ransomware now operates as a professionalised, profit-driven ecosystem, where malicious actors collaborate, trade intelligence, and lease attack tools much like legitimate software vendors. The rise of ransomware-as-a-service (RaaS) has even lowered the barrier to entry, giving less skilled affiliates access to ready-made payloads and automated encryption kits in exchange for a percentage of the ransom.
What makes it especially destructive is the precision and psychology behind the attacks. Rather than randomly striking, attackers conduct weeks of reconnaissance – learning behaviours, studying employee hierarchies, and identifying systems most critical to operations. They often infiltrate through phishing emails or compromised credentials, quietly moving laterally through the network to gain elevated access. Once embedded, they disable defences, exfiltrate sensitive data, and target backup repositories before finally encrypting production systems.
At that point, the goal shifts from technical control to financial coercion. Victims are locked out of their systems and presented with a ransom note demanding payment, sometimes in cryptocurrency, in exchange for a decryption key. Increasingly, the threat includes public exposure of stolen data – a tactic designed to pressure leadership into paying to protect their reputation and customer trust. Even when ransoms are paid, recovery is rarely clean: data may be incomplete, corrupted, or resold on the dark web, and repeat targeting is common once an organisation is identified as a payer.
It’s this blend of stealth, strategy, and human manipulation that makes ransomware so difficult to defend against. By the time the encryption begins, attackers have already spent weeks ensuring recovery options are limited. This background isn’t designed to scaremonger, but to highlight why resilience must start long before an attack ever reaches the endpoint.
The Foundations of Ransomware Resilience
Ransomware resilience isn’t achieved through a single product or policy – it’s the outcome of strategic, technical, and cultural alignment. Financial institutions, in particular, must approach it as a continuous process of readiness: Anticipating compromise, containing impact, and restoring normality quickly and transparently:
Assume-Breach Philosophy
The first step is shifting from a defensive mindset to an assume-breach philosophy. In practice, this means recognising that even the most sophisticated systems can and will be breached – and building architectures and response strategies designed to limit damage when this happens. It’s a pragmatic approach, grounded in the reality that attackers are increasingly sector agnostic. No organisation is too small or too secure to be targeted, but the financial sector remains a favourite because it offers both high disruption value and potentially significant monetary reward.
Building meaningful resilience, therefore, demands layered defence and disciplined execution. The goal is to slow attackers down at every stage – detecting them early, limiting lateral movement, and ensuring business continuity when systems are disrupted. Behavioural analytics and continuous monitoring can surface and neutralise subtle anomalies that would otherwise go unnoticed – such as phishing, spear phishing, and malware, with email still the number one entry point for ransomware.
Zero Trust & MFA
Meanwhile, zero trust policies and multi-factor authentication methods add a second layer of protection, blocking unauthorised access even if credentials are compromised.
When incidents do occur, a well-practised response framework ensures action is fast and coordinated, minimising disruption across critical systems, with the ability to switch to secure replica environments to keep operations running while remediation takes place. Secure, immutable, air-gapped backups underpin it all, providing a safety net that guarantees recovery can begin from a clean and uncompromised state.
Human readiness is equally critical. Technology can contain an attack, but only people can recover from one effectively. Regular simulation exercises, incident rehearsals, and cybersecurity awareness training help teams respond calmly and cohesively, transforming response from reactive to instinctive. This operational maturity is reinforced by strong governance. Frameworks such as DORA, NIST, and ISO 27001 provide the structure to align technical teams, compliance leads, and executive decision-makers around shared resilience goals. When combined with skilled practitioners and clear accountability, they embed security into ‘business as usual’ – moving resilience from a strategy to a sustained organisational capability.
Why Multi-Layered Backup is Critical
When ransomware strikes, the speed and integrity of data recovery determine whether disruption lasts minutes or days – and whether the impact cascades through wider global markets. As the last and most decisive line of defence when every other control fails, it’s also fundamental to customer trust and compliance. Yet too often, backup is treated as a static safeguard rather than a dynamic resilience layer.
Since modern ransomware often seeks out and encrypts traditional backups first, a single backup copy or centralised repository is no longer sufficient. True resilience today depends on a multi-layered approach – combining offsite or cloud-diverse storage, immutable data copies that cannot be altered or deleted, and isolated environments to protect against lateral movement.
How frequently these backups are tested is equally important. Too often, financial institutions only discover weaknesses when recovery is already underway, at which point strategies can’t be magically strengthened, and it becomes a race against the clock to minimise downtime and reputational fallout. Regular, automated recovery testing changes that dynamic. It not only confirms that files can be restored, but provides verifiable assurance that systems come back online in the correct order, data dependencies remain intact, and teams have the muscle memory to act quickly and confidently when the worst happens.
The Power of Shared Accountability
In a digital economy so deeply interconnected, no organisation operates in isolation. This is especially true in financial services, where supply chains and service providers form the backbone of day-to-day operations. While this interdependence is a strength in many ways, it also means resilience is no longer defined by how well a single institution can defend itself, but by how effectively every partner in its ecosystem upholds their part of the security chain.
This is where shared accountability becomes critical. It recognises that cloud providers, managed service partners, and financial institutions each have distinct but complementary roles to play in securing data, systems, and infrastructure. When accountability is clearly defined – and when partners collaborate rather than operate in silos – visibility improves, incident response accelerates, and the risk of systemic failure decreases.
Shared accountability also extends beyond contractual obligation. It’s about building a culture of collective readiness: sharing intelligence, rehearsing joint incident scenarios, and supporting smaller or less-resourced partners to raise their security baseline. The result is a unified entity capable of anticipating, absorbing, and recovering from disruption together.
Looking Ahead
To view cyberattacks as inevitable might seem pessimistic to some, but it’s an unfortunate truth that no amount of investment can eliminate risk entirely. In an era where threats are growing in both scale and sophistication, readiness becomes the true differentiator – particularly in such a high-stakes sector. For financial institutions, that means embedding security into culture, strengthening connections across supply chains, and continually testing their ability to withstand and recover as a united ecosystem. Only then can resilience become a strategic advantage rather than a defensive necessity, and unlock the cloud’s transformative potential with absolute confidence.
Ash Gawthorp, CTO and Co-founder of Ten10, on building the right foundations to shape the AI era in the UK
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A recent study shows that UK businesses expect to increase their AI investment by an average of 40 percent over the next two years, following an average spend of £15.94 million this year. With investment surging, the UK is clearly in the fast lane, but the question is whether that momentum will convert into real, durable strength.
This rapid acceleration places the UK at a pivotal moment in its ambition to lead in artificial intelligence. Investment is rising, government focus is strengthening, and organisations across every sector are exploring AI at pace, creating a sense of real momentum. However, anyone who has experienced previous technology cycles will recognise the familiar tension that emerges during periods of rapid progress and optimism. Breakthroughs often attract significant attention and capital before entering a more grounded, sustainable phase.
The pressure today is not on AI as a whole. Instead, it is focused on a specific path, where belief in ever-larger transformer models delivering general intelligence continues to grow. This progress has been remarkable, but it represents only one path within a much broader AI landscape. As excitement reaches its peak, the market will inevitably stabilise. The long-term value will come through robust engineering, strong talent pipelines, and successful deployment in real-world environments.
The task now is to use this moment wisely. Long-term success depends on building deep capability at home, rather than relying on hype or outsourcing key foundations to external providers that sit outside our oversight and control.
The Limits of Scale as Strategy
A significant share of today’s investment is based on the assumption that increasing compute and model size will inevitably lead to artificial general intelligence (AGI). Transformer architectures have delivered extraordinary capability and accelerated progress in ways few predicted. They remain powerful systems for prediction and pattern recognition across language, images and other data.
However, scale is not a guarantee of general reasoning or broad intelligence. Many researchers believe that transformative progress may require developments beyond today’s dominant architecture. If that proves correct, the markets surrounding large closed models will experience a natural cooling. This would be an adjustment based on speculative expectation, not a failure of AI as a discipline. The industry would then shift toward approaches that prize clarity, modularity and measurable outcomes. Engineering discipline and architectural flexibility will matter far more than sheer size.
One Architecture Cannot Become a National Dependency
AI will continue to advance. The question for the UK is whether it builds capability that can evolve alongside that progress, or whether it locks itself to a narrow set of global platforms. A handful of model providers currently influence pricing, model behaviour and development cycles. When enterprises rely entirely on opaque APIs, they inherit changes without knowing why outputs shift, how models adapt or when pricing dynamics move. That introduces fragility that grows over time.
Some experimental use cases can tolerate opacity, but critical public services and regulated industries cannot. Lending, diagnostics, fraud detection and other high-stakes applications demand clarity over how decisions are formed and how logic stands up to scrutiny. In those environments, transparency and auditability shift from abstract ideals to essential operational requirements.
If the UK intends to embed AI deeply into essential systems, it must champion architectures that allow observability, explainability, control and replacement. Dependence on decisions made offshore is not a foundation for long-term strength.
Specialised Agents Reflect How Sustainable Systems Evolve
A practical and resilient approach to AI is already taking shape. Rather than depending on a single model to handle every task, organisations are assembling systems made up of specialised components. This mirrors the way effective teams work, where roles are defined, responsibilities are clear, and handovers are structured. One model transcribes speech, another classifies information, and a third retrieves or summarises content. Each performs a focused function that can be observed, validated and improved.
This modular design makes systems easier to maintain and evolve. New components can be adopted without rewriting entire frameworks. If performance changes or drift appears, individual parts can be evaluated or replaced without widespread disruption. This reflects long-standing engineering principles that value clarity, observability and the ability to substitute components when better options emerge.
Financial efficiency supports this approach as well. Running powerful frontier models for every interaction introduces cost and latency that scale quickly. Task-specific agents can often deliver the same outcome faster and more economically. Across thousands of interactions, the savings and performance gains become significant.
Engineering as the Anchor of Trustworthy AI
As AI becomes embedded in real systems, success relies on foundational engineering practices. Observability, continuous testing, performance monitoring and controlled deployment are essential. These are not new concepts created for AI, but long-established techniques that have been adapted to a new class of technology.
In early exploratory phases, it can be tempting to treat large models as something separate from traditional software systems. However, the moment AI begins to influence real decisions, the fundamentals return. Enterprises must be able to trace behaviour, explain recommendations and ensure consistent reliability, while regulators expect clarity and boards seek evidence-based decisions around technology choices, cost structures and risk.
Organisations that approach AI as engineered infrastructure, rather than a mysterious capability, will be far better equipped to scale safely and confidently.
Building Skills that Make Capability Real
The UK is fortunate to have strong research institutions, a sophisticated regulatory mindset and a robust software talent base. To convert these strengths into durable national advantage, investment in skills must expand beyond narrow data expertise. Data scientists remain crucial, but sustainable AI delivery depends equally on software engineers, cloud specialists, machine learning specialists, testers, governance experts and operational teams who run systems at scale.
Leading organisations recognise that AI delivery is a multidisciplinary effort. As architectures become more modular, value will flow from those who can integrate, monitor and guide AI systems responsibly. The UK must ensure that thousands of professionals have access to this training and experience. Real leadership emerges when capability is widely shared, not concentrated in a small group.
Governance that Accelerates Innovation
Strong governance does not slow innovation. It accelerates meaningful adoption by building confidence. When organisations can demonstrate transparency, control and reliability, AI can extend into more critical functions.
For national strategy, this becomes a competitive advantage. Industries that manage financial and clinical outcomes are not resistant to technology. They simply require evidence that systems behave consistently and transparently. If the UK excels in building AI that is observable, testable and replaceable, trust will grow and adoption will move faster.
Shaping a Resilient AI Future
Every technology cycle begins with excitement and eventually settles into maturity. Those who succeed through this transition are the ones who invest in capability while enthusiasm is high. When the current market resets, leadership will belong to those with engineering depth, system agility, responsible governance and the skills to integrate specialised intelligence across complex environments.
The UK has an opportunity to define this standard. Strength will come from transparency, interoperability and the ability to adapt to model and architecture changes without disruption. It is a quieter strategy than making declarations about imminent artificial general intelligence, yet it builds the resilience required to lead over the long term.
The future will reward systems that can evolve, remain auditable and operate securely at scale. With the right foundation, the UK can shape this era of AI not through scale alone, but through excellence in engineering, governance and talent. That foundation is the true measure of AI power, and now is the moment to build it.
New research from myPOS, the European payments provider for small and medium-sized businesses, reveals that Britain’s shift toward tap-to-pay is leaving…
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New research from myPOS, the European payments provider for small and medium-sized businesses, reveals that Britain’s shift toward tap-to-pay is leaving traditional PIN codes behind. As contactless becomes the country’s top payment preference, almost a third of young adults now admit they can’t remember the four digits once central to everyday spending.
myPOS data reveals 29% of Gen Z struggle to remember, or have completely forgotten, their PIN. Highlighting how digital-first habits are shaping consumer behaviour. However, it isn’t just younger groups that are feeling the effects. One in five Boomers (20%) say they face the same issue as reliance on physical cards significantly declines.
Contactless Payments
This shift has been driven largely by the dominance of contactless card and mobile payments. Over two-thirds of Brits (69%) say tapping, via card, mobile phone, or smartwatch, is now their primary method of payment. In contrast, just 16% rely mainly on chip and PIN, and only 14% primarily use cash. A further 10 % of Brits now live entirely wallet-free, using only their mobile or smartwatch for day-to-day spending.
Convenience-led behaviours are accelerating the decline of PIN usage across the UK. Nearly half of British consumers (47%) say they would happily go completely contactless if it meant shorter queues in shops and venues. Flexibility and convenience (42%) and speed (34%) remain the largest drivers behind the rise of tap-to-pay.
“As the UK embraces contactless and mobile payments, it’s clear that the traditional PIN is becoming less central to everyday transactions. Businesses and payment providers should ensure security and convenience go hand-in-hand, while recognising that consumer habits are evolving rapidly.”
Katja Hakoneva, Product Manager at Tuxera, on delivering tomorrow’s data storage security today
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Smart meters are no longer just data endpoints. They’re intelligent, connected nodes embedded into the national infrastructure. As energy networks undergo rapid digital transformation, the focus has largely been on secure communications and real-time data transmission. But beneath the surface lies the local data storage, which often becomes a critical blind spot.
Smart meters store large volumes of sensitive data from energy usage profiles to firmware logs and grid event histories on embedded memory. If this information is accessed, altered, or deleted, it can trigger billing inaccuracies, regulatory breaches, and customer mistrust. With meters expected to operate in the field for up to 20 years, data-at-rest security is a critical requirement.
Storage Vulnerabilities: The Silent Cyber Threat
These embedded systems face multifaceted risks. Attackers may gain access to stored data by physically tampering with a meter or exploiting software vulnerabilities that bypass weak authentication. Malicious actors could manipulate logs to alter billing records, mislead consumption analytics, or mask larger cyberattacks on grid infrastructure.
In many cases, such intrusions go undetected until tangible damage, such as lost revenue or reputational fallout. With increasing dependence on smart infrastructure, utilities can no longer afford to treat embedded storage as a passive component.
Counting the Real Costs of Cybersecurity
Securing smart meters comes with technical requirements, as well as, operational and resourcing demands. For many UK manufacturers and utilities, managing cybersecurity internally means building and retaining specialist teams, often requiring three to five full-time professionals to handle vulnerability monitoring, patch management, and threat response throughout the year.
Aligning with regulatory frameworks frequently demands hardware upgrades to handle stronger encryption and secure configurations, impacting Bill of Materials (BOM) costs and development timelines. Many existing software stacks require optimisation to support modern security protocols within resource-constrained devices. These efforts are necessary, with a single undetected cyberattack costing companies an average of $8,851 (≈£6,900) per minute, and the consequences extending beyond financial loss to potential regulatory fines and service disruptions.
The CRA and the new Era of Cyber Regulation
The Cyber Resilience Act (CRA), set to come into force across the EU by 2027, will reshape how connected devices are designed, developed, and supported. For UK-based vendors serving the European market, or collaborating with EU counterparts, compliance with CRA is becoming a strategic imperative.
Key CRA requirements include:
Security by design: Devices must be secure from the outset, not retrofitted post-deployment.
No known vulnerabilities at market launch: Products must undergo security validation prior to release.
Default secure configurations: Devices should avoid insecure settings out of the box.
Lifecycle management: Vendors must support patching and vulnerability resolution throughout the device’s operational lifespan.
For smart meters, which often run in the field for two decades or more, the CRA introduces accountability that extends well beyond product launch. Compliance with the CRA will become part of the CE marking process, meaning global manufacturers must align if they wish to sell into the EU energy market.
Engineering Security: Confidentiality, Integrity, and Authenticity
Designing resilient smart meters starts with three pillars:
Confidentiality protects sensitive user data from unauthorised access. This includes encrypting both data and encryption keys, restricting user access levels, and securing communication channels.
Integrity ensures stored data remains unaltered and trustworthy. Power failures, for instance, can corrupt memory. Using flash-optimised file systems and secure boot processes can prevent such vulnerabilities.
Authenticity confirms that firmware and data updates come from trusted sources. Techniques like digital signatures and update validation prevent attackers from injecting malicious code into meters.
Together, these pillars enable smart meters to meet regulatory expectations while protecting both users and grid operations.
Future-proofing Data Storage
Cybersecurity for smart meters is not just a feature; it requires organisational readiness. Frameworks like the CRA, NIST, and IEC 62443 emphasise secure processes, documentation, and people alongside secure products.
For companies looking to prepare, it is smart to start with common pillars such as maintaining up-to-date Software Bills of Materials (SBOMs), conducting regular supply chain and risk assessments, keeping detailed test reports, and establishing clear incident response plans. Internally, training staff on cybersecurity best practices, setting clear data retention policies, and defining access controls and responsibilities are critical steps to ensure cybersecurity is embedded within the culture of the organisation. This approach ensures security is not a one-off compliance task but a sustainable practice that protects smart infrastructure long-term.
Smart meters deployed today could still be operating in the 2040s. This timeline intersects with the anticipated emergence of quantum computing, which may break today’s encryption standards. Though post-quantum cryptography is still evolving, vendors must prepare now to ensure systems remain secure in a post-quantum world. Smart meter software should be designed with cryptographic agility to allow it to adapt and upgrade algorithms as threats evolve.
Lessons from Long-Term Deployment
Smart meters are designed for longevity, but memory wear remains a primary failure point. Meters that lack flash-aware storage systems face early data loss, increasing the cost of maintenance, replacements, and warranty claims.
Utilities and OEMs that embed file systems capable of wear levelling, garbage collection, and secure boot processes have extended meter lifespans by more than 50%, even in challenging conditions. One example showed meters surviving over 15,000 power interruptions without any data loss.
Integrating secure storage delivers operational and commercial benefits. It ensures compliance with CRA and other evolving global frameworks, reduces maintenance and warranty costs, minimises carbon impact through fewer replacements, enhances brand credibility and trust with procurement teams, strengthens the business case for longer-term contracts and partnerships. As the smart energy market matures, these benefits are becoming differentiators, especially as digital infrastructure grows in complexity.
Delivering Tomorrow’s Data Storage Security Today
The next generation of smart infrastructure will be fast and connected, as well as, secure, resilient, and regulation-ready. For vendors and utilities alike, embedding data protection deep into the meter architecture is a business-critical move.
By preparing for the CRA today, smart meter manufacturers will position themselves as forward-thinking, trustworthy partners in tomorrow’s energy ecosystem, delivering technology that’s not only built to last but built to protect today and tomorrow.
Michael Ault, Country Manager at integrated payments specialists myPOS, offers strategic advice for SMEs looking to scale through digital transformation and diversification
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Scaling a small business is one of the most rewarding, yet complex journeys for any entrepreneur. While growth brings opportunities for greater reach, higher revenue, and stronger market presence, it also demands foresight, discipline, and the ability to manage risk strategically. Securely integrating new technology is the main obstacle for 47% of SME’s, even though 76% of these businesses intend to expand their IT investment. This underscores a key point of tension, as many businesses want to grow through digital transformation but struggle to do so securely and sustainably.
The business landscape continues to evolve with changing customer expectations, technology, and economic conditions. For UK SMEs, the key to long-term success lies in achieving growth but also in building resilience. Sustainable scaling comes down to three principles: embracing technology pragmatically, diversifying intelligently, and investing in people and partnerships that strengthen resilience.
Leveraging Digital Transformation
Digital transformation is the foundation of business growth, especially for small business. Cloud-based solutions, automation, and data analytics help to streamline operations, reduce inefficiencies, and create better customer experiences. However, transformation must be purposeful, not performative.
The smartest approach is to scale technology investment incrementally, integrating flexible, modular systems that evolve with business needs. This approach not only lowers risk but also helps ensure digital maturity evolve over time. When SMEs use modular, cloud-based technology, operations run more smoothly and changes can be effectively analysed. Ultimately, resilience is not built through one-time upgrades but through a culture of continuous digital evolution.
Diversifying Revenue Streams
Depending on a single product, service, or market leaves a business vulnerable to sudden changes in demand. Diversification, when guided by customer insight and data can turn volatility into opportunity. Expanding into online sales, introducing subscription models, or targeting fresh customer segments can make income streams much more stable and sustainable.
At myPOS, we know that even simple changes based on data, such as adding additional payment options or tapping into cross-border e-commerce, can help cash flow and protect against market shocks. The goal of technology is to mitigate specific challenges without adding layers of complexity.
Investing in Employee Development
Your people are pivotal to your ability to grow as a business; empowered teams are the engine of sustainable scale. A team that feels supported and motivated will bring fresh ideas, adapt to challenges, and push the business forward. Investing in training, mentoring, and development opportunities builds skills that pay back in the form of innovation and improved performance.
In fast-changing industries, having employees who are confident in learning and adapting can make the difference between struggling through disruption and taking advantage of it. Equally, strong partnerships extend this resilience beyond the organisation. Building resilience at the team level creates resilience for the whole business, so fostering a culture of continuous learning and celebrating employee contributions is key to maintaining motivation.
Focusing on Financial Health and Flexibility
Financial resilience underpins sustainable growth. Scaling often requires upfront investment, and without healthy cash flow or reserves, opportunities can be lost. Monitoring income and expenses closely, cutting unnecessary costs, and preparing for seasonal fluctuations gives businesses more control.
Having flexible financing options, like credit lines, small business loans, or even crowdfunding, provides a level of agility. Instead of being caught off guard by unexpected challenges, businesses with financial flexibility are positioned to respond quickly and strategically.
Financial management software can make it easier to track performance, spot issues early, and forecast future needs. When you can see your finances in real time, you can make proactive, data-driven decisions instead of waiting for problems to happen. In markets that change quickly, this kind of financial management helps small firms plan with confidence, stay flexible, and establish a stronger base for long-term growth.
Prioritising Customer Relationships and Feedback
Your customers are not just buyers; they are advocates, sources of insight, and the foundation of repeat business and brand loyalty. Businesses that scale successfully often place customer relationships at the heart of their strategy by actively gathering feedback, responding quickly to issues, and personalising interactions, which shows customers they are valued.
This loyalty becomes a form of resilience. In periods of uncertainty, a base of satisfied, returning customers provides more stability than constantly chasing new ones. Successful businesses use CRM tools to track customer preferences and automate follow-ups so no opportunity to strengthen a relationship is missed.
Building Strategic Partnerships
Partnerships can accelerate growth while also spreading risk. Working with other businesses, organisations, or influencers can provide access to new audiences, shared expertise, or additional resources. Collaboration can also create opportunities for joint marketing, co-branded initiatives, or innovative product and service offerings.
In times of uncertainty, strong partnerships act as a support network. By aligning with others who share your values and vision, you create opportunities that are mutually beneficial and more resilient than going it alone. It is important to find partners whose goals and audiences complement your own for the best long-term impact.
The next stage of small business success will be defined by resilience rather than speed, the ability to adapt, recover, and continue to create value in the fact of uncertainty. For SMEs, this means developing adaptable growth plans that include flexible technology, diverse models and empowered employees.
Ben Goldin, Founder and CEO of Plumery, explores the key banking trends for 2026 – from fraud and digital assets to stablecoins and AI applications
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As we head into the second half of the decade, several emerging trends will come to the fore in 2026. The interconnectedness among these trends is also noteworthy. Artificial intelligence (AI) and progressive modernisation act as common threads.
A strong current throughout 2026 is the shift from customer-first banking to human-first banking. This relates to the concept of ethical banking. It focuses on creating financial services that have a positive social and environmental impact.
Human-first banking aims to get even closer to the customer by understanding their actual human needs, rather than just consumer needs. For example, a bank should be acting as a coach to improve a customer’s financial health, not solely as an advisor on which products they should buy. Banks can build trust in a digital world through tailored and empathetic interactions, effectively simulating the experience customers formerly had with their personal banker.
To attain that level of hyper-personalisation, banks will need to be capable of processing vast amounts of transactional data, which can only be accomplished by deploying AI and big data tools. This requirement, in turn, will turbocharge progressive modernisation, another trend that has been bubbling under the surface for the past few years.
Traditional banks are using progressive modernisation to deal with legacy infrastructure that is not fit for purpose in a digital-first, AI-driven world. Instead of a big bang replacement of core banking systems, which is risky and can take years, banks are creating change from within existing architecture. Banking is leveraging technologies that support a multi-core strategy. With this approach, banks can add new cores for specific products that require greater agility and innovation. Modern cores are necessary for deploying the latest AI and big data tools because they provide a unified, real-time data foundation to deliver hyper-personalisation.
Fraud Threats
Fraud will remain a top concern throughout 2026. Adversaries use AI to expand the range of techniques, such as impersonation scams and identity theft, as well as accelerate and scale fraudulent activity.
According to the UK Finance Half Year Fraud Report 2025, £629.3 million was stolen by criminals in the first six months of this year, and there were 2.09 million confirmed cases across both authorised and unauthorised fraud. Card not present cases rose 22% to 1.65 million and accounted for 58% of all unauthorised fraud losses.
However, the good news is that there was a 21% increase in prevented card fraud in the first half of 2025. The £682 million which was stopped from being stolen is the highest-ever figure reported.
To combat fraud, new and improved tools to help banks identify, verify and onboard customers will come to market in 2026. The move away from paper-based identity (ID) and widespread adoption of digital ID will play a key role in the fight against fraud. Hence the UK government’s recently announced plans to roll out a new digital ID scheme.
In addition, I expect to see a fundamental shift in fraud detection using real-time behavioural analytics, data analytics for proactive risk identification, and other applications of AI and machine learning in this space.
Digital Assets and Stablecoins
Digital ID verification is also essential for fighting fraud in the digital assets and stablecoins space. Another hot topic at several banking and payments industry conferences last year.
In 2026, digital assets and stablecoins will become much more mainstream. Banks have left the sidelines and are now actively engaged with running pilots. For example, in September a consortium of nine European banks, including CaixaBank, ING and UniCredit, announced an initiative to launch a euro-denominated stablecoin.
Central banks and regulators are developing a comprehensive agenda for digital assets. Banks will need to blend traditional fiat currencies and assets with their digital counterparts. This trend is also driving a progressive modernisation approach, as legacy core banking systems weren’t designed to manage digital assets, nor do they support moving money via blockchain-based rails. I expect to see more banks looking to deploy a multi-core strategy where digital assets are managed and stored elsewhere, but they can still provide a seamless and unified experience to customers.
AI
Last year, I predicted that the industry would adopt a ‘meet-in-the-middle’ approach to AI, with banks beginning to uncover the real value that the technology can deliver. I also predicted consolidation, recalibration and stabilisation in the market.
GenAI Banking Applications
My predictions held true, by and large. In 2025, institutions explored what is possible, relevant and achievable within the banking context, then specifically for each individual institution within its legacy architectures and technological environments.
This trend will evolve into more practical actions and initiatives over the next 12 months to provide greater clarity around where GenAI shines versus where it’s not applicable.
To gain clarity, it’s important to understand the difference between AI and GenAI. The latter is built on stochastic principles, which uses probability to model systems that appear to vary in a random manner. This means that the same input could potentially generate different outputs – this isn’t acceptable for automated financial operations, which requires much more determinism. Hence, I believe that GenAI will be used chiefly in scenarios where there’s human intervention.
One area where GenAI is applicable is in conversational applications. For example, banks will begin launching more interactive user interfaces. Customers will be able to interact with the bank as they would a human. Moving beyond simple, frequently asked questions to actual actions.
GenAI in the Back Office
Similarly in the back office, banks can leverage GenAI to provide guidance to their employees and accelerate certain tasks. Using the technology to improve efficiency and help staff do more will have a positive impact on customer experience. Processes will take much less time.
It will also help to bring unbanked segments or non-standard customers, which are difficult and costly to onboard because they require a bespoke assessment, into regulated financial services. Applying GenAI can make the bespoke process much more efficient by providing data-driven insights to support faster and smarter decision-making. This will make it much cheaper to serve these segments. Including smaller and medium-sized enterprises, which will drive financial inclusion and improve customers’ financial health.
Fawad Qureshi, Global Field CTO, Snowflake, on realising possibilities for innovation in this new AI era
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Without cloud migration, businesses face the end of innovation. In this new AI era, businesses operating within the closed architectures of legacy systems do not have the flexible, data-driven foundation to engage with these new technologies and ensure a strong pipeline of necessary innovation. And as AI continues to evolve, those not able to keep pace with innovation risk being left behind.
Cloud migrations are the foundation to modernise and drive business growth over the long term. When organisations migrate to a cloud-based environment, it’s crucial to focus on the tangible business value a migration will deliver, rather than simply shifting from one system to another. Moving a company’s customer-facing applications and all of their data to a cloud-based environment has the benefits that are increasingly real and measurable.
Migration isn’t just a Plug and Play approach – Which migration fits your needs?
There are two approaches to cloud migration, broadly speaking: horizontal and vertical, each with their own benefits and potential challenges. A vertical approach sees organisations migrating applications one by one: this approach is a good choice if certain systems have to be prioritised, or if the applications being migrated do not have many interdependencies. Vertical migration allows for focused efforts and risk management on individual systems, and requires fewer resources. Horizontal migration moves entire system layers at the same time. This is the best solution when businesses have tight deadlines to retire legacy systems, or if their systems are tightly integrated. Horizontal migrations tend to be faster by allowing for parallel work streams, but they require more technical expertise.
Organisations often adopt a mixture of the two approaches, for example, horizontally migrating important systems such as data platforms, while taking a vertical approach to customer-facing applications. Whatever approach an organisation takes, it’s vital that the migration also includes a culture shift, preparing employees to adapt to new, consumption-based models and the possibilities of the new technology. Migration is also just the start of the journey, unlocking the potential of AI-driven use cases and seamless data collaboration, including new ways to achieve business value.
Before diving straight in, ensure it’s with a Data-First Mindset
When migrating to the cloud, a data-first approach is essential. For those acting as the catalyst for change, whether that be IT managers or even CIOs, data must be front of mind before planning any successful migration. Understanding how data is used within the organisations, including its structure, governance needs, and how it delivers value and business outcomes, is imperative. This applies doubly when it comes to large, complex systems with many interconnected applications.
Before migrating, businesses must comprehensively assess their current ecosystem. It’s imperative that the end-to-end business product survives the migration, intact. Organisations should maintain internal control over core competencies around data, such as business process knowledge, data governance and change management. These areas include institutional knowledge that external parties may not grasp. Businesses should also maintain direct oversight over compliance requirements and risk management.
Technical activities such as cloud infrastructure optimisation, performance testing, and specialised migration tooling are something, by contrast, that can be handled by external expertise. Code conversion can also benefit from purpose-built tools that use technologies including AI. Technical parts of the immigration tend to evolve rapidly and require specialist knowledge, so are ripe for outsourcing. While doing so, those steering the migration need to ensure clear governance around outsourced activities, including regular knowledge transfer sessions.
Different parts of the business all have a role to play: IT and engineering lead on technical implementation, handling the technical side of business requirements, while finance will identify ROI opportunities and manage cloud costs. It helps to create a cross-functional steering committee with representation from every department to ensure that different areas of the business are aligned and ready to address challenges.
Adaptability and Flexibility is the key to business longevity
Migration is never one-size-fits-all, and business leaders should be prepared to be flexible and adapt. There are multiple kinds of horizontal migration, from a simple ‘lift and shift’ focused on moving systems as they are to a ‘move and improve’ where migration is followed by optimisation to reduce technical debt. They should be ready to adapt at their own pace, choosing data platforms which offer agnostic architecture and the freedom to choose between data models and tools to ensure minimal disruption.
Flexibility is also important in choosing the tools used for migrations. Flexible data platforms will offer the support businesses need to deal with collaboration and governance frameworks. For businesses operating in EMEA, where different countries can have varying policies, pay close attention to issues around data quality, security and compliance, particularly when it comes to data sovereignty and issues around European data residency.
A Shared Destiny
The shift to the cloud fundamentally changes security. The traditional cloud ‘shared responsibility’ model clearly demarcated duties between the provider and the customer. However, a more advanced approach is emerging: the ‘shared destiny’ model. This model recognises that in the event of a breach, reputational damage affects both parties. This shared risk incentivises the cloud provider to be a more proactive partner, actively helping customers strengthen their security posture rather than simply managing their own side of the demarcation line.
As ‘destinies’ intertwine, you help eliminate the vulnerability created due to password simplicity. Put simply, in a ‘shared responsibility’ model, the cloud provider is only responsible for securing infrastructure, while the customer remains responsible for securing data and apps in the cloud, as well as for configuration. In a ‘shared destiny’ model, the cloud provider plays a more proactive role to ensure that their customers have the best possible security posture.
Taking a ‘shared destiny’ approach allows businesses to be more proactive in securing data, using approaches such as multi-factor authentication, secure programmatic access and more comprehensive cloud monitoring services. Choosing a modern, AI-driven data platform offers the best security foundations here, offering security controls across cloud service providers and the entire data ecosystem.
A Pathway to Growth
In today’s world, the bigger risk is standing still. Nothing changes if nothing changes.
If organisations are holding back on innovation due to technological limitation, then the time to migrate is clear. There is no need to face an end to possibilities when the path towards success lies in reach, offering an opportunity to bring businesses up to date with modern requirements, and pave the way for the adoption of technologies such as AI.
However, as we’ve seen, it’s not just a case of plug and play. Organisations must ensure a flexible, data-driven approach to migration, while keeping security front of mind via a ‘shared destiny’ approach. To deliver this, the right choice of a modern, flexible data platform will ensure the whole organisation can work together effectively and deliver a path to future innovation and growth.
Robert Cottrill, Technology Director at digital transformation company ANS, explores how businesses can harness the potential of AI while mitigating the growing risks to cybersecurity and privacy
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AI can transform businesses, but is it also opening the door to cyber risks? Fuelled by competitive pressure and rising government support through the UK’s Industrial Strategy, it’s no surprise that more and more businesses are racing to adopt AI.
But there’s a catch. The more businesses scale their AI adoption, the bigger their attack surface becomes. Without a proactive and structured approach to securing AI systems, organisations risk trading short-term efficiencies for long-term vulnerabilities.
The AI Boom
AI investment is skyrocketing. Businesses are deploying generative AI tools, machine learning models, and intelligent automation across nearly every function, from customer service and fraud detection to supply chain optimisation. Platforms like DeepSeek and open-source AI models are now part of the mainstream tech stack.
Initiatives like the UK’s AI Opportunities Action Plan are fuelling experimentation and adoption. AI is now seen not just as a productivity tool, but as a critical lever for digital transformation.
However, the rapid pace of AI deployment is outpacing the development of the security frameworks required to protect it. When integrated with sensitive data or critical infrastructure, AI systems can introduce serious risks if not properly secured. These risks include data leakage through AI prompts or model training, as well as AI-generated phishing and social engineering attacks
While technical threats often take centre stage, businesses also can’t forget the increasing regulatory requirements surrounding AI. As AI systems become more powerful, enabling businesses to extract valuable insights from vast datasets, they also raise serious ethical and legal challenges.
Regulatory frameworks like the EU AI Act and GDPR aim to provide guardrails for responsible AI use. But these regulations often struggle to keep up with the rapid advancements in AI technology, leaving businesses exposed to potential breaches and misuse of personal data.
The Need for Responsible AI Adoption
To build resilience while embracing AI, businesses need a dual approach:
1. Prioritise AI-specific training across the workforce
Cybersecurity teams are already stretched. Introducing AI into the mix raises the stakes. Organisations must prioritise upskilling their cybersecurity professionals to understand how AI can both protect and threaten systems.
But this isn’t just a job for the security team. As AI tools become embedded in daily workflows, employees across functions must also be trained to spot risks. Whether it’s uploading sensitive data into a chatbot or blindly trusting algorithms, human error remains a major weak point.
A well-trained workforce is the first and most crucial line of defence.
2. Adopt open-source AI responsibly
Another key strategy for reducing AI-related risks is the responsible adoption of open-source AI platforms. Open-source AI enhances transparency by making AI algorithms and tools available for broader scrutiny. This openness fosters collaboration and collective innovation, allowing developers and security experts worldwide to identify and address potential vulnerabilities more efficiently.
The transparency of open-source AI demystifies AI technologies for businesses, giving them the confidence to adopt AI solutions while ensuring they stay alert about potential security flaws. When AI systems are subject to global review, organisations can tap into the expertise of a diverse and engaged tech community to build more secure, reliable AI applications.
To adopt responsibly, businesses need to ensure that the AI they are using aligns with security best practices, complies with regulations, and is ethically sound. By using open-source AI responsibly, organisations can create more secure digital environments and strengthen trust with stakeholders.
Securing the Future of AI
AI is a transformative force that will redefine cybersecurity. We’re already seeing AI being used to automate threat detection and response. But it’s also powering more advanced attacks, from deepfake impersonation to large-scale automated exploits.
Organisations that succeed will be those that embed cybersecurity into every stage of their AI journey, from innovation to implementation. That means making risk management part of the innovation conversation, not a downstream fix.
By taking a responsible approach, investing in training, leveraging open-source AI wisely, and embedding cybersecurity into every layer of the business, organisations can unlock AI’s potential while defending against its risks.
AI is a double-edged sword, but with thoughtful adoption, businesses can confidently navigate the complex landscape of AI and cybersecurity.
Can Taner, Chief Product Officer at Bitpace, analyses the most important shifts in the crypto and payments landscape
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The crypto industry has entered a phase of unbundling. Instead of one-size-fits-all platforms that try to do everything, businesses are looking to specialised providers that solve real-world problems with focus and precision. This shift defines how leading firms now build products: client-first, agile, and compliance-ready by design.
Solving Real Problems with Real Products
The key to building effective crypto payment solutions is understanding what businesses actually need. Payments should help companies operate faster, more efficiently, and at lower cost. Rather than chasing every trend, the focus should be on creating tools that remove friction and add measurable value.
That’s why many providers now offer modular solutions designed to work seamlessly across industries:
Payment gateway – enabling merchants to accept crypto securely, with instant conversion to fiat if needed, reducing volatility risk.
Global settlements – allowing businesses to move funds cross-border quickly and cost-effectively, bypassing traditional bottlenecks.
API integration –giving partners the tools to embed crypto payment functions directly into their platforms, delivering a frictionless experience for end-users.
OTC services –providing access to large-scale crypto trades, executed with discretion, high liquidity, and competitive pricing.
Each product is tailored to solve a specific pain point. Instead of bundling everything into a rigid system, we focus on flexible modules that businesses can adopt individually or together.
Agility and Expertise in Product Development
For providers, being specialised also means being agile. Every client problem requires a different approach, and in-house expertise allows them to respond quickly without compromising quality. From compliance to sales to product development, teams must collaborate to find creative solutions that meet the highest regulatory and technical standards.
This agility is only possible if they invest in deep domain knowledge. Product and engineering teams that understand the nuances of payments, crypto, and regulation can adapt quickly to market changes while keeping compliance at the core of every decision.
How to Launch New Products Effectively
Launching a new product in crypto, or any fast-evolving sector, demands structure and discipline. The most successful teams follow a process that balances creativity with rigour.
Start with ideation. Listen closely to client feedback, analyse emerging trends, and identify where the market still falls short. Great products don’t begin with technology, but with a clear problem to solve.
Do the research. Test assumptions early, model potential use cases, and validate compliance requirements before writing a single line of code. A strong evidence base prevents costly pivots later.
Plan collaboratively. Bring product, legal, compliance, sales, and technology teams together from the outset. Aligning goals across functions ensures that innovation doesn’t come at the expense of security or scalability.
Build with resilience in mind. Security, interoperability, and performance should be built into the product from day one, not retrofitted at the end.
Test thoroughly. Create safe environments to simulate real-world conditions and identify weaknesses before launch. Testing isn’t just a single step, but an ongoing cycle.
Launch deliberately. Roll out in phases, gather user feedback, and support early adopters closely. A careful launch builds trust and sets the stage for sustainable growth.
Each of these stages is designed to reduce risk, accelerate learning, and maximise long-term value, principles that define successful product development in today’s crypto landscape.
How Specialisation Wins
Launching products in crypto is about precision and collaboration. The great unbundling of crypto is rewarding those who specialise, focusing on solutions that solve real business challenges. Specialised providers win because they put the client first. That focus on expertise and flexibility is what defines success in the new era of crypto payments.
Joe Logan, CIO at iManage, on the need to avoid the hype, manage cybersecurity, focus on ROI and balance change management to get the best results with AI
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Across the enterprise, AI promises transformational power – however, it’s not as simple as just plugging it into the organisation and instantly reaping the benefits. What are some of the top things CIOs need to focus on to avoid any pitfalls, unlock its value, and best position themselves for success with AI?
1) Separate the Hype from Reality
Here’s what hype looks like: using AI to “radically transform the way you do business” or to “accelerate comprehensive digital transformation” or – heaven forbid – to “completely change our industry.” These are big statements – and absolutely dripping with hype.
Getting real with AI requires identifying specific use cases within the organisation where a particular type of AI can be deployed to achieve a specific goal. For example, maybe you want to reduce customer churn by 20% and have identified an opportunity to use chatbots powered by large language models to provide more effective customer service. That’s what reality looks like.
In separating the hype from reality, organisations gain the added benefit of clearing up any misconceptions – at any level of the organisation – about what AI can and can’t do, thus performing an important “level set” around expectations.
2) Understand the Implications for Cybersecurity
On one side, any AI tool you’re using has access to data, and that means that access needs to be controlled like any other system within your tech stack. The data needs to be secured and governed, and issues around privacy, sovereignty, and any other regulatory requirements need to be thoroughly addressed.
As part of this effort, organisations also need to be aware of the security measures required to protect the AI model itself from bad actors trying to manipulate that model. For example: prompt injection – inputs that prompt the model to perform unintended actions – can affect the model and its responses if not carefully guarded against.
Securing your AI system is one side of the coin; the other side is understanding how to apply AI to cybersecurity. There are a growing number of use cases here where AI can help identify risks or vulnerabilities by analysing large amounts of data, helping organisations to prioritise the areas they need to focus on for risk mitigation.
In summary? While any usage of AI will require you to “play defence” on the security front, it will also enable you to “play offence” more effectively. In that sense, AI has multiple implications for cybersecurity.
3) Focus on the Right Kind of ROI
When it comes to ROI for any AI investments, don’t narrowly focus on absolute numbers when it comes to metrics like time savings or cost savings. While well-suited to industrial workplaces that are churning out widgets every day, absolute numbers can be an awkward fit when applied to a knowledge work setting.
The advice here for any knowledge-centric enterprise is: Don’t get hung up on the idea of actual dollars and cents or a specific number – instead, look for a relative improvement from a baseline. So, rather than saying “We’re going to reduce our customer acquisition costs by $100,000 this year”, it’d be more appropriate to focus on reducing existing customer acquisition costs by 10%. Likewise, don’t focus on each junior associate in the organisation completing five more due diligence projects per calendar year; look to complete due diligence projects in 30% less time.
4) Give Change Management its due
Change management has always mattered when it comes to introducing new technology into the enterprise. AI is no different: Successful adoption requires a focus on people, process, and technology – with a particular emphasis on those first two items.
A major challenge is educating the workforce with an eye towards improving their AI literacy – essentially, enabling them to understand what’s possible and how they can apply AI to their daily workflows.
Know that a centralised model of control that dictates “this is how you can experiment with AI” is probably going to be ineffective. It will be too stifling for innovative individuals in the organisation. Far better to provide centres of excellence or educational resources to those people who are most inclined to take the initiative and move forward with AI experiments in their team or department.
One caveat here: It’s essential to have guardrails in place as teams and individuals experiment with AI, to prevent misuse of the technology. That’s the tightrope that CIOs need to walk when introducing AI into the organisation. Striking the right balance between “total control” and “freedom to explore, but with appropriate oversight and guardrails”.
The Future of AI Depends on what CIOs do next
The promise of AI is massive, but only if CIOs adopting the technology focus on the right areas. And that means filtering out the hype, keeping security implications top of mind, redefining ROI, and guiding change with a steady hand. By paying attention to these areas, CIOs can safely navigate a path forward with AI. And ensure that it isn’t just a technology with promise and potential, but one that delivers actual enterprise-wide impact.
Ben Francis, Insurance Lead at Risk Ledger, on navigating cyber threats by reinforcing security from the inside out
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Cyber insurance has evolved from a straightforward risk transfer mechanism into an integral component of enterprise risk strategy. As a result, the conversation has shifted beyond simply securing coverage to embracing three foundational elements: transparency in risk exposure, accountability for security measures, and active collaboration throughout the digital ecosystem.
Rather than asking ‘are you covered?’, the more pertinent question has become ‘can you demonstrate measurable risk reduction?’. Insurers and insureds alike are recognising that what matters now is how well an organisation understands and manages its digital exposure, especially across its extended supply chain. Recent data reveals that 46% of organisations experienced at least two separate supply chain-related cyber incidents in the past year, a clear sign that exposure often lies beyond direct control.
From Risk Transfer to Risk Visibility
In recent years, the cyber insurance market has matured significantly. Once viewed as a reactive safety net to cushion the financial impact of attacks, it is now becoming a proactive tool for managing and mitigating risk. This shift is partly driven by insurers, who increasingly expect and work with organisations to demonstrate strong security practices and a nuanced understanding of their threat landscape, including risks deep within their digital supply chains; an area where many businesses still fall short.
At the same time, the industry faces a growing challenge from systemic cyber risk within their portfolios, as many businesses rely on the same cloud providers, payment systems and digital platforms, increasing the chance of a single point of failure. Insurers must gain visibility into how policyholders are connected, not only to suppliers but to each other. Tools and frameworks that map and monitor these interconnections will be essential to avoid underestimating the wider impact of seemingly isolated cyber events.
Mapping Beyond Third Parties
It is no secret that cyber attackers often target the weakest link in a supply chain. These are not always direct suppliers, but fourth, fifth or even sixth-tier vendors that have indirect but critical access to systems and data. Unfortunately, many organisations lack visibility beyond their first tier, creating blind spots that attackers can easily exploit. From an insurance perspective, this presents a clear challenge. If an organisation cannot account for who it is connected to, it cannot adequately quantify its risk and neither can its insurer. Mapping these extended connections is more than just a technical exercise; it means actively practiced risk governance and responsibility. Insurers increasingly want to know how their policyholders are identifying and managing indirect dependencies, particularly in sectors like financial services and retail where disruption can ripple across entire markets.
Collaboration as a Risk Strategy
One of the more underappreciated aspects of cyber resilience is the role of peer collaboration. Unlike physical incidents, cyber threats rarely exist in isolation. A single compromised vendor can impact multiple organisations simultaneously, a fact that has been highlighted by high-profile supply chain attacks such as SolarWinds and MOVEit.
As a result, businesses need to think beyond their own perimeters and adopt a more collective mindset. This includes building relationships with industry peers, sharing threat intelligence and participating in sector-wide initiatives aimed at improving visibility and preparedness.
In highly regulated sectors, such as insurance, this collaboration is increasingly being encouraged by oversight bodies. Frameworks like the Digital Operational Resilience Act (DORA) in the EU and initiatives from the Prudential Regulation Authority (PRA) and the Financial Conduct Authority (FCA) in the UK are pushing for more transparency around third-party risk. In this context, openness is no longer optional; it will be a regulatory expectation.
For insurance providers, greater collaboration between policyholders also means better data on emerging threats and more accurate portfolio management. For businesses, it offers a chance to anticipate vulnerabilities that may not yet have hit their own networks but are affecting others in their industry.
Proactive Transparency Builds Trust
Organisations that take a proactive, transparent approach to cyber risk management are more likely to secure cover and potentially favourable terms, not just in terms of premiums, but also in access to additional services such as forensic support, incident response sources and legal counsel.
Demonstrating a mature cyber posture is not about claiming perfection. No organisation is immune to breaches. What insurers are looking for is evidence of a structured approach: the existence of incident response plans, robust governance, effective supply chain risk management, and above all, an honest view of risk.
A Shift in Mindset
Ultimately, our understanding of cyber insurance must keep evolving. It should not be treated as a simple checkbox exercise, but as a collaborative relationship between insurers and the organisations they support – one built on shared insight, clear communication, and a drive for continuous improvement.
The organisations best equipped to navigate today’s threats will be those that prioritise transparency. Not only does it lead to stronger protection, but it also builds a culture of accountability that reinforces security from the inside out.
Vertiv expects powering up for AI, Digital Twins and Adaptive Liquid Cooling to shape future Data Centre Design and Operations
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Data Centre innovation is continuing to be shaped by macro forces and technology trends related to AI, according to a report from Vertiv, a global leader in critical digital infrastructure. The Vertiv™ Frontiers report, which draws on expertise from across the organisation, details the technology trends driving current and future innovation, from powering up for AI, to digital twins, to adaptive liquid cooling.
“The data centre industry is continuing to rapidly evolve how it designs, builds, operates and services data centres, in response to the density and speed of deployment demands of AI factories,” said Vertiv chief product and technology officer, Scott Armul. “We see cross-technology forces, including extreme densification, driving transformative trends such as higher voltage DC power architectures and advanced liquid cooling that are important to deliver the gigawatt scaling that is critical for AI innovation. On-site energy generation and digital twin technology are also expected to help to advance the scale and speed of AI adoption.”
Extreme densification – accelerated by AI and HPC workloads; gigawatt scaling at speed – data centres are now being deployed rapidly and at unprecedented scale
Data centre as a unit of compute – the AI era requires facilities to be built and operated as a single system
Silicon diversification – data centre infrastructure must adapt to an increasing range of chips and compute
The report details how these macro forces have in turn shaped five key trends impacting specific areas of the data centre landscape.
1. Powering up for AI
Most current data centres still rely on hybrid AC/DC power distribution from the grid to the IT racks, which includes three to four conversion stages and some inefficiencies. This existing approach is under strain as power densities increase, largely driven by AI workloads. The shift to higher voltage DC architectures enables significant reductions in current, size of conductors, and number of conversion stages while centralising power conversion at the room level. Hybrid AC and DC systems are pervasive, but as full DC standards and equipment mature, higher voltage DC is likely to become more prevalent as rack densities increase. On-site generation, and microgrids, will also drive adoption of higher voltage DC.
2. Distributed AI
The billions of dollars invested into AI data centres to support large language models (LLMs) to date have been aimed at supporting widespread adoption of AI tools by consumers and businesses. Vertiv believes AI is becoming increasingly critical to businesses but how, and from where, those inference services are delivered will depend on the specific requirements and conditions of the organisation. While this will impact businesses of all types, highly regulated industries, such as finance, defence, and healthcare, may need to maintain private or hybrid AI environments via on-premise data centres, due to data residency, security, or latency requirements. Flexible, scalable high-density power and liquid cooling systems could enable capacity through new builds or retrofitting of existing facilities.
3. Energy autonomyaccelerates
Short-term on-site energy generation capacity has been essential for most standalone data centres for decades, to support resiliency. However, widespread power availability challenges are creating conditions to adopt extended energy autonomy, especially for AI data centres. Investment in on-site power generation, via natural gas turbines and other technologies, does have several intrinsic benefits but is primarily driven by power availability challenges. Technology strategies such as Bring Your Own Power (and Cooling) are likely to be part of ongoing energy autonomy plans.
4. Digital twin-driven design and operations
With increasingly dense AI workloads and more powerful GPUs also come a demand to deploy these complex AI factories with speed. Using AI-based tools, data centres can be mapped and specified virtually, via digital twins, and the IT and critical digital infrastructure can be integrated, often as prefabricated modular designs, and deployed as units of compute, reducing time-to-token by up to 50%. This approach will be important to efficiently achieving the gigawatt-scale buildouts required for future AI advancements.
5. Adaptive, resilient liquid cooling
AI workloads and infrastructure have accelerated the adoption of liquid cooling. But conversely, AI can also be used to further refine and optimise liquid cooling solutions. Liquid cooling has become mission-critical for a growing number of operators but AI could provide ways to further enhance its capabilities. AI, in conjunction with additional monitoring and control systems, has the potential to make liquid cooling systems smarter and even more robust by predicting potential failures and effectively managing fluid and components. This trend should lead to increasing reliability and uptime for high value hardware and associated data/workloads.
Vertiv does business in more than 130 countries, delivering critical digital infrastructure solutions to data centres, communication networks, and commercial and industrial facilities worldwide. The company’s comprehensive portfolio spans power management, thermal management, and IT infrastructure solutions and services – from the cloud to the network edge. This integrated approach enables continuous operations, optimal performance, and scalable growth for customers navigating an increasingly complex digital landscape.
Jon Abbott, Technologies Director of Global Strategic Clients at Vertiv, asks how we can build a generation of data centres for the AI age
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The promise of artificial intelligence (AI) is enlightenment. The pressure it places on infrastructure is far less elegant.
Across every layer of the data centre stack, AI is exposing structural limits – from cooling thresholds and power capacity to build timelines and failure modes. What many operators are now discovering is that legacy models, even those only a few years old, are struggling to accommodate what AI-scale workloads demand.
This isn’t simply a matter of scale – it is a shift in shape. AI doesn’t distribute evenly, it lands hard, in dense blocks of compute that concentrate energy, heat and physical weight into single systems or racks. Those conditions aren’t accommodated by traditional data hall layouts, airflow assumptions or power provisioning logic. The once-exceptional densities of 30kW or 40kW per rack are quickly becoming the baseline for graphics processing unit- (GPU) heavy deployments.
The consequences are significant. Facilities must now support greater thermal precision, faster provisioning and closer coordination across design and operations. And they must do so while maintaining resilience, efficiency and security.
Design Under Pressure
The architecture of the modern data centre is being rewritten in response to three intersecting forces. First, there is density – AI accelerators demand compact, high-power configurations that increase structural and thermal load on individual cabinets. Second, there is volatility – AI workloads spike unpredictably, requiring cooling and power systems that can track and respond in real time. Third, there is urgency – AI development cycles move fast, often leaving little room for phased infrastructure expansion.
In this environment, assumptions that once underpinned data centre design begin to erode. Air-only cooling no longer reaches critical components effectively, uninterruptible power supply (UPS) capacity must scale beyond linear load, and procurement lead times no longer match project delivery windows.
To adapt, operators are adopting strategies that prioritise speed, integration and visibility. Modular builds and factory-integrated systems are gaining traction – not for convenience, but for the reliability that controlled environments can offer. In parallel, greater emphasis is being placed on how cooling and power are architected together, rather than as separate functions.
Exploring the Physical Gap
There is a growing disconnect between the digital ambition of AI-led organisations and the physical readiness of their facilities. A rack might be specified to run the latest AI training cluster. The space around it, however, may not support the necessary airflow, load distribution or cable density. Minor mismatches in layout or containment can result in hot spots, inefficiencies or equipment degradation.
Operators are now approaching physical design through a different lens. They are evaluating structural tolerances, rebalancing containment zones, and planning for both current and future cooling scenarios. Liquid cooling, once a niche consideration, is becoming a near-term requirement. In many cases, it is being deployed alongside existing air systems to create hybrid environments that can handle peak loads without overhauling entire facilities.
What this requires is careful sequencing. Introducing liquid means introducing new infrastructure: secondary loops, pump systems, monitoring, maintenance. These elements must be designed with the same rigour as the electrical backbone. They must also be integrated into commissioning and telemetry from day one.
Risk in the Seams
The more complex the system, the more attention must be paid to the seams. AI infrastructure often relies on a patchwork of new and existing technologies – from cooling and power to management software and physical access control. When these systems are not properly aligned, risk accumulates quietly.
Hybrid cooling loops that lack thermal synchronisation can create blind spots. Overlapping monitoring systems may provide fragmented data, hiding early signs of imbalance. Delays in commissioning or last-minute changes in hardware specification can introduce vulnerabilities that remain undetected until something fails.
Avoiding these scenarios requires joined-up design. From early-stage planning through to testing and operation, infrastructure must be treated as a whole. That includes the physical plant, the digital control layer and the operational processes that bind them.
Physical Security Under AI Conditions
As infrastructure becomes more specialised and high-value, the importance of physical security rises. AI racks often contain not only critical data but hardware that is financially and strategically valuable. Facilities are responding with enhanced perimeter control, real-time surveillance, and tighter access segmentation at the rack and room level.
More organisations are adopting role-based access tied to operational state. Maintenance windows, for example, may trigger temporary access privileges that expire after use. Integrated access and monitoring logs allow operators to correlate physical movement with system behaviour, helping to identify unauthorised activity or unexpected patterns.
In environments where automation and remote management are becoming standard, physical security must be designed to support low-touch operations with intelligent systems able to flag anomalies and initiate response workflows without constant human oversight.
Infrastructure as an Adaptive System
The direction of travel is clear. Infrastructure must be able to evolve as quickly as the workloads it supports. This means designing for flexibility and for lifecycle. It means understanding where capacity is needed today, and how that might shift in six months. It means choosing platforms that support interoperability, rather than locking into closed systems.
The goal is not simply to survive the shift to AI-scale compute. It is to build a foundation that can keep up with whatever comes next – whether that is a new training model, a change in energy market conditions, or a new set of regulatory constraints.
CoreX, a high-growth Elite Consulting and Implementation Partner of ServiceNow and NewSpring Holdings platform company, has announced the successful completion…
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CoreX, a high-growth Elite Consulting and Implementation Partner of ServiceNow and NewSpring Holdings platform company, has announced the successful completion of its acquisition of InSource’s ServiceNow business unit. InSource is a fellow Elite Partner recognised for deep delivery expertise and an unwavering commitment to client success. The transaction officially closed in late December 2025.
This agreement unites two high-performing ServiceNow partners in the ecosystem. Together, CoreX and InSource now operate as a single, purpose-built organisation designed to scale with intent, elevate enterprise transformation outcomes, and meet the accelerating demand for AI-enabled, end-to-end ServiceNow solutions worldwide.
InSource integration into CoreX delivering value for ServiceNoe customers
With InSource’s 1,500+ successful implementations and a 4.76 CSAT rating, the combined organisation, more than doubling its US-based employee headcount, now operates at a level of scale and technical depth that firmly positions CoreX among the top-tier Consulting and Implementation Partners in the global ServiceNow ecosystem. The acquisition doubles the firm’s ServiceNow certifications and brings together advanced platform specialisation and a people-first culture grounded in long-term client success.
“This is not growth for growth’s sake, but rather a strategic, deliberate move of scale,” said Rick Wright, Head of CoreX. “By fully integrating InSource into CoreX, we have created a focused consultancy built for scale, execution, and long-term value for ServiceNow customers.”
Reflecting on the integration, Mark Lafond, former President & CEO of InSource, added, “InSource was built on delivery strength, trust, and long-term client relationships. Joining forces with CoreX allows us to take everything we do best and amplify it on a much larger stage. This is the right home for our people, the right platform for our customers, and the right partner to accelerate the next chapter of growth.”
By unifying CoreX’s innovation roadmap and AI readiness with InSource’s long-standing operational delivery excellence, the combined organisation now offers a truly integrated model for enterprise transformation across industries. This integration enables clients to move faster from strategy to execution while maintaining the governance, resilience, and scalability required for modern enterprises.
Just as importantly, the acquisition strengthens CoreX’s geographic footprint and delivery capacity across key global delivery hubs, including North America and Latin America, enabling the firm to serve enterprise clients with greater speed, continuity, and depth.
“Our acquisition of InSource fundamentally changes the scale of impact we can deliver for customers,” Wright added. “CoreX is now purpose-built to lead the next era of ServiceNow-powered transformation.”
With this transaction, CoreX is now among the top global ServiceNow Elite Partners, distinguished not just by certifications or scale, but by consistent delivery of measurable, enterprise-level outcomes on the ServiceNow AI Platform.
About CoreX
Founded in 2023, CoreX is a global ServiceNow consultancy specialising in business-focused transformation that unlocks hidden value from the Now Platform. Backed by unmatched industry leadership, extensive functional experience, and the most seasoned ServiceNow team in the ecosystem, CoreX delivers strategic guidance and AI-enabled innovation to power sustained success. Learn more at corexcorp.com
About NewSpring Holdings
NewSpring Holdings, NewSpring’s majority investment strategy, focused on control buyouts and sector-specific platform builds, brings a wealth of knowledge, experience, and resources to take profitable, growing companies to the next level through acquisitions and proven organic methodologies. Founded in 1999, NewSpring partners with the innovators, makers, and operators of high-performing companies in dynamic industries to catalyze new growth and seize compelling opportunities. Having completed over 250 investments, the Firm manages approximately $3.5 billion across five distinct strategies covering the spectrum from growth equity and control buyouts to mezzanine debt. Partnering with management teams to help develop their businesses into market leaders, NewSpring identifies opportunities and builds relationships using its network of industry leaders and influencers across a wide array of operational areas and industries.
Jan Van Hoecke, VP AI Services at iManage and a highly experienced computer scientist with a passion for technology and problem-solving. on navigating the AI landscape for success in 2026
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The AI landscape faces a number of big shifts in 2026. Agentic AI will undergo a reality check as enterprises discover the gap between marketing hype and actual capabilities, while organisations will go through a mindset change from treating AI hallucinations as crises to managing them, acknowledging the inherent limitations of the technology. There will also be a shift in how data will be structured in AI systems, to help the move from just finding facts (“what”) to understanding reasons (“why”). Middleware application providers will face new challenges, as those vendors controlling both platforms and data will become more influential. Finally, standardised AI chat interfaces will evolve into smarter, dynamically generated, task-specific user experiences that adapt to immediate needs.
Agentic AI Reality Check
2026 is the year when agentic AI will get a reality check, as the gap between marketing promises made in 2025 and their actual competencies will become starkly visible. As enterprise adopters share the mixed successes of agentic AI, the market will begin to differentiate between true autonomous agents and the clever workflow wrappers.
Currently, many products promoted as AI agents are, in reality, rigidly programmed systems that simply follow predefined paths. They cannot independently plan or adapt in real-time to accomplish tasks. The current evolution of AI agents closely resembles the development of autonomous vehicles: early self-driving cars could only maintain lane position by relying strictly on preset instructions, and likewise, today’s AI agents are limited to executing narrowly defined tasks within established workflows. True autonomy, where AI agents can dynamically perform and solve complex problems better than humans and without human intervention, remains, for now, an aspirational goal.
AI Hallucination Goes from Crisis to Management
In 2026, the AI hallucination crisis will reach a critical juncture as organisations realise they must learn to coexist with the current fundamentally imperfect technology – until a new technology comes into play that can effectively address the issue. The focus will shift from AI hallucination ‘crisis’ to management.
As the industry deliberates who carries the liability for AI’s mistakes and inaccuracies – the tool makers or the users – enterprises will stop waiting for vendors to solve the problem and take matters into their own hands. They will adopt a variety of pragmatic risk mitigation strategies – from double and triple-checking work, and enforcing human oversight for high-stakes decisions, to taking hallucination insurance policies.
Major model builders acknowledge that current foundational LLM technology cannot eliminate hallucinations and ambiguity through incremental improvements alone. New technology is needed. Until then, and perhaps with the realisation that a technological breakthrough is years away, users will start driving the hallucination conversation – both by building systematic defenses within how they use AI, and forcing vendors to accept shared responsibility through better documentation and clearer model limitations.
The Next Evolution in AI Data Architecture Lies in a Shift from “What” to “Why”
There will be a fundamental shift in how data is structured for AI systems, driven by the limitations of current approaches in answering complex questions. While Retrieval Augmented Generation (RAG) has proven effective at locating information and answering “what” questions, it struggles with the deeper “why” and “how” inquiries.
This limitation stems from RAG’s flat-file architecture, which excels at locating information but fails to capture the complex interconnections and relationships that underpin meaningful understanding and knowledge, especially in specialised domains like legal and professional services information.
The solution lies in AI-driven autonomous structuring of data. These systems will be better placed (than humans) to reveal critical relationships across multiple data points at scale, also highlighting the contextual dependencies essential for answering the “why” and “how” questions effectively.
Consequently, in 2026, with machines taking the lead, the method of structuring data will undergo a complete transformation, gradually eliminating the human role in creating structure, to reveal the business-critical interconnections across multiple data points.
Middleware AI Apps Squeeze
Given the essential link between data and AI, middleware companies that specialise in building custom applications layered on top of data platforms will begin to get pushed to the margins, forced to compete on niche features – while the core value of data and insight is captured by the platform owners. The true leaders will be those organisations that both own and manage their data, while also offering an AI-powered interface that enables users to interact with their data securely and efficiently, fully leveraging the capabilities of modern AI technology.
Shift to AI-generated, Task-Oriented User Interfaces
In 2026, the current traditional vendor-designed, standard AI chat-based user interfaces will transition to dynamically AI-generated task-specific user interfaces that adapt to users’ immediate needs. This represents a fundamental shift from standardised software – for example, where everyone uses identical Microsoft Word or SharePoint interfaces – to personalised, short-term user interfaces that exist only as long as the user requires them for a specific task.
This transformation will also address the critical pain point that users typically have – i.e, the crushing cognitive load of navigating bloated, feature-rich software. Instead of searching through endless menus in an overstuffed application like Excel, the user will simply state their goal – “Compare the Q3 and Q4 sales figures for our top 5 products and show me a chart” – and the AI will instantly generate a temporary, purpose-built interface – a “micro-app” – solely designed for that one single task.
In the context of dynamically generated user interfaces, both data storage and the creation of bespoke interfaces will be managed by AI. The AI organisations that will truly lead in providing such bespoke user interface-generating capability are those that possess and control their own data.
About iManage
iManage is dedicated to Making Knowledge Work™. Our cloud-native platform is at the centre of the knowledge economy, enabling every organisation to work more productively, collaboratively, and securely. Built on more than 20 years of industry experience, iManage helps leading organisations manage documents and emails more efficiently, protect vital information assets, and leverage knowledge to drive better business outcomes. As your strategic business partner, we employ our award-winning AI-enabled technology, an extensive partner ecosystem, and a customer-centric approach to provide support and guidance you can trust to make knowledge work for you. iManage is relied on by more than one million professionals at 4,000 organisations around the world.
Driving Business Transformation Through Cloud & AI
Microsoft’s Shruti Harish, Head of Solution Engineering for Cloud and AI Platforms across the tech giant’s Manufacturing and Mobility vertical, talks to Interface about how to achieve successful AI implementations augmented by Cloud. Our future focused fireside chat covered everything from driving value through cloud modernisation to responsible AI.
“Leaders should align AI initiatives with clear business outcomes and foster a culture that embraces change. The focus is shifting toward AI-operated, human-led models where intelligent agents handle tasks and humans guide strategy.”
Virgin Media O2: Democratising Data as a Cultural Movement
Mauro Flores, EVP for Data Democratisation at Virgin Media O2, talks to Interface about the leading telco’s data journey and how it is supporting colleagues to innovate faster, make smarter decisions and deliver brilliant customer experiences.
“Data-driven insights are essential. They’re helping power our decisions like optimising our network performance, anticipating outages before they happen, identifying and preventing fraud, personalising offers and pricing to build customer loyalty, and forecasting demand so we invest in the right things.”
CIBC Caribbean: Shaping the future of Banking in the Caribbean
Deputy CIO Trevor Wood explains how CIBC Caribbean is blending technology, culture, and customer-centricity to deliver seamless digital experiences across the region with a ‘Future Faster’ strategy.
“We want to lead in every market we operate, build maturity across our practices and be architects of a smarter financial future for all.”
And read on for deep AI insights from ANS’s CIO on why AI isn’t just for big business, Emergn’s CTO on how your business can get AI-ready and Kore.ai’s Chief Strategy Officer on taming AI-sprawl with governance-first platforms.
We also hear from Celonis, Snowflake, ServiceNow, Make and Zoom with their tech predictions for 2026 and chart the key dates for your diary with global networking opportunities at the latest tech events and conferences across the globe.
Santo Orlando, Practice Director – App, Data and AI Services at Insight, on how your organisation can level up with Agentic AI
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By now, most of us have heard of Generative AI. Many businesses have already adopted the technology for tasks like customer service, code generation and content creation. Generative AI, however, is only the start; we’re only scratching the surface of the potential that AI has to offer
Enter Agentic AI
Unlike Generative AI, which relies on human input and prompts, Agentic AI can act autonomously to fulfil complex tasks without human intervention. As a result, nearly 45% of business leaders think Agentic AI will outpace Generative AI in terms of impact, and more than 90% expect to adopt it even faster than they did with generative AI. However, despite its promise, our joint understanding of Agentic AI – and how to implement it – is still very much in its infancy.
So, where do you start? To kickstart your Agentic AI journey here are five fundamental steps to consider.
Generative AI vs Agentic AI
If Generative AI is like having a personal assistant, supporting you one-on-one to speed up your tasks, then Agentic AI is more like having a dedicated team of smart, individual coworkers who can take initiative and get things done across your business – without needing constant oversight.
One powerful example of this in action is in sales. With Agentic AI, organisations are able to receive real-time insights during discovery calls. The AI ‘agents’ allow sales reps to respond with timely, relevant information, helping them build trust, operate faster and close deals more effectively.
By collecting and analysing data from across teams, agents can uncover patterns, translate complex metrics into actionable strategies and even highlight opportunities that might otherwise be unintentionally overlooked. In some early implementations, sales teams have reported saving five to ten hours per rep each month – adding up to thousands of hours redirected toward deeper customer engagement.
The one-to-one relationship we’ve grown accustomed to with Generative AI has evolved into the one-to-many dynamic of Agentic AI, which is capable of handling tasks for multiple users and automating entire business processes. Even more impressively, agents can make decisions, control data and take actions on their own. A capability that can seem daunting without a clear understanding of how it works.
That’s why businesses need to start small, and here are a few practical steps to get going quicklyand wisely with agentic AI.
Step 1: Getting your data ready
Agentic AI is the logical progression for organisations already exploring generative tools. However, the data needs to be in an optimal condition – clean, organised and secure – before autonomous agents can be deployed effectively.
As such, eliminating redundant, outdated and trivial (ROT) data is vital. Without removing ROT, agents may rely on obsolete information, leading to inaccurate or misleading outputs. For example, this could happen if a company deploys an HR chatbot that’s connected to outdated data sources. If an employee were to ask about their 2025 benefits, the chatbot might pull information from as far back as 2017, resulting in confusion and misinformation.
Proper file labelling, standardised document practices and use of version histories in place of multiple saved versions helps to ensure agents access only the most relevant and accurate information.
Step 2: Start with low-risk cases
Agents work on a transactional basis, charging for each operation, which can quickly add up. As such, it’s wise to experiment with simple, low-stakes applications first. This approach allows for quicker deployment and demonstrates immediate value to the business without significant costs or risks.
One example could be using an agent to assess sentiment in social media responses following a product launch. This can offer real-time feedback on public perception and inform messaging strategies. Other low-risk use cases include generating reactive press releases and monitoring competitor websites. Additionally, prioritising automation of routine tasks, especially those involving platforms like Salesforce, SharePoint, or Microsoft 365, allows teams to maximise impact without costly system overhauls.
Overall, organisations need to be willing to fail fast and expect failure. It won’t be perfect from the start. However, an experimental pilot approach helps to efficiently refine AI agents, reducing the risk of costly mistakes and making sure that only effective solutions are scaled up.
Step 3: Create a single source of truth
Establishing a dedicated, cross-functional team to explore agentic AI use cases helps prevent siloed adoption and supports enterprise-wide visibility. This team should span as much of the organisation as possible and include representatives from departments such as marketing, finance and technical solutions.
Collaborative workshops can then act as a forum to identify key processes that would benefit from autonomous capabilities and help businesses align potential applications with specific departmental objectives and broader business goals.
Step 4: Learn, learn and learn
Many companies underestimated the importance of training and governance with Generative AI – and Agentic AI is no different. Organisations need to establish clear governance to define how AI agents should and shouldn’t be used, covering not just technical implications, but HR, compliance and risk concerns as well.
Equally, businesses and those employed must understand Agentic AI’s full functionality to get the most out of it. Like with almost all technical training, AI education cannot be viewed as a one-time ‘tick-box’ exercise. Ongoing learning is necessary to keep pace with new capabilities and best practices.
For example, consider what’s already emerging, like security agents that automate high-volume threat protection and identity management tasks; sales agents that find leads, reach out to customers and set up meetings; and reasoning agents that transform vast amounts of data into strategic business insights.
Step 5: Reviewing ROI
Enthusiasm around Agentic AI is high. But before organisations dive in headfirst, it’s important they first define success. Technology can’t be the solution if there is uncertainty surrounding the goal. Successful deployment requires a clear definition of the problem organisations are looking to solve and knowledge of how to align the solution with measurable business value. Without this, initiatives risk stalling at the experimental stage.
Key performance indicators should also be identified early. These may include increased productivity, time savings, cost reduction or improved decision-making. Establishing these benchmarks and taking a data-driven approach ensures that AI initiatives align with business goals and demonstrate tangible benefits to stakeholders.
Moving forward
The process of switching to Agentic AI is about changing how businesses handle everyday problems with wide ranging effects, not just about using cutting edge technology. Iteration and learning along the way, as well as deliberate, measured adoption are the keys to increasing value. It’s simple. Success with AI starts with small, straightforward actions and use cases.
Kyle Hill, CTO of leading digital transformation company and Microsoft Services Partner of the Year 2025, ANS, explores how businesses of all sizes can make the most of their AI investment and maintain a competitive edge in an era of innovation
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Across the world, businesses are clamouring to adopt the latest AI technologies, and they’re willing invest significantly. According to Gartner, generative AI has produced a significant increase in infrastructure spending from organisations across the last few months, which prompted it to add approximately $63 billion to its January 2024 IT spending forecast.
Capable of reshaping business operations, facilitating supply-chain efficiency, and revolutionising the customer experience, it’s no wonder major enterprises are keen to channel their budgets towards AI. But the benefits of AI can extend beyond large enterprises and make a considerable difference to small businesses too if adopted responsibly.
Game-Changing Innovation
Most SMBs don’t have the same ability for taking spending risks as their larger counterparts, so they need to be confident that any investments they do make are worthwhile. It’s therefore understandable why some might assume it to be an elite tool reserved for the major players.
To understand how SMBs can make the most of their AI investments, it’s important to first look at what the technology can offer.
Across industries, AI is promising to be a game changer, taking day-to-day operations to a new level of accuracy and efficiency. AI technology can enhance businesses of all sizes by:
Enhancing customer experience
Businesses can use AI tools to process and analyse vast amounts of data – from spending habits and frequent buys to the length of time spent looking at a specific product. They can then use these insights to provide a more tailored experience via personalised recommendations, unique suggestions and substitution offers when a product is out of stock. And, with AI chat functions, businesses can provide more timely responses to any questions or requests, without always needing an abundance of customer service staff on hand.
Powering day-to-day procedures
One of the most common and inclusive uses of AI across organisations is for assisting and automating everyday tasks including data input, coding support and content generation. These tools, such as OpenAI’s ChatGPT and Microsoft Copilot applications, don’t require big investments to adopt. Smaller teams and businesses are already using them to save valuable employee time and resources and boost productivity. This also saves the need for these organisations to outsource these capabilities where they might not have them otherwise.
Minimising waste
AI is also helping businesses to drive profit, minimising wasted resources, and identifying potential disruptions. By tracking levels of supply and demand, AI can automatically identify challenges such as stock shortages, delivery-route disruptions, or a heightened demand for a particular product. More impressively, however, they are also capable of suggesting solutions to these problems – from the fastest delivery route that avoids traffic, to diverting stock to a new warehouse. Such planning and preparation help businesses to avoid disruptions which costs valuable time, money, and resources.
According to Forbes Advisor, 56% of businesses are already using AI for customer service, and 47% for digital personal assistance. If organisations want to keep up with their cutting edge-competitors, AI tools are quickly becoming a must-have for their inventory.
For SMBs looking to stay afloat in this competitive landscape of AI innovation, getting the most out of their technological investment is crucial.
Laying down the foundations
Adopting AI isn’t as straightforward as ‘plug and play’ and SMBs shouldn’t underestimate the investment these tools require. Whilst many of the applications may be easy to use, it’s important that business leaders take time to fully understand the technology and its potential uses. Otherwise, they risk missing some major benefits and not getting the most from their investment, particularly as they scale out.
Acknowledging the potential risks and challenges of implementing new AI tools can help organisations prepare solutions and ensure that their business is equipped to manage the modern technology. This can help businesses to avoid costly mistakes and hit the ground running with their innovation efforts.
SMB leaders looking to implement AI first need to ask the following:
What can AI do for me?
Are day-to-day administration tasks your biggest sticking points? Or are you looking to provide customer service like no-other? Identifying how AI might be of most use for your business can help you to make the most effective investments. It’s also worth considering the tools and applications you already have, and how AI might enhance these. Many companies already use Microsoft Office, for instance, which Microsoft Copilot can seamlessly slot into, making for a much smoother rollout.
Can my business manage its data?
AI is powered by data, so having sufficient data-management and storage processes in place is necessary. Before investing in AI, businesses might benefit from first looking at managed data platforms and services. This is crucial for providing the scalability, security and flexibility needed to embrace innovation in a responsible and effective way.
What about regulation?
The use and development of AI are becoming increasingly regulated, with legislation such as the EU AI Act providing stringent, risk-based guidance on its adoption. Keeping up with the latest rules and legislative changes is vital. Not only will this help your business to maintain compliance, but it will also help to maintain trust with customers and employees alike, whose data might be stored and processed by AI. Reputational damage caused by a data breach is a tough blow even for big businesses, so organisations would be wise to avoid it where possible.
Embracing Innovation
This new age of AI is exciting; it holds great transformative potential. We’ve already seen the development of accessible, affordable tools, such as Microsoft Copilot, opening a world of new innovative potential to businesses of all sizes. Those that don’t dip their toes in the AI pool risk getting left behind.
The question smaller businesses ask themselves can no longer be about whether AI is right for them; instead, it should be about how they can best access its benefits within the parameters of their budget.
By thoroughly preparing and taking time to understand the full process of AI adoption, SMBs can make sure that their digital transformation efforts are a success. In today’s world, this is the best way to remain fiercely competitive in a continuously evolving landscape.
About ANS
ANS is a digital transformation provider and Microsoft’s UK Services Partner of the Year 2025. Headquartered in Manchester, it offers public and private cloud, security, business applications, low code, and data services to thousands of customers, from enterprise to SMB and public sector organisations. With a strong commitment to community, diversity, and inclusion, ANS aims to empower local talent and contribute to the growth of the Northwest tech ecosystem. Understanding customers’ needs is at the heart of ANS’s approach, setting them apart from any other company in the industry.
The ANS Academy is rated outstanding by Ofsted and offers in-house apprenticeships across a range of technology disciplines. ANS has supported more than 250 apprentices to gain qualifications in the last decade via apprenticeships across technology, commercial, finance, business administration and marketing.
ANS owns and operates five IL3‐accredited data centres in Manchester and has an ecosystem of tech partners including Microsoft (Gold Partner), AWS, VMWare, Citrix, HPE, Dell, Commvault and Cisco. It is one of the very few organisations to have received all six of Microsoft’s Solutions Partner Designations.
Jalal Charaf, Chief Digital & AI Officer of the University Mohammed VI Polytechnic (UM6P) and Managing Director of Ecole Centrale Casablanca on how Africa can seize its moment to lead on data
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In today’s world, data is not just about numbers and technology; it shapes how people live, how governments plan, and how businesses grow. It influences who gets a loan, who receives medical care, and who has access to education. That’s why control over data, called data sovereignty, is becoming one of the most important sources of power in the 21st century.
Unfortunately, Africa is still on the margins of this new reality. Although the continent is home to over 1.4 billion people, 18% of the world’s population, it provides less than 4% of the data used to train today’s most powerful AI systems. Most African data is stored in foreign data centres, beyond the reach of African laws and courts. This is no longer just a ‘digital divide’, it’s a dependence on outside systems that don’t fully understand or represent African realities.
What’s Holding Africa Back?
There are several key reasons why Africa remains largely underrepresented in the global digital economy.
First, representation. Most AI systems are built on data from outside Africa. As a result, they often misjudge or misrepresent African realities, whether it’s credit scoring, medical diagnostics, or speech recognition. The absence of African data creates blind spots that affect real lives.
Third, governance. With 29 different national data protection laws, Africa lacks a unified approach to managing data. In contrast, the European Union negotiates data rules as a single bloc. Africa’s fragmented regulatory landscape makes it harder to attract investment or protect citizens’ rights.
Morocco offers a model of what digital sovereignty can look like. In June 2025, a consortium led by Nexus Core Systems announced a 500-megawatt, renewables-powered AI infrastructure project on the Atlantic coast. Phase one, with 40 MW of NVIDIA’s Blackwell AI chips, will go live in early 2026, exporting compute power across Europe, the Middle East, and Africa.
Critically, this infrastructure is under Moroccan jurisdiction, not subject to U.S. laws like the CLOUD Act. The project proves that African countries can host cutting-edge data systems while protecting their own legal and strategic interests.
How Africa Can Lead
To turn early momentum into lasting sovereignty, African governments, institutions, and partners must work together across four pillars:
Data creation and curation. Countries should invest at least 1% of GDP in digital public infrastructure, such as national ID systems, crop mapping satellites, and open data portals. These systems ensure that African data reflects African lives.
Compute and storage. Regions with access to renewable energy can build local ‘green AI corridors’ linked by neutral internet exchanges. This keeps data close to where it’s generated and cuts dependence on foreign servers.
Policy and regulation. The African Union should lead a continent-wide Data Sovereignty Compact, a framework to harmonise data protection, localisation, and AI ethics. A unified legal environment will attract investment and support responsible innovation.
Talent and research. African universities and public agencies should develop homegrown AI talent. Governments can require that models trained on African data are hosted locally. Research must be rooted in African languages, priorities, and realities, not just imported standards.
A Role for Everyone: From Governments to Global Partners
Governments should commit at least 10% of their ICT budgets to data sovereignty and adopt AU-wide standards. Local cloud facilities and fibre infrastructure deserve long-term funding, not just short-term pilots.
Private industry must shift from short-lived cloud credits to permanent, on-the-ground investment. Companies should publish annual data localisation reports and follow the example set by Nexus Core Systems.
Universities, civil society groups, and non-profits also have a responsibility. Open data repositories, civic tech labs, and ethical data governance initiatives must be scaled up to support innovation that’s inclusive and local.
Africa has everything it needs to become a global leader in digital intelligence. Its young population, growing tech talent, and renewable energy potential are powerful advantages. But sovereignty will not be handed over, it must be built.
We must act now, before the rules of the digital world are written without us. Morocco’s Nexus Core project shows what’s possible when ambition meets action. It’s time for the rest of the continent to follow suit, and shape a future where Africa owns its data, tells its stories, and sets its own course.
Cathal McCarthy, Chief Strategy Officer at Kore.ai, on why now is the time for enterprises to take stock and set themselves up for a long-term, successful future in applying AI where it can make the most difference
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The generative AI boom has triggered a wave of enterprise experimentation. From proof-of-concepts to customer-facing AI Agents, which can be launched at pace but too often in isolation. This comes as MIT’s latest report finds that only 5% of Generative AI pilots are successful, with the majority failing due to poor integration with enterprise systems and in-house implementations without engagement with expert vendors.
As adoption grows, so does the call for accountability. Control and centralisation is more important than ever. Siloed operations and experimentation pilots have meant that there are a trail of disconnected tools, incomplete experiments and sometimes confusion within enterprises of where AI is being used and who is using it, meaning it can’t be governed effectively.
Now is the time for enterprises to take stock and set themselves up for a long-term, successful future in applying AI where it can make the most difference. The state of play today shows where clear changes are needed.
AI Islands
In a recent report from Boston Consulting Group and Kore.ai, 80% of AI leaders say they now favour platform-based strategies over scattered deployments. These platforms are not just about efficiency; they’re quickly becoming the only viable model for visibility, scalability and governance.
The consequences of fragmentation are starting to show. CIOs and CTOs are sounding the alarm on siloed AI solutions that make it harder to measure impact, manage risk, or move quickly. This is often the case when AI tools and solutions are implemented in-house and without proven expertise.
These ‘AI islands’ are hard to govern, expensive to integrate and nearly impossible to scale responsibly. More than half surveyed in the report say current AI solutions are slowing them down and nearly three-quarters highlight explainability and compliance as top concerns. Clearly, connecting these AI islands together via a common platform can offer more long-term benefits such as better governance, faster time to market, and cost consolidation.
Regulation Demands New Architecture
Where governance could have been considered a final step by some, it now has to be a design principle from the outset. Transparency, auditability, and oversight must be built into the very fabric of how AI is developed, deployed and monitored.
Take the EU AI Act for example, the world’s first broad AI law, now applying to general-purpose AI models from August 2nd, 2025. The rules aim to boost transparency, safety and accountability across the AI value chain while preserving innovation.
According to the BCG report, 74% of leaders believe new regulations will significantly influence how they roll out AI across their organisations. And for good reason. Fragmented systems don’t just introduce inefficiency, they create gaps that regulators, stakeholders and customers are not ready to accept.
For all the talk of regulation as a constraint, it’s also an opportunity. Regulations should be seen as catalysts, rather than roadblocks. Companies that ensure governance is hard-wired into their AI projects don’t just avoid risk, they create greater trust. And this means greater adoption. This is what leaders need to see, as increased adoption of AI products ensures sustainable, long-term growth.
Enterprises in industries holding sensitive and personal data like BFSI, healthcare and retail, are already adopting a platform-based approach. Not only does this ensure integration across the business but also means it future proofs compliance, meeting industry and government regulated standards today but also building in parameters for upcoming regulations.
Gaining Control
Adopting a platform model doesn’t limit creativity. And it doesn’t mean sacrificing flexibility. Instead of juggling multiple tools, you get one place to plug in what you’ve built and get the best of what’s out there. By running all of your AI capabilities under one unified platform and set of guardrails, your teams across the organisation move forward with one framework, which means, they move faster, make quicker decisions and have a clear understanding of what is – and isn’t – working.
Most importantly, a platform turns compliance into a competitive and operational advantage. You can swap models, scale pilots and grow without silos tripping you up, and bring centralised control. This momentum is crucial for scaling and growing an organisation. Platforms create the foundation to scale AI responsibly and effectively and that’s key for future-proofing AI projects and creating impact that matters.
This month’s cover story focuses on the digital transformation journey continuing at the United States Department of Agriculture (USDA). In conversation with Fátima Terry, USDA’s former Digital Service Deputy Director, we revisit the sterling work being carried out and find out how technology is being humanised to deliver value to the American people this organisation serves.
“One of the things we did was partner with multiple USDA teams that focused on customer experience and digital service delivery for their programs,” she explains. “We also partnered with other federal-wide agencies and departments to move forward and evaluate the progress of digital transformation by cross-pollinating success models to everyone connected.”
Ayoba: A Super-App for Africa
Ayoba, part of the MTN telco group, is a super-app platform built in Africa, for Africa. Esat Belhan, Chief Technology & Product Officer, reveals how it is bringing more people to digital so they can be tech-savvy and educated on digital capabilities…
“In order to do that, one thing you could do is give away free data, but that data could be easily wasted on another data-heavy app, like TikTok, in just a couple of hours. So, the real solution is that the valuable and insightful content Ayoba provides should be provided for free, and that we provide instant messaging and short video content, to keep people using our platform for their communication and entertainment needs.”
Kraft Kennedy: Supporting MSPs with People and Processes
Nett Lynch, CISO at Kraft Kennedy, explains how the company’s new division, Legion, solves cyber pain-points for MSPs with a collaborative, business-centred approach.
“A lot of MSPs struggle with client strategy, they’re talking tech instead of business. We’re nerds – we love the tech, we love the features. But we need to admit clients aren’t focused on those things. They don’t necessarily care how or why it works. They just want it to work and align to their business goals.”
And read on to hear from FICO’s CIO on using AI to transform technical operations; learn from KnowBe4 how AI Agents will be a game changer for tackling cybercrime; and discover how data centres are meeting the demands of the AI boom with Vertiv.
Interface hears from Emergn CTO Fredrik Hagstroem on approaches to AI best practice that can drive positive business transformations
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What does it actually mean for an organisation to be AI-ready, beyond having the right tools and data
“Being AI-ready is fundamentally about openness to learning and the ability to react quickly. While having the right tools and well-managed data is essential, true readiness is defined by an organisation’s capacity to operate, monitor, and measure the effectiveness of AI solutions.
We often see organisations invest heavily in implementation and tooling, only to realise that no one is prepared to take responsibility for running, monitoring, and improving AI systems.
AI-savvy organisations design solutions differently depending on the type of work, operational versus knowledge work, and, for knowledge work, focus on measuring effectiveness rather than just productivity.”
Where do most companies go wrong when trying to embed AI into their operations?
“Many companies treat AI solutions like traditional IT projects, using user acceptance as a checkpoint between development and handover to IT operations. This approach often fails before it even begins.
AI performs tasks that typically require human intelligence, perception, reasoning, and decision-making. While AI can execute these tasks with far greater precision and consistency than humans, someone within the organisation remains ultimately accountable for the results.
The most common misstep is underestimating the need to provide users with the right level of oversight and control so they can accept accountability for AI-driven decisions.
For example, explaining how AI decisions are made and demonstrating that they are ethical and fair depends not only on transparency and traceability but also on maintaining control and proper training data records.”
How can leaders prevent transformation fatigue during AI-driven change initiatives?
“Change is inevitable, so responding to it is part of effective leadership. AI will transform how businesses operate, but transformation fatigue arises when people feel constantly subject to change rather than in control of it.
Deliberate planning and thoughtful communication help, but the most effective approach is to empower people to feel more in control. This often involves organising teams around value streams that cut across business, technology, and operations.
Leaders can ensure teams have the skills and information necessary to take ownership of outcomes and make adjustments based on real results. This is especially important with AI solutions, which should be structured to provide continuous feedback, allowing teams to monitor performance, improve models, and refine processes based on learning.”
What kind of mindset and cultural shift is required for AI to deliver long-term value?
“Delivering long-term value from AI requires a shift from control to collaboration, and from predictability to adaptability. Organisations focused on individual targets and siloed accountability often struggle to realise AI’s full potential.
Value emerges when teams adopt a collective mindset, defining success by shared outcomes, whether customer experience, business impact, or strategic growth. Individual productivity only matters when it benefits the whole system.
Another critical shift is embracing uncertainty. Traditional corporate cultures often reward certainty and fixed plans. Cultures that support experimentation, feedback loops, and incremental change are more likely to see lasting benefits from AI.
This cultural evolution isn’t just about tools; it’s about how work is structured, how teams interact, and how decisions are made. Empowering teams to act fast, learn fast, and improve fast is central to sustaining AI-driven value.”
How can organisations balance AI experimentation with maintaining trust, transparency, and alignment with business goals?
“Each AI initiative should be evaluated based on the type of work and value it aims to deliver, whether efficiency, experience, or innovation. Different goals require different levels of oversight and distinct success metrics, making a portfolio approach to investment essential. Maintaining alignment with business goals means focusing on outcomes rather than outputs.
This requires systems where feedback, transparency, and learning are built in from the start, allowing initiatives to fail gracefully. Trust begins with a clear governance framework, as AI, like any transformative technology, can have unintended consequences. Transparency is not just audit trails; it’s about inviting dialogue, sharing lessons learned, and adapting as standards and regulations evolve.
Experimentation and learning go hand in hand. Delivering incremental value early builds credibility and transparency, helping teams understand what works and what doesn’t. Ultimately, AI is only valuable to the extent that it drives the business toward its strategic goals.”
How do organisations deal with some of the risks associated with AI – hallucinations, privacy issues, etc. – and how do they go about both securing essential data and overcoming employee resistance to the technology?
“Treating AI adoption as an iterative, feedback-driven process is key to managing risks. Success is less about getting everything perfect from the start and more about structuring work to minimise unintended consequences and adapt quickly.
“Hallucinations” is a misleading term. Today’s AI doesn’t imagine things; it follows programmed rules based on probabilities and patterns. Like any software, AI carries risks of errors or mismanaged data.
What is new is how AI uses data, to train models that imitate human decision-making. Without careful management, models can produce biased or unethical outcomes. Technology does not remove employee accountability. Recognising this allows organisations to design AI solutions with lower risk.
Designing solutions with humans in the loop is critical. It promotes transparency and explainability and is the most effective way to overcome resistance while maintaining control over outcomes.”
Ralph Hogaboom is a seasoned cybersecurity leader, a CISO with a deep commitment to public service and a human-centred approach to information security. Our cover star talks about creating a people-led cybersecurity function for the Washington State Department of Natural Resources (DNR) defined by long-term thinking, commitment to the vision and keeping empathy at the forefront.
“Now we’re the team that helps people get to ‘yes’,” says Hogaboom. The core of it, he explains, is an approach to cybersecurity focused on people, their needs and outcomes, rather than a systems or technology-centric approach.”
IAG Firemark Ventures: Transforming Insurance
We check in again with Scott Gunther, General Partner at IAG Firemark Ventures, on how the company is bringing powerful investments to life to transform how insurance is delivered.
“We realised that if we were going to bring the best of the outside world in, we needed to be a truly global CVC.”
Delta Dental: Cybersecurity as a Business Enabler
Alex Green, CISO at Delta Dental Plans Association, talks cyber risk, resilience, and practicing servant leadership in a uniquely challenging cybersecurity environment.
“Cybersecurity isn’t about locking everything down; It’s about managing risk in a way that allows the business to operate, adapt, and grow.”
Chief Information Officer, Jan Bouwer, explores the work Alexforbes has undertaken to modernise and expand its financial services for its 1.2 million members and retail customers alike. “Alexforbes can now engage its 1.2 million members more directly, offering a wider range of services.”
University of Tasmania: A Technology Transformation for the People
We spoke to four members of the University of Tasmania‘s, research, and student services team to dig into the incredible work the university is doing to support researchers and students, and what such a complex operation entails.
“We recognise that not all potential students get the support they need to go to university,” says CIO Kathleen Mackay. “But we want to be able to provide that support.”
Samsung and OpenAI Announce Strategic Partnership to Accelerate Advancements in Global AI Infrastructure
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Samsung will bring together technologies and innovations across advanced semiconductors, data centres, shipbuilding, cloud services and maritime technologies
OpenAI, Samsung Electronics, Samsung SDS, Samsung C&T and Samsung Heavy Industries have announced a letter of intent (LOI) for their strategic partnership to accelerate advancements in global AI data centre infrastructure and develop future technologies together in relevant fields. This expansive collaboration will bring together the collective strengths and leadership of Samsung companies across semiconductors, data centres, shipbuilding, cloud services and maritime technologies.
The signing ceremony was held at Samsung’s corporate headquarters in Seoul, Korea, attended by Young Hyun Jun, Vice Chairman & CEO of Samsung Electronics; Sung-an Choi, Vice Chairman & CEO of Samsung Heavy Industries; Sechul Oh, President & CEO of Samsung C&T; and Junehee Lee, President & CEO of Samsung SDS.
Samsung Electronics
Samsung Electronics will work with OpenAI as a strategic memory partner to supply advanced semiconductor solutions for OpenAI’s global Stargate initiative. With OpenAI’s memory demand projected to reach up to 900,000 DRAM wafers per month, Samsung will contribute toward meeting this need with its extensive lineup of high-performance DRAM solutions.
As a comprehensive semiconductor solutions provider, Samsung’s leading technologies span across memory, logic and foundry with a diverse product portfolio that supports the full AI workflow from training to inference.
The company also brings differentiated capabilities in advanced chip packaging and heterogeneous integration between memory and system semiconductors, enabling it to provide unique solutions for OpenAI.
Samsung SDS
Samsung SDS has entered into a potential partnership with OpenAI to jointly develop AI data centre and provide enterprise AI services.
Leveraging its expertise in advanced data center technologies, Samsung SDS will collaborate with OpenAI in the design, development and operation of the Stargate AI data centers. Under the LOI, Samsung SDS can now provide consulting, deployment and management services for businesses seeking to integrate OpenAI’s AI models into their internal systems.
In addition, Samsung SDS has signed a reseller partnership for OpenAI’s services in Korea and plans to support local companies in adopting OpenAI’s ChatGPT Enterprise offerings.
Samsung C&T and Samsung Heavy Industries
Samsung C&T and Samsung Heavy Industries will collaborate with OpenAI to advance global AI data centers, with a particular focus on the joint development of floating data centers.
Floating data centers are considered to have advantages over data centers because they can address land scarcity and lower cooling costs. Still, their technical complexity has so far limited wider deployment.
Building on their proprietary technologies, Samsung C&T and Samsung Heavy Industries will also explore opportunities to pursue projects in floating power plants and control centers, in addition to floating data center infrastructure.
Starting with the landmark partnership with OpenAI, Samsung plans to fully support Korea’s goals to become one of the world’s top three nations in AI and create new opportunities in the field.
Samsung is also exploring broader adoption of ChatGPT within the companies to facilitate AI transformation in the workplace.
About OpenAI
OpenAI is an AI research and deployment company. Our mission is to ensure that artificial general intelligence benefits all of humanity.
About Samsung Electronics Co., Ltd.
Samsung inspires the world and shapes the future with transformative ideas and technologies. The company is redefining the worlds of TVs, digital signage, smartphones, wearables, tablets, home appliances and network systems, as well as memory, system LSI and foundry. Samsung is also advancing medical imaging technologies, HVAC solutions and robotics, while creating innovative automotive and audio products through Harman. With its SmartThings ecosystem, open collaboration with partners, and integration of AI across its portfolio, Samsung delivers a seamless and intelligent connected experience.
Join 3,000+ industry decision makers and influencers at Smart Retail Tech Show for your opportunity to gain the tools to stay ahead in a competitive market
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If you’re in retail and looking to stay ahead in a fast-changing market, the Smart Retail Tech Expo is a must-attend event. With thousands of industry professionals, the show is a hub for innovation, showcasing the latest technologies to enhance the customer journey, streamline operations, and drive growth. Whether it’s improving operations, enhancing safety, enabling contactless payments, or elevating the customer experience, it’s all on the show floor.
Regardless if you’re an independent retailer or part of a global chain, this is your chance to explore cutting-edge solutions!
Why Attend Smart Retail Tech Expo?
With only pre-qualified decision-makers and key influencers in attendance, it’s the perfect place to network, learn, and invest in the future of retail.
Visitors include Key Decision-Makers: CTO | Director of Retail Experience | Digital Transformation Director | Director of Innovation | Head of Customer Experience | Head of Digital & E-commerce
3,200 visitors in attendance
86% have purchasing authority
76% are looking to source new products & services
95% are senior management or above
Smart Retail Tech Expo is where retail innovation happens! Small business or global, discover cutting-edge solutions and in one place and shape retail’s future.
“Thanks @smartretailexpo! Packed with innovation, connected with lots of great problem solving startups doing amazing work in the space!”
Daniel Himsworth, Marks & Spencer
Keynote speakers include experts from e-commerce, retail, and tech backgrounds, alongside many more. They will be sharing insights from their personal journey and future-proofed strategies on customer engagement, globalising your business, social media commerce, and lots more. Come and hear from the industry’s biggest voices and learn about how to keep ahead in the white and private-label sector. Keynote speakers include expert insights from Pinterest, Tik Tok, Uber Eats, Alibaba and many more…
Register now for free tickets and gain insider knowledge… Beyond networking, Smart Retail Tech Expo offers expert-led sessions and insights into emerging trends, sourcing strategies, and retail technology—giving you the tools to stay ahead in a competitive market.
Join over 25,000 entrepreneurs, SME owners, and senior professionals at Excel London for The Business Show London 2025
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The world’s largest award-winning business event, The Business Show London 2025, is returning to Excel London on the 12th and 13th of November 2025. Join over 25,000 SMEs and startups at this premier London business expo, designed to provide the support and resources you need to start, grow, or scale your business.
As always, the event offers free expert advice and insights from some of the biggest names in the industry. Building on last year’s impactful keynotes, this year’s business conference features fresh faces—business leaders who have thrived in recent years. In today’s digital landscape, this is a rare opportunity to gain face-to-face experience, advice, and inspiration from those who have been in your position and succeeded.
Whether you’re looking to network at one of the best business networking events in London or seeking new business partnerships, this event is your gateway to unlocking growth. For enquiries, registration, or to book a stand, contact the team today and secure your place at the UK’s leading SME business event.
Why Attend The Business Show London?
This flagship London business expo offers unparalleled opportunities to connect with industry leaders, discover cutting-edge solutions, and gain practical insights to accelerate your business.
“Vibrant, electric and inclusive ….the atmosphere I felt today at The Business Show, London excel as a keynote speaker representing Google. Such an incredible turn out, engaged listeners and wonderful to also have 121’s with many entrepreneurs on business growth utilising AI!”
Harmony Murphy, Google
With thousands of exhibitors, inspiring keynote speakers, and interactive show features, the show caters to startups, established businesses, and everyone in between. Whether you’re looking to connect with startups, explore small business exhibitions, or attend the UK’s leading business growth conference, this event will equip you with fresh ideas and practical strategies to help your business succeed.
500+ exhibitors
86% attendee satisfaction rate
75% attendees plan to return
6 show features
Don’t miss your chance to participate in one of the top business networking events in London.
Register now for free tickets and join the UK’s most ambitious business minds to gain new partnerships, expert advice, and business development opportunities.
Robert Cottrill, Technology Director at digital transformation company ANS, explores how businesses can harness the potential of AI while mitigating the growing risks to cybersecurity and privacy
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AI can transform businesses, but is it also opening the door to cybersecurity risks?
Fuelled by competitive pressure and rising government support through the UK’s Industrial Strategy, it’s no surprise that more and more businesses are racing to adopt AI.
But there’s a catch. The more businesses scale their AI adoption, the bigger their attack surface becomes. Without a proactive and structured approach to securing AI systems, organisations risk trading short-term efficiencies for long-term vulnerabilities.
The AI Boom
AI investment is skyrocketing. Businesses are deploying generative AI tools, machine learning models, and intelligent automation across nearly every function, from customer service and fraud detection to supply chain optimisation. Platforms like DeepSeek and open-source AI models are now part of the mainstream tech stack.
Initiatives like the UK’s AI Opportunities Action Plan are fuelling experimentation and adoption. AI is now seen not just as a productivity tool, but as a critical lever for digital transformation.
However, the rapid pace of AI deployment is outpacing the development of the security frameworks required to protect it. When integrated with sensitive data or critical infrastructure, AI systems can introduce serious risks if not properly secured. These risks include data leakage through AI prompts or model training, as well as AI-generated phishing and social engineering attacks
While technical threats often take centre stage, businesses also can’t forget the increasing regulatory requirements surrounding AI.
As AI systems become more powerful, enabling businesses to extract valuable insights from vast datasets, they also raise serious ethical and legal challenges.
Regulatory frameworks like the EU AI Act and GDPR aim to provide guardrails for responsible AI use. But these regulations often struggle to keep up with the rapid advancements in AI technology, leaving businesses exposed to potential breaches and misuse of personal data.
The Need for Responsible AI Adoption with Cybersecurity
To build resilience while embracing AI, businesses need a dual approach:
1. Prioritise AI-specific training across the workforce
Cybersecurity teams are already stretched. Introducing AI into the mix raises the stakes. Organisations must prioritise upskilling their cybersecurity professionals to understand how AI can both protect and threaten systems.
But this isn’t just a job for the security team. As AI tools become embedded in daily workflows, employees across functions must also be trained to spot risks. Whether it’s uploading sensitive data into a chatbot or blindly trusting algorithms, human error remains a major weak point.
A well-trained workforce is the first and most crucial line of defence.
2. Adopt open-source AI responsibly
Another key strategy for reducing AI-related risks is the responsible adoption of open-source AI platforms. Open-source AI enhances transparency by making AI algorithms and tools available for broader scrutiny. This openness fosters collaboration and collective innovation, allowing developers and security experts worldwide to identify and address potential vulnerabilities more efficiently.
The transparency of open-source AI demystifies AI technologies for businesses, giving them the confidence to adopt AI solutions while ensuring they stay alert about potential security flaws. When AI systems are subject to global review, organisations can tap into the expertise of a diverse and engaged tech community to build more secure, reliable AI applications.
To adopt responsibly, businesses need to ensure that the AI they are using aligns with security best practices, complies with regulations, and is ethically sound. By using open-source AI responsibly, organisations can create more secure digital environments and strengthen trust with stakeholders.
Securing the Future of AI
AI is a transformative force that will redefine cybersecurity. We’re already seeing AI being used to automate threat detection and response. But it’s also powering more advanced attacks, from deepfake impersonation to large-scale automated exploits.
Organisations that succeed will be those that embed cybersecurity into every stage of their AI journey, from innovation to implementation. That means making risk management part of the innovation conversation, not a downstream fix.
By taking a responsible approach, investing in training, leveraging open-source AI wisely, and embedding cybersecurity into every layer of the business, organisations can unlock AI’s potential while defending against its risks.
AI is a double-edged sword, but with thoughtful adoption, businesses can confidently navigate the complex landscape of AI and cybersecurity.
Anna Collard, SVP Content Strategy & Evangelist KnowBe4 – Africa, on leveraging AI-driven cybersecurity systems to fight cybercrime
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Artificial Intelligence is no longer just a tool. It is a game-changer in our lives, our work as well as in both cybersecurity and cybercrime. While businesses leverage AI to enhance defences, cybercriminals are weaponising AI to make these attacks more scalable and convincing.
In 2025, research shows AI agents, or autonomous AI-driven systems capable of performing complex tasks with minimal human input, are revolutionising both cyberattacks and cybersecurity defences. While AI-powered chatbots have been around for a while, AI agents go beyond simple assistants. They function as self-learning digital operatives that plan, execute, and adapt in real time. These advancements don’t just enhance cybercriminal tactics, they may fundamentally change the cybersecurity battlefield.
How Cybercriminals Are Weaponising AI: The New Threat Landscape
AI is transforming cybercrime, making attacks more scalable, efficient, and accessible. The WEF Artificial Intelligence and Cybersecurity Report (2025) highlights how AI has democratised cyber threats. Thus enabling attackers to automate social engineering, expand phishing campaigns, and develop AI-driven malware. Similarly, the Orange Cyberdefense Security Navigator 2025 warns of AI-powered cyber extortion, deepfake fraud, and adversarial AI techniques. And the 2025 State of Malware Report by Malwarebytes notes, while GenAI has enhanced cybercrime efficiency, it hasn’t yet introduced entirely new attack methods. Attackers still rely on phishing, social engineering, and cyber extortion, now amplified by AI. However, this is set to change with the rise of AI agents. Autonomous AI systems are capable of planning, acting, and executing complex tasks—posing major implications for the future of cybercrime.
Here is a list of common (ab)use cases of AI by cybercriminals:
AI-Generated Phishing & Social Engineering
Generative AI and large language models (LLMs) enable cybercriminals to craft more believable and sophisticated phishing emails in multiple languages. Without the usual red flags like poor grammar or spelling mistakes. AI-driven spear phishing now allows criminals to personalise scams at scale, automatically adjusting messages based on a target’s online activity. AI-powered Business Email Compromise (BEC) scams are increasing. Attackers use AI-generated phishing emails sent from compromised internal accounts to enhance credibility. AI also automates the creation of fake phishing websites, watering hole attacks and chatbot scams. These are sold as AI-powered ‘crimeware as a service’ offerings, further lowering the barrier to entry for cybercrime.
Deepfake-Enhanced Fraud & Impersonation
Deepfake audio and video scams are being used to impersonate business executives, co-workers or family members to manipulate victims into transferring money or revealing sensitive data. The most famous 2024 incident was UK based engineering firm Arup that lost $25 million after one of their Hong Kong based employees was tricked by deepfake executives in a video call. Attackers are also using deepfake voice technology to impersonate distressed relatives or executives, demanding urgent financial transactions.
Cognitive Attacks
Online manipulation—as defined by Susser et al. (2018)—is “at its core, hidden influence, the covert subversion of another person’s decision-making power”. AI-driven cognitive attacks are rapidly expanding the scope of online manipulation. By everaging digital platforms, state-sponsored actors increasingly use generative AI to craft hyper-realistic fake content. They are subtly shaping public perception while evading detection. These tactics are deployed to influence elections, spread disinformation and erode trust in democratic institutions. Unlike conventional cyberattacks, cognitive attacks don’t just compromise systems—they manipulate minds, subtly steering behaviours and beliefs over time without the target’s awareness. The integration of AI into disinformation campaigns dramatically increases the scale and precision of these threats, making them harder to detect and counter.
The Security Risks of LLM Adoption
Beyond misuse by threat actors, business adoption of AI-chatbots and LLMs introduces significant security risks. Especially when untested AI interfaces connect the open internet to critical backend systems or sensitive data. Poorly integrated AI systems can be exploited by adversaries. This enables new attack vectors, including prompt injection, content evasion, and denial-of-service attacks. Multimodal AI expands these risks further, allowing hidden malicious commands in images or audio to manipulate outputs.
Moreover, many modern LLMs now function as Retrieval-Augmented Generation (RAG) systems. Dynamically pulling in real-time data from external sources to enhance their responses. While this improves accuracy and relevance, it also introduces additional risks, such as data poisoning, misinformation propagation, and increased exposure to external attack surfaces. A compromised or manipulated source can directly influence AI-generated outputs. Potentially leading to incorrect, biased, or even harmful recommendations in business-critical applications.
Additionally, bias within LLMs poses another challenge. These models learn from vast datasets that may contain skewed, outdated, or harmful biases. This can lead to misleading outputs, discriminatory decision-making, or security misjudgements, potentially exacerbating vulnerabilities rather than mitigating them. As LLM adoption grows, rigorous security testing, bias auditing, and risk assessment, especially in RAG-powered models, are essential to prevent exploitation and ensure trustworthy, unbiased AI-driven decision-making.
When AI Goes Rogue: The Dangers of Autonomous Agents
With AI systems now capable of self-replication, as demonstrated in a recent study, the risk of uncontrolled AI propagation or rogue AI – AI systems that act against the interests of their creators, users, or humanity at large – is growing. Security and AI researchers have raised concerns that these rogue systems can arise either accidentally or maliciously. Particularly when autonomous AI agents are granted access to data, APIs, and external integrations. The broader an AI’s reach through integrations and automation, the greater the potential threat of it going rogue. This means robust oversight, security measures, and ethical AI governance essential in mitigating these risks.
The Future of AI Agents for Automation in Cybercrime
A more disruptive shift in cybercrime can and will come from AI Agents. These transform AI from a passive assistant into an autonomous actor capable of planning and executing complex attacks. Google, Amazon, Meta, Microsoft, and Salesforce are already developing Agentic AI for business use. However, in the hands of cybercriminals, its implications are alarming. These AI agents can be used to autonomously scan for vulnerabilities, exploit security weaknesses, and execute cyberattacks at scale. They can also allow attackers to scrape massive amounts of personal data from social media platforms. They can automatically compose and send fake executive requests to employees. And, for example, analyse divorce records across multiple countries to identify individuals for AI-driven romance scams, orchestrated by an AI agent. These AI-driven fraud tactics don’t just scale attacks, they make them more personalised and harder to detect. Unlike current GenAI threats, Agentic AI has the potential to automate entire cybercrime operations, significantly amplifying the risk.
How Defenders Can Use AI & AI Agents
Organisations cannot afford to remain passive in the face of AI-driven threats. Security professionals need to remain abreast of the latest developments. Here are some of the opportunities in using AI to defend against AI:
AI-Powered Threat Detection and Response
Security teams can deploy AI and AI-agents to monitor networks in real time, identify anomalies, and respond to threats faster than human analysts can. AI-driven security platforms can automatically correlate vast amounts of data to detect subtle attack patterns. These might otherwise go unnoticed. AI can create dynamic threat modelling, real-time network behaviour analysis, and deep anomaly detection. For example, as outlined by researchers of Orange Cyber Defense, AI-assisted threat detection is crucial as attackers increasingly use “Living off the Land” (LOL) techniques that mimic normal user behaviour. Making it harder for detection teams to separate real threats from benign activity. By analysing repetitive requests and unusual traffic patterns, AI-driven systems can quickly identify anomalies and trigger real-time alerts, allowing for faster defensive responses.
However, despite the potential of AI-agents, human analysts still remain critical. Their intuition and adaptability are essential for recognising nuanced attack patterns. They can leverage real incident and organisational insights to prioritise resources effectively.
Automated Phishing and Fraud Prevention
AI-powered email security solutions can analyse linguistic patterns, and metadata to identify AI-generated phishing attempts before they reach employees, by analysing writing patterns and behavioural anomalies. AI can also flag unusual sender behaviour and improve detection of BEC attacks. Similarly, detection algorithms can help verify the authenticity of communications and prevent impersonation scams. AI-powered biometric and audio analysis tools detect deepfake media by identifying voice and video inconsistencies. However, real-time deepfake detection remains a challenge, as technology continues to evolve.
User Education & AI-Powered Security Awareness Training
AI-powered platforms deliver personalised security awareness training. They can simulate AI-generated attacks to educate users on evolving threats, helping train employees to recognise deceptive AI-generated content. And strengthen their individual susceptibility factors and vulnerabilities.
Adversarial AI Countermeasures
Just as cybercriminals use AI to bypass security, defenders can employ adversarial AI techniques. For example, deploying deception technologies – such as AI-generated honeypots – to mislead and track attackers. As well as continuously training defensive AI models to recognise and counteract evolving attack patterns.
Using AI to Fight AI-Driven Misinformation and Scams
AI-powered tools can detect synthetic text and deepfake misinformation, assisting fact-checking and source validation. Fraud detection models can analyse news sources, financial transactions, and AI-generated media to flag manipulation attempts. Counter-attacks, like those shown by research project Countercloud or O2 Telecoms AI agent “Daisy” show how AI based bots and deepfake real-time voice chatbots can be used to counter disinformation campaigns as well as scammers by engaging them in endless conversations to waste their time and reducing their ability to target real victims.
In a future where both attackers and defenders use AI, defenders need to be aware of how adversarial AI operates. And how AI can be used to defend against their attacks. In this fast-paced environment, organisations need to guard against their greatest enemy: their own complacency. While at the same time considering AI-driven security solutions thoughtfully and deliberately. Rather than rushing to adopt the next shiny AI security tool, decision makers should carefully evaluate AI-powered defences to ensure they match the sophistication of emerging AI threats. Hastily deploying AI without strategic risk assessment could introduce new vulnerabilities, making a mindful, measured approach essential in securing the future of cybersecurity.
To stay ahead in this AI-powered digital arms race, organisations should:
Monitor both the threat and AI landscape to stay abreast of latest developments on both sides.
Train employees frequently on latest AI-driven threats, including deepfakes and AI-generated phishing.
Deploy AI for proactive cyber defense, including threat intelligence and incident response.
Continuously test your own AI models against adversarial attacks to ensure resilience.
The deadline for entries for the National DevOps Awards is September 19th. Finalist will be announced September 26th. Don’t miss out – book your place before the October 14th deadline.
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For nearly a decade, the DevOps Awards have celebrated innovation and excellence in DevOps, recognising the hard work and achievements driving the community forward. As an independent awards program, it highlights leaders who are shaping the future of DevOps.
Being shortlisted is a significant achievement, marking you as a key player in the industry. The awards are open to businesses of all sizes, as well as teams and individuals worldwide. With 16 diverse categories, entries are judged against a clear set of criteria, ensuring fairness and prestige.
The awards offer a unique platform to showcase your expertise, gain visibility, and connect with top professionalsin DevOps and quality engineering.
Join us in London this year and share your insights with some of the brightest minds in the field.
The DevOps Awards ensures fair and unbiased judging through an anonymous evaluation process. All judges -led by Dávid Jámbor Senior Director – Technology and Secure Infrastructure BCG – are seasoned senior professionals and they assess award entries purely on merit, with all identifying information removed. This guarantees that every winner is recognised solely for their exceptional achievements, regardless of company size, budget, or market influence.
Enterprise-wide AI platform security protects sensitive data and governs integrations to help organisations scale Agentic AI with confidence
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ServiceNow the AI platform for business transformation, has unveiled its new Zurich platform release. It delivers breakthrough innovations with faster multi-agentic AI development, enterprise-wide AI platform security capabilities, and reimagined workflows. New intelligent developer tools enable secure vibe coding with natural language. This helps turn employees into high-velocity builders and creators and lower the barrier to app creation. Built-in security capabilities, including ServiceNow Vault Console and Machine Identity Console, natively secure sensitive data across workflows. This governs integrations to help organisations scale Agentic AI and innovations with confidence. The introduction of autonomous workflows turns data into action through agentic playbooks. Uniquely offering the flexibility to apply AI and human input in workflows where and when it’s needed for greater control and efficiency.
AI Transformation with ServiceNow
Enterprise leaders are racing to move beyond table-stakes AI implementations to unlock transformative, tangible results. According to Gartner, “By 2029, over 60% of enterprises will adopt AI agent development platforms to automate complex workflows previously requiring human coordination.” The ServiceNow AI Platform delivers this transformational promise across the enterprise. It underpins a new era of highly efficient human-AI collaboration.
“Zurich marks a turning point for enterprise AI. ServiceNow is delivering multi-agentic AI systems in production that are not just powerful, but governable, secure, and built for scale,” said Amit Zavery, president, COO, and chief product officer at ServiceNow. “We are transforming the enterprise tech stack to be AI-native. From autonomous workflows that act on data with precision, to developer tools that democratise high-velocity innovation. With built-in controls for security, risk, and compliance, we’re helping organisations move beyond experimentation. And into a new era of intelligent execution.”
Vibe Coding Meets Enterprise Scale
According to Gartner, “Agentic AI features will be near ubiquitous, embedded in software, platforms and applications, transforming user experiences and workflows.” The introduction of ServiceNow Build Agent and Developer Sandbox provides resources for employees to work with AI more efficiently. They can now do this conversationally, and at scale, to solve real problems in every corner of the business.
Build Agent is a breakthrough for enterprise app creation—bringing vibe coding to the rigor of the ServiceNow AI Platform. In seconds, employees can turn an idea into a production-ready application by asking in natural language. Say, “Create an onboarding app that assigns tasks to HR, IT, and Facilities,” and Build Agent handles the rest. Design, build, logic, integrations, testing, and industry-leading governance included. What sets it apart is enterprise discipline: every app comes with audit trails, security, and compliance built in. Developers and citizen creators alike get the speed of AI with the confidence of enterprise-grade control, in a streamlined interface.
Developer Sandbox empowers developers to build better applications, faster, while maintaining the highest standards of quality. Sandboxes provide isolated environments within a single instance, so multiple teams can collaborate, build, and test new features without conflicts, and rapid scale doesn’t come at the cost of control. Teams can version, iterate, and deliver without waiting in line for developer resources. Developers can safely experiment with vibe coding, test AI-powered workflows, and resolve version control issues before changes go live. This reduces rework, shortens feedback loops, and helps teams ship higher-quality applications rapidly with lower risk.
Security That Enables AI Strategy
As enterprises adopt autonomous workflows powered by agentic AI, securing how these systems access data and communicate across environments is essential. Zurich introduces new built-in AI platform security capabilities to make it easier to protect sensitive information. It can also govern integrations and manage growing AI footprints.
The newServiceNow Vault Console provides a guided experience to discover, classify, and protect sensitive data across workflows. For example, an admin managing customer service operations can now identify personal data across tickets, apply different types of protection policies, and track compliance activity. The console also offers recommendations for protecting newly discovered sensitive data, along with customizable dashboards to monitor key metrics. What used to require manual configuration across multiple tools can now be managed in one place, with intelligent insights and a streamlined experience.
Machine Identity Console addresses the need for integration security with enterprise-grade authentication and authorization, delivering control over bots and APIs head on. As the ServiceNow AI Platform scales, every API connection, including those from AI agents, introduces another identity to manage and determine what it can access. This console gives platform teams visibility into all inbound API integrations using machine identities such as service accounts and keys, flags outdated or weak authentication methods, and provides clear steps to strengthen security. If an integration is using basic authentication or hasn’t been active in 100 days, the console spots it and helps resolve it.
Digital Transformation
“At Kanton Zürich, digital transformation is central to how we deliver secure and efficient public services. Since 2018, ServiceNow has enabled us to centralize and standardize our processes with data security as a top priority,” said Jürg Kasper, head of business solutions, Kanton Zürich. “Zurich’s latest advancements in both security and AI will allow us to automate more complex workflows, unlocking new efficiencies that enhance how we serve our citizens—with greater speed, clarity, and assurance.”
Without built-in security and trust, scaling AI comes with risk. These new security features in Zurich build upon ServiceNow’s AI Control Tower, announced in May 2025, which provides enterprise-wide visibility, embedded compliance, and end-to-end lifecycle governance for Agentic AI systems. By centralising oversight of every AI agent, model, and workflow, native or third-party, the AI Control Tower ensures organisations can scale AI with confidence, aligning innovation with enterprise-grade security and trust.
Turn Data Into Outcomes With Autonomous Workflows
As organisations rapidly scale AI, they face the added challenge of delivering solutions consistently, reliably, and responsibly. Enterprises need the right guardrails, full visibility, and strong governance to achieve service delivery. Or they risk eroding trust and slowing results. ServiceNow’s AI Platform does all this in a single platform. It sets a new standard for how organisations can create autonomous workflows to turn data into action and AI into measurable business impact.
Agentic playbooks from ServiceNow bring people, automation, and AI together seamlessly, powering autonomous workflows. A traditional playbook is a structured sequence of automated steps. These are based on predefined business rules and processes—ideal for ensuring consistency, efficiency, and trust. Agentic playbooks amplify this model by embedding AI into the trusted framework. AI agents eliminate manual effort, completing tasks in seconds and accelerating execution. This frees employees to focus on higher-value work where human judgment matters most. For example, in a credit card support situation, an agentic playbook can guide an AI agent to verify someone’s identity. It can freeze a card, send a replacement and notify the customer while allowing a human agent to step in. The result: governed, efficient, and trusted work—supercharged by AI to deliver faster, smarter outcomes.
The ServiceNow Zurich platform release also seamlessly combines Process and Task Mininginsights within a unified platform. These new capabilities give organisations an end-to-end understanding of how work gets done. Revealing where human expertise is essential, and where AI agents can deliver the greatest impact. With process intelligence built directly into the platform, customers can move seamlessly from insight to action. Streamlining operations, applying AI where it matters most. And accelerating real business outcomes without the complexity of disconnected legacy tools.
Mike Puglia, General Manager, Kaseya Cybersecurity Labs, on how the need for regulatory support to better support industries when tackling cybercrime
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Cyberattacks keep coming hard and fast, but things are beginning to change. In the past few months, law enforcement has announced arrests of three people in the Marks & Spencer breach, seven members of the hacking group NoName057, five affiliates of Scattered Spider and also disrupted the infrastructure of gangs such as Flax Typhoon, Star Blizzard and others.
Earlier this year, the UK retail industry felt the pressure. Brands, including Marks & Spencer, Harrods and Co-op – and by proxy, their customers – became victims of the hacking group, Scatter Spider. Other businesses are now on high alert as this wave of security breaches is expected to continue. For as long as bad actors can reap rewards and the risk of consequences remains small, they will keep attacking. Ransomware-as-a-service lowers the bar to entry further, allowing even those without specialised skills to launch successful ransomware campaigns.
Along with the threats, regulatory pressure on businesses is growing. Organisations must be able to prove they have strong security defences in place or risk paying hefty fines for non-compliance. However, this means we are essentially punishing the victim, not the perpetrator. By putting the onus on the victims to protect themselves, we are missing an important truth… Because there is no bullet-proof defence, even the best security strategies will not end cybercrime for good.
It’s Time to Treat Cybercrime as Crime
What the industry needs instead is a change in how we approach cybercrime. Rather than blaming the victims, we must start treating it as the serious criminal activity it is. It is high time we addressed cybercrime’s fundamental drivers. Opportunity, motive and the widespread perception that criminals can still get away without punishment. As is the case with physical crime, it takes a two-pronged approach to curb cybercrime: Prevention – and an effective response.
Those who attempt physical theft, for example, face trials and potentially prison. While we have seen a growing number of cybercriminals arrested in recent months, the truth we are only scratching the surface. In the digital world, everything is accessible from everywhere, all the time. This creates an inherent vulnerability that makes perfect protection impossible. In many cases, it also makes it much harder to track down the offenders and hold them accountable.
The Problem with Cryptocurrency and Jurisdiction
The cybercrime landscape has also undergone a significant transformation. While in the past, hackers were mostly focused on stealing financial data, there has been a dramatic shift towards ransomware. It’s far easier to encrypt an organisation’s data and demand a ransom than finding buyers for stolen credit card info.
This transformation has further accelerated because cryptocurrency allows cyber attackers to be paid in anonymous currency. Anywhere in the world, at any time. Previously, criminals had to physically collect payments or transfer money to traceable bank accounts. Now, they can operate with anonymity whilst easily converting their loot into real euros, pounds and dollars. This means ‘following the money’ is no longer a useful way for law enforcement to track nefarious activity. If we made it impossible for criminals to anonymously convert cryptocurrency into real currency, we could change the risk-reward calculation.
The second key issue with fighting cybercrime is the question of jurisdiction. Many cybercriminals are based in countries where western governments have no recourse. When hackers operate from non-cooperative jurisdictions, it may be impossible to extradite them. And they may find their activities tolerated by their local government or even supported. As we have seen with the recent arrests – the threat actors were outside of Russia and China – where many attacks come from.
These two factors – anonymous payment systems and safe havens – create an environment where cybercrime can and will continue to flourish. While organisations can do their best to make it harder for criminals to attack, it is foolish to believe individual businesses will be able to solve the cybercrime problem on their own.
Stop Blaming the Victim
So, what needs to happen? First, the victim-blaming approach must change. We simply cannot regulate every business to become an impenetrable fortress. When a person is physically robbed, police respond to investigate the crime and help recover stolen property. With cybercrime, victims face reputational damage, fines and higher insurance premiums. Incidents often raise questions about where the business’ cybersecurity strategy failed, rather than a recognition that a crime has been committed against them.
A first step forward towards solving the cybercrime problem would require governmental and societal recognition that cyberattacks represent crimes against businesses and individuals, not merely failures of those organisations to adequately defend themselves. While many countries have ramped up policing efforts against cybercrime, these are generally underfunded considering the scale of the problem.
Secondly, we need to urgently address the anonymous payment systems that keep fuelling cybercrime. This is not an easy problem to solve, but governments must find better ways to trace and regulate how cryptocurrency is converted into real money.
It is also time we introduced real and severe consequences for cybercriminals. The number one deterrent to any type of crime is fear of being caught and punished. The internet has essentially eliminated this, enabling hackers to operate from nations that turn a blind eye. To address this will require more political pressure on ‘safe harbour’ countries to charge, punish and extradite cybercriminals. Where nations refuse to cooperate, potential sanctions such as restrictions on internet connectivity might force governments to reconsider their tolerance for criminal activities.
Finally, we need to acknowledge that regulations such as GDPR, PCI and NIS have their limits. Despite increasingly complex compliance requirements, cybercrime has continued to grow. While regulations can provide critical and much-needed guidance to businesses, they must be combined with properly funded law enforcement – empowered with tools to bring criminals to justice across jurisdictions.
To truly disrupt the criminal ecosystem, systemic changes are needed. We are starting to see governments give law enforcement the tools they need, but it is very early in that process. Because ultimately, we will not solve the cybercrime problem with defence measures alone.
About Kaseya
At Kaseya, our mission is to empower you to simplify and transform IT and cybersecurity management with innovative platform solutions.
Our Mission:
Since 2000, Kaseya has delivered the technology that IT departments and managed service providers need to reach new heights of success. More than 500,000 IT professionals globally use Kaseya products to manage and secure 300 million devices.
Kaseya’s commitment to our customers goes beyond listening to your needs and puts words into action to deliver innovative solutions that empower your business. But we don’t stop there. Kaseya’s first-of-its-kind Partner First Pledge program shares the risk our partners experience because we know a true partner is with you through the ups and downs of life.
TechEX Europe – Powering the Future of
Enterprise Technology at Amsterdam’s RAI Arena September 24-25
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TechEx Europe unites five leading enterprise technology events — AI & Big Data, Cyber Security, Data Centres, Digital Transformation and IoT — into one powerful experience designed for organisations driving change. Five events, two days, one ticket – register for your pass here.
From scaling infrastructure to unlocking new efficiencies, this is where decision-makers and their teams come to connect, explore real-world use cases, and discover the technologies that will shape their next phase of growth.
AI & Big Data Expo
The AI & Big Data Expo is the premier event showcasing Generative AI, Enterprise AI, Machine Learning, Security, Ethical AI, Deep Learning, Data Ecosystems, and NLP
Speakers include:
Cybersecurity & Cloud Expo
The Cyber Security & Cloud Expo, is the premier event showcasing the latest in Application and Cloud Security, Hybrid Cloud, Data Protection, Identity and Access Management, Network and Infrastructure Defence, Risk and Compliance, Threat Intelligence, DevSecOps Integration, and more. Join industry leaders to explore strategies, tools, and innovations shaping the future of secure, connected enterprises.
Speakers include:
IOT Tech Expo
IoT Tech Expo is the leading event for IoT, Digital Twins & Enterprise Transformation, IoT Security, IoT Connectivity & Connected Devices, Smart Infrastructures & Automation, Data & Analytics and Edge Platforms.
Speakers include:
Digital Transformation
The Digital Transformation Expo is the leading event for Transformation Infrastructure, Hybrid Cloud, The Future of Work, Employee Experience, Automation, and Sustainability.
Speakers include:
Data Center Expo
The Data Centre Expoand conference is the premier event tackling key challenges in data centre innovation. It highlights AI’s Impact, Energy Efficiency, Future-Proofing, Infrastructure & Operations, and Security & Resilience, showcasing advancements shaping the future of data centre.
The Financial Transformation Summit (FTS), presented by MoneyNext, took place June 18-19 2025 at London’s ExCeL Centre, Royal Victoria Dock. With over 2,000 attendees, 300+ speakers, and 400 roundtables, it stood out as one of the most immersive and interactive events in the financial services calendar.
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FinTech Strategy hit the conference floor at the heart of the action delivering insights from experts across Banking, Insurance, Wealth, and Lending at Financial Transformation Summit (FTS).
Financial Transformation Summit attendees from banking, insurance, wealth, lending, fintech, consultancy, and regulatory sectors convened for two days packed with keynotes, panel talks, immersive demos, and networking among 60+ exhibitors and startups.
Co-located streams – Banking, Insurance, Wealth, and Lending part of themed zones– meant that ticket-holders could explore adjacent sectors fluidly across a guiding theme: culture, collaboration, and customer centricity driving tech adoption and transformation.
Programme Highlights
Keynotes & Panels
1. Data Silos & Cross‑Institutional Collaboration
A panel featuring senior leaders from EVLO, Aon, Schroders, and Brit Insurance tackled how institutions – despite collectively spending over $33 billion annually on data – still struggle to collaborate due to privacy concerns and regulation. Innovative solutions included federated learning, anonymised client IDs and consent-backed APIs.
2. Digital Insurance via Wallets
Anna Bojic (Miss Moneypenny Technologies) unveiled a fresh take on insurance – embedding policy and claim data into Apple/Google Wallets. The idea: dynamic customer interaction directly from smartphone wallets, enhancing real‑time engagement and retention.
3. ESG Economics & Market Reality
Marc Kahn (Investec) challenged ESG orthodoxy, urging firms to emphasise human and planetary wellbeing – beyond purely financial returns – to capture stakeholder trust and sustainable growth.
4. People & Psychological Safety
Kirsty Watson (Aberdeen Group) and Vikki Allgood (Fidelity International) underlined that technological investments are futile without organisational design and psychological safety. Allgood cited a McKinsey study revealing only 26% of leaders build teams with a sense of safety – a critical step toward innovation.
5. Human‑Centred AI
Monica Kalia (Planda AI) championed AI that models individual financial contexts – recognising diversity within demographic cohorts and personalizing services accordingly.
Roundtable Experiences at FTS
At the event’s heart were the TableTalk roundtables – 400+ small-group sessions, each led by a subject-matter expert. These were limited to six participants each, enabling deep, peer-led discussions on themes like:
AI in risk and compliance
Open banking integration
ESG data standards
Cyber resilience
Change management and culture adaptation
Attendees consistently praised their interactive nature – far removed from the stage‑focused “listening” format often critiqued at other conferences.
Demonstrations & Exhibitor Showcase
Over 60 exhibitors presented tech-driven innovations: Generative AI, open‑banking APIs, ESG reporting tools, embedded finance solutions, and more. A few standouts were:
CRIF highlighted AI-powered credit scoring with ESG overlays – promising dynamic risk assessments backed by sustainability data
Emerging FinTechs demoing AI compliance engines, digital wallet insurance packaging, and data-sharing platforms
Hylanddemonstrated the intuitive end-user experience of its Hyland Content Innovation Cloud™ and showed how easy it is to configure, tailor and deploy solutions that can empower key stakeholders across any business
The demo zone allowed engaging, hands-on exploration and real-time Q&As; it complemented the content with practical insights.
Standout Themes & Strategic Insights
1. Tech is Not Enough Without Culture
Recurrent messaging emphasised that culture, trust, governance, and psychological safety are foundational – not secondary – to digital initiatives. Technology alone won’t deliver transformation without a people-first mindset.
2. Cross‑Sector Data Collaboration
Despite heavy investment, institutions still operate in silos. Shared, secure infrastructure and regulatory-aligned frameworks are being prototyped, but broad adoption remains a work in progress.
3. AI-as-a-Personalisation Backbone
AI is shifting from automation to empathy. Organisations showcased tools to hyper-personalise offers yet maintain privacy and inclusion – moving beyond outdated demographic frameworks into genuine behavioural understanding.
4. Embedded Finance & Digital Wallets
Insurance via wallet applications and embedded finance models point to seamless customer journeys – less app hopping, more value delivered at the point of need.
5. Rebalancing ESG & Profit Metrics
Speakers emphasised integrating ESG factors into performance metrics – not just for compliance, but as an operative advantage anchored in long-term stability and stakeholder trust.
Who Should Attend FTS Next Year?
Ideal for:
Transformation and change leaders
CTOs, CIOs, and Heads of Innovation
Data and AI strategists
Operational and HR leaders focused on culture
FinTech innovators and solution providers
If you’re crafting digital transformation strategies, an attuned leader in financial services, or a consultant embedding tech in legacy environments, this summit provides rich, actionable content.
Expect next year’s event to build on this foundation:
More AI-specific tracks, possibly Generative AI streams
ESG deep-dives with case studies on implementation
Expanded regulator involvement around data governance and cross-border compliance
FTS: Final Verdict
Overall, the FTS 2025 delivered on its brand promise:
Interactive and inclusive: 400 roundtables empowered voices across levels.
Cross‑sector learning: Banking, Insurance, Wealth, and Lending streams offered both breadth and depth.
Insightful keynotes: Big ideas on AI, ESG, data-sharing, and culture were well-explored.
Real-world relevance: Exhibitor demos connected theory with practice.
Networking with purpose: Opportunities to engage, learn, and collaborate were abundant.
The Financial Transformation Summit struck a compelling balance between big-picture vision and granular, execution-level insight. It emphasised that while technology enables; culture, customer centricity and collaboration drive real progress. The format – with its roundtables, demos, and keynotes – offered a dynamic platform for knowledge exchange.
If you attended, chances are you left with practical next steps. If you didn’t, you missed one of the most interactive, future-focused events shaping financial services transformation today.
Join thousands of data centre industry leaders and innovators at London’s Business Design Centre for three co-located events – DCD>Connect, DCD>Compute and DCD>Investment September 16-17
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Data Center Dynamics (DCD) is connecting the data center ecosystem. Secure your pass for three-colocated events covering the entire digital infrastructure ecosystem across two days at London’s Business Design Centre – DCD>Connect, DCD>Compute and DCD>Investment.
Bringing together more than 4,000 senior leaders working on Europe’s largest data center projects. DCD>Connect | London will drive industry collaboration, help you forge new partnerships and identify innovative solutions to your core challenges.
“First class event that presented a wide variety of perspectives and technologies in an engaging and informative forum” – Data Center Project Architect, AWS
DCD Compute
Uniting enterprise and hyperscale leaders driving scalable AI Infrastructure from silicon to software…
New workloads are fundamentally reshaping IT infrastructure, as accelerated hardware innovation is enabling more new workloads. How can you keep up in this rapid cycle of new AI models, new hardware, new software, and the race to be first to market?
The Compute event series, run in partnership with SDxCentral, empowers leaders to make sharp decisions on IT infrastructure and AI deployment. Join 400+ peers from enterprise, hyperscale, and top IT infrastructure and architecture innovators to shape the future of compute—on-prem or in the cloud.
400+ Decision-Makers for IT Infrastructure, Architecture, AI, HPC and Quantum Computing
60+ industry-leading speakers at the forefront of innovation across cloud and on-prem compute
Hosted in partnership with SDxCentral
DCD Investment
Connecting senior dealmakers driving the economic evolution of digital infrastructure…
The world depends on digital infrastructure, and there’s never been more pressure on the industry to scale at speed. The Data Center Dynamics Investment series helps the leading dealmakers behind this growth to make informed decisions faster, through top-tier content, tailored networking, and best-practice sharing.
Dynamic Programme: A brand new format including leadership roundtable discussions allows for 2025 attendees craft their own agenda at the Forum.
50 Speakers: The C-suite operators, leading investors, and advisors in data centers are converging to strategize on the industry’s evolving landscape.
Exclusive Networking Opportunities: The Investment Forum is separated from the main DCD Connect programme and show floor, offering private networking and dealmaking opportunities to take place in an optimal setting.
Collaborating with Amdocs has been a game-changer for Telkom. Here’s why.
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As telecom companies race to adopt generative AI, a critical shift is underway – from generic copilots to deeply verticalised, telco-grade agents. Amdocs, in collaboration with AWS and NVIDIA, is leading this evolution with its amAIz Agents – introducing a new class of AI agents built specifically for the telecom industry.
Unlike general-purpose AI, verticalised agents are built with domain-specific knowledge, reasoning, and telco ontology that reflect the complexity of telecom operations. These agents understand service plans, billing structures, and network topologies, enabling them to deliver context-aware responses and take meaningful action.
Amdocs, NVIDIA and AWS released a publication that defines and showcases how AI agents can be tailored for specific telecom domains, illustrating the concept of ‘agent verticalization’ and its impact on operational efficiency and customer experience. These domain-specific agents, across every telco domain like care, sales, network, and marketing, work in coordination, enabling end-to-end automation and intelligent customer engagement through seamless orchestration.
In the whitepaper, ‘AI Verticalization for Telco’, Amdocs outlines the essential traits of telco-grade agents such as composable architecture, reasoning, and agentic experience, and enterprise-grade traits such as trust, security, and cloud-native scalability.
Amdocs: Three decades as a key transformation partner
It’s a rare thing, in the fast-paced world of technology, for partnerships to last decades. However, for Telkom, Amdocs has been by its side for almost 30 years. The latter has played a critical role in supporting both mobile and wireline operation through its B/OSS platforms. These platforms are regarded as industry leaders, and Telkom has been able to navigate major shifts with Amdocs’s help, from legacy to next-gen digital stacks.
“We have been in this game for some time, being the digital backbone of choice for South Africa, really, Amdocs has been a strategic partner of Telkom for over 30 years,” says Dr Noxolo Kubheka-Dlamini, Chief Digital and Information Officer at Telkom. “We have a shared goal of delivering a better, faster, and more seamless experience to our customers. What stands out about Amdocs is their deep domain expertise, strong delivery capabilities, commitment to our success, and ability to evolve with our ambitious goals. We see them as an extension of our own teams.”
This month’s cover star, Dr. Noxolo Kubheka-Dlamini – Chief Digital and Information Officer at Telkom Consumer & Small Business, speaks to the process of leading an ongoing digital transformation
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Welcome to the latest issue of Interface magazine!
Our cover star talks us through the process of leading an ongoing digital transformation that is pragmatic, strategic and embedded in business goals at South Africa’s largest telecommunications platform provider. “By the time we entered the mobile space in 2010, the market was already saturated,” explains Dr. Noxolo Kubheka-Dlamini, Chief Digital & Information Officer at Telkom Consumer & Small Business. “Our ambitions were constrained by limited capital, inherited legacy systems, regulatory shackles, and the sheer inertia of being a former state-run monopoly.” However, Telkom’s “willpower and commitment never faded” resulting in “notable and consistent performance against all odds”. Today, Telkom is playing a pivotal role in ensuring access to meaningful connectivity, driven by the company’s vision to become South Africa’s digital backbone: bridging the digital divide and enabling inclusive participation in its digital economy.
Kynegos: Shining a Spotlight on Transformation, Innovation and Sustainability
Kynegos, a spin-off from Capital Energy, is a business built on strategy. It exists to develop technological solutions for strategic industries. Capital Energy needed an independent platform that could scale digital solutions beyond the energy sector, and foster collaboration with startups and technology centres. Kynegos has filled this gap, and is being leveraged to create co-innovation ecosystems. This allows Capital Energy to develop digital tools that address current and future industrial challenges, keeping the company’s finger on the pulse. We spoke to CEO Victor Gimeno Granda, about its backstory, its values, and the road ahead. “Not only do we develop digital assets for the renewable sector, but for green data centres as well. My perspective is that sustainability is going to be more relevant than ever in the next 18 months.”
York County: The Human Side of AI
York County’s IT team has spent the past decade redefining what local government tech can and should be. From pioneering community cybersecurity workshops to forging statewide collaboration through ValGITE, the county has systematically brought innovation into its operations. This broad portfolio of initiatives has strengthened infrastructure and elevated service delivery. And also earned York County the number one spot in the Digital Counties Survey for jurisdictions under 150,000 population.
“Since I became deputy director eight years ago, this has been one of my goals,” reflects Tim Wyatt, director of information technology at York County. “And over the last eight years, we’ve been in the top 10, but we finally landed that number one place. I think it’s a great reflection for my team, the county, and all the dedication to try to do what’s right by the citizens. It’s just something I’m incredibly proud of. I think it accurately reflects the hard work of my team.”
Wade Trim: Bridging the Cybersecurity Skills Gap
Wade Trim provides consulting engineering, planning, surveying, landscape architecture and environmental science services to meet the infrastructure needs of government and private corporations. With a cybersecurity skills gap leaving vacancies unfilled, Wade Trim’s Senior Manager of Information Security, Eric Miller, spoke with Interface about how stepping away from education-focused rigidity could unlock swathes of latent talent. “Our industry puts emphasis on certifications. However, being passed over for jobs because you don’t have a particular certification or degree in favour of someone fresh out of college has shown me that the best candidates are those that can tell me their story. What brings them to this point in their career? Tell me what qualifies you for this role. That’s how I interview.”
York Catholic District School Board: York Catholic District School Board: Community and Communication at the Heart of IT Strategy
The challenges facing an IT leader in 2025 call for a new kind of approach. One that favours partnerships over transactions, collaboration over competition, and centres people rather than technology for technology’s sake. These perspectives ring especially true in an organisation like the York Catholic District School Board (YCDSB). It emphasises values like “service, community, collaboration, and fait rather than academic excellence alone,” explains Scott Morrow, YCDSB’s Chief Information Officer (CIO). “It’s not actually about the technology; it’s about enablement.”
We spoke with Morrow to learn more about his approach to IT leadership. From building and maintaining a team amid the IT talent crisis, to driving digital transformation initiatives across the organisation. And broader strategic objectives across a changing technology landscape increasingly defined by cybersecurity and the rise of AI.
FinTech Strategy meets Eastern Horizon Founder & CEO Christine Le to discuss client expectations and the changing landscape of wealth management
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Financial Transformation Summit 2025 EXCLUSIVE
At Financial Transformation Summit, Christine Le, a Chartered Financial Planner and Founder & CEO of Eastern Horizon Wealth Management, spoke on an investment panel – “Generational Wealth Transfer: Meeting the Expectation of Younger Clients”. Appearing with industry colleagued representing Citi Global Wealth, HFMC Wealth and Lightbox Wealth, Le considered: What trends and technologies are shaping NextGen investment decisions, and how can WMs stay ahead? Can digital wealth platforms meet the demand for hyper-personalised, user-friendly experiences? How does social responsibility & ESG investing influence younger investors, and how can advisors align with these priorities? How can wealth managers build and maintain trust with NextGen investors?
Following the panel, we spoke with Christine to find out more…
Hi Christine, tell us about your role at Eastern Horizon?
“I’m a Chartered Financial Planner and the Founder & CEO of Eastern Horizon Wealth Management. We are a financial advisory firm and also a partner practice of St. James’s Place. They are among the biggest wealth management firms in the UK based on assets under management. We get a lot of support from St. James’s Place in terms of technology compliance and investment solutions. At my practice, we focus on a diverse range of clients including ethnic minorities, especially British Asians in the UK. I’m also the president of the Vietnam Investment and Finance Association in the United Kingdom (VIFA). We aim to provide useful financial information for Vietnamese people in the UK and become a bridge between Vietnam and the UK.”
You were part of a panel at this Summit focused on Generational Wealth Transfer. Can you give us an overview of your thoughts?
‘’Having worked in the financial services industry for over 15 years, I’ve observed a persistent gap in how the industry serves diverse client segments – particularly ethnic minority communities in the UK. This gap is especially pronounced when it comes to financial education and long-term planning, including wealth transfer across generations. When I speak to members of my own Vietnamese community, I often find that there’s a limited understanding of how to navigate financial systems effectively – from managing investments and pensions to planning for intergenerational wealth. It’s not due to a lack of interest or ambition, but rather a lack of access to culturally relevant and accessible financial advice.
“This is where I believe I can make a meaningful difference. I not only bring professional expertise and technical knowledge to the table, but also a deep understanding of the cultural values, family dynamics, and communication styles that shape financial decision-making in the community. That cultural insight is key to building trust, something that is essential when discussing personal finances and planning for the future. My goal is to help bridge that gap – to empower families with the knowledge and tools they need to make informed financial decisions, preserve their wealth, and pass it on confidently to the next generation.’’
Why is this an exciting time for the business?
“At the moment the world is so integrated, and many people can benefit. A lot of people want to go to the UK, invest into the UK. I think with that in mind this is an exciting time to run my business and to be able to bridge that gap, providing sufficient knowledge for people as a trusted source when they come to the UK and need to understand the financial regulations. We can give people solid support to understand the financial processes of settling and building wealth in the UK.”
What other trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“Right now, everyone is talking about AI, and for good reason. In my business, we rely heavily on digital tools to streamline administrative tasks. It’s truly a game-changer. Compared to starting a business 15 years ago, when I would have needed a full-time assistant just to take meeting notes and summarise action points, many of those processes can now be automated, saving both time and cost. Another advantage is in how we communicate. Many of my clients are British Vietnamese. While they understand and speak English, they often feel more comfortable communicating in Vietnamese. We use AI-powered translation tools to make this process faster and more seamless. These technologies are allowing us to broaden the range of services we offer and tailor our support to each client’s needs.”
What pain points are your clients experiencing that you need to address? How are you meeting the challenge?
“It’s about meeting the client’s highest priority. When people come to me, they maybe want to support their children to get onto the property ladder or plan for their retirement. They might be looking to buy a new car or move home. So, as a regulated financial advisor, I can sit with a client and talk them through key priorities and tailor the solutions best for them and help them overcome the pain points of decision-making.
“Additionally, the UK’s financial regulations are complex and changing all the time. It’s very difficult for people to follow. It’s my job as a financial advisor to follow up those changes and stay up to date with the regulations to assess how it can impact our clients and then give them the best recommendations. Allied to this, many of our clients will need support with cross-border services as they move freely between different countries they need somebody they can trust, an expert that knows what they’re doing and who can provide the right financial services for them.”
Tell us about a recent success story…
“Success for Eastern Horizon is to know that our clients feel they have somebody to rely on. For example, I have an old friend who came to me as a client. She was based in Vietnam but wanted to relocate to the UK. She had assets across Europe and in Vietnam and needed to understand the big picture of financial planning in the UK. We examined her assets across different countries to bring them into the UK and find the best solution for her to utilise tax efficient savings, pensions and investments to support her family and her business in the long term.”
What’s next for Eastern Horizon when it comes to wealth management? What future launches and initiatives are you particularly excited about?
“Over the next few months, we are keen to collaborate with different associations and communities across the UK – whether that’s related to Vietnam or British Asian communities and offer useful information and workshops and webinars tailored to different audiences. Also, with my work for the Vietnam Investment and Finance Association I want to organise workshops for those keen to invest in the UK but don’t know where to start. They often don’t have anyone to support them so I would like to focus on building a network to offer that bridge to investment in the UK.”
Why do you think the evolution of collaboration between traditional institutions and FinTechs is set to continue? What are you excited about?
“I spent five years working at the intersection of FinTech and WealthTech – where wealth management meets technology. During that time, I witnessed firsthand how the financial services landscape is evolving. Large incumbent banks bring undeniable strengths: scale, regulatory rigour, and long-standing client trust. However, they often struggle with agility. Their legacy infrastructures, many of which still aren’t cloud-based, make digital transformation slow and complex. On the other hand, FinTechs are born digital. They’re nimble, innovative, and quick to adapt to changing customer needs. But without the reputation and stability that traditional institutions have built over decades, they can face challenges in gaining consumer trust or navigating regulatory environments alone. What became clear to me is that banks and FinTechs cannot operate in silos.
“Collaboration is not just beneficial, it’s essential. When they work together, they combine the best of both worlds: the reliability and compliance of traditional finance with the innovation and customer-centric design of new technology. With my own practice, we apply this mindset. We actively look for ways to streamline administrative processes using digital tools – reducing costs, improving efficiency, and freeing up more time to focus on what matters most: building strong, human relationships with our clients. The goal is to use technology not to replace that human connection, but to enhance it. By doing so, we can deliver modern, efficient, and deeply personalised financial services that clients trust.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for Eastern Horizon?
“I’ve attended several events this year, and this has truly been one of the most enjoyable and well-organised in the UK. What stood out was the impressive mix of voices – from established financial institutions to bold, forward-thinking startups. Engaging with such a diverse group of speakers has been both insightful and thought-provoking. I’ve come away with fresh perspectives, challenged some of my own assumptions, and found new ideas to explore as we continue building meaningful partnerships for Eastern Horizon Wealth Management.”
About Christine Le and Eastern Horizon Wealth Management
As an Appointed Representative of St. James’s Place, Practice Lead, and business owner, Christine leverages over 15 years of experience in financial services and wealth tech to serve our clients, acquired through extensive work in multinational financial services firms in the UK. This rich background has equipped Christine with the skills and knowledge necessary to effectively oversee the business, ensuring that every facet is managed with the highest level of professionalism.
Christine founded and built this Practice to help clients prosper, build financial security, and attain peace of mind while overcoming financial obstacles.
Her primary focus is on nurturing enduring relationships with her clients, offering them trusted guidance as their financial requirements evolve over time. Throughout her advisory process, clarity remains paramount. By closely collaborating with her clients, Christine strives to identify the most efficient and tax-effective strategies to help them achieve their objectives. Specialising in tailored solutions, Christine is dedicated to understanding her clients’ financial goals and crafting strategies that align with their vision for the future.
FinTech Strategy meets with Citigroup’s Head of ESG Credit Management, Mauricio Masondo, to discover the future for ESG and sustainable finance
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Financial Transformation Summit 2025 EXCLUSIVE
At Financial Transformation Summit, Mauricio Masondo, Head of ESG Credit Management at Citigroup, featured on a sustainability panel – ‘The Future of ESG and Sustainable Finance: Balancing Profit and Purpose’. Alongside peers fromGenerali AM, Gallagher Re and Arma Karma, Masondo considered: What key metrics should FIs use to track ESG progress, and how can they ensure authenticity in their sustainability efforts? Developing a holistic ESG strategy amid evolving regulations – key challenges and solutions. How can FIs leverage technology to meet sustainability goals and drive long-term profitability? How can FIs move beyond offering ESG products to embedding sustainability into their core business models?
Following the panel, we spoke with Mauricio to find out more…
Hi Mauricio, tell us about your role at Citigroup?
“In my 32 years with Citi my career has primarily focused on wholesale credit, and in recent years I built out our portfolio management function. For the past year specifically, I’ve been leading the integration of ESG and climate considerations into our credit processes.As Head of ESG Credit Management, my role is to embed ESG requirements into our credit processes in a way that’s consistently and efficiently applied through technology, policies, training, and governance frameworks. Our strategic approach was not to create an ESG silo that replicates existing processes, but rather to integrate ESG considerations seamlessly into our current workflows. This means any credit analyst can now underwrite ESG credits, sustainable loans, or green loans, rather than requiring dedicated specialists. We’ve equipped our entire team with the knowledge and tools they need to handle these transactions effectively.”
You were part of a panel at this Summit focused on the future for ESG and sustainable finance. Can you give us an overview of your thoughts?
“Data standardisation is absolutely critical, especially as we advance into the AI era. I often reference Moody’s as an excellent example of strategic foresight. Moody’s operates two key businesses – credit ratings and data analytics – and early in their AI journey, they made the strategic decision to structure and normalise all their credit research data. This proved to be transformational because it enabled them to deploy AI solutions much more rapidly with clean, structured datasets. We’re working to apply this same principle at Citi. We’re developing processes to structure climate-related data in a way that will be usable across multiple applications. For example, we’re working on integrating emissions data and climate risk assessments into our credit risk rating models. We’re also exploring how this structured approach could support underwriting processes and securitisations, where comprehensive data packages could facilitate risk transfer transactions with institutional investors. The goal is to build normalised, structured data as the foundation for various applications, from portfolio management to AI-driven solutions. While we’re still in the early stages of many of these initiatives, the potential is significant.”
Why is this an exciting time for the business?
“We’re witnessing the convergence of several transformative trends. However, one of our biggest challenges is policy divergence across jurisdictions. Countries are taking vastly different approaches to ESG requirements, and for a global bank like Citi, this creates significant complexity in standardising processes across multiple regulatory environments. While challenging, this divergence also creates opportunities to develop scalable, cost-effective solutions that can adapt to various regulatory frameworks.Second, AI is revolutionising how we approach ESG challenges. It’s helping us structure data more effectively, enhance reporting capabilities, contextualise information, and identify trends that would have been impossible to detect manually.
“Previously, comprehensive ESG analysis required significant time, resources, and personnel. AI has made these processes more accessible and cost-effective.Most importantly, there’s been a fundamental shift in how the industry, and governments, view ESG. It’s evolved beyond compliance and emissions reporting to become a significant business opportunity. We need to capitalise on this transition – moving from reactive reporting to proactive opportunity capture. The capital is there, and if traditional banks don’t seize these opportunities, asset managers, private credit firms, and private equity will. We’re partnering strategically with reinsurance companies and asset managers to develop innovative solutions that unlock transition capital and help companies fund decarbonisation projects.”
What other trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“Trade flows are experiencing significant disruption due to current tariff policies. This creates both challenges and opportunities for our clients. Companies are reassessing their supply chain vulnerabilities and seeking greater resilience in their operations.I anticipate we’ll see a regionalisation of trade flows rather than a complete deglobalisation. European companies will likely increase intra-regional trade while reducing intercontinental transactions. We’re seeing similar patterns emerging in Asia and the Middle East. This shift requires banks to be more agile in how we structure trade finance and working capital solutions to meet these evolving needs.”
What pain points are you experiencing that you need to address? How are you meeting the challenge?
“Working capital finance requires increasingly creative solutions that leverage advanced technology. Banks are recognising that FinTechs often have greater agility in developing and implementing these technologies. There’s significant efficiency in having one FinTech serve multiple banks rather than each institution developing independent solutions. This collaborative approach allows us to move faster while reducing development costs and time-to-market.”
Tell us about a recent success story…
“I designed and led the implementation of an early warning monitoring system for Citi’s credit portfolio. The project began with a fundamental concept: create a data lake, develop meaningful metrics, and engage data scientists to interpret the insights. We collaborated with trade officers and partnered with external specialists to enhance our capabilities.Initially, there was scepticism about the system’s value, particularly because we built it as an independent function within our portfolio management organisation, separate from traditional banking and risk management structures. However, this positioning allowed us to collect unique client data and develop insights that weren’t available elsewhere in the organisation.A critical component of our success was establishing a dedicated credit expert team that oversees the entire process.
“This team leads the engagement and communication of alerts, ensuring that insights are properly interpreted and actionable recommendations reach the right stakeholders.The evolution was remarkable. We progressed from generating a few alerts daily to dozens per day, and eventually to hundreds of alerts weekly. More importantly, we developed sophisticated processes for interpreting and acting on these alerts, with our expert team serving as the bridge between data insights and business action. Bankers and risk managers began to recognise the value, and today, three years later, the system is integral to how we conduct annual reviews and client presentations. It’s incredibly rewarding to provide our bankers with comprehensive data and insights that strengthen their client relationships.”
What’s next for Citigroup when it comes to ESG? What future launches and initiatives are you particularly excited about?
“While it may sound clichéd, AI truly is transformative for our industry. The breadth of use cases and the rapid pace of learning make it essential to our strategic direction. We’ve established a strategic partnership with Google and are investing significantly in AI use case development and implementation across our operations. From an operational perspective, AI will undoubtedly increase our efficiency as an industry. More importantly, it’s enabling us to evolve our business models and create client solutions that weren’t previously feasible. This opens entirely new avenues for innovative product development. Additionally, since CEO Jane Fraser joined, we’ve embarked on a comprehensive transformation program that’s delivering strong results in terms of financial performance and returns. We’ve restructured and simplified our operations, which positions us more competitively as we refresh our leadership teams and attract new talent. The trajectory is very promising.”
Why do you think the evolution of collaboration between banks and FinTechs is set to continue? What are you excited about?
“The current tariff environment is creating opportunities for FinTechs that facilitate connections between banks, investors, and corporations. It’s also presenting consolidation opportunities for private equity firms within the rapidly expanding FinTech ecosystem.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for Citigroup?
“The panel brought together diverse perspectives from FinTech, asset management, insurance, and banking – all addressing common challenges that span our sectors. This cross-industry dialogue creates tremendous opportunities for collaboration and mutual understanding.The key now is translating these conversations into action. We need to maintain these connections, expand the dialogue, and avoid making decisions in isolation. FinTechs possess the agility to implement changes in their operating models far more quickly than large incumbents like us. However, our procurement systems and processes aren’t always conducive to collaborating with smaller, innovative companies.Events like this highlight the need to streamline how institutions like Citi can collaborate with and learn from FinTechs. We must accelerate our ability to adapt to a rapidly changing world.”
We’re helping build more sustainable, economically vibrant communities around the world.
At Citi, helping our clients navigate the challenges and embrace the opportunities of our rapidly changing world is fundamental to our mission of enabling growth and economic progress.
FinTech Strategy spoke with Veritran’s CMO, Jorge Sanchez Barcelo, at Money20/20 Europe to find out more about the tech firm’s partnership with Manchester City reimagining CX to create a frictionless digital experience for fans
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Money20/20 Europe Exclusive
In an era where technology defines the customer journey, Jorge Sanchez Barcelo, Chief Marketing Officer at Veritran, is leading a bold charge into a new frontier: one where financial technology fuses with fandom, and CX becomes both frictionless and deeply personal.
Jorge’s professional journey has always followed the arc of digital transformation. From his earlier roles at AT&T and Banorte to now helming marketing at Veritran, a global technology company, his mission is clear: make life easier, better, and more secure for end users – whether they’re banking customers or football fans.
“Our technology without a purpose is nothing. It’s just code,” Jorge says. “We build for people. And that purpose has taken us far beyond banking.”
From Buenos Aires to Global Ambitions
Founded in Buenos Aires almost 20 years ago, Veritran started building mobile applications before the iPhone even existed – when, as Jorge jokes, “phones were just for calls, texts, and the occasional game of Snake”.
“Our guys were visionaries,” he continues. “They were talking about applications when we didn’t even have smartphones. Back then, you had to build a separate app for every phone model because we didn’t have iOS or Android,” he recalls.
Despite those early technical hurdles, the company maintained a singular focus: democratising access to financial services. “Once a person starts managing their own finances, they gain control,” reasons Jorge. “And control is the first step toward growth.”
That mission has proven timeless, and borderless. Today, Veritran has a solid footprint across Latin America and has expanded into the US and Europe.
Why Experience Matters More Than Ever
Jorge is acutely aware that in financial services, trust is everything. A slick PowerPoint is not enough to win over banks.
“When I meet with a financial institution, they don’t want theory. They want proof. They want to see our tech working in the real world. But many banks are reluctant to share their strategies, even with non-competitors.”
This desire to demonstrate capability led Veritran to seek a bold new marketing approach – one that would provide a visible, secure, and non-competitive environment to showcase its tech.
Enter Manchester City: A Blueprint for CX Innovation
The solution arrived via the pitch, not the boardroom. Veritran entered into a partnership with Manchester City, one of the best football teams in the world.
“Manchester City is digitally five to seven years ahead of most clubs,” says Jorge.
Veritran’s technology now supports key digital operations at Manchester City, helping the Club streamline processes such as user registration, membership management, and ticketing. This collaboration reflects a shared commitment to innovation and operational excellence.
What began as a strategic partnership has evolved into a strong example of how financial technology can reinforce digital infrastructure in the sports sector. As more organisations seek reliable and scalable solutions, the model developed with Manchester City demonstrates the value of secure, efficient platforms designed to support long-term digital growth.
Breaking the Sponsorship Mold
Unlike traditional sports sponsorships, which often come with hefty price tags and limited strategic collaboration, Veritran’s deal with City was rooted in partnership.
“Our partnership is beneficial for both companies, we share value,” explains Jorge. “With the brand reach of Manchester City’s clubs we have been able to promote our company worldwide.”
This model has opened the door to future collaborations, not only with sports clubs, but also with entertainment companies in the US who are eyeing similar digital transformations.
Applying FinTech Learnings in New Territories
As Veritran enters new markets, they carry the lessons of regulated finance into less restricted sectors.
“In banking, every innovation has to pass through layers of regulation,” notes Jorge. “But in entertainment or sports, you can think outside the box and start with the experience, not the compliance checklist.”
That freedom has allowed Veritran to experiment with new ideas, such as smile-based stadium access or face-based payments.
“We call it ‘mouthful access’ – just smile, and you’re in. You can’t do that in banking… yet.”
Blending Brand and Utility: A New Era for Embedded Finance
What sets Veritran apart isn’t just its technology stack – it’s the way it applies that stack to create emotional resonance and operational value in new settings. For Jorge and his team, the convergence of financial services and lifestyle touchpoints is the most exciting, and underexplored, frontier.
“When we embed finance into a stadium or a music festival, we’re not just processing payments,” he explains. “We’re creating seamless, branded experiences that extend customer relationships beyond the bank branch or app.”
This philosophy echoes a wider FinTech trend: the shift from siloed services to contextual, embedded finance – delivered where customers already are, not where institutions want them to be.
As financial brands seek new ways to engage digitally-native consumers, Jorge believes partnerships with lifestyle, sports, and entertainment brands offer huge untapped potential.
Jorge notes that younger generations expect everything to be digital, instant, and intuitive. They don’t separate banking from shopping or attending an event, it’s all part of one journey. “If we can integrate services invisibly into those moments, that’s where the magic happens.”
He’s quick to add that the financial industry still has work to do in aligning with this shift – both culturally and technologically.
“It’s not just about APIs or infrastructure. It’s about mindset. The organisations that embrace this new way of thinking – who see CX as a shared responsibility across ecosystems – will lead the next decade.”
With Veritran’s cross-industry collaborations accelerating, Jorge is confident they’re not just shaping financial journeys – they’re reshaping everyday experiences.
Embedding Finance in the Fan Journey
Jorge sees a massive opportunity to embed financial services into sports and entertainment ecosystems, particularly in underbanked regions like Latin America.
“In the UK, stadiums are already cashless. In Latin America, we still have guys walking around selling Coca-Cola for cash from their pockets. We want to change that.”
By introducing digital wallets, biometric payments, and embedded insurance services (e.g., ticket protection at the point of sale), Veritran enables clubs to become financial service providers.
“Imagine buying a match ticket and adding travel insurance in one click. That’s the level of seamless we’re aiming for.”
Pain Points Driving Demand
So what are clients asking for?
Jorge says it comes down to three priorities:
Integrated Payments Ecosystems Clients want unified platforms that support seamless payments across channels and partners
Digital Onboarding & Identity Reducing friction while enhancing security is top of mind – especially in customer acquisition
End-to-End Security Suites With AI-driven fraud and evolving regulations, security isn’t optional; it’s a strategic asset
Veritran’s flexibility as a tech partner, not just a vendor, allows it to co-create with clients. This often means integrating with their existing partners, such as banks, card networks, or insurers.
What’s Next for Veritran?
According to Jorge, the company is at a pivotal moment. Its technology is gaining traction in new verticals with strong investment appetite – such as entertainment and live events.
“These sectors have the budget and the ambition. No one’s serving them with the kind of Fintech-grade CX we provide.”
The company is also exploring opportunities in public transportation and other infrastructure-heavy sectors where transactions are frequent and still inefficient.
“Everywhere there’s a transaction, there’s an opportunity to simplify.”
FinTech is set to play an expanding role in everyday life whereJorge believes the very definition of FinTech is evolving.
“It’s not just about banks anymore. If you buy a coffee, book a train, or enter a concert – those are all transactions. And if we can simplify them, that’s FinTech too.”
That’s why Veritran sees future growth in collaborative ecosystems where banks, brands, and non-traditional players converge to serve the customer journey holistically.
Why Money20/20?
Jorge credits the annual Money20/20 Europe conference with helping shape Veritran’s partnerships – including the initial connection with Manchester City.
“It’s one of our top five global trade shows. We don’t just send a team – we send our top execs, including our CEO. It’s where deals happen.”
Building with Purpose for the Future
In an industry flooded with features and hype Veritran differentiates by staying grounded in user value.
“Tech for tech’s sake is meaningless. But tech that improves how someone lives, spends, or connects – that’s everything,” says Jorge.
From its Argentine roots to a global stage, Veritran’s journey underscores one enduring truth: In customer experience, the future belongs to those who build it with purpose.
FinTech Strategy meets with Seema Desai, COO at iwoca, to hear how customer experience is being redefined in a digital lending era
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Financial Transformation Summit 2025 EXCLUSIVE
At the Financial Transformation Summit, Seema Desai, COO at iwoca, spoke on a panel (alongside representatives from Zopa Bank and Citibank) about the shifting needs for customer experience in digital lending. How can lenders create hyper-personalised loan products to meet diverse customer needs? What are the best practices for maintaining a human touch in automated lending processes? How can lenders build and maintain customer loyalty in a competitive market? What role does omnichannel strategy play in delivering a seamless lending experience?
Following the panel, we spoke with Seema to find out more…
Hi Seema, tell us about your role at iwoca?
“I am the Chief Operating Officer at iwoca. We provide fast and flexible finance to small businesses across the UK and Germany. In my role as COO, I’m responsible for all of our UK operations teams. So, all of our agents that engage with customers throughout the customer journey. And I make sure that we’re offering a really high quality service that is also highly efficient.”
You were part of a panel at this Summit focused on redefining CX in the era of digital lending. Can you give us an overview of your thoughts?
“So, maintaining that personal touch is really important because that personal touch helps us to build trust with our customers. We all know that when dealing with money, that trust element is super important. There’s lots of things that iwoca does to maintain that. For example, every customer has a dedicated account manager. They can get through to them via a direct number. We also respond to emails fast, every email on the same day. And then we commit to answering at least 80% of calls in less than 60 seconds. We’ve got 10,000 new applications every month and about 30,000 customers making repayments currently. We’re doing all of this with an account management team of just 30 people. So, to maintain that level of personal touch whilst also being able to deal with that volume of customers, we absolutely have to leverage digital technology to be able to do that really efficiently. And there’s many ways that we do that…
“First of all, we make sure that our account pages and our signup flow is as clear and seamless as possible so that customers can self-serve if they want to. But we also make sure that with our operations activities, we’ve broken down every step of every operational process into a task that is visible on our in-house built CRM system. And then what we can do is run tests on every single step of those to see where having human interaction really adds the most value. So, we are constantly upgrading where we apply human interaction in a really forensic way to make sure that it’s optimised as much as possible.”
Why is this an exciting time for the business?
“It’s really exciting right now. We’ve been having some record months recently and broken some big milestones. We are now approving around 10,000 new business loans every month, which is huge. Our loan book across the UK is almost £1 billion. And then a bit closer to home, we’ve also just moved offices. We’ve got more space and we’re still able to attract exceptional talent into iwoca and it’s great to have a new home in central London to do that.”
What trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“Embedded finance is a big trend right now. It’s important for us to make sure that customers can access lending when and where they need it. We’re integrating lots of partners through our open API – around a third of our applications come through partner channels. So, that’s a very important trend and growing for us in the future. We’re also seeing a lot of hyper-personalisation. We know that customers want to be able to tailor loan products exactly to their needs, and we want our products to be able to provide that flexibility to them. We’re looking at increasing loan amounts, changing durations and offering different types of repayment schedules with interest only options. And that’s hugely exciting. And one of the big trends that I’ve heard about here at FTS, and which we are working on at iwoca, is how we leverage AI and what we might be able to do with AI to make us even more efficient, but still maintain an excellent customer service.”
What pain points are your customers experiencing that you need to address? What are they asking you for help with? How are you meeting the challenge?
“So, it’s important to remember that iwoca exists in order to solve pain points for customers because customers were just relying on traditional lenders. Those traditional lenders, the big banks, have much longer application processes, typically taking weeks and sometimes just aren’t able to lend to those customers at all because it’s not within their risk appetite. Whereas at iwoca you can get a loan within minutes. We can also lend to customers that banks couldn’t lend to because we’re able to use data and data science to be able to understand the risk level and different customers much better.”
Tell us about a recent success story…
“We are operational in the UK and Germany, and a success story for us is the fact that we are now working with a loan book of almost a £1 billion and we are profitable. And we have been for quite a while now, since early 2023. So, it’s a real success story for us that we’re able to use that profitability to fund our core business growth but also use it to invest in solving other pain points for customers beyond lending.”
What’s next for iwoca? What future launches and initiatives are you particularly excited about?
“Yeah, there’s a lot of things that we’re working on right now. I’m excited about some of the AI tools that we are trialling to make our service even more efficient. There’s a number of exciting applications out there, so there’s a lot of people at iwoca exploring and exploiting different AI technologies. It’s going to be very exciting to see how that rolls out across our business in the rest of this year. And then also looking at new ventures that are beyond lending, which we may be launching later this year or early next.”
Why do you think the evolution of collaboration between banks and FinTechs is set to continue? What are you excited about?
“Collaboration is hugely important to us and our business model. Traditional banks are able to access capital more cheaply than we can, but they’re able to provide us with access to their balance sheet so that they provide financing to us so that we can then lend to our customers. So, with their financing, we are able to use our data and our technology to reach customers that they wouldn’t be able to reach directly. At the moment, something like 80% of our funding comes from banks such as Barclays and Citi. So, they’re hugely important to us and we are continuously reviewing with them the performance of our own book and finding ways that we’d be able to lend to more of our customers.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for iwoca?
“This is my first time at this event, and I’ve been really impressed. It’s been really well organised and the panels have been insightful with some great speakers. I’ve learned quite a lot. I’ve met some really interesting people and I’m really impressed by the diversity of people that are coming here. So, I was just on a panel with somebody from Zopa, which is where I used to work. I also met somebody in the audience who came from Lloyd’s, which is where I worked about 15 years ago. So, it’s great to see that this ecosystem being brought together at FTS.”
Fast, flexible finance empowers small businesses to manage their cash flow better and seize opportunities – making their business and the economy stronger as a whole. At iwoca, we do just that. We help businesses get the funds they need, when they need it, often within minutes. We’ve already made several billion pounds in funding available to over 100,000 businesses since we launched in 2012 and positioned ourselves as a leading Fintech in Europe. Our mission is to finance one million businesses. We’ll get there by continuing to make our finance ever more relevant and accessible to more businesses by combining cutting-edge technology, data science and a 5-star customer service.
FinTech Strategy speaks with Jonas von Oldenskiöld, Head of Partnerships at Qover, about the future for the insurance industry
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Financial Transformation Summit 2025 EXCLUSIVE
At Financial Transformation Summit, Jonas von Oldenskiöld, Head of Partnerships at Qover, spoke on a panel (alongside peers from Davies Group, Accenture, Superscript and YuLife) entitled ‘Bridging the Gap: How InsurTech is Reinventing Traditional Insurance Processes’.
Following the panel, we spoke to Jonas to find out more…
Hi Jonas, tell us about your role at Qover?
“I’m the Head of Partnerships at Qover. We are focused on embedded insurance. We try to enable that for a lot of different players in the markets. Everything from motor insurance, SMEs, going the whole way down to simple things like classes[1] such as travel, trying to be the enabler between the typical risk carrier and the distribution platform.”
You spoke on a panel at the Summit about InsurTech innovation. Give us an overview of your thoughts…
“It was a very interesting group of people on the panel coming from different angles across the industry. And the key things for me were around where InsurTech needs to go now and how it enables insurance companies at this point in time. The common understanding was that we, the InsurTechs, come from being disruptors to being more of a force into them where we can plug in and help them to change a little bit the behaviours that are currently going on. Being that catalyst in the organisation and helping them to drive innovation. Because I think a lot of large organisations have realized that innovation cannot be driven by a single hidden team somewhere, it needs to be driven from a business perspective.”
Why is this an exciting time for Qover?
“I think there are many reasons. Of course, you cannot be at an event like this without speaking about AI and the opportunity that gives to us. Also, we’re seeing a generational shift. The industry needs to get ready to service a completely different type of customers going forward and that will drive a lot of exchanges we’ll see in the next couple years.”
What other trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“I think a key one is to be able to navigate the future role of AI regulation. That will be very interesting to see what opportunities are there and what opportunities would be possible to use. More importantly, I think it is taking data from something, using data from something that is good to have, to really put it in the forefront of the operation to start planning your business process from a data perspective. This is the data that we need to have in order to deliver a good product rather than having data as the outcome of the whole process. You have set up and try to do something from that perspective. So, we need to turn the table on that.”
What other pain points your customers are experiencing that you need to address? What are they asking you for help with? How are you meeting the challenge?
“They particularly need help with the UX and how to deliver the product. I think the underlying product itself doesn’t change so much, but it’s a lot about the delivery, making sure that it actually does get delivered at the point in time that we like to call events driven. So, for us it is distributing insurance when you have a life event, if that is having a child, buying a car, buying a house or whatever it might be, data can help us to drive that. So, for us it’s very much around the delivery rather than the product underneath.”
Tell us about a recent success story…
“We’re very proud that we now have several new motor programmes in place where we have been working with large motor organisations that have realized that they’re not only selling a car, they’re selling a means of transportation and convenience, which also then includes insurance across that whole journey. We recently announced partnerships with both Volvo and BMW. And we have more in the pipeline. So, I think that has been a great success where large established industries have realised they need to go further in order to have that UX design.”
What’s next for Qover? What future launches and initiatives are you particularly excited about?
“In 2025, our focus is on expanding into more new verticals. We are involved in driving that engagement to see where we can expand. We started traditionally with a lot of the travel organisation and bike providers. We’re now working with neobanks[2] , traditional banks and the motor industry. I also see more opportunities in areas like utilities, in SME supporting functions, everything from accountancy to data provision and being a software provider. These expansions will be the goal over the next 24 months.”
Why do you think the evolution of collaboration between industries and InsurTechs is set to continue? What are you excited about?
Partnerships is one of the key things changing the insurance industry. We still have some very large players around. They’re fulfilling their function, and they do it very well. But in order for them to adapt into the new situation, partnerships are important. You always need to be able to work at scale, which is important for them. Of course, with a partnership you lose a little bit of control compared to acquiring something or developing it yourself. But on the other hand you win on the speed to market and potentially also on the cost side. So, for me, the winners will be the ones that can handle partnerships in the right way. And at the end of the day, a partnership is a relationship. You can have as many contracts as you want, but it comes down to people.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for Qover?
“We get a lot of good feedback and the great thing with events like this is that you have the chance to do networking both informal and formal. You’re having a formal agenda but also have a chance to rotate around. I always make sure to join the sessions and round tables. It has been interesting to speak to peers across the industry. It’s a good way of getting away from the desk and finding some new inspiration.”
Embedded insurance orchestrators… We’re creating a global safety net with insurance,
empowering people to live life to the fullest.
Qover was founded in 2016 by Quentin Colmant and Jean-Charles Velge. From the very beginning, our co-founders had a clear vision of the future of insurance: a simple, transparent and accessible service across borders.
Through embedded insurance, we can create a global safety net that protects everyone, everywhere. To that end, our embedded insurance orchestration platform enables any company to harness the power of technology to embed insurance as a native component of or add-on to their core product or service.
In doing so, embedded insurance becomes a powerful tool for businesses to enrich their value proposition, enable their success and care for their community.
FinTech Strategy meets Vikki Allgood, Director of Technology Strategy at Fidelity, to discuss the fundamental importance of culture in driving a successful business transformation
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Financial Transformation Summit 2025 EXCLUSIVE
At Financial Transformation Summit, Vikki Allgood, Director of Technology Strategy at Fidelity International, gave a keynote speech entitled ‘Psychological Safety – The Hidden Key to Transforming Your Business’. Following her appearance, we spoke to Vikki to learn more…
Hi Vikki, tell us about your role at Fidelity?
“I am Director of Technology Strategy for Fidelity. We’re looking at how we can ensure we can adapt our response to our business’ needs through our technology to meet whatever demand is coming over the horizons tomorrow. And in the years to come.”
You spoke at this Summit about psychological safety driving business transformation. Tell us more…
“At Fidelity, our strategy for our technology has culture as our foundational pillar. Talking with our leaders over the last 18 months, we looked to understand how we can create a brilliant culture, recognising that psychological safety is a fundamental element in that.
“Transformations often stumble because the business plan forgets its most volatile, and most valuable component, the people asked to deliver it. Without psychological safety, even well‑funded and organised programmes stall. Teams focus more on protecting themselves instead of challenging ideas. That’s when the risks remain hidden until it’s costly, and the collective new ideas to solve the biggest challenges are never formed. That’s why we ask leaders to invest time and energy in building a culture where it’s safe to question, experiment, challenge the status quo and admit what’s not working. In that environment the behaviours every transformation depends on (curiosity, creativity, problem‑solving, healthy challenge) all naturally emerge.
Psychological safety isn’t some new trendy HR slogan, it’s a timeless basic human need wired into our biology through millennia of evolution. When people sense social threat, the amygdala floods the body with cortisol and the prefrontal cortex (the part of our brain we rely on for reasoning, innovation, etc.) literally dims. Remove the threat, and the brain’s chemistry flips, dopamine and oxytocin rise, and teams move from cautious compliance to bold collaboration. Leaders must ask themselves if their teams can lean in and challenge effectively or if they are staying quiet to protect themselves. The hidden key is simple, but non‑negotiable, leaders must consciously, relentlessly and courageously build psychological safety through everything they do and say. If they do that, then your technology and transformation plans will have the human engine they need to succeed.”
Why is this an exciting time for Fidelity?
“I think that within the industry, all the opportunities that are coming along, and our ability to adapt to our customers’ needs, is what makes it exciting. We are all on an exponential curve of change. Technical possibilities, customer expectations, regulatory demand, industry landscapes, are all going to keep moving, with new challenges and opportunities presenting themselves. We are ensuring that we can meet those needs of our customers both today and tomorrow. Finding new ways to do that is pretty exciting.”
What trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“So, from a technology perspective, I would say that we are making sure that all our foundational elements are there so that we can respond and adapt. One of Fidelity’s differentiators is that we have historic long running relationships with our customers. We are reintegrating our data strategy to allow us to better leverage this, in addition to market data, allowing us to provide personalised solutions to our customers.
“AI is absolutely generating a buzz for us right now as well, and not just Generative AI. We’re seeing a push towards Agentic AI and how we can look to provide faster, quicker, more cost-effective services for our business partners who can then provide better outcomes for our customers. This in combination with our long-standing history gives us a unique opportunity.”
What pain points are your customers experiencing that you need to address? What are they asking you for help with? How are you meeting the challenge?
“We need to understand the new generations entering the wealth space and what their expectations are and how they engage with us. We’re looking to ensure we can keep pace with their demands. For example, we’ve just launched Pay by Bank allowing our customers to pay money into their accounts in a faster more secure way. This feature leverages the Open Banking Technology that is now available to financial institutions.”
Tell us about a recent success story for Fidelity…
“Across the technology landscape, we have been amplifying our existing cloud strategy by removing complexity in our hybrid setup, reducing the number of dependencies back to on-premises. This is a well-known challenge for financial institutions who have regulatory reasons to have highly confidential systems in house. This will allow us to respond at pace to what customers need. Looking a couple of years down the line nobody can be sure what the next big opportunities are going to be, so ensuring we’re building that foundation to respond to what comes over the horizon is fundamental.”
What’s next for Fidelity? What future launches and initiatives are you particularly excited about?
“Security is incredibly important to us. With that in mind, we are exploring Quantum to understand both the opportunities and risks that it could present in the future and how we can stay at the forefront of it. Ensuring a secure and reliable service for our customers is an absolute non-negotiable part of our strategy.”
Why do you think the evolution of collaboration between banks and FinTechs is set to continue? What are you excited about?
“I think the reality is that we need the collective mindsets to come together to create the best outcomes. We’re never going to have all the answers all by ourselves. So, starting to engage and work with people and collaborate means that we get to have a better, wider perspective. Coming to events like this, we get to learn, understand what other industries are doing, what other areas are looking at, and it helps to widen our perspectives and have more opportunities to find those out of the box ideas that are going to then help our customers.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for Fidelity?
“I was particularly keen to attend this conference because I think transformation and how we can do this successfully is so important at the moment. The reality is, sadly, and I covered this in my talk, a staggeringly large number of transformations miss the mark or fall short. And so, learning and embracing how you can ensure that you go after it and you get the value that you’re aiming for, that is for me what’s important. As I said, getting that learning, talking to each other, understanding what’s worked, what hasn’t worked and sharing tips and techniques is actually incredibly powerful and something you can then take back and use at your organisation.”
It has been more than 50 years since we were founded. We’ve seen many market cycles – bull and bear, boom and bust. We have stayed the course through different investment environments regardless of market performance.
The needs of our customers have always steered our decisions, which is why we’ve stuck to our core activity of investing. We believe this is what allows us to excel – and, even more importantly, to repay the trust placed in us by our customers.
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FinTech Strategy met with Standard Chartered’s Head of Digital Assets – Financing & Securities Services, Waqar Chaudry, at Money20/20 Europe to discuss how the bank is connecting traditional with digital, collaborating with FinTechs directly and via SC Ventures, and taking a measured approach to entering the crypto market
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Money20/20 Europe Exclusive
There is a buzz in the air at Money20/20 Europe. Waqar Chaudry, Head of Digital Assets – Financing & Securities Services at Standard Chartered, has just spoken on Mastercard’s Horizon Stage about the great digital assets opportunity. We meet up with him at his bank’s stand in the heart of the action at the Amsterdam RAI Arena.
Waqar works in custody to secure digital assets at Standard Chartered. It also has a fund accounting business and offers transfer agent services. “The financing in the Financing & Securities Services elements are in our FX Prime offering,” he explains. “At the moment my sole focus is on crypto custody, tokenisation and building an ecosystem around those products.”
The Rise of Digital Assets
It’s an exciting time for Standard Chartered with crypto custody and the rise of stablecoins and tokenisation… Whether the asset is Bitcoin, a tokenised money market, or anything tokenisable, there have been a lot of conversations with the bank’s partners in terms of the technology quest.
“Most of the conversations historically have been led by the fact that technology does give you the capability to do 24/7 trading and settlement. Risk management from the technology side is much better. The blockchain dream is sold to everyone, which remains true,” notes Waqar. “The issue has been that on the business side, tackling the areas that actually can work with this technology. You have your near instant settlement availability on blockchains. On the other side you have a T+1 or T+3 cash settlement time – that doesn’t gel very well.
“Entrenched in the day-to-day business of these really large institutions is to be able to inject a new piece of technology. And then suddenly say, hey, all these things are solved. For all the inefficiencies in the system it doesn’t work that quickly. We’re actually taking one step at a time. That’s why it’s exciting that we can see in five or ten years from now what the world will look like. Basically, in our vernacular that means we have near instant settlements and near instant international transfer of value. So, that’s the kind of stuff that we are really interested in for the future.”
Meeting the Blockchain Challenge
Waqar explains that when something like a blockchain comes into a traditional bank, and especially blockchains like the ones that support an asset like Bitcoin, you don’t know who the counterparties are (which are clear on the SWIFT network).
“You have to build capability from a technology side, operations side, risk management side,” he continues. “You need to develop the governance of all those functions to be able to get the value of the asset in the ecosystem. And then be able to add value to that to transact on it. We don’t yet have those ingredients, so it becomes very challenging for us to accept the assets. A lot of the work that the bank has done over the past five years has been around embedding those elements into our day-to-day operations. It’s about understanding the risk profile of the coins and understanding the risk profile of the blockchains.”
Waqar’s team works on how to protect the ecosystem from risks from both an AML and KYC point of view. “We’re also making sure that by doing that we don’t create such a burden to the client that the service becomes useless,” he adds. “We’re trying to balance that out and that’s where the challenges lie at the moment. The next stage is to also be able to integrate all of our traditional cash and assets rails into this. And that’s where the next level of risks will come in… Where people are not used to seeing things on the blockchain… They are used to seeing things on the SWIFT network or a CSD. But when the blockchains come in, profiles will change and that’s where we have to meet the challenges.”
Traditional Meets Digital
For an asset manager with a variety of equities and bonds, but keen to start in crypto and other digital assets, the rails are very different… “The liquidity venues and the way you settle the instrument are very different. And they don’t naturally talk to each other,” confirms Waqar. “It’s a big challenge. But to be able to go with the provider that has all the capabilities, which includes the cash side, the asset side, the crypto side and the blockchain side, is something people are looking for now. Without having the end-to-end picture, it would be very difficult for our clients to have an equitable strategy for their clients. We need to be able to service them appropriately based on the rails they operate in.”
Reacting to FinTech Trends
For Standard Chartered’s clients it’s increasingly important for payments to facilitate activity on-chain regardless of the use case of digital assets. “There is a key challenge with payments at the moment. If you do transfer value across geographies or between B2B and B2C, what do you do with that value afterwards?” asks Waqar.
“Are you going to keep it on the books for your treasury or account purposes or are you going to find a way to liquidate the position to pay your employees or pay your service provider? Without the capability to store the asset appropriately and then convert it into a usable form, you can’t do much with it. The only thing you can do is actually transfer value. So, for us what’s important in payments is that we get the transfer value happening immediately. Or as quickly as possible. And then also connect our payment infrastructure and the banking behind. We aim to support the transfer of value from a digital asset into an actual cash asset.”
Building on Success
Standard Chartered’s work with OKX in Dubai has spurred demand the bank didn’t expect. “The key ingredient is that a really large crypto exchange has come together with a really large bank,” reasons Waqar. “When you combine the product features of a large bank like ours with the liquidity of OKX it creates a unique proposition in the market. The traditional players have started to show interest in that because now they can buy diverse assets, pledge them as collateral and start trading while the assets remain safe in a genuine large institutional bank. And at the same time, they also have access to a highly regarded institutional exchange. That story is for us quite important and we’re fostering these relationships more and more…”
It’s been a real success story for Standard Chartered on the money market fund side which is also connected to what the bank is doing on the collateral side. “Money market funds are used to gain value and have an asset that does generate yield on the one side, but also the capability to use the asset as collateral is important,” adds Waqar.
“The money market fund that we launched for China Asset Management in Hong Kong, albeit it’s a retail use case for a start, but then the ambitions are big. The next thing is how do we start using that same asset for pledging for trading purposes and then how do we inject that into a portfolio basket of assets that people buy? At Standard Chartered, we aim to create a supermarket of tokens in a centralised ecosystem. So, our collateral story and the tokenised money market funds is connected, and we want to continue building around it. We’re thinking about other assets now too… We’re looking at equities, bonds and enabling more cryptocurrencies in the same ecosystem as well. It’s just the start of all the things we need to build in the future.”
Why Money20/20?
“This is my first time coming to Money20/20 Europe. Digital asset companies are here alongside financial services and related FinTechs. It’s great that they’re able to talk to each other and it’s quite evident there are lots of great meetings happening. There are many companies here we are either supporting or we’re working with. We’ve also had meetings with UK government representatives geared to attracting talent into the country. They’re trying to make sure that their FinTech ecosystem grows quite significantly for us in the UK and for other footprint markets in Asia; Middle East and Africa are also quite important in how we do that and continue to grow.”
The Evolution of Collaboration between Banks and FinTechs
Standard Chartered is also working in harmony with its ventures partner SC Ventures. The bank is working closely with Libeara for tokenisation and with Zodia Custody as Saas. “Our core institutional bank and our Ventures business are quite tightly coupled from that point of view,” says Waqar. “And it’s quite obvious that the reason for that is how we’ve made significant investments into them. We’ve given part of our DNA into this ecosystem and now, at the bank, they’re building the ecosystem around these capabilities, so we’re keen to bring them in and use their solutions for our services as well.”
Standard Chartered may be a traditional bank but it is a seasoned collaborator with innovative FinTechs. “They need traditional services too,” reasons Waqar. “Once they get to a critical mass, a FinTech may not have the bandwidth to manage certain client sizes. By partnering with some of the FinTechs, we’re seeing that once a certain size of a client comes in, they prefer to work with a large institution like ours. So, that partnership is proactively managed as well from our side. From our ventures side, bringing their innovative approach to product development and technology into the bank, building the ecosystem around risk management and governance from the bank side and then connecting into the FinTechs outside of that ecosystem is something I think is quite an interesting proposition for us. We’re going to keep building on top of that.”
Standard Chartered – Financing & Securities Services
Promoting your future in global securities
We’re ready to help you flourish in emerging and frontier securities services markets
In today’s fast-moving markets, especially across Asia, Africa and Middle East, success isn’t just about the solutions you choose – it’s about the partnerships you build.
Standard Chartered has been committed to these regions for decades. We understand both the promise and challenges. That’s why we go beyond delivering end-to-end custody, fund, and fiduciary solutions – we actively help shape the markets themselves.
By working with local governments and industry associations, we bring you early insights and access to new opportunities. Partnering with leading asset managers, fintechs, and infrastructure providers, we connect you to the best of the industry, via a single partner. Because in a world of complexity, collaboration is your greatest advantage.
FinTech Strategy meets Ishtiaq M Ahmed, Senior Product Manager – Emerging Tech, Innovation & Ventures at HSBC, to learn more about the future of payments – real-time, cross-border and beyond
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Financial Transformation Summit 2025 EXCLUSIVE
At the Financial Transformation Summit 2025, Ishtiaq M Ahmed, HSBC’s Senior Product Manager, for Emerging Technology, Innovation & Ventures, joined a panel with J.P. Morgan, Revolut, Lloyds and EY to explore how real-time payments, embedded finance and global collaboration are shaping the future of financial services. How are real-time payments reshaping banking infrastructure? What are the regulatory challenges for cross-border payments? How can banks compete with FinTechs in the rapidly evolving payments space? How are digital wallets and mobile payment platforms changing consumer spending behaviours?
We spoke with Ishtiaq after the session to explore what drives HSBC’s approach to innovation, how customer expectations are evolving, and why trust remains at the core of transformation.
Hi Ishtiaq, tell us about your role at HSBC?
“I work on Global Product within HSBC’s Emerging Technology, Innovation & Ventures team. Our focus is to deliver next-generation propositions, particularly across payments, embedded finance and frontier technologies. We work on horizon 2 and 3 initiatives, with a view to turning emerging ideas into viable, scalable solutions. The goal isn’t just to experiment. It’s to test, validate and shape innovations that will help us serve customers better and redefine how financial services operate in the years ahead.”
It’s a transformational time for payments with the rise of open banking and a national vision for the UK. Give us your overview…
“Payments is possibly the most loved area by both FinTechs and banks. A lot of what is happening in payments, it’s where a lot of meaningful innovation is already landing. It’s no longer theory or ideation, its practical and accelerating. The UK’s National Payments Vision is ambitious, and rightly so. But ambition needs alignment. We need stronger collaboration between Banks, FinTechs, Regulators and infrastructure service providers. This journey will take time and coordination. It’s more a marathon than a sprint, and we’re only just getting started.”
Why is this an exciting time for HSBC?
“Simply because the way technology has penetrated our lives and the influence of technology on how banking is evolving are very closely knitted. Technology is no longer on the edges of banking; it’s embedded in every customer interaction.”
What trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“The shift towards alternative payment methods is one I feel strongly about. For decades, the path was linear: cash to cheque to card. Now, we’re entering a new chapter. Pay by Bank, or direct account-to-account payment, is gaining traction. Some regions have already scaled it. In the UK, it’s about to accelerate. This trend will unlock lower costs, faster movement of money and better control for users. It’s not just about technology. It’s about user experience and future-ready infrastructure.”
What other pain points are your customers experiencing that you need to address? What are they asking you for help with? How are you meeting the challenge?
“I think for customers it’s very simple. As a customer myself, I look for speed, ease, and simplicity in everything that I do. That’s universal. But what makes it complex today is the influence of AI, automation and data. People want innovation, but not at the expense of trust. So, while we innovate, we keep trust as the anchor. The real test is whether customers can do more, faster and easier, while still feeling their money is protected and their experience is safe. That’s the balance we aim to strike.”
Tell us about a recent success story…
“We’re particularly proud of the work we’re doing on embedded payments. The goal is to make payments feel invisible – integrated into the environment the customer is already in. Whether that’s a retail website, a social app or a business platform, customers shouldn’t have to toggle across apps to complete a payment. We have already launched products in this space, and we’re continuing to build. It’s about making banking ambient – present where the customer is, not where the bank wants them to be.”
Why do you think the evolution of collaboration between banks and FinTechs is set to continue? What are you excited about?
“FinTechs bring urgency and imagination. Banks bring trust, infrastructure and scale. The opportunity is not in competing, but in co-creating. We have seen some encouraging partnerships, and we’re still working at the surface level. There’s a much deeper layer of value if we can move beyond tactical deals into genuine joint innovation.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for HSBC?
“Events like this are important because they bring together different voices with a shared interest in shaping the future. What stood out to me is how open the audience and panellists are to challenging ideas and exploring new perspectives. These are places where real conversations happen; where you meet regulators, banks, FinTechs and enablers all under one roof. It’s these intersections that move the industry forward.”
About HSBC Emerging Technology, Innovation & Ventures
HSBC Emerging Technology, Innovation & Ventures team is a global group of technologists, data scientists and venture specialist dedicated to shaping the banks future capabilities. Our goal is to deliver world class digital-first banking across HSBC’s global footprint.
Our mission is to drive meaningful innovation across the organisation by identifying and unlocking opportunities that enhance customer experience, improve operational efficiency and embrace disruptive technologies.
Our approach is rooted in experimentation, rapid prototyping, continuous iteration. By working closely with both internal and internal partners and external collaborators, we test and refine new ideas, prioritising solution that are scalable, impactful and aligned with the needs of our customers.
We actively partner with leading technology firms, FintTechs, academic institutions and policy makers to stay at the forefront of digital innovation and accelerate time to market.
By combining the scale, trust and resilience of HSBC with agility and mindset of a tech start-up, we aim to nurture transformative ideas, drive strategic innovation and shape the future of banking.
FinTech Strategy speaks with Matt Bazley, Account Executive at Hyland, to explore how the content intelligence and process automation specialists are helping to drive operational efficiencies for their financial services clients
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Financial Transformation Summit 2025 EXCLUSIVE
Hyland empowers organisations with unified content, process and applications intelligence solutions, unlocking the profound insights that fuel innovation. The Hyland team was at Financial Transformation Summit to reveal the ways organisations can transform their processes with the Hyland Content Innovation Cloud™. By combining AI-powered automation with built-in integrations to productivity tools and business applications, Hyland streamlines workflows across multiple channels, accelerating response times, boosting productivity and improving customer satisfaction.
At the event, Neil Rayment, Sales Solution Engineer, demonstrated the intuitive end-user experience and showed how easy it is to configure, tailor and deploy solutions that can empower key stakeholders across any business. We spoke to Hyland’s Matt Bazley, Account Executive for Financial Services, to find out more…
Hi Matt, tell us about your role at Hyland?
“I’m the Account Executive responsible for banking across the UK and Ireland. I’ve been with the company for just over 18 months. Across my career, I’ve been helping financial services institutions for over 15 years with digital transformations and various programmes.”
What are the key digital transformation solutions Hyland offers Financial Services organisations? How are they making a difference? What are some of the use cases you’re exploring?
“Hyland is at the cutting edge of the content space. We have what we call our Content Innovation Cloud, which is delivering content intelligence, process intelligence and application intelligence. What that means in reality is that we’re helping organisations get access to their content that they don’t currently have access to because it’s spread over many siloed systems and sat in an unstructured format. So, with our content and intelligence, we’re able to get access to that unstructured data, which is around about 80% of an organisation’s data in the financial services sector. And we’re able to then provide knowledge and insight on that content, which helps organisations to make better strategic decisions. Allied to that, with this process intelligence, we’re able to help automate processes across the business. Whether it be orchestrating use cases and workflows or integrating with other systems to deliver application intelligence, we’re able to manage that whole end-to-end life cycle of information across an organisation.”
Why is this an exciting time for the business?
“We’re excited because our strategy is really leading the way. We’re leveraging large language models (LLMs) and AI to be able to deliver these real-life use cases that solve actual challenges. A lot of the time AI projects fail because businesses are trying to implement AI that isn’t actually a solution solving a problem. Whereas the AI we’re using is to actually solve a real-life challenge that businesses face because they want to be hyper-personalised for customers and more customer-centric. And you can’t really do that if you’re only leveraging 20% of the data you hold about your customers. And that’s why getting access and insight around this unstructured data is really vital for financial services organisations right now. We are able to help them leverage that unstructured data and meet them where their data is at. So, it’s not a case of having to migrate all of that data into different platforms or into our platform. We confederate across your information wherever it’s held as a financial services organisation; and that’s really a game-changing position for us and for the industry.”
What trends are you seeing across the Financial Services landscape? What will be important for you and your customers?
“AI is the big one. Although it is a bit of a buzzword that everyone’s mentioning nowadays, we’re actually delivering AI solutions to solve problems that businesses face. And that’s one of the real trends in the industries. Most AI projects fail, and companies want AI projects that succeed and deliver real value. The other thing we’re seeing is the rise of hyper-personalisation as part of being really customer-focused and customer-centric. Again, by helping businesses leverage that 80% of information around their customers that they don’t currently have access to, and provide insights on that information, we’re helping those organisations to become really specific and personalised in their dealings with their customers.
“The final piece is around data and governance. So, security around our data as customers, because we’re all consumers at heart and want to know that our information is secure. Using best-in-class processes around security and governance is what we’re really focused on. And that’s a real trend in the market as well. We’re making sure that while we’re leveraging that information about customers, we’re keeping it safe and only using it for what it’s intended for and making sure the processes and governance around that information are really robust.”
What other pain points are clients in the FS space experiencing that you need to address? What are they asking you for help with? How are you meeting the challenge?
“The one big one is the siloed information across multiple systems as part of digital transformation strategies. Over the years, I’ve seen many businesses implement point solutions. They might be best-in-class point solutions… But that means you end up with information and data and processes across 10, 15 or 20 systems. How do you then unify that data and leverage it to make the user journeys more effective? And also the customer journeys better, whatever channel those customers are using?
“What we see is that while trying to be omnichannel for their customers, organisations end up with multiple solutions. One for their mobile app, a solution for their website, a solution for in-branch banking… So, you end up with omnichannel processes that are actually siloed processes. What we are trying to help businesses do is to unify those processes. We can break down those silos and make it a really seamless, integrated journey internally and externally for colleagues and customers.”
Tell us about a recent success story …
“A great example is our work with ABN AMRO – a bank that is one of our longstanding and valued customers. They were looking for a solution because of this very challenge. The bank had multiple siloed systems holding a lot of information and a very complex architecture. They went to market and Hyland was able to prove our solution was able to manage the sheer volume and complexity of the information and content that they had. And most importantly we were able to help them integrate with their line-of-business systems very easily to create that seamless internal/external journey for both users and customers.”
What’s next for Hyland? What future launches and initiatives are you particularly excited about?
“It’s all about continuing to grow for us. With the Content Innovation Cloud, the reception we’ve received from the market, from our customers, has been absolutely tremendous. Businesses are so excited to see the ability and capability of what we’re able to do. And what we’re able to deliver for them in terms of real value through the Content Innovation Cloud. We’ve got customers onboarded already. It’s now about expanding that list of customers who are going to see real value from leveraging the cloud, our AI solutions and driving efficiencies with our content process and application intelligence across their businesses.”
Why do you think the evolution of collaboration between banks and FinTechs is set to continue? What are you excited about?
“Across the market over the last 15-20 years the banks are starting to see FinTechs more as allies than competitors. And they’re leveraging these technologies rather than trying to challenge them. I think that’s going to continue because FinTechs are far more agile. And as customer expectations continue to evolve and become more demanding, banks need to evolve and deal with these demands more effectively and more fluidly. And that’s why leveraging FinTechs is going to be a key differentiator over the next 10 years. That trend is going to continue where banks and FinTechs work together and collaborate rather than challenge each other.”
Why Financial Transformation Summit? What is it about this particular event that makes it the perfect place to embrace innovation? What’s the response been like for Hyland?
“It’s my fourth year coming here with a couple of different companies and I always find this event really valuable. Not only to obviously promote our products and our brand… But to speak to key decision-makers and peers across financial services. We aim to learn from them about whether the challenges we perceive as a vendor are seen by them as a customer. We will continue to learn and evolve our business around key market challenges. Hyland can then focus our solutions around the real-world problems our peers are seeing across financial services. Coming to this event is a great way to meet as many people as possible. And just really enjoy having those meaningful conversations with leaders in the financial services sector.”
Hyland puts your content to work, making it smarter and more accessible in the moment of need.
Hyland’s content, process and application intelligence solutions empower customers to deliver exceptional experiences to those they serve. The solutions capture, process and manage high volumes of diverse content, helping you improve, accelerate and automate operational decisions and workflows.
This month’s cover story features SSEN Transmission’s journey to build a digitally-enabled, AI-ready energy business to meet the country’s clean power, energy security and net zero goals.
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Welcome to the latest issue of Interface magazine!
SSEN Transmission: Digitally Enabling the Grid of the Future
James McLean is the Chief Information Officer (CIO) of SSEN Transmission, a growing Business Unit of SSE Plc. In our lead feature this month, he charts the company’s journey to build a leadership team for IT capable of meeting Transmission’s goals, while facing the daily challenges of operations and programme delivery, allied with focusing on the drive for cyber-readiness, architecture expansion and the growing need for data and analytics.
“The business case was to stand up core systems to deliver foundational technologies capable of driving efficiencies across an expanding enterprise,” he explains. “During my first few months I dialled into how SSEN Transmission operates and considered staffing plans. What does my organisation look like? At this point there were just seven people on the IT team and as T1 was ending we had some deliverables to do in preparation to ramp up for T2.”
“It’s been a unique and interesting challenge leading a constantly growing organisation,” reflects James. “The majority of our people have never worked for SSEN Transmission before, and they’ve come from other industries. We’ve been fortunate in the fact that our business sector is attracting strong talent keen to be part of our energy security and net zero ambition as we work towards that goal.”
Craig Thomas, CIO at the Merit Systems Protection Board.
The Merit Systems Protection Board: Championing Public Sector Change
Digital transformation on a public sector budget is no mean feat, and the operational requirements of a government agency compounds the challenge.
Craig Thomas, CIO at the Merit Systems Protection Board, met with Interface to explain how he and his team overhauled each of MSPB’s legacy systems one-by-one.
“The digital transformation has been critical to MSPB operations because the agency can absorb much more organisational change without having to spend time and money retrofitting IT systems. The environment that we’re in now requires the ability to move very quickly and to change direction with minimal effort.”
Carnival Corporation: Maturing Cybersecurity Across Global Operations
Carnival Corporation’s CISO, Margarita Rivera. With two decades’ experience in the cybersecurity space, she has witnessed immense change both in the fabric of the industry and in its growing importance in increasingly complex and risk-prone digital environments.
With a wealth of multi-industry experience, deeply transferable qualifications, and a front-row seat to the profound changes seen in cybersecurity over the past 20 years, Rivera is ideally placed to lead the ongoing process of securing the company’s digital and data environments.
“People saw cyber as just an IT or tech problem, and I think today folks realise that cybersecurity is much more than that,” says Rivera. “We’re much more involved with many other stakeholders, ingrained in other parts of the business, helping to drive change in a positive fashion and providing guardrails for faster innovation that’s accelerating the way the business can operate.”
“When I first started, there weren’t a lot of women in the tech and cybersecurity space,” she says. “I was one of the first. I remember going to conferences and being the only woman in the room. Now, thankfully there’s been a lot of change.
“I recently met with a partner that’s helping us with a project here, and I looked around the room to see it’s probably sixty-forty, with the sixty in favour of having more women-representative engineers and founders. That’s quite exciting. I think there’s a special skillset that women possess that they bring to the table in terms of creativity and collaboration.”
Appian: Redefining Enterprise Transformation With AI
Gregg Aldana, VP, Head of Global Solutions Consulting, shares what CIOs are really asking for in 2025 and beyond, how Appian is answering that call like no other platform, and why he believes the most progressive and impactful approach to AI is by embedding it inside the most critical processes.
“When I first came to Appian a little under a year ago, one of the first things that came up was the need to spend time with customers,” says Aldana. “If you really want to learn what’s driving and going on in the industry, you’re not going to find out from just reading analyst reports or looking online. You’ve got to go out and physically meet with and talk to people that are leading these changes. Meeting with 200+ CIOs and CTOs a year gives you a front seat to reality.”
Accenture is helping SSEN Transmission manage hundreds of infrastructure projects vital to achieving the UK’s Net Zero ambition. Effective delivery…
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Accenture is helping SSEN Transmission manage hundreds of infrastructure projects vital to achieving the UK’s Net Zero ambition. Effective delivery required addressing fragmented data and disconnected tools that can slow the flow of information between systems. SSEN Transmission sought a partner to help reshape its approach for data-driven execution on capital projects.
Meeting the Digital Challenge with Accenture
SSEN Transmission partnered with Accenture to embrace automation and digitisation in response to increasing project demands, a challenge reflected across the wider Capital Projects sector. Through the adoption of BIM (Building Information Modelling) and the implementation of Integrated Project Management (IPM), which was developed with Oracle and Microsoft, this collaboration laid the groundwork for more connected ways of working and continues to promote transformation across the organisation.
Key Benefits Delivered
Accenture supported with IPM (Integrated Project Management) and Building Information Modelling (BIM) customised to meet specific needs and achieve key goals:
Digitise processes for a single unified environment
Unify data for a standardised and trusted source of truth
Create a scalable platform for delivering capital projects
“With a unified real-time view of project data, SSEN Transmission has improved efficiency and strengthened collaboration across internal teams and with external partners. This allows for more time focused on higher value insight-led work, supporting better outcomes, faster decisions and much more agile delivery”
Huda As’ad, Managing Director, Capital Projects & Infrastructure, UKI
Building for the Future
More than a solutions provider, Accenture helps with strategy and issupporting SSEN Transmission’s continued focus on refining best practice for smooth project delivery. The partnership is helping to evolve ways of working and strengthening the digital foundation for future readiness.
“Our collaboration is built on a strong digital foundation that can scale with SSEN Transmission’s growing needs. By unifying systems, data, and process, we are enabling the faster adoption of new capabilities and supporting the shift towards a fully data-driven capital project delivery”
Nithin Vijay, Managing Director, Industry X – Capital Projects & Infrastructure
Accenture: A Partner for the Journey
Transformation is a journey that begins with the right foundation across people, data and process. It also requires a digital partner that brings together the best of industry experience, process excellence and technology to:
Develop a clear, actionable strategy for digital and data transformation
Embed industry best practices to optimise processes and drive continuous improvement
Enable smarter, more consistent delivery aligned to a long-term vision, from strategy through to execution
And that’s where Accenture makes its mark, helping clients navigate the journey with confidence.
Learn more about how Accenture is supporting SSEN Transmission on its digitisation journey with Huda As’ad, Managing Director, Capital Projects & Infrastructure, UKI and Nithin Vijay, Managing Director, Industry X – Capital Projects & Infrastructure
Hermann Tischendorf is the Chief Information & Technology Officer at MTN MoMo (the telco’s mobile money division). He reveals a bold roadmap for leveraging FinTech to drive financial inclusion across the African continent.
“MoMo is comparable in monthly active users to some of the top ten FinTechs globally. We’re playing in the same league as Revolut or Nubank – but in much more complex markets,” notes Hermann. “Access to financial services is fundamental. Without it, people are excluded from the global economy. Our services are the equaliser. They allow individuals in frontier markets to participate in trade, store value, and ultimately improve their quality of life.”
Pima Community College: Digital Transformation on a Public Sector budget
Higher education is typically seen through this lens. Slow to adopt new technologies, traditionally inflexible, and held back by a lack of funding. At Pima Community College in Tucson, Arizona, a quiet revolution is underway that subverts these expectations. The college is a publicly funded, two-year higher education institution. Serving Pima County and beyond, it has an annual student body of 38,000 served by almost 2,500 faculty and staff.
Led by Isaac Abbs, Assistant Vice Chancellor for IT and CIO, the college is undergoing an extensive IT transformation. This has unlocked immense value through bold, visionary leadership. Crucially, it is being achieved without a major increase in budget explains Abbs.
“If, as an IT leader, you become a truly innovative partner and move the organisation forward, the dollars are there.”
State of Missouri: Security as a Foundation for Innovation
Megan Stokes, Director of Cloud Security & Strategy at State of Missouri, digs into the many ways in which the agency is leveraging technology – and how it’s keeping the citizens of Missouri at the forefront.
“I have the opportunity to guide agencies through best practices, helping them access the right resources, the right expertise, and make sure that the solutions they’re building on are really secure and well architected going forward,” she explains. “That includes a focus on risk management, access control, optimisation, governance and compliance, and long-term strategy. There’s always something new to think through, and that keeps the role really exciting and engaging. There’s always lots of work to be done.”
RAKBANK: A Banking Transformation in the UAE
Our cover story explores the digital transformation journey of RAKBANK in the UAE. Head of Digital Transformation, Antony Burrows, reveals the agile practices, enterprise-wide enablement and people-first culture delivering digital banking with a human touch.
“Culture is the cornerstone,” Antony stresses. RAKBANK codifies this into its Four Cs Framework – Connect, Communicate, Collaborate and Celebrate. “Here in the UAE, banks are pivoting from a model of ‘we know everything’ to recognising that one of the best ways to deliver continuous change and value to customers is through partnerships with startups and FinTechs. It’s no longer banks versus startups – it’s banks and startups, working together for the customer. This shift is especially meaningful as banks expand beyond traditional services to focus on customers’ broader financial lives.”
Digital DNA – Exploring core infrastructure, platform strategies, and foundational technologies.
Embedded Intelligence – AI, machine learning, data strategies, and real-time analytics.
Beyond Fintech – Partnerships between fintechs and other sectors like retail, health, and climate.
Governance 2.0 – Regulation, digital identity, privacy, and ESG compliance.
Day three featured more impactful sessions across all four pillars, offering attendees more valuable insights and strategies for innovation.
Highlights from Key Sessions at Money20/20 Europe:
How to Create and Leverage FinBank Partnerships
The discussion focused on the evolution and success of FinTech partnerships with banks. Key points included the shift from transactional partnerships to more collaborative, value-driven relationships, emphasizing joint KPIs and product creation.
Alex Johnson, Chief Payments Officer, Nium
“You really have to differentiate. You really have to stand out for a bank to say, ‘Yeah, I like what you offer enough to go through, six months of onboarding.’ Dare I say, maybe more.”
John Power, SVP, Head of JVs & AQaaS, Fiserv
“The legacy system, it’s a fact of life. They’re there. They’re pervasive. They’re going to be here for a long time, and banks historically have made huge investments in those platforms and systems. So I think both the challenge for the for the bank and the opportunity for the FinTech is, how do you at the front end of those legacy systems develop new products that can scale and that you can bring cross border easily and readily.”
“It really is cutting the line to be able to deliver opportunity for customers and to be able to expand propositions for new customers.”
“The economic development supply chains shifting to low to middle income countries are incredibly important right now, and cross border payment rails have not been good in low middle income countries.”
Where Fintech goes Next: Tapping into Platforms and Verticals
The discussion centred on the democratisation of financial services through embedded finance. The panel emphasised the importance of data quality, personalisation, and strategic partnerships in delivering seamless financial experiences – ultimately enhancing customer satisfaction and improving business efficiency.
“Embedded finance is going to be defined by region and use cases.”
Amy Loh, Chief Marketing Officer – Pipe
“Small businesses don’t want to manage their business through a bunch of different tools that are stitched together. They’re looking to platforms to do everything for them and keep high end services.”
“Most platforms or merchants out there trying to diversify revenue, and they will get auxiliary revenue, or maybe get primary revenue through FinTech activity.”
The Neobanks Strike Back
In a dynamic exploration of neobanking’s evolution, Ali Niknam revealed bunq’s remarkable journey from a tech-driven startup to a sustainably profitable digital bank. By leveraging AI across every aspect of their operations, bunq has transformed traditional banking, reducing support times to mere seconds and creating a hyper-personalised user experience. Niknam emphasised the power of user-centricity, showing how innovative features like simple stock trading and multi-language support can democratise financial services.
The bank’s strategic approach – focusing on user needs rather than investor expectations – has enabled them to expand thoughtfully, with plans to enter the UK and US markets. By embracing technological change and maintaining a relentless commitment to solving real customer problems, bunq exemplifies the next generation of banking.
Ali Niknam, Founder & CEO, bunq
“Somewhere in the 70s, we let go of the gold standard, and now currencies are basically floating. The only reason why a dollar or a euro is worth what it’s worth is because of trust and perception. Philosophically, it’s very logical that we have found another abstraction layer by introducing stablecoin, which is not much else than a byte number that has a denomination currency as a backing asset that itself doesn’t have anything as a backing asset. A lot of people might ask, ‘Why would you need a stablecoin? We have euros. I go get a coffee, pay with Apple Pay or cash.’ But there are many countries on this planet where the local currency is not stable. If your country has an inflation rate of 30,000% like Zimbabwe, you would really love to use a different currency. The US dollar has been the currency of choice, but as a normal person, you cannot access the US dollar. A US dollar stablecoin that you can access by simply having a mobile phone – that’s going to be transformational for large groups of people.”
Innovating When Regulation Can’t Keep Up: Lessons from NASA
Lisa Valencia covered an array of topics, from her 35 year career at NASA and Guinness World Record to the rise of private entities like SpaceX, which has launched 180 missions this year, and the increasing role of public-private partnerships in space exploration. The speaker also touched on international collaborations, particularly with the European Space Agency and the Italian Space Agency, and the potential for space tourism and colonization of the moon.
Lisa Valencia, Programme Manager/Electrical Engineer – Pioneering Space, LC (ex NASA)
“Back in the day, NASA got 4% of the national budget. Now it’s down to just 0.1%, so we’ve had to get creative with private partnerships. SpaceX is the perfect success story. They came to us in 2007 needing money after some rocket mishaps, and look at them now! From my balcony, I see their launches every other day. They’re planning 180 launches this year alone.Talk about a return on investment!”
“We’re planning to colonise the South Pole on the moon. The idea is to extract water and hydrogen from the regolith—both for living there and for fuel.”
Scaling Internationally in 2025: Funding, Innovating, and Breaking into New Markets
The conversation focused on the growth and strategy of fintech companies, particularly those with a strong presence in Europe and the US. The panel featured Ingo Uytdehaage, CEO and co-founder of Adyen, and Alexandre Prot, CEO of Qonto. Both leaders expressed a preference for organic growth over acquisitions, emphasizing the importance of scaling efficiently before pursuing an IPO.
Ingo Uytdehaage, CEO and co-founder of Adyen
“I think an important part of scaling a company is not just thinking about your product, but also considering the markets you want to address, and how you ensure you become local in each country.”
“We realised over time that if we really want to bring the customers, we need to have the best licenses to operate. A banking license gives you a lot of flexibility.”
“Being independent from other companies, other financial institutions, that gives you flexibility to build what your customers really want.”
“I think it’s very important, also in Europe, that we continue to be competitive. If you think about regulations and AI, we shouldn’t try to do things completely differently compared to the US.”
Alexandre Prot, CEO of Qonto
“We need to be very strict about tech integration and avoiding legacy which slows us down.”
“We still need to scale a lot before we have a successful IPO. A few team members are working on it and getting the company ready for it. But, the most important thing is just scaling efficiently in the business, and maybe an IPO would be welcome in a couple of years.”
Putting The F in Fintech
The panel discussion focused on the role of women in FinTech based on personal experiences.
Iana Dimitrova, CEO, OpenPayd
“At times, being underestimated is helpful, because if you’re seen as the competition, driving an agenda is becoming more difficult. So what I found, actually, over a period, is that bringing your emotional intelligence, leaving the ego outside of the outside of the room, and just focusing on execution is is incredibly helpful.”
Megan Cooper, CEO & Founder, Caywood
“The moment we start defining ourselves as like a female leader or a female entrepreneur, you almost kind of put yourself in a bit of a box. And so I think just seeing yourself on an equal playing field and then operating it on an equal playing field and interacting in that way is quite advantageous.”
“We can’t just want diversity and hope it happens. We actually have to be intentional about creating it.”
Valerie Kontor, Founder, Black in Fintech
“Black women make up 1.6% over the FinTech workforce, but when we look at the financial reality of black women by the age of 60, only 53% of black women have enough money in their bank account to retire. We need to start marrying people in FinTech and the people that we need to serve.”
Money20/20 Europe 2025 closed its doors but the next edition of the conference will return to Amsterdam from June 2–4, 2026, promising to continue the tradition of shaping the future of financial services…
US Department of Homeland Security: Integrating with the Intelligence Community
Zeke Maldonado, CIO at the US Department of Homeland Security (DHS) is tasked with integrating the Department with the intelligence community. During times of change, governments need innovative, strategic leadership more than ever. And that’s where inspirational figure like Maldonado come into play.
“I remain committed to the DHS mission and want to take it to the next level. Many of the services we provide require substantial improvements, and I am eager to see how our modernisation efforts can help achieve the desired objectives. We play a crucial role in automating and enhancing the vetting process for non-US citizens, making it significantly more efficient.”
Cotality: The AI-powered Property Platform
Cotality,the AI-powered property and location intelligence platform, is making the real estate industry more efficient, smarter, and more resilient against climate change by leveraging the Google Cloud Platform.
Chief Data and Analytics Officer, John Rogers, explains how… “Buying a home is the biggest purchase in most people’s lives, so we’re passionate about making sure the system works for them.”
Nemko Digital: Pioneering Trustworthy AI
Nemko boasts more than 90 years of building trust in physical products, Today, Nemko’s digital division is leading the way in defining that trust in an increasingly complex and connected world with its pioneering approach to trustworthy AI reveals Managing Director, Dr Shahram Maralani.
“We want to be one of the top five players in this space. Our goal is to make the world a safer place.”
Security, AI, and Digital Resilience: A look inside Visions CIO + CISO
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The cybersecurity landscape has never been so fast-moving or complex. The stakes have never been higher. A worsening geopolitical reality and increasingly sophisticated cyber threats mean that the role of security leaders is more pivotal than ever as devastating cyber breaches become a matter of “when,” not “if.” It’s a time for information and skill sharing, networking, and collective action in an industry facing a more challenging future than ever.
Visions CIO + CISO Summit brings together executive security and technology leaders and experts from the largest organisations in multiple industries to network and learn from the people driving innovation in the IT and cyber spaces. This year’s event took place between April 28-30, and featured 8 tentpole sessions, over 30 presentations from key industry figures, and more than 30 speakers across the various panels, fire-side chats and peer-to-peer round tables that comprise the rest of the event. Speakers and solutions providers at this year’s event included Illumio, Threatlocker, LastPass, Claranet, Okta, Covertswarm, Intruder, and Ripjar RPC Services. Also in attendance were IT and security professionals from large scale enterprises, including Currys, Astley Digital, 24/7 Home Rescue, H&M Group, IBM, MUFG (Mitsubishi Financial Group), Federated Hermes, Deliveroo, Experian, Saint-Gobain, and Nordea GSK.
At the event, and afterwards, we were lucky enough to catch up with some of the leaders speaking at Visions and get their perspectives on key trends affecting the IT space — from the ever-relevant issue of security to AI and digital resilience.
1. What’s the general outlook for the IT and fintech sectors right now? Is this a scary time? An exciting one?
“It’s an exciting time, particularly within the UK banking sector, where we’re seeing a real shift toward customer-centric innovation. Financial institutions are working hard to deliver seamless, secure, and personalised experiences—often by leveraging cloud, AI, and advanced analytics.”
“There’s a strong emphasis on modernising legacy systems, improving digital onboarding, and enhancing fraud prevention without compromising user experience. This push for technology-driven customer satisfaction is creating space for smarter, faster, and more agile solutions—making it a great time to be contributing to the evolution of digital trust and transformation in financial services.”
2. What are some of the challenges organisations are facing that you can help them with? What problems are they asking you to solve?
“Many organisations are grappling with how to secure cloud environments at scale without slowing down innovation. Key challenges include visibility across hybrid or multi-cloud setups, managing identity and access with precision, and operationalising zero trust.”
“There’s also a strong demand for integrating security earlier in the development lifecycle—what we often refer to as shifting security left. People are asking how to reduce complexity, automate controls, and move away from reactive postures to proactive, real-time risk mitigation.”
1. What kind of outlook does an organisation like Federated Hermes have right now towards the industry? Is this a scary time? An exciting one?
2025 is shaping up to be a very dynamic year for the markets at large. There are rapid developments, from geopolitics to booming technology innovation with AI, that are impacting how the markets move as well changing the environment we operate in as a business. As a global asset manager, Federated Hermes is staying abreast of these changes to ensure we can be where the markets are, whilst maintaining efficiency in our operations for strong profitability.
2. What problems are people asking you to solve right now?
The ever changing world of cyber has historically been difficult for businesses to decipher. In the last few years, it has become even more difficult to keep up, with the advent of AI and how it is changing the technology landscape. Whilst businesses are trying to understand this new technology and embed it into their products and operations, cyber-criminal enterprises are leaping ahead in innovation and starting to leverage it in novel ways. The challenge this brings is two-fold.”
“On one hand, businesses are trying to find the right use cases for AI to get their return on investment at every level. This applies to core business functions, as well as Technology departments and the Security organisations. As cyber strategists we are now being forced to be innovators ourselves and not just passive consumers of the latest products and market trends. This brings a new perspective to how we design controls, build our roadmaps and prioritize our budget items. Boards and executive teams are looking for Security teams who are embracing AI and maximizing the effectiveness and efficiency of their programmes.”
“The second challenge is on the defensive side. The average person, as well as the average corporate employee, is lagging behind in understanding what the latest AI models are capable of, let alone understanding how they can be used to conduct cybercrime. Working in security, we find ourselves in a situation where we both need to find ways to keep up with cyber criminals to defend our enterprises, as well as keep educating our staff and management teams so that we can bring them on this journey.”
1. Would you say this is an exciting time for Astley Digital?
“Astley Digital is at a pivotal point in its journey, experiencing remarkable growth and expanding our service offerings. We’re actively exploring partnerships with innovative cybersecurity companies like ThreatLocker, enabling us to provide even more robust endpoint security solutions for our clients.”
“Additionally, the evolving landscape of cybersecurity is presenting us with unique opportunities to leverage AI for predictive threat analysis, streamline incident response, and enhance our managed security services. This moment is particularly exciting as we are positioning ourselves not just as a service provider but as a thought leader in cybersecurity strategy, risk management, and digital transformation for businesses across various sectors.”
2. What are some of the key challenges organisations are facing that you can help them with? What problems are they asking you to solve?
“Organisations today are grappling with a rapidly changing threat landscape, and one of the most significant challenges is maintaining a strong cybersecurity posture amidst evolving threats. At Astley Digital, we address critical issues such as:
“Endpoint Security: Many organisations struggle with managing endpoint security across remote and hybrid workforces. We provide comprehensive solutions that restrict unauthorised software and applications, preventing potential breaches and maintaining data integrity.”
“Third-Party Risk Management: Ensuring third-party vendors maintain security standards is another pressing concern. We work closely with our clients to assess, monitor, and mitigate third-party risks to prevent supply chain attacks.”
“Incident Response and Recovery: Companies are seeking rapid and effective incident response strategies. We offer real-time monitoring, response planning, and post-incident analysis to minimise business disruptions.”
“Regulatory Compliance: Compliance is a growing concern, especially in highly regulated industries. Our team assists with implementing frameworks that align with industry standards, ensuring data protection and reducing legal risks.”
“We are really fortunate to have reach and presence with clients across different sectors. We have professional service specialisms that respond to many of the trickiest and most important strategy and skill challenges that clients face; technology, cyber security, AI, data, and digital regulations to name a few. Not only is it a great time to be helping clients with those issues and helping them make their businesses more capable, effective, successful and resilient, from a selfish perspective it’s an incredible privilege for our people to be trusted by clients to help with these super interesting initiatives.”
2. What are some of the key challenges organisations are facing that you can help them with? What problems are they asking you to solve?
“We help clients with everything from assessing and improving their resilience positions, to complying with the intersections of a range of existing regulations, frameworks and standards, through to future gazing and thinking about what’s possible through challenging the status-quo.”
“Lately that has included a lot of work on things like AI readiness, development of use cases, working on AI explainability and the human element of potential resistance to the kinds of change that AI and other emerging tech are delivering.”
“Of course an evergreen core of our work is digital resilience, including cyber security, so we do a lot on ensuring that new technology adoptions including those with AI sprinkled throughout them, are digitally and operationally resilient by design.”
“We’re at a turning point where AI is no longer a side conversation—it’s embedded in the way Deliveroo operates. That shift brings real momentum and urgency to the work we do in securing AI adoption and protecting digital environments.”
2. What are some of the key challenges organisations are facing that you can help them with? What problems are they asking you to solve?
“The main concern is how to adopt AI without opening the door to unmanaged risk. Businesses know they can’t sit this one out, but they’re looking for help building the right guardrails to manage risk; especially with evolving regulation and the rise of AI-powered threats like deepfake vishing and advanced phishing.”
1. What are you here at Visions to discuss with your peers in the cybersecurity and IT space?
“The first panel I was part of was the Threat Detection & AI Panel Discussion. We were looking at establishing trust, mitigating risks, and safeguarding security in the age of AI. I focused on how to balance the benefits of AI with the challenges of building trust, managing risks, and ensuring security.”
“Then, I had a deep dive into looking at an age where individuals don’t verify, they just take information, no longer researching to see if the information is correct.”
“I always remain sceptical, whilst understanding the value of efficiency. AI is now embedded in so many tools, but now the main concern is the people within the organisation. Monitoring and education are essential. People will often try to find a shortcut and the easy way to go about things. Until training, governance and understanding is at a level where there can be trust, I suggest turning it off.”
1. These are challenging times for cybersecurity teams. How has 2025 been going for you and Ripjar?
“Ripjar utilises new and emerging technology to solve customer problems in cyber threat investigations and anti-financial crime compliance. We’ve been able to help organisations achieve record results – identifying connections, anomalies and potential risks, while reducing false positives and increasing true positives – leading to best-in-class results in many industries. We’re excited to be sharing that technology, alongside further innovations, with other organisations as we expand our global coverage.”
“The advent of generative AI creates vast risks and opportunities. It also shifts perspectives on existing machine learning and artificial intelligence technologies. It has been exciting to see how the newest AI can be combined with non-generative AI and other technologies to create new solutions to the problems that keep our customers awake at night.”
2. What are some of the challenges organisations are facing that you can help them with?
“Ripjar serves customers in several areas. Our anti-financial crime customers are trying to make sense of the ever-expanding business risks presented by their customers and counterparties in a tumultuous world. We’re able to help them in that journey, whether it’s responding to changing Russian or Middle East sanctions or aligning with the massive political changes that have impacted PEP (politically exposed persons) regimes all around the world.”
“Using foundational AI, we find broad risks in the media – which is often referred to as negative news or adverse media. That means reading through millions of daily news articles to identify risk signals which are important to those handling the world’s global payments or trading internationally. Agility is a key requirement for our customers, and machine learning and AI make it possible to make sense of huge quantities of structured and unstructured data quickly and accurately.”
“Our cyber customers are sophisticated threat investigators working in complex environments, including a number of MSSPs. They rely on our data fusion and investigations software to identify potential threats to their data and ultimately their businesses.”
Looking at the future
The shadows of GenAI, looming threats, and a shifting regulatory landscape loom over the global cybersecurity and IT communities, but the tone is also optimistic. While every leader we spoke to at Visions CIO + CISO acknowledged the threat posed by emerging technologies, many were also excited by the potential of GenAI tools to detect threats and help strengthen cybersecurity defenses.
Given how quickly the circumstances surrounding cybersecurity have changed in just a few short years, it’s almost impossible to predict where we’ll be by the end of the decade. However, the experts we spoke to at Visions are approaching the future with both eyes open — watchful for new risks, and determined to capitalise on new opportunities.
The next Visions CIO + CISO Summit (Autumn, UK) is taking place at the Allianz Stadium in London on 13 – 15 October, 2025. Learn more and register to attend here.
Transformational success with technology is about more than just ‘keeping the lights on’. Our cover story this month spotlights National Grid with the story of an innovation programme empowering everyone across the organisation on a shared transformation journey. Global Head of Data Strategy, Andrew Burns, tells Interface how connections like these are driven by data.
“We have new energy sources, greater demand and an opportunity to gather more data than ever before. Technologies like artificial intelligence (AI) and augmented reality (AR) are revolutionising how we use that data. Today, data and these technologies are combining to increase our ability to deliver value to our customers, and society.”
Asian Hospital and Medical Center: Leading the technology revolution in healthcare
Asian Hospital and Medical Center, one of the largest and fastest growing premiere hospitals among the close to 30 hospitals in the Metro Pacific Health Group, is the pioneer of an integrated healthcare network in the Philippines. Frank Vibar, CITO at Asian Hospital and the former Group CIO of the MPH Group, reveals the IT strategic roadmap that will deliver a true regional hospital.
“AHMC’s vision is to become the centre of global expertise in caring for the unique needs of our patients and the communities we serve.”
Also in this issue of Interface…
We hear from Tecnotree on the year ahead for the Telco industry; get the lowdown on meeting the challenges of integrating Agentic AI from Confluent; learn about the importance of Cybersecurity investment in OT (Operational Technology) from Claroty; and discover how IoT-enabled digital customers are reshaping customer experiences with Content Guru.
Deepak Parameswaran, Sector Head – Energy, Manufacturing & Resources at Wipro, talks innovation with National Grid’s Global Head of Data Strategy Andrew Burns
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Partners for over 25 years, Wipro and National Grid have been laying the foundation for progress… By taking data to the cloud, creating value and leveraging their common work to deliver advanced, data-driven innovations across the National Grid enterprise.
Meeting the transformation challenge
As a utility, National Grid seeks to provide safe, affordable, and reliable electric and natural gas service for its customers. As such, the company is hyper-focused on natural gas, electricity grid modernisation, customer satisfaction and the integration of business and technology processes across the entire business as gas and electricity demand increases across the markets. Wipro offers actionable solutions, providing the innovative technology and domain expertise necessary for organisations like National Grid to transform and become leaders in sustainability within their respective industries.
Delivering bespoke solutions for Innovation
Traditional utility technologies can pose challenges in terms of complexity and capital investment. With Cloud and AI technologies emerging as game changers, Wipro delivers a proven ecosystem, incorporating analytics, IoT, Generative AI, and Augmented Reality, tailored to meet the needs of customers, assets, and grid management. This makes for easier, scalable, and faster to market solutions that allow National Grid to quickly realise the benefits. Wipro’s Utility Enterprise solutions have delivered on key elements of the digital transformation journey at National Grid. This allows for a constant data presence across the globe, creating a common, secure cloud environment.
Wipro’s partnership with National Grid
Wipro’s collaboration with National Grid continues to be built on a foundation of continuous innovation, with a commitment to:
Staying ahead of utility business trends
Supporting National Grid’s clean energy transition
Developing sophisticated data and AI solutions for enhanced customer service
Maintaining agility to address emerging challenges
“Wipro has been our biggest partner in executing use cases through the Innovation Lab, enabling us to be agile and deliver multiple projects with direct, tangible business benefits. Their support has been vital in ensuring a clear, efficient process and rapid execution, making them key to our success.”
Andrew Burns, Global Head of Data Strategy, National Grid
Click here to read more about National Grid’s Innovation story
InsurTech Insights Europe 2025: A Transformational Gathering for the Future of Insurance
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InsurTech Insights Europe 2025, held on March 19-20 at the InterContinental London – the O2, reaffirmed its status as the premier conference for insurance technology professionals across the continent. Drawing more than 6,000 attendees from over 80 countries, the event brought together C-level executives, startup founders, investors, and tech leaders. They explored the evolving future of insurance powered by innovation and digital transformation.
Key Themes
With seven stages and over 400 speakers, the conference agenda was packed with compelling keynotes, forward-looking panel discussions, fireside chats, and practical workshops.
The overarching theme of the 2025 edition was crystal clear: artificial intelligence (AI) is no longer a futuristic concept, it’s the driving force behind today’s insurance innovation. Topics like automation, generative AI, claims transformation, underwriting analytics, embedded insurance, cyber security, and ESG all reflected a dynamic industry poised for rapid acceleration.
A Focus on Leadership & Diversity
One of the standout sessions was the panel discussion titled “The ROI of Gender Diversity: Breaking the Glass Ceiling for Women in Leadership”, held on the Purple Stage. Featuring high-level voices from Solera, unlock VC, and AXA XL, the panel addressed the often-overlooked yet crucial importance of gender diversity in executive roles. The discussion didn’t stop at raising awareness; it presented measurable business outcomes tied to diverse leadership and called for action to foster inclusivity across all levels of the industry.
Complementing this session was “The Women in Insurance Power Group Meet-up”, a networking event held at the Sky Bar on the 18th floor. Attendees not only connected over lunch but were also invited into an exclusive WhatsApp group, encouraging long-term collaboration and support among female leaders and allies in the space.
The Innovators Hub and the ITI Marquee: Where the Future Was Born
A major addition to this year’s conference was the debut of the ITI Marquee. A vibrant, purpose-built zone dedicated to showcasing bold ideas and startup brilliance. This space housed the Innovators Hub, which included its own dedicated Innovator’s Stage. Here, early-stage ventures and InsurTech pioneers pitched their solutions to panels of VCs, corporate innovation leads, and fellow founders.
This setting offered more than exposure, It cultivated real-time connections between startups and investors, giving many smaller players their first shot at meaningful partnerships or funding opportunities. The diversity of ideas, from AI-powered claims processors to data-driven risk models for climate insurance, reflected the industry’s hunger for next-gen solutions.
Keynote InsurTech Highlights
One of the most talked-about moments of the event came from Daniel Schreiber, CEO and Co-Founder of Lemonade, whose opening keynote explored how AI can dramatically enhance customer experience in insurance. He challenged the audience to rethink not just how insurance is sold or serviced, but why it’s offered. And how technology can transform its social impact.
Another crowd favourite was the session on “The Path to Embedded Insurance”, which unpacked how insurance products are increasingly being bundled into digital ecosystems like ecommerce platforms, mobility apps, and smart home technologies. This wasn’t just a hype piece. Real-world case studies from European neobanks and auto insurers illustrated how embedded models are already driving customer growth and retention.
Among the compelling keynotes on the Main Stage, Sofia Kyriakopoulou, a Fintech Strategy AI Champion and Group Chief Data & Analytics Officer at SCOR, revealed how GenAI innovation at one of the world’s largest reinsurers is transcending the realm of proof of concepts to become fully productive.
InsurTech Deep Dives: AI, Data & Digital Claims
Sessions throughout the week made it clear that AI is at the forefront of virtually every area of insurance operations. Whether it was applied in predictive underwriting, fraud detection, or personalised customer engagement, companies are looking to AI not just for marginal gains but foundational transformation.
A standout workshop on AI in Claims Automation included live demos from startups using computer vision and NLP to automate damage assessment. Meanwhile, a session on Data-Driven Underwriting shared how insurers are replacing traditional risk proxies with real-time data streams, from wearables to smart meters.
Cybersecurity was another hot topic, with insurers discussing how to build resilient cyber products in the face of increasing digital threats and regulatory complexity.
Global Meets Local: The Power of Diversity
Although a European event at heart, the conference had a distinctly global flair. Speakers came from the U.S., Singapore, Brazil, South Africa, and the Middle East. They brought diverse perspectives on shared challenges such as climate change, digital regulation, and consumer trust.
Simultaneously, European startups shone on stage. Companies from the UK, Nordics, DACH, and Benelux presented innovative, often niche solutions for localised market challenges—from parametric crop insurance to real-time mobility coverage.
Trade Exhibition & Brand Visibility
The exhibition floor was a hive of activity, featuring booths from established players like Munich Re, Swiss Re, Guidewire, Duck Creek, and Cognizant, alongside vibrant startup showcases. Product demos, swag giveaways, and live challenges kept engagement high and made it easy for brands to stand out.
The conference proved to be a golden opportunity for brand elevation, allowing companies to position themselves as thought leaders or rising disruptors in front of an incredibly curated audience.
InsurTech Insights Europe: The Verdict
The closing remarks from Kristoffer Lundberg, CEO of InsurTech Insights, captured the spirit of the event:
“It’s a privilege for us to gather together the sharpest minds in the industry to discuss the role of AI in insurance. The direction and impact of these technologies will shape the space for decades to come.”
Indeed, InsurTech Insights Europe 2025 wasn’t just a conference, it was a strategic gathering. A melting pot of ideas and a launchpad for the next generation of insurance products and platforms. Attendees walked away not just with new business cards, but with fresh ideas, collaborative leads, and the motivation to drive innovation within their own organisations.
As the insurance industry continues to evolve amid mounting global challenges and rapidly advancing tech, this event served as a timely and energising reminder… The future is not something to wait for—it’s something to build, together.
Meet, greet, and learn from fellow IT professionals at VISIONS CIO + CISO Leadership Summit on the 28th to the 30th of April 2025. At the Allianz Stadium in London, you’ll discover the newest solutions and strategies on the market, while making meaningful connections with your peers.
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Over the course of the VISIONS event, attendees will have access to over 30 presentations and eight different sessions, as well as panels involving numerous expert speakers, and peer-to-peer roundtables.
Interface Magazine is thrilled to announce that our magazine is a media partner of VISIONS UK! For the CIO + CISO Leadership Summit, VISIONS is offering a VIP code for our readership. Secure your free pass here and use the code INTF-VIP for the full VIP experience!
Taking the challenge out of change
The pressure to modernise is at an all-time high, but the VISIONS CIO + CISO Leadership Summit provides a welcoming and informative atmosphere for you to learn about updating your systems, tackling cybersecurity threats, and building AI strategies.
The event is reserved for executives, and aims to support your professional and departmental goals across the board. The programme is tailored to enlighten, educate, and support CIOs and CISOs in their technology journeys.
Agenda
Eight sessions
30+ presentations
30+ speakers across panels, fireside chats and peer-to-peer roundtables
Alongside your free pass, use the VIP code INTF-VIP to also gain access to the following:
Complimentary accommodation for one night
On-site food and drinks provided
Multiple networking receptions with open bar
Travel reimbursement
Designed to address your challenges
This event aims to put an end to the usual wandering around the exhibition hall in order to find the information you want. During registration, you’ll have the chance to explain the current challenges you’re facing in business, and Visions will do the hard work in arranging meetings with a tailored set of solutions providers. You’ll be connected directly with the people who can help, in a bespoke, no-pressure environment.
Register today! Click here to book, and use our unique media partner code for VIP treatment: INTF-VIP
Tech Show London is coming to Excel March 12-13. Register for your free ticket now!
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Unlock unparalleled value with a single ticket that gets you free access to five industry-leading technology shows. Welcome to Cloud & AI Infrastructure, DevOps Live, Cloud & Cyber Security Expo, Big Data & AI World, and Data Centre World.
Tech Show London has it all. Don’t miss this immersive journey into the latest trends and innovations.
Discover tomorrow’s tech today
Unleash Potential, Embrace the Future. Hear from the greatest tech minds, all in one place.
Dive into a world where cutting-edge ideas shape your tomorrow. Tech Show London is the epicentre of technology innovation in London and beyond, hosting the brightest minds in technology, AI, cyber security, DevOps, and cloud all under one roof.
The Mainstage Theatre is not just a stage; it’s a launchpad for innovative ideas. Witness a stellar lineup featuring world-renowned experts from across the tech stack, influential C-level executives, key government figures, and the vanguards of AI and cybersecurity. All ready to share ideas set to rock the industry.
GLOBAL INSPIRATION, LOCAL IMPACT
Seize the opportunity to be inspired by global visionaries. Furthermore, with speakers from the UK, USA, and beyond, prepare to be inspired by transformative concepts and actionable strategies from technology insiders, ensuring your business stays ahead in an ever-evolving technology landscape.
Where the future of technology takes the stage
Secure your competitive edge at Tech Show London, the UK’s award-winning convergence of the industry’s brightest tech minds.
On 12-13 March 2025, gain vital foresight into the disruptive technologies reshaping your market, and position your organisation at the forefront of technology’s next frontier.
If you’re defining your business’s tech roadmap, register for your free ticket to join us at Excel London.
Parag Pawar, Partner – Banking & Financial Services, on how Hexaware’s services and platforms can streamline any transformation journey
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Parag and his team at Hexaware have been working closely with the European Bank for Reconstruction & Development (EBRD) on a digital transformation program focused on the bank’s Compass ERP program.
This ongoing collaboration is set to scale to meet EBRD’s future needs says Parag: “Hexaware’s strategy is based on building and deploying AI-infused technology platforms. With our talented and passionate workforce, we are uniquely positioned to enable transformation.”
Why Hexaware?
With 32,000+ professionals across Asia Pacific, Europe, and the Americas, Hexaware—backed by The Carlyle Group—delivers a blend of deep domain expertise and transformative technologies.
Its proprietary platforms help address the unique challenges of financial services and FinTech:
RapidX™: Accelerates software engineering and code analysis, enabling legacy modernization and faster time-to-market.
Amaze®: This platform simplifies cloud migrations and helps customers streamline their cloud operations and leverage the potential of AI.
Tensai®: Drives automation, streamlining workflows and enhancing operational efficiency.
But technology is just part of the equation – expertise drives transformation. From modernising legacy systems to deploying intelligent automation, Hexaware’s tailored approach helps ensure that solutions align with your business goals.
Hexaware strives for a record of delivering scalable growth, reducing costs, and elevating customer experiences. Whether you’re an established financial leader or an emerging FinTech innovator, Hexaware looks forward to be your partner for thriving in the digital era.
Hexaware: Shaping the future of financial services, one solution at a time
“A CIO will only be as successful as the team and the partnerships they build around them. It’s why we chose Hexaware as the strategic partner for our Compass program, EBRD’s ERP transformation. Having the right partner to work closely with us is key to any successful change journey within an IT organisation. You can’t run a bank at the scale of EBRD without this type of partnership. The nuances required, the skill they’re offering along with the design thinking and innovation they’re able to bring to the table in a short space of time is truly impressive. We’re counting on Hexaware to continue making a big impact.”
Subhash Chandra Jose, Managing Director for Information Technology, EBRD
Click here to read more about EBRD’s journey towards delivering a transformation programme to support the bank’s global investment efforts
Head of Group Payment Strategy, Lee McNabb, explains how a customer-centric vision, allied with a culture of innovation, is positioning NatWest at the heart of UK plc’s Open Banking revolution: “The market we live in is largely digital, but we have to be where customers are and meet their needs where they want them to be met. That could be in physical locations, through our app, or that could be leveraging the data we have to give them better bespoke insights. The important thing is balance… At NatWest, we’ll keep pushing the envelope on payments for a clear view of the bigger picture with banking that’s open for everyone.”
EBRD: People, Purpose & Technology
We speak with the European Bank for Reconstruction & Development’s Managing Director for Information Technology, Subhash Chandra Jose. With the help of Hexaware’s innovation, his team are delivering a transformation programme to support the bank’s global investment efforts: “The sweet spot for EBRD is a triangular union of purpose, people, and technology all coming together. This gives me energy to do something innovative every day to positively impact my team and our work for the organisation across our countries of operation. Ultimately, if we don’t get the technology basics right, we can’t best utilise the funds we have to make a real difference across the bank’s global efforts.”
Begbies Traynor Group: A strategic approach to digital transformation
We learn how Begbies Traynor Group is taking a strategic approach to digital transformation… Group CIO Andy Harper talks to Interface about building cultural consensus, innovation, addressing tech debt and scaling with AI: “My approach to IT leadership involves creating enough headroom to handle transformation while keeping the lights on.”
University of Cinicinnati: Where innovation comes to life
Bharath Prabhakaran, Chief Digital Officer and Vice President at the University of Cincinnati (UC), on technology, innovation and impact, and how a passion for education underpins his team’s work. “The foundation of any digital transformation in my opinion is people, process, technology – in that order,” he states. “People and culture are always the most challenging areas to evolve because you’re changing mindset and behaviour; process comes a close second as in most organisations people are wedded to legacy ways of working. In some respects, technology is the easy part, you always implement the tools but they’ll not be effective if you don’t have the right people and processes.”
IT: A personal career retrospective
It’s fascinating, looking back at something as complex and profoundly impactful as IT. And for Claudé Zamboni, who is preparing to retire after over 40 years in the sector, it’s been an incredible time to be deeply involved in technology. “There have been monumental changes from when I first entered IT, where it was basically a black box,” says Zamboni. “People didn’t know what the IT team was doing, and those in IT would just handle problems without telling anyone how. It only started to become more egalitarian when the internet got more pervasive. We realised that with information being available everywhere, we would lose the centralisation function of IT. But that was okay, because data is universal.”
“Turning transformation into a non-event is our North Star,” explains Thorsten Spihlmann, Head of Business Development for Transformation in the Cloud Lifecycle Management department at SAP. The evolution of SAP’s Business Transformation Centre (BTC) is future proofing customer experience. “The BTC is a comprehensive solution that helps users streamline the process of migration to S/4HANA,” says Spihlmann. “In the end, it’s one central platform – one central orchestration layer – which guides you through all phases of the project. The BTC enables users to access source systems, profile data for insights, enhance and transform data, provision it to target systems, and validate data integrity… Our customers’ interests are always top of mind.”
Nestlé: A CIO Leading by Example
Nestlé‘s Oceania’s CIO, Rosalie Adriano, dives deep into how her breadth of experience in transformational change led to her becoming one of 2024’s top 50 CIOs in Australia. “I want ideas to be freely shared. Innovation is encouraged. This approach breaks down silos and creates a sense of unity and purpose.”
Poundland & Dealz: The Value of Digital
Dean Underwood, IT Director at Poundland & Dealz, talks challenges, cultural shift and the company’s digitally transformation… “We must prove that spending on technology is as impactful as investing in product pricing,” he says. “For example, my request to fund a new data warehouse competes with the Commercial Director’s goal to maintain affordable prices. The customer always comes first, but investing in supply chain efficiencies lowers operating costs, helping us keep prices down. It’s our responsibility to demonstrate the value of every investment.”
Schenectady County Government: Delivering Critical and Secure Infrastructure
Schenectady County’s CIO Gabriel A. Benitez discusses the role of IT as a steward for citizens, leadership and the power of teams, and why security is crucial to the organisation… “We support and serve to keep Schenectady County running. That covers a broad remit, but some of the key departments we work with include Finance, Law Enforcement, Emergency Management, Public Health, Glendale Nursing Home, County Clerk, District Attorneys, Public Defender, Conflict Defender, Probation, Social Services, Veteran’s Affairs, Engineering & Public Works, and Department of Motor Vehicles.”
Interface looks back on another year of ground-breaking tech transformations and the leaders driving them. We spoke with tech leaders…
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Interface looks back on another year of ground-breaking tech transformations and the leaders driving them. We spoke with tech leaders across a broad spectrum of sectors – from banking, health and telcos to insurance, consulting and government agencies. Read on for a round up of some of the biggest stories in Interface in 2024…
EY: A data-driven company
Global Chief Data Officer, Marco Vernocchi, reflects on the transformation journey at one of the world’s largest professional services organisations.
“Data is pervasive, it’s everywhere and nowhere at the same time. It’s not a physical asset, but it’s a part of every business activity every day. I joined EY in 2019 as the first Global Chief Data Officer. Our vision was to recognise data as a strategic competitive asset for the organisation. Through the efforts of leadership and the Data Office team, we’ve elevated it from a commodity utility to an asset. Furthermore, our formal strategy defined with clarity the purpose, scope, goals and timeline of how we manage data across EY. Bringing it to the centre of what we do has created a competitive asset that is transforming the way we work.”
Lloyds Banking Group: A technology and business strategy
Martyn Atkinson, CIO – Consumer Relationships and Mass Affluent, on Lloyds Banking Group‘s organisational missive around helping Britain prosper, which means building trusted relationships over customer lifetimes by re-imagining what a bank provides.
“We’ve made significant strides in transforming our business for the future,” he reveals. “I’m really proud of what the team have achieved with technology but there’s loads more to go after. It’s a really exciting time as we become a modern, progressive, tech-enabled business. We’ve aimed to maintain pace and an agile mindset. We want to get products and services out to our customers and colleagues and then test and learn to see if what we’re doing is actually making a meaningful difference.”
Arianne Gallagher-Welcher, Executive Director for the USDA Digital Service, in the Office of the OCIO, on the USDA’s tech transformation and how it serves the American people across all 50 states.
“If you’d told me after I graduated law school that I was going to be working at the intersection of talent, HR, law, regulations, and technology and bringing in technologists, AI, and driving innovation and digital delivery, I’d say you were nuts,” she says. “However, it’s been a very interesting and fulfilling journey. I’ve really enjoyed working across a lot of different cross-government agencies. USDA is the first part of my career where I’m really looking at a very specific mission-driven organisation versus cross-agency and cross-government. But I don’t think I’d be able to do that successfully without the really great cross-government experiences I’ve had.”
Virgin Media O2 Business: A telco integration supporting customers
David Cornwell, Director – SMEs, on the unfolding telco integration journey at Virgin Media O2 Business delivering for Business customers
“If you’ve got the wrong culture, you can’t develop your people or navigate change…” David Cornwell is Director of Technical Services for SMEs at Virgin Media O2 Business. He reflects on the technology journey embarked upon in 2021 when two giants of the telco space merged. A new opportunity was seized to support businesses with the secure, reliable and efficient integration of new technology.
Nick Edwards, Group CDO at The AA, on the organisation’s incredible technology transformation and how these changes directly benefit customers.
“2024 has been a milestone year for the business,” explains Edwards. “It marks the completion of the first phase of the future growth strategy we’ve been focused on since the appointment of our new CEO, Jakob Pfaudler.” Revenues have grown by over 20%, allowing The AA to drive customer growth with technology. “All of this has been delivered by our refreshed management team,” he continues. “It reflects the strength of our people across the business and the broader cultural transformation of The AA in the last three years.”
Dave Murphy, Financial Services Lead, Global at Publicis Sapient, gave us the lowdown on its third annual Global Banking Benchmark Study.
The report reveals that artificial intelligence (AI) dominates banks’ digital transformation plans, signalling that their adoption of AI is on the brink of change. “AI, machine learning and GenAI are both the focus and the fuel of banks’ digital transformation efforts,” he says. “The biggest question for executives isn’t about the potential of these technologies. It’s how best to move from experimenting with use cases in pockets of the business to implementing at scale across the enterprise. The right data is key. It’s what powers the models.”
Chief Information Officer Simon Birch and Chief Customer & Transformation Officer Danielle Handley discuss Bupa’s transformation journey across APAC and the positive impact of its Connected Care strategy.
“Connected Care is our primary mission. We’ve been focusing our time, investment and energy to reimagine and connect customer experiences,” says Simon. “It’s an incredibly energising place to be. Delivering our Connected Care proposition to our customers is made possible by the complete focus of the organisation and the alignment leaders and teams have to the Bupa purpose. Curiosity is encouraged with a focus on agility, collaboration and innovation. Ultimately, we are reimagining digital and physical healthcare provision to customers across the region. Furthermore, we are providing our colleagues with amazing new tools to better serve our customers throughout all of our businesses.”
Gregg Aldana, Global Area Vice President, Creator Workflows Specialist Solution Consulting at ServiceNow, on how a disruptive approach to technology can drive innovation.
While the whole world works towards automating as many processes as possible for efficiency’s sake, businesses like ServiceNow are supporting that change evolution. ServiceNow’s platform serves over 7,700 customers across the world in their quest to eliminate manual tasks and become more streamlined. We spoke to Aldana about how it does this and the ways in which technology is evolving.
Innovation Group: Enabling the future of insurance
James Coggin, Group Chief Technology Officer on digital transformation and using InsurTech to disrupt an industry.
“What we’ve achieved at Innovation Group is truly disruptive,” reflects Group Chief Technology Officer James Coggin. “Our acquisition by one of the world’s largest insurance companies validated the strategy we pursued with our Gateway platform. We put the platform at the heart of an ecosystem of insurers, service providers and their customers. It has proved to be a powerful approach.”
Chief Information Officer William Sanson-Mosier on the development of advanced technologies to empower emergency responders and enhance public safety
“Ultimately, my motivation stems from the relationship between individual growth and organisational success. When we invest in our people, and we empower them to innovate with technology and problem-solve, they can deliver exceptional results. In turn, the organisation thrives, solidifying its position as a leader in its field. This virtuous cycle of growth and innovation is what drives me.” CIO William Sanson-Mosier is reflecting on a journey of change for the San Francisco Police Department (SFPD). Ignited by the transformative power of technology to enhance public safety and improve lives.
We chat with the CIO of Urenco, Sarah Leteney, about the ways this unique business leverages technology, and the big difference a small team can make.
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Urenco does things a little differently. It has to. It supplies uranium enrichment services and fuel cycle products for the nuclear industry – a niche that requires a lot of specialist care and attention. Urenco has a clear vision for the net zero world. A world in which carbon-free energy is the norm. And for its CIO, Sarah Leteney, this means approaching the world of technology in different and interesting ways.
Leteney speaks exclusively to Interface Magazine about what it means to operate IT in a high-risk environment that requires an enormous amount of consistency. She also discusses the types of systems that are vital to Urenco, how the business leverages suppliers, bringing in the most talented possible people, and how Urenco balances a small team with a high pressure environment.
How does the role of CIO within the nuclear industry differ from one for a consumer goods company?
Most CIOs spend their time thinking about how to talk to customers through the rapid exchanges that are needed to maintain the flow of high volumes of traffic. They need to know how to keep up with their competitors in terms of customer experience and how to quickly bring new products to market.
At Urenco, we are quite literally the polar opposite of this. We are concerned with the consistency and timeliness of highly individualised communications with our customers, how internal control software can enable the accurate flow of information to our regulators, and how to support our teams to keep track of every gram of raw material, and product in our organisation. Our systems are vital to keep our operations safe and reliable. It is not fast-paced – rather a very careful and considered environment where accuracy is everything.
What is it like to enable and provision services in such an environment? Can you keep in touch with market trends? Is there much recognition of what you do?
I work in a high threat environment and there are many special considerations to understand. There is a certain cadence and rhythm to what we do and we have to work at a pace which suits the organisation, rather than keep up with the latest trends in the IT industry. Although, we do keep abreast of developments through networks such as Gartner and Aurora and introduce them where appropriate and relevant.
In relation to the recognition of this role, like every other CIO out there, you are noticed more when something is not working properly. That said, Urenco is very good at making you feel as if you are part of something that matters. People readily ask you questions and understand when something is a minor glitch compared to something more significant. And we actively encourage people to report issues because that is how you get continuous improvement. Overall, the organisation takes care of my team, we’re not under siege when things go wrong and what we do is widely appreciated.
What sorts of systems are you looking after and what are the challenges around these?
We have all the same systems that you see in many other large organisations, plus a few really niche products used only in our industry.
Like lots of businesses, we are on a SAP journey, moving existing systems into S4. This programme impacts all parts of the organisation and we have to drive the changes forward from a business point of view. We consider the IT team an enabler for this work as it’s ultimately the transformation of our business processes which we are trying to facilitate.
We also look after the information assets of the organisation – both the structured and unstructured data. Like many organisations, it’s an on-going process to work out how to extract genuine business insights from vast amounts of historical data which has been stored in multiple places and not always in the most logical manner. We have a significant amount of historical information which still remains important (think plant designs and maintenance records, etc.) so effective archiving and retention policies are very much at the forefront of our minds. It’s so easy to over store or over classify information in an effort to be ‘safe rather than sorry’, but in reality, as well as increasing on-going costs, this sort of behaviour tends to make it harder to find what you need. We are investigating new technologies to help us search through our data faster and more effectively than ever before.
We’re also currently extending into the Operational Technology sphere, sharing our experience and tools with our OT colleagues and directly addressing operational security challenges, investing significantly in our cyber defences to further strengthen our plant security services.
What is it like to work in a company with a large turnover but a relatively small number of employees? How does that affect the service you provide?
We try to think through what every employee needs from IT and provide them with the level of service their role requires, regardless of their position in the business. We are in the fortunate position where having fewer employees means individual changes to software, hardware, or SAAS costs tend to have a less significant impact on our profitability than in many organisations with higher staff complements. Many organisations have tiers of users which determine the level of service received. However, in our organisation, every minute of everyone’s time is important, as we don’t have many employees driving our engine forward. We are investing in our employee experience as one of the key organisational imperatives working alongside our colleagues in the People and Culture team, and this is going to be an on-going focus for us for the next few years.
Whilst the company turnover is important, it is less of a driving factor for us in IT. We benchmark ourselves against what proportion of operational expenditure we are investing in IT and IS to ensure we invest an appropriate amount in IT for an organisation of this size.
How do you work with your team to ensure they can provide the most effective service to the business?
We are organised primarily around our production sites, with a centralised team to provide shared services like architecture and finance. The organisation is only two layers deep in most teams, so information flow is mainly managed by direct cascade. The senior team is made up of heads of shared functions and site IT managers, and opinions flow freely between them.
Our IT Leadership team has a monthly two-day meeting where we come together in person. We sit together without our PCs and the constant pinging of information. This helps us to realign, to reprioritise matters, and include coaching and learning techniques. We all have daily pressures in our lives, and these meetings are about supporting each other and working effectively together.
Once a quarter we also visit one of our sites as a group, hosted by our IT site managers. This is critical to us because we cannot do our jobs without thoroughly understanding the experience of IT services on the ground. These visits also allow us to meet up with our business colleagues as part of their site leadership teams so we can exchange experiences and strategic thinking quite freely in person.
We also run monthly townhall meetings for all members of the IT team, and invite our colleagues from Information Security to join us. We have found this to be a really valuable information exchange point. IS can hear exactly what we are saying to the wider team on the ground, so they can gain real insight into our issues first hand. Our key suppliers are also invited to these sessions on a quarterly basis, again to foster free exchange of information.
How about diversity and inclusion – what are you doing within that area and what have you achieved?
This is one of the biggest areas I would like to tackle further. Within our company, like the whole of the nuclear sector, the age of our employees is increasing year on year as we have a very low employee turnover. So we have a small number of vacancies on an annual basis and we are working hard to get a better talent pool for when these opportunities arise, reaching out to people with a wider range of backgrounds.
Our strategy includes blind sifting, engaging with people who have had periods of time out of the workplace and may need to work certain hours, and being open to job-sharing. It is possible for us to be very flexible and we are trying to ensure this is known out in the world of recruitment.
One area we are doing really well in right now is neurodiversity. We have a significant proportion of our team who identify as neurodivergent and a new staff network focussing on the specific issues of importance to this community was actually started by a member of our team.
I’d love to see an ethnicity and gender mix in the future which is closer to the population norms in each of our operating countries and I’m pleased to say that our talent acquisition partners are working hard to promote our roles in new talent pools with a much more diverse population.
How do you work with your suppliers to maintain a good relationship with them?
We’re currently in the process of diversifying our IT supply base. We have had a couple of really strong suppliers for a long period of time who work very closely with us, but what we are aiming to do now is widen our group of key suppliers to create a supplier ecosystem consisting of four different types of partner – Advisory, Development, Configuration, and Support. A key part of this initiative will be about embedding the behaviours we would like suppliers to demonstrate when working with us to create an inclusive and transparent relationship, which we are progressing through setting up a Urenco Academy to provide initial onboarding and on-going behavioural reinforcement of Urenco’s core values across our partnerships.
You recently won a CIO 100 award. How did that come about and what reaction did you get from people who know you?
The CIO 100 award came about through my external mentor asking me why I wasn’t looking at it! He encouraged me to put myself forward for consideration. Sometimes you need a bit of a push from a critical friend to remind you that whilst you see how much remains to be done, it’s good to acknowledge the great results you have already achieved.
The most gratifying thing about the whole experience for me was that you are judged by really experienced CIOs, so they fully understand the complexity of what you do. I’m incredibly grateful and humbled to be included in such an inspiring group of people, who are all wrestling with organisational struggles and trying to keep up in a fast-paced world, solving problems all day, every day.
My colleagues were delighted for me and sent lots of congratulatory messages. I think my team were slightly surprised because they also don’t always see what a good job they are all doing. One of them was even inspired to send an AI-created poem in celebration!
Urenco gave me the opportunity to take on a challenging and exciting role initially as an interim CIO. They chose to promote from within despite having strong external candidates, and not only that, but they asked if I would like to have a mentor in my first year to help me to cement the skills I wanted to strengthen for my own peace of mind. I’m not sure what else I could have asked for from this organisation. When I look at the award all I really think, looking back over the last three years, is ‘how amazing is that’!
We say goodbye to 2024 focused on the technology innovation the new year will bring. Our cover story highlights a…
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We say goodbye to 2024 focused on the technology innovation the new year will bring. Our cover story highlightsa technology transformation journey change for the San Francisco Police Department (SFPD)
Welcome to the latest issue of Interface magazine!
San Francisco Police Department: A Technology Transformation
San Francisco Police Department (SFPD) CIO William ‘Will’ Sanson Mosier is ignited by the transformative power of technology to enhance public safety and improve lives. “Ultimately, my motivation stems from the relationship between individual growth and organisational success. When we invest in our people, we empower them to innovate, problem-solve, and deliver exceptional results. In turn, the organisation thrives, solidifying its position as a leader in its field. This virtuous cycle of growth and innovation is what drives me.”
OSB Group- Building the Bank of the Future
Group Chief Transformation Officer Matt Baillie talks to Interface about maintaining the soul of a FinTech with the gravitas of a FTSE business during a full stack tech transformation at OSB Group. “We’ve found the balance between making sure we maintain regulatory compliance and keeping up with customer expectations while making the required propositional changes to keep pace with markets on our existing savings and lending platforms.”
Urenco: Accuracy is Everything
We speak with the CIO of Urenco – an international supplier of enrichment services and fuel cycle products for the civil nuclear industry. Sarah Leteney talks about the ways this unique business leverages technology, and the big difference a small team can make. “We work in a high threat environment and there are many special considerations to understand. There is a rhythm to what we do to work at a pace which suits the organisation, rather than keep up with the latest trends in IT.”
Langham Hospitality Group SVP, Sean Seah, talks hospitality informed by innovation, and falling in love with the problem, not the solution. “You’ve got to pilot something small – ideate it, then you can incubate it, and if it works you figure out how to industrialise it.”
Midcounties Co-operative: A Digital Transfomation
The Midcounties Co-operative is home to over 645,000 members and employs more than 6,200 people across multiple brands and locations, including over 230 food retail stores across the UK. We spoke with CIO Jacob Isherwood to learn about its approach to data management. “Whether you’re running a nursery, managing a natural gas pipeline, or selling tins of beans, data helps manage complexity and meet challenges from a place of understanding.”
Xerox has been a household name for decades. For many, it’s associated with photocopiers and printers. After all, it’s the…
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Xerox has been a household name for decades. For many, it’s associated with photocopiers and printers. After all, it’s the largest print company in the world. But it’s also a technology powerhouse that’s been at the forefront of a great deal of innovation. It has undergone a journey of evolution and reinvention into an IT and digital services provider. That’s what led to the business acquiring a large managed service provider, Altodigital, in 2020.
Derek Gunton has spent nearly 20 years in the technology sphere. He came to Xerox as part of the Altodigital acquisition. Altodigital also started out as a management print organisation and evolved into the IT services side, so its journey mirrors Xerox’s in many ways. “Now, as we move into the next technological age powered by AI and automation, we’ve put ourselves in a good position,” says Gunton.
“Xerox continues to evolve as a company. It recently announced the acquisition of another large managed services IT business called Savvy, which will double the size of the IT services business. That gives us a lot of speciality, a lot of scale, and prepares us for that leap into the technologies of the future.”
Supporting Lanes Group’s technology
Xerox has been supporting Lanes Group in its own growth journey for a few years now. It doesn’t provide print services, but the IT and digital services Xerox is gradually becoming known for. The relationship began during the COVID-19 pandemic, when the working environment was very different. Businesses were trying to figure out how to continue to operate as normally as possible and provide certainty for staff.
“There were just two of us from Xerox working with them, and we were talking about room planning software,” says Gunton. “How do you manage how many people are in the building? How do they book spaces, or manage people in line with the COVID legislation that was in place? The conversation started there. Then, we were asked what we could do around providing some managed service desk support just to assist the internal team at the time – and it’s grown from there. Four years later, we have over 30 members of staff dedicated to the Lanes account, supporting more than 4,000 users across over 50 states.
“We’re very much an operation that compliments Lanes Group. The thing that has always worked well is that we have the ability to respond and scale. Lanes have been on their own journey over the last few years to the point that they’re truly industry-leading, and we’ve managed to keep up whilst always looking to innovate, make suggestions, and bring new solutions to the table.”
An integrated technology partnership
Lanes Group supports key utilities including water and gas. What it does is absolutely critical. If there are problems in those areas, millions of people can be affected. So while Lanes has a huge responsibility to always be ready to support those utilities at all times, Xerox has just as much of a responsibility to be in a position to support Lanes.
“It’s massively important, and everybody in our business is briefed on what Lanes does to ensure we understand that responsibility,” says Gunton. “In my career, I’ve seen lots of different structures in terms of how we work with clients. Sometimes it can be very much a supplier-client relationship where it’s very siloed and formal. What sets our relationship with Lanes Group apart is that it’s a very integrated partnership. There are several meetings every week. There are dedicated program managers, and every product area has its owner. We have very strict SLAs to adhere to and the only way to deliver what Lanes needs is through communication and mutual support.”
Streamlining inconsistencies
A perfect example of the collaborative relationship between Xerox and Lanes Group is the secure network solution Xerox put in place. Effectively, Xerox mapped out and replaced the network infrastructure of all Lanes Group sites, giving better visibility, better control, and a better user experience.
“When we first reviewed the sites, there were over 50 of them running independently. That was difficult for the IT team to manage,” says Gunton. “It led to a lot of inconsistencies. We had mixed feedback from end users. Our aim was to introduce a technology system that would give the users the ability to have a consistent experience across all sites. We worked with our partners at HPE to identify the latest Ariba access solutions available, and deployment across all sites has been very successful. It’s also improved security, giving users the ability to skip length authentication processes. The user experience is really smooth now, which is what we were after.”
Creating agility
Working as partners, not in a supplier-client capacity, has made all the difference for the two businesses. From robot process automation to take manual tasks away from humans, to the increased use of AI-driven tools, Xerox is providing Lanes with what it needs to be agile. It’s a relationship based on trust and a shared goal.
“I do appreciate the help from the stakeholders at Lanes, because they embrace the same kind of culture,” Gunton says. “Often we’ll do joint meetings where we all address the same problem or desire to innovate together. We trust each others’ skill sets and openness to really come up with a solution. Ultimately, it’s all people-driven. It’s based on having really clever people in the right places, and we’ve built up a really solid team over the years.”
The evolution Lanes Group is going through isn’t going to slow down any time soon. That means Xerox’s work won’t either. Gunton states: “Our broad priorities with Lanes also reflect the current UK landscape. Data integration and automation are the areas we’re continuing to focus on. We have to think about how we deliver that. In terms of data, there needs to be one true source. You have to be really confident in the information you have, being as accurate as possible.”
What’s key for Xerox is ensuring that Lanes Group is able to shift from being reactive to more proactive. That is its focus. “We’re already delivering technology solutions to better equip Lanes to respond in that manner. I think the next year is going to be really exciting as we continue to develop that. We believe that we will continue to put Lanes at the forefront of their industry with the solutions that we supply.”
This month’s cover story throws the spotlight on the ground-up technology transformation journey at Lanes Group – a leading water…
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This month’s cover story throws the spotlight on the ground-up technology transformation journey at Lanes Group – aleading water and wastewater solutions and services provider in the UK.
Welcome to the latest issue of Interface magazine!
In a world driven by transformation, it’s rare a leader gets the opportunity to deliver organisational change in its purest form… Lanes Group – the leading water and wastewater solutions services provider – has started again from the ground up with IT Director Mo Dawood at the helm.
“I’ve always focused on transformation,” he reflects. “Particularly around how we make things better, more efficient, or more effective for the business and its people. The end-user journey is crucial. So many times you see organisations thinking they can buy the best tech and systems, plug them in, and they’ve solved the problem. You have to understand the business, the technology side, and the people in equal measure. It’s core to any transformation.”
Mo’s roadmap for transformation centred on four key areas: HR and payroll, management of the group’s vehicle fleet, migrating to a new ERP system, and health and safety. “People were first,” he comments. “Getting everyone on the same HR and payroll system would enable the HR department to transition, helping us have a greater understanding of where we were as a business and providing a single point of information for who we employ and how we need to grow.”
Schneider Electric provides energy and digital automation and industrial IoT solutions for customers in homes, buildings, industries, and critical infrastructure. The company serves 16 critical sectors. It has a vast digital footprint spanning the globe, presenting a complex and ever-evolving risk landscape and attack surface. Cybersecurity, product security and data protection, and a robust and protected end-to-end supply chain for software, hardware, and firmware are fundamental to its business.
“From a critical infrastructure perspective, one of the big challenges is that the defence posture of the base can vary,” says Cassie Crossley, VP, Supply Chain Security, Cybersecurity & Product Security Office.
“We believe in something called ‘secure by operations’, which is similar to a cloud shared responsibility model. Nation state and malicious actors are looking for open and available devices on networks. Operational technology and systems that are not built with defence at the core and not normally intended to be internet facing. The fact these products are out there and not behind a DMZ network to add an extra layer of security presents a big risk. It essentially means companies are accidentally exposing their networks. To mitigate this we work with the Department of Energy, CISA, other global agencies, and Internet Service Providers (ISPs). Through our initiative we identify customers inadvertently doing this we inform them and provide information on the risk.”
Persimmon Homes: Digital Innovation in Construction
As an experienced FTSE100 Group CIO who has enabled transformation some of the UK’s largest organisations, Persimmon Homes‘ Paul Coby knows a thing or two about what it takes to be a successful CIO. Fifty things, to be precise. Like the importance of bridging the gap between technology and business priorities, and how all IT projects must be business projects. That IT is a team sport, that communication is essential to deliver meaningful change – and that people matter more than technology. And that if you’re not scared sometimes, you’re not really understanding what being the CIO is.
“There’s no such thing as an IT strategy; instead, IT is an integral part of the business strategy”
WCDSB: Empowering learning through technology innovation
‘Tech for good’, or ‘tech with purpose’. Both liberally used phrases across numerous industries and sectors today. But few purposes are greater than providing the tools, technology, and innovations essential for guiding children on their educational journey. Meanwhile, also supporting the many people who play a crucial role in helping learners along the way. Chris Demers and his IT Services Department team at the Waterloo Catholic District School Board (WCDSB) have the privilege of delivering on this kind of purpose day in, day out. A mission they neatly summarise as ‘empower, innovate, and foster success’.
“The Strategic Plan projects out five years across four areas,” Demers explains. “It addresses endpoint devices, connectivity and security as dictated by business and academic needs. We focus on infrastructure, bandwidth, backbone networks, wifi, security, network segmentation, firewall infrastructure, and cloud services. Process improvement includes areas like records retention, automated workflows, student data systems, parent portals, and administrative systems. We’re fully focused on staff development and support.”
Combining advanced technology with a people-led focus is the name of the game for Bravo Consulting Group. Bravo was founded…
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Combining advanced technology with a people-led focus is the name of the game for Bravo Consulting Group. Bravo was founded in 2007 by President and CEO Gino Degregori. He had his sights squarely set on leveraging Microsoft technologies to deliver cloud services, application modernization, and cybersecurity compliance. Bravo’s aim is to simplify how organisations create, share, and secure their intelligent information. In nearly 17 years of its existence, the business has grown into a premier Microsoft solutions provider serving the federal government, the Department of Defense, the Intelligence Community, and multiple Fortune 500 organisations.
Human-centric leadership and core values
Degregori began his career in software engineering and entrepreneurship. However, he quickly realised that his true calling was beyond just developing software and implementing Microsoft technologies. “I saw an opportunity to build an amazing organisation that provides real value to our customers through our people and innovative solutions,” Degregori explains. “While the cloud didn’t exist in 2007, development, automation, and security were already crucial.”
Degregori founded Bravo on core values that remain the cornerstone of the company today. “Our vision is to attract and create kind leaders who make an impact on our customers, partners, and communities,” he explains. “We lead with empathy, embracing kind leadership. This means prioritising the growth and wellbeing of our team members and clients. We view every interaction from a win-win perspective with a strong sense of accountability.
“It’s not just about implementing technology in your organisation; it’s about truly advancing the mission. Collaborating with great people enables us to deliver outstanding results,” he emphasises. Degregori also hosts The Kind Leader Podcast where he discusses empathetic leadership with industry leaders, embodying the values Bravo champions.
By fostering a culture of empathy and innovation, Bravohas established itself as a leader in cloud services, application modernization, and cybersecurity. Degregori’s commitment to building a people-centric organisation ensures that Bravo not only meets but exceeds the expectations of its clients, driving meaningful and impactful results.
Strategic partnership with AvePoint
Bravo’s commitment to collaborating with exceptional partners has been the cornerstone of its longstanding relationship with AvePoint. For 15 out of its nearly 17 years of existence, Bravo has partnered with AvePoint—a testament to the enduring strength and value of this collaboration. When Bravo first started, the Microsoft ecosystem was rapidly evolving, with many businesses transitioning away from legacy systems. AvePoint’s advanced SharePoint migration and administration tools played a pivotal role in this transition, enabling Bravo to assist over 100,000 users across various verticals in successfully migrating and managing their content and data.
“Our partnership with AvePoint allowed us not only to migrate vast amounts of content and data efficiently but also to reduce costs, which we passed on to our customers,” says Degregori. “It was a phenomenal opportunity to leverage AvePoint’s tools for seamless content and data migration. We recognized early on that AvePoint was poised for significant success, and from then on, our collaboration deepened, enabling us to develop even better solutions.”
This partnership is a key reason customers choose Bravo. By integrating Bravo’s expertise in the Microsoft ecosystem with AvePoint’s suite of tools, Bravo delivers a unique value proposition centred on data management, compliance, and AI-driven solutions. Customers benefit from a holistic approach that not only prepares them for new technologies but also ensures regulatory compliance, cost efficiency, and superior results.
Together, Bravo and AvePoint empower organisations to confidently navigate their digital transformation. Leveraging Microsoft’s advancements in AI and AvePoint’s robust data management tools, they offer cutting-edge solutions that address the evolving needs of modern businesses. This collaboration enables organisations to optimise their data, maintain stringent compliance standards, and harness the power of AI to drive innovation and efficiency.
Expanding horizons through collaboration
For the first decade, Bravo focused exclusively on the federal sector. Recently, Degregori made the strategic decision to expand Bravo’s services into the commercial sphere. “Our strong partnership with AvePoint was instrumental in this successful expansion,” he says. “AvePoint is a global organisation, and through our collaboration, we developed a strategy to penetrate the commercial market. We leveraged our combined services, expertise, and certified professionals at Bravo to build trust and confidence with the AvePoint commercial folks.”
The unique relationship between Bravo and AvePoint has facilitated this long-standing and successful collaboration. Degregori attributes their success to three key factors: communication, clarity, and trust.
“First, strong communication ensures continuous understanding. Second, clarity about our collective goals – focusing not just on our objectives but also on AvePoint’s – allows us to align our efforts effectively. Lastly, trust is paramount. We need to rely on each other through both successful projects and challenging ones. This mutual trust ensures we can support each other through thick and thin,” Degregori explains.
“We are always learning. When things don’t go as planned, we sit down, discuss the lessons learned, and find ways to improve. This continuous learning and mutual support strengthen our partnership and drive our shared success.”
Future growth
The future of Bravo and AvePoint is exceptionally promising as technology evolves at an unprecedented pace. Both organisations are at the forefront, leveraging the Microsoft ecosystem. With Microsoft’s substantial investments in generative AI, their reach is set to expand even further into the Fortune 500 globally.
“This momentum allows us to continuously leverage advanced tools, integrating them to deliver unparalleled value to our customers,” says Degregori. This focus on the human element—the customer—ensures that Bravo remains true to its core values.
“I am immensely grateful for the opportunity to lead an incredible organisation like Bravo and to maintain a long-term partnership with AvePoint. Ultimately, while we discuss technology and solutions, it’s all about people. We’re constantly seeking ways to connect better as partners and employers. This human-centric approach is what drives us to deliver superior solutions.”
This vision and commitment to both technological excellence and human connection make Bravo and AvePoint’s partnership not only resilient but also highly impactful for their clients. Together, they are poised to lead the way in digital transformation, ensuring that organisations are not only equipped with the latest innovations but also supported by a team that values their success.
Our cover story reveals the digital transformation journey at global insurance services company Innovation Group using InsurTech advances to disrupt…
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Our cover story reveals the digital transformation journey at global insurance services company Innovation Group using InsurTech advances to disrupt the industry.
Welcome to the latest issue of Interface magazine!
We’re excited to be publishing the biggest ever issue of Interface this month. It’s packed with insights from the cutting edge of digital technologies across a diverse range of sectors; from InsurTech to Travel via eCommerce, Banking, Manufacturing and Public Services.
Innovation Group: Enabling the Future of Insurance
“What we’ve achieved at Innovation Group is truly disruptive,” reflects Group Chief Technology Officer James Coggin.
“Our acquisition by one of the world’s largest insurance companies validated the strategy we pursued with our Gateway platform. We put the platform at the heart of an ecosystem of insurers, service providers and their customers. It has proved to be a powerful approach.”
Leeds Building Society: Tech Transformation Driven by Data
Carole Roberts, Director of Data at Leeds Building Society, on a digital transformation program driven by the mutual power of people and culture.
“We’ve made the decision to move to a composable architecture. It’s going to give us much more flexibility in the future to be able to swap in and out components rather than one big monolithic environment.”
AvePoint: Securing the Digital Future
Kevin Briggs, Vice President of Public Sector at AvePoint, discusses pioneering data security and management transformation in the global public sector.
“We ensure the security, accessibility and integrity of data for customers with missions from everything from finance and health services, through to national security, innovation, and science.”
Saudia: Taking off on a Digital Journey
Abdulgader Attiah, Chief Data & Technology Officer at Saudia, on the digital transformation program towards becoming an ‘offer and order’ airline.
“By the end of this year we will have established the maturity level for data technology, and our digital and back-office transformations. In 2025 we will begin implementing our retailing concept and the AI features that will drive it. The building blocks will be in place for next year’s initiatives where hyper personalisation for retailing is a must.”
Publicis Sapient: Global Banking Benchmark Study
Dave Murphy, Financial Services Lead, International – gives Interface the lowdown on the third annual Global Banking Benchmark Study and the key findings Publicis Sapient revealed around core modernisation, GenAI, data analytics transformation and payments.
“AI, machine learning and GenAI are both the focus and the fuel of banks’ digital transformation efforts. The biggest question for executives isn’t about the potential of these technologies. It’s how best to move from experimenting with use cases in pockets of the business to implementing at scale across the enterprise. The right data is key. It’s what powers the models.”
Habi: Unleashing liquidity in the LATAM market
Employees at Habi discuss its mission to help customers buy and sell their homes more effectively.
“At Habi, you can talk with the AI agent and you can provide information that streamlines the whole process.”
USDA FPAC: Achieving customer experience balance
Abena Apau and Kimberly Iczkowski, from USDA FPAC on the incredible work the organisation is doing to support farmers across America.
“We’ve created a new structure for ourselves, based on the fact that the digital experience is not the be all and end all, and we have to balance it with the human touch.”
Adecco Group: Digital Transformation driven by business outcomes
Geert Halsberghe, Head of IT, Benelux, at Adecco Group, talks transformation management, cultural consensus, and ensuring digital transformation starts (and stays) focused on solving business problems.
“It’s very crucial to make sure that we aren’t spending money on IT transformation for the sake of IT transformation.”
La Vie en Rose: Outcome-focused Digital Transformation
Éric Champagne, CIO of La Vie en Rose, on ensuring digital transformations are defined by communication, vision, and cultural buy-in.
“I don’t chase after the latest technology just because it seems cool… My focus is on aligning technology with the business strategy and real needs.”
Breitling: Digital Transformation and the omnichannel experience
Rajesh Shanmugasundaram, CTO at Breitling, talks changing customer expectations, data, AI, and digitally transforming to deliver the omnichannel experience.
“The CRM, the marketing, our e-commerce channels — they’ve all matured so much… we’re meeting our customers wherever they are or want to be.”
Our cover star, EY’s Global Chief Data Officer Marco Vernocchi, tells Interface why data is a “team sport” and reveals…
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Our cover star, EY’s Global Chief Data Officer Marco Vernocchi, tells Interface why data is a “team sport” and reveals the transformation journey towards realising its potential for one of the world’s largest professional services organisations.
Welcome to the latest issue of Interface magazine!
Global Chief Data Officer, Marco Vernocchi, reflects on the data transformation journey at one of the world’s largest professional services networks.
“Data is pervasive, it’s everywhere and nowhere at the same time. It’s not a physical asset, but it’s a part of every business activity every day. I joined EY in 2019 as the first Global Chief Data Officer. Our vision was to recognise data as a strategic competitive asset for the organisation. Through the efforts of leadership and the Data Office team, we’ve elevated data from a commodity utility to an asset. Our formal data strategy defined with clarity the purpose, scope, goals and timeline of how we manage data across EY. Bringing data to the centre of what we do has created a competitive asset that is transforming the way we work.”
PivotalEdge Capital
Sid Ghatak, Founder & CEO of asset management firm PivotalEdge Capital, spoked to us about the pioneering use of “data-centric AI” for trading models capable of solving the problems of trust and cost.
“I’ve always advocated data-driven decision-making throughout my career,” says Ghatak. “I knew when I started an asset management firm that it needed to be data-centric AI from the very beginning. A few early missteps in my career taught me the importance of having a stable and reliable flow of data in production systems and that became a criterion.”
LSC Communications
Piotr Topor, Director of Information Security & Governance at LSC Communications, discusses tackling the cyber skills shortage, AI, and bringing together the business and IT to create a cyber-conscious culture at a global leader in print and digital media solutions.
Topor tells Interface: “The main challenge we’re dealing with is overcoming the disconnect between cybersecurity and business goals.”
América Televisión
Interface meets again with Jose Hernandez, Chief Digital Officer at América Televisión, who reveals how the company is embracing new business models, and maintaining market leadership in Peru.
“Launching our FAST channel represents a pivotal step in diversifying our content delivery and monetisation strategies. Furthermore, aligning us with global trends while catering to the changing viewing habits of our audience,” says Hernandez.
Also in this issue of Interface, we hear from eflow about new approaches to Regtech; get the lowdown on bridging the AI skills gap from CI&T; and GCX on the best ways to navigate changing cybersecurity regulations.
Our cover story this month focuses on the work of Chief Information Officer Simon Birch and Chief Customer & Transformation…
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Our cover story this month focuses on the work of Chief Information Officer Simon Birch and Chief Customer & Transformation Officer Danielle Handley leading Bupa’s digital transformation journey across APAC and delivering a positive impact with its Connected Care strategy.
Welcome to the latest issue of Interface magazine!
“ConnectedCare is our primary mission and we’ve been spearheading time, investment and creativity to reinvent and reinvigorate customer experiences,” says APAC CIO Simon Birch. “Delivering that ConnectedCare proposition to our customers is made possible by the collegiate focus of the organisation. Ultimately, what we’re able to achieve is supporting our most important colleagues, our healthcare practitioners working across our facilities.”
Reflecting on that transformation goal, Chief Customer & Transformation Officer Danielle Handley believes that stakeholder engagement and alignment, while building relationships across the enterprise, have been key to their early success. “We’ve found the champions within the enterprise who are going to form part of the coalition of the willing to start to lead transformation here at Bupa.”
Vodafone: Personalising Embedded Insurance
Halil Teksal, Global Head of Fintech at Vodafone, discusses disruption in insurance, personalisation, and giving customers exactly what they need at the right time. “The main thing we’re aiming for is simplicity. How can we have really easy-to-use personalised solutions? At the end of the day, that’s what customers want. When they buy a smart device, they want to buy the insurance quickly from a reliable provider. It’s important that we satisfy all of those needs.”
Young businessman writing on adhesive notes on glass partition in modern office, ideas, innovation, planning, strategy
Walden Group: Advanced technology for a healthier tomorrow
Denis Connolly, CIO of Walden Group and CEO of Walden Digital, talks about the incredible work the organisation is doing to leverage data and technology for the overall improvement of the world’s health. “We’ve created all these new initiatives just in the last year or so, moving from technology being a cost centre to being an R&D and development-focused organisation.”
Also in this issue, Samer Fouani, Head of Cyber Transformation & Identity Access Management at TAL discusses the cyber journey for colleagues and customers at one of Australia’s leading insurers; Mark Turner, Chief Commercial Officer at Pulsant, explores how medium-sized businesses can best leverage new developments in AI; Martin Hartley, Group Chief Commercial Officer of emagine, examined the role of artificial intelligence in personalising the customer experience for financial services and Marius Stäcker, CEO of ToolTime, shares his four top tips for successfully implementing new software and driving digital transformation.
This month’s cover story sees our sister brand Fintech Strategy reporting from Money20/20 Europe in Amsterdam – a pivotal event…
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This month’s cover story sees our sister brand Fintech Strategy reporting from Money20/20 Europe in Amsterdam – a pivotal event in the fintech calendar, drawing over 8,000 participants from 2,300 companies worldwide.
Welcome to the latest issue of Interface magazine!
The RAI Amsterdam Convention Centre was the location for the world’s leading fintech conference. Money20/20 Europe offered a unique blend of insightful keynotes, panel discussions, and networking opportunities that underscored the transformative power of emerging technologies in financial services. We met with SC Ventures, Lloyds Banking Group, OSB Group, AirWallex, Plaid, Paymentology, Episode Six, Mettle (Nat West Group) and more to take the pulse of the latest trends across the fintech landscape.
Under the theme of ‘Human X Machine’, Money20/20 Europe explored the relationship between humans and intelligent machines, focusing on how the partnership between artificial and human intelligence will forge a new era in finance…
Publicis Sapient: Global Banking Benchmark Study
Interface was also proud to partner with Publicis Sapient at Money20/20 Europe for the launch of its third annual Global Banking Benchmark Survey. The survey draws on the insight of over 1000 senior executives in financial services across various global markets and focuses on the goals, obstacles, and drivers of digital transformation.
We spoke with Head of Financial Services Dave Murphy about its findings. “The survey focuses on how to think about solving problems end-to-end. Banks are dealing with legacy issues and taking a customer first view into solving the challenges. The practical application of AI across the banks is a significant theme as they look to automate decision-making and deliver better credit risk models.”
At the launch event for the study, Eoghan Sheehy, Associate MD, and Grace Ge, Senior Principal, highlighted that banks are primarily focused on improving existing processes rather than introducing new ones. Data Analytics and AI are identified as key priorities for digital transformation, with a focus on internal use cases and efficiency.
Eoghan and Grace also discussed the challenges faced by banks, including regulation, competition from companies like Amazon, and the need to attract talent. They emphasised the importance for financial institutions of modernising core infrastructure and building cloud infrastructure to support ongoing digital transformation. The study also notes the prevalence of the development of custom-made tools and the prioritising of internal use cases for AI implementation. Eoghan and Grace also provided examples of repeatable use cases and discussed the success factors for Data Analytics and AI.
STO Building Group: Enabling and Empowering People
Claudia Healey, Chief Human Resources Officer at STO Building Group, spoke to Interface about the HR platform empowering its people in pursuit of a strategic vision… “Culture is the number one priority in a people business like STO Building Group (STOBG). If you’re not nurturing and inspiring your folks, well, they can just vote with their feet. They don’t have to stay. Or they could do worse, they could quit and stay. And that’s something we would never want. Meeting your people where they’re at, understanding their goals and aspirations, and how you can help them reach their potential is vital. Realising how you can really see your people and truly understand what matters to them, is an incredible priority.”
Also in this issue, AI hype has previously been followed by an AI winter, we hear from Scott Zoldi, Chief Analytics Officer at FICO who asks, ‘Is the AI bubble set to burst?’ Elsewhere, we round up the top events in tech and learn how businesses can ensure their cloud storage is more sustainable in an age of rising demand for data and AI. Cloud storage without the climate cost is possible explains Fasthosts CEO Simon Yeoman.
Global cloud services point-of-sale provider, GK Software, was founded over 30 years ago in Germany. For most of its existence,…
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Global cloud services point-of-sale provider, GK Software, was founded over 30 years ago in Germany. For most of its existence, its focus was on expanding across Europe. However, in 2015, GK broke into the US when its partnership with SAP helped it drive into that vital market. The business has been thriving stateside ever since. Its core business is a point-of-sale software platform – CLOUD4RETAIL – which features the OmniPOS solution. Today, GK is ranked highly in global POS installations and has been among the top three for the last five years.
GK is an organisation committed to continuous improvement and customer engagement. It is evolving, getting into newer technologies like AI in a big way. It’s leveraging its expertise to improve insights into what its retail customers and their shoppers need. This includes everything from price optimisation to loyalty to self-service technologies.
Its ability to provide these services, through its expertise, is what attracted Virginia ABC to GK Software. Virginia ABC was a previous user of SAP’s point-of-sale (POS) solution, but as the authority evolved, it required an updated POS.
GK Software meets Virginia ABC
Enter: GK Software. “As a result of our relationship with SAP and with Paul Williams at Virginia ABC, we were shortlisted in their new point-of-sale solution selection,” explains Max Francescangeli, Regional Sales Director at GK Software.
“With Virginia ABC, we went through quite an extensive selection process. It’s a government agency, so the rules are very strict,” says Francescangeli. “But we were able to prove that we could use our expertise to address and solve all of their problems in spite of the unique environment they operate in. They needed a flexible solution that would interact well with their legacy platforms during implementation. We were certainly able to provide that. So, we were eventually awarded the business and the project has been extremely successful.”
The approach GK takes with its customers during these projects highlights just how much out-of-the-box capability its solution has. GK’s team spent a lot of time with Virginia ABC. The organisation examined its business requirements and using a consultative approach to show how its software could be configured. This was so it could meet the end-state business requirements and take advantage of best-of-breed capabilities that exist within GK’s platform.
“Rather than going there and trying to do a lot of customisation, we wanted to help them take advantage of the software as it exists,” Francescangeli adds. There were also other areas where GK was able to provide a lot of value and expertise to Virginia ABC. These include payment processing and its partner ecosystem. Virginia ABC was previously using a payment provider with limited capabilities, but GK was able to step in and expand the technology set. “We gave them more hardware choices, expanding what they could do with their in-store devices.”
Virginia ABC also needed more advanced reporting and analytics within its environment. So, GK introduced a solution called Advanced Central Electronic Journal and Reporting. Francescangeli continues: “It saved them a tremendous amount of effort, and gave them a lot of flexibility. We implemented that very quickly and they gained business value from it immediately.”
An evolving partnership
GK Software and Virginia ABC worked on initial deployment for the first 12 months of the project, and GK has continued to supply its services ever since. Each year after the first, Virginia ABC has expressed interest in something else GK offers. As a result, the relationship has remained close and Virginia ABC continues to expand the partnership.
“Paul and his team have been champions of ours and we’re champions of theirs as well,” Francescangeli states. “Due to the relationship we have with Virginia ABC, we have been able to secure business from other retailers in the same space because they have confidence that we know how to handle the market.”
“GK checks a lot of boxes retailers are looking for,” Bill Miller, North American VP of Sales at GK adds. “We’re in this inflection point where we offer modern technology that also has a lot of functionality out of the box, and that’s what people want. That’s what Virginia ABC wanted, and that’s what we supplied.”
Our cover story this month focuses on the work of Arianne Gallagher-Welcher. As the Executive Director for the USDA Digital…
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Our cover story this month focuses on the work of Arianne Gallagher-Welcher. As the Executive Director for the USDA Digital Service, in the Office of the OCIO, her team’s mission is to drive a tech transformation at the USDA. The goal is to better serve the American people across all of its 50 states.
Welcome to the latest issue of Interface magazine!
Welcome to a new year of possibility where technology meets business at the interface of change…
“We knew that in order for us to deliver what we needed for our stakeholders, we needed to be flexible – and that has trickled down from our senior leaders.” Arianne Gallagher-Welcher, Executive Director for the USDA Digital Service reveals the strategic plan’s first goal. Above all, the aim is to deliver customer-centric IT so farmers, producers, and families can find dealing with USDA as easy as using an ATM.
BCX: Delivering insights & intelligence across the Data & AI value chain
We also sat down with Stefan Steffen,Executive Leader for Data Insights & Intelligence at BCX. He revealed how BCX is leveraging AI to strategically transform businesses and drive their growth. “Our commitment to leveraging data and AI to drive innovation harnesses the power of technology to unlock new opportunities, drive efficiency, and enhance competitiveness for our clients.”
Momentum Multiply: A culture-driven digital transformation for wellness
Multiply Inspire & Engage is a new offering from leading South African insurance provider Momentum Health Solutions. Furthermore, it is the first digital wellness rewards program in South Africa to balance mental health and physical health in pursuing holistic wellness. CIO, Ndibulele Mqoboli, discusses re-platforming, cloud migrations, and building a culture of ownership, responsibility, and continuous improvement.
Clark County: Creating collaboration for the benefit of residents
Navigating the world of local government can be a minefield of red tape, both for citizens and those working within it. Al Pitts, Deputy CIO of Clark County, talks to us about the organisation’s IT transformation. He explains why collaboration is key to support residents. “We have found our new Clark County – ‘Together for Better’ – is a great way to collaborate on new solutions.”
Also in this issue, we hear from Alibaba’s European GM Jijay Shen on why digitalisation can be a driving force for SMEs. We learn how businesses can get cybersecurity right with KnowBe4 and analyse the rise of ‘The Mobility Society’.
For our first cover story of 2024 we meet with Lloyds Banking Group’s CIO for Consumer Relationships & Mass Affluent,…
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For our first cover story of 2024 we meet with Lloyds Banking Group’s CIO for Consumer Relationships & Mass Affluent, Martyn Atkinson, to learn how an ambitious growth agenda, combined with a people-centred culture, is driving change for customers and colleagues across the Group.
Welcome to the latest issue of Interface magazine!
Welcome to a new year of possibility where technology meets business at the interface of change…
Lloyds Banking Group: A technology & business strategy
“We’ve made significant strides in transforming our business for the future,” explains Martyn Atkinson, CIO for Consumer Relationships & Mass Affluent at Lloyds Banking Group. “I’m really proud of what the team have achieved. There’s loads more to go after. It’s a really exciting time as we become a modern, progressive, tech-enabled business. We’ve aimed to maintain pace and an agile mindset. We want to get products and services out to our customers and colleagues. We’ll test and learn to see if what we’re doing is actually making a meaningful difference.”
AFRICOM: Organisational resilience through cybersecurity
We also speak with U.S. Africa Command’s (AFRICOM) CISO Ryan Larsen on developing the right culture to build cyber awareness. He is committed to driving secure and continued success for the Department of Defence. “I often think of every day working in cyberspace a lot like counterinsurgency warfare and my time in Afghanistan. You had to be on top of your game every minute of every day. The adversary only needs to get lucky one time to find you with that IED.”
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ALIC: Creating synergy to scale at speed with Lolli
Since 2009 the Australian Lending & Investment Centre (ALIC) has been matching Australians with loans that help build their wealth. It has delivered over $8.3bn in loans to more than 22,000 leading Australian investors and businesses. Managing Director Damian Brander talks ethical lending and the challenges of a shifting financial landscape. ALIC has also built Lolli – a broker enhancement platform built by brokers, for brokers.
Sime Darby Motors: Driving digital, cultural, and business transformation together
Sime Darby Berhad is one of the oldest and most successful multinational companies in Malaysia. It has a twin focus on the Industrial and Motors sectors. The company employs more than 24,000 people, operating across 17 countries and territories. Sime Darby Motors’ Chief Digital & Information Officer Tuan Jean Tee shares how he makes sure digital, cultural, and process transformation go hand in hand throughout one of APAC’s largest automotive multinationals.
Also in this issue, we hear from Microsoft on the art of sustainable supply chain transformation, Tecnotree map the key trends set to impact the telecoms industry in 2024 and our panel of experts chart the big Fintech predictions for the year ahead.
Our final cover story for 2023 explores how Deputy CIO May Cheng is accelerating a digital customer and product-centric approach…
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Our final cover story for 2023 explores how Deputy CIO May Cheng is accelerating a digital customer and product-centric approach to IT management for the International Trade Administration (ITA).
Welcome to the latest issueof Interface magazine!
Interface showcases leaders at the forefront of innovation with digital technologies transforming myriad industries.
We connect once more with the tech trailblazers at the International Trade Administration. Deputy CIO May Cheng and her team areaccelerating adoption of ITA’s customer and product-centric approach to IT management. In addition, their focus is on Agile, DevSecOps, Value Proposition, and Human Centred Design. “In 2023, we launched 13 products, three MVPs and saw enhancements operationalised. Moreover, the digital model has enabled a partnership between business and IT. The result is clearer lines of shared responsibility, transparency in resources, and a continuous learning culture across the agency.”
Businessman touching data analytics process system with KPI financial charts, dashboard of stock and marketing on virtual interface. With American flag in background.
Royal Papworth Hospital NHS Trust: Digitally transforming patient care
The Royal Papworth Hospital NHS Foundation Trustis centred on bringing tomorrow’s treatments to today’s patients with a clear mission to provide excellent, specialist care to patients suffering from heart and lung disease. We hear from Andrew Raynes who took up his role as CIO in 2017. He is overseeing a digital transformation program bringing value to staff and patients. “Using the global language of interoperability… we’ll see greater efficiency in terms of use of technology and sweating our assets. Furthermore, exploiting the benefits to support seamless care by allowing standards to do the heavy lifting.”
Toronto Community Housing: Supporting tenants with tech
Toronto Community Housing houses tenants in 106 of Toronto’s 158 neighbourhoods. It ensures over 43,000 low and moderate-income families are supported in their continuously managed homes. Luisa Andrews, VP Information Technology Services tells us it’s the best role she’s had in her career. “It’s the most challenging, and where I’ve seen the most progress in a short amount of time. I’m proud of my team and what we’ve accomplished in five years. We, and our partners, have enabled the corporation, through technology, to do what it needs to do for our tenants.”
Marshfield Clinic Health System:
Marshfield Clinic Health System provides care at over 50 locations across the US state of Wisconsin. Chief Data & Analytics Officer Mitchell Kwiatkowski explains its tech mantra to us: “We’re trying to toe that line while examining new technologies as they come out. We’re aiming to understand what they are, how they can help, and implementing things that are mature enough and show promise. I don’t think healthcare is necessarily risk-averse; it’s a highly regulated area that doesn’t always have deep pockets for investment. However, it’s people’s health at stake, so we have to be careful…”
Also in this issue, we get the lowdown on the tech trends for 2024 from Hitachi Vantara innovation guru Bjorn Andersson. We also hear from the WatchGuard Threat Lab research team with their cybersecurity predictions for the year ahead.
Janina Bauer, Global Head of Sustainability at Celonis provides some expert insight into the reality of implementing sustainable practices…
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Janina Bauer, Global Head of Sustainability at Celonis provides some expert insight into the reality of implementing sustainable practices…
Please tell us more about yourself and your role at Celonis.
I have been involved in sustainability long before it became mainstream. I did a Master’s in Business Administration with a focus on sustainability, and also worked at the U.N. analysing and researching the implementation of its Sustainable Development Goals. I bring that passion for exploring the big ideas around technology and sustainability to my role at Celonis, where I am Global Head of Sustainability. I took over Celonis’ sustainability programme in 2020, overseeing both our progress internally, and our external work where we help our customers using the Celonis Platform, enabling them to operationalise sustainability in all of their business processes.
Why is it essential businesses embed sustainability into business objectives, strategy and decision-making?
Going forward, there is no longer a separation between a business’ bottom line and their sustainability ‘green line’. To be a high-performing organisation in today’s business world, and tomorrow’s, companies need to be both profitable and sustainable. Future-proofed organisations are on top of both aspects, and ensure that sustainability and profitability are embedded into every single decision. There’s no contradiction between being a profitable business and not harming the environment you operate in. In fact, actions that boost sustainability also boost profitability by cutting waste. A key thing to remember is that everyone has a part to play in an organisation’s sustainability journey. It’s not something simply for people with ‘sustainability’ in their job title, but for leaders and workers in every part of the business.
Why are organisations struggling to implement their sustainability goals?
There are several barriers holding businesses back, including the inaccurate perception that sustainability is simply a cost, whereas it often goes hand in hand with profitability. Organisations which are struggling to implement their sustainability goals are often dealing with a people problem. If sustainability is seen as being the business of sustainability specialists only, rather than being integral to an organisation’s DNA, it can be hard to secure alignment and buy-in across the whole business.
Education, in the form of courses and clear communication within an organisation, can help to address fears and reluctance around sustainability, and the perceived cost of embracing change. The other key issue is siloed, unconnected systems which make it harder for business leaders to truly understand their carbon footprint. Many organisations have more than 300 IT systems, and the average business process runs across 10 different systems, with data buried in separate systems from transactional data in ERP (Enterprise Resource Planning) software to Excel Spreadsheets. Process mining can help business leaders unravel this and identify where efficiencies can be made. This in turn helps to support sustainability objectives and reduce costs and waste.
Should companies should place a greater emphasis on reducing Scope 3 emissions?
When it comes to sustainability objectives, do you think companies should place a greater emphasis on reducing Scope 3 emissions?
For most organisations, Scope 3 emissions, which includes those from all of their downstream and upstream activities, are the Holy Grail when it comes to having an impact on emissions. That’s where the biggest carbon footprint lies and that’s where the most exciting opportunities for rapid progress are.
The data required for a real-time view of Scope 3 emissions is already at businesses’ fingertips – it’s just that it’s buried inside siloed carbon-accounting tools and other software. The first step is to extract this data using process intelligence technologies, and then organisations can make real progress.
How important is technology in helping companies make sustainability gains?
The first step towards having genuine impact in sustainability is to measure the environmental impact of the organisation’s current operations. This is where technology plays a crucial role. Technologies such as process intelligence enable business leaders to make informed decisions around sustainability, working like an ‘X-Ray’ on existing data and highlighting value opportunities, as well as allowing business leaders to understand the full journey of the goods they sell, and all the emissions associated with this. This data allows IT leaders to measure and drive sustainability, comparing performance against best-practice models and collaborating with partners and suppliers to reduce emissions.
What actions do you hope to see from COP28 that will result in tangible outcomes for the corporate world in 2024?
COP28 has offered a unique opportunity to embrace real and meaningful action to combat climate change, as well as a crucial dialogue between politicians, business leaders and decision makers. What I hope to see is more organisations embracing technology and innovation to make strides towards real sustainable change, with a particular focus on decarbonising supply chains and different industry sectors. Many pledges have been made at COP28 with good intentions, but now it falls on leaders to back up those pledges with real, measurable outcomes, using technology to turn their words into actions. Of course, process mining is not a ‘silver bullet’ which can tackle climate change on its own, but it does offer a crucial way for business leaders to find hidden value opportunities and make real advancements in sustainability.
A passionate advocate for diversity, inclusion and equity of opportunity, Executive GM Ana Marinkovic leadsa team of 1,600+ small business experts. They lend over $1.2bn a month to Australian small businesses. National Australia Bank (NAB) plays a major role in propelling entrepreneurship across the country. Delivering better outcomes for small business owners sits at the very heart of NAB’s strategy. “Our scale and connectivity help us to tackle some of the biggest challenges facing our business and the communities we operate in,” says Ana.
TUI: Making travel plans mobile
The mobile side of TUI has never been more vital. TUI’s mobile apps were officially launched in 2013 and began as something of a proof of concept. For the entire international industry, moving from web to mobile devices was a huge shift. The initial set of apps were very skeletal and only integrated for UK and Nordic customers.
One of this year’s goals is to accelerate the native journey to make all the customer journeys native. This will further improving the customer experience. After a recent UI refresh, the app look and feel is fresh and sleek, and has plenty of exciting features for customers to enjoy. “Just in the last couple of months we’ve introduced an integration with OpenAI for a travel planner that helps you choose excursions,” Donia adds. “Seeing it grow over the years is so exciting.”
TARA Energy Services: tech fuelling growth
“Continuous improvement is woven into the fabric of the culture at TARA Energy Services,” says its proud Director of IT, Paul Parzen. “Every day, we face new challenges, both operationally in the field and strategically in the boardroom. We must make sure the organisation’s IT strategy for data management, core infrastructure, network architecture, and security is ready to meet them.”
Link Group: Shaking up UK’s pension market via digitalisation
“Some people might say, ‘wow, a pension. That sounds a little boring.’ But at the end of the day, what we do is help people retire in the best way possible and that’s a pretty good place to be.”
Those are the words of Dee McGrath, CEO of Link Group’s Retirement Solutions since May 2019. The company is a global, digitally-enabled business connecting millions of people with their pension assets – safely, securely and responsibly.
Evara Health: Technology delivering care for all
Evara Health’s mission statement is to help people become healthy and live healthy lives, and that means all people. A lot of health organisations don’t serve everybody and their treatments aren’t available under many types of insurance. However, Evara Heath doesn’t turn anybody away. It supports the underserved and the uninsured, and patients are treated regardless of whether they can afford it. Around 25% of patients have no insurance at all, and over half are covered by Medicaid, which isn’t accepted by everyone.
A passionate advocate for diversity, inclusion and equity of opportunity, Executive GM Ana Marinkovic leadsa team of 1,600+ small business experts. They lend over $1.2bn a month to Australian small businesses. National Australia Bank (NAB) plays a major role in propelling entrepreneurship across the country. Delivering better outcomes for small business owners sits at the very heart of NAB’s strategy. “Our scale and connectivity help us to tackle some of the biggest challenges facing our business and the communities we operate in,” says Ana.
TUI: Making travel plans mobile
The mobile side of TUI has never been more vital. TUI’s mobile apps were officially launched in 2013 and began as something of a proof of concept. For the entire international industry, moving from web to mobile devices was a huge shift. The initial set of apps were very skeletal and only integrated for UK and Nordic customers.
One of this year’s goals is to accelerate the native journey to make all the customer journeys native. This will further improving the customer experience. After a recent UI refresh, the app look and feel is fresh and sleek, and has plenty of exciting features for customers to enjoy. “Just in the last couple of months we’ve introduced an integration with OpenAI for a travel planner that helps you choose excursions,” Donia adds. “Seeing it grow over the years is so exciting.”
TARA Energy Services: tech fuelling growth
“Continuous improvement is woven into the fabric of the culture at TARA Energy Services,” says its proud Director of IT, Paul Parzen. “Every day, we face new challenges, both operationally in the field and strategically in the boardroom. We must make sure the organisation’s IT strategy for data management, core infrastructure, network architecture, and security is ready to meet them.”
Link Group: Shaking up UK’s pension market via digitalisation
“Some people might say, ‘wow, a pension. That sounds a little boring.’ But at the end of the day, what we do is help people retire in the best way possible and that’s a pretty good place to be.”
Those are the words of Dee McGrath, CEO of Link Group’s Retirement Solutions since May 2019. The company is a global, digitally-enabled business connecting millions of people with their pension assets – safely, securely and responsibly.
Evara Health: Technology delivering care for all
Evara Health’s mission statement is to help people become healthy and live healthy lives, and that means all people. A lot of health organisations don’t serve everybody and their treatments aren’t available under many types of insurance. However, Evara Heath doesn’t turn anybody away. It supports the underserved and the uninsured, and patients are treated regardless of whether they can afford it. Around 25% of patients have no insurance at all, and over half are covered by Medicaid, which isn’t accepted by everyone.
Nigel Greatorex, Global Industry Manager at ABB, on how digital technologies can support decarbonisation and net zero goals
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Nigel Greatorex is the Global Industry Manager for Carbon Capture and Storage (CCS) at ABB Energy Industries. He explains how digital technologies can play a critical role in the transition to a low carbon world by enabling global emissions reductions. Furthermore, he highlights the role of CCS and how challenges can be overcome through digitalisation.
Meeting our global decarbonisation goals is arguably the most pressing challenge facing humanity. Moreover, solving this requires concerted global action. However, there is no silver bullet to the global warming crisis. The solution requires a mix of investment, legislation and, importantly, innovative digital technologies.
Decarbonisation digital technologies
It’s widely recognised decarbonisation is essential to achieving net zero emissions by 2050. Decarbonisation technology is becoming an increasingly important, rapidly growing market. It is especially relevant for heavy industries – such as chemicals, cement and steel. These account for 70 percent of industrial CO2 emissions; equal to approximately six billion tons annually.
CCS digital technologies are increasingly seen as key to helping industries decarbonise their operations. Reaching our net zero targets requires industry uptake of CCS to grow 120-fold by 2050, according to analysis from McKinsey & Company. Indeed, if successful, it could be responsible for reducing CO2 emissions from the industrial sector by 45 percent.
A Digital Twin solution
ABB and Pace CCS joined forces to deliver a digital twin solution. It reduces the cost of integrating CCS into new and existing industrial operations. Simulating the design stage and test scenarios to deliver proof of concept gives customers peace of mind. Indeed, system designs need to be fit for purpose. Also, it demonstrates the smooth transition into CCS operations. Additionally, the digital twin models the full value chain of a CCS system.
Cybersecurity leader Shinesa Cambric on Microsoft’s innovation journey to identify, detect, protect, and respond to emerging threats against identity and access
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This month’s cover story highlights a cybersecurity program protecting billions of users.
Welcome to the latest issueof Interface magazine!
Interface showcases leaders at the forefront of innovation with digital technologies transforming myriad industries.
Shinesa Cambric is on a mission to drive innovation for cybersecurity at Microsoft. Moreover, by embracing diversity and opening all channels towards collaboration her team tackles anti-abuse and delivers fraud-defence. Continuous Improvement doesn’t just play into her role, it defines it…
“In the fraud and abuse space, attackers are constantly trying to identify ways to look like a legitimate user,” warns Shinesa. “And this means my team, and our partners, have to continuously adapt. We identify new patterns and behaviours to detect fraudsters. At the same time, we must do it in such a way we don’t impact our truly ‘good’ and legitimate users. Microsoft is a global consumer business and any time you add friction or an unpleasant experience for a consumer, you risk losing them, their business and potentially their trust. My team’s work sits on the very edge of the account sign up and sign in process. We are essentially the first touch within the customer funnel for Microsoft – a multi-billion dollar company.”
ABB: Digital Technolgies contributing towards Net Zero
Nigel Greatorex, Global Industry Manager for Carbon Capture and Storage (CCS) at ABB Energy Industries, explains how digital technologies can play a critical role in the transition to a low carbon world. He highlights the role of CCS in enabling global emissions reductions and how challenges can be overcome through digitalisation…
“It is widely recognised decarbonisation is essential to achieving net zero emissions by 2050. Therefore, it’s not surprising that emerging decarbonisation technology is becoming an increasingly important, and rapidly growing market.”
CSI: How can your IT estate improve its sustainability?
Andy Dunn, Chief Revenue Officer at IT solutions specialist CSI, reveals how digital technologies can contribute to ESG obligations: “Sustainability is a now seen as a strategic business imperative, so much so that 74% of companies consider Environmental, Social and Governance (ESG) factors to be very important to the value of their company. Additionally, we know almost three in four organisations have set a net zero goal. With an average target date of 2044, 50% of organisations are seeking more energy efficient products and services.”
https://www.youtube.com/watch?v=tsDaZiSO1ho
“Optimising energy use and consolidating servers and storage infrastructure form a strong basis for shaping a more environmentally friendly and efficient IT estate. It no longer needs to be the Achilles Heel of an ESG policy. “
Mia Platform: Sustainable Cloud Computing
Davide Bianchi, Senior Technical Lead at Mia Platform, explores the silver lining of sustainable cloud computing. He reveals how it can help us reduce our digital carbon thumbprint with collaboration, efficient use of applications, containerisation of apps, microservices and green partnerships.
“We’re already on an important technological path toward ubiquitous cloud computing. Correspondingly, this brings incredible long-term benefits too. These include greater scalability, improved data storage, and quicker application deployment, to name a few.”
Also in this issue, we hear from Doug Laney, Innovation Fellow at West Monroe and author of Infonomics and Data Juice. Also, we learn how companies can measure, manage and monetise to realise the potential of their data. And, Deputy CIO Melvin Brown discusses the people-centric approach to IT supporting America’s civil service at The Office of Personnel Management (OPM).
Doug Laney is Innovation Fellow at West Monroe and a leading Data & Analytics strategist. We caught up with the author of Infonomics and Data Juice to talk tech and how companies can measure, manage and monetise to realise the potential of their data
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Our cover story explores the rise of data and information as an asset.
Welcome to the latest issueof Interface magazine!
Interface showcases leadersaiming to take advantage of data, particularly in a new world of AI technologies where it is the fuel…
How to monetise, manage and measure data as an asset
Our cover star is pretty big in the world of analytics… We meet the guy who defined Big Data. Doug Laney is Innovation Fellow at West Monroe and a leading Data & Analytics strategist. We caught up with the author of Infonomics and Data Juice to talk tech and learn how companies can measure, manage and monetise to realise the potential of their information. In his first book Laney advised companies to stop being fixated on hindsight-oriented analytics. “It doesn’t actually move the needle on the business. In the stories I’ve compiled over the last decade, 98% have more to do with organisations using data to diagnose, predict, prescribe or automate something. It’s not about asking questions about what happened in the past.”
Canvas Worldwide: A data-driven media business
Continuing this month’s data theme, we also spoke with Alisa Ben, SVP, Head of Analytics at full-service media agency Canvas Worldwide. Data has transformed the organisation, and what its clients do. “We look holistically at the client’s business and sometimes the tools we have might be right for them, sometimes not. It’s more about helping our clients achieve their business outcomes.”
TUI Musement: from digital transformation to digital pioneer
At travel giant TUI, handling data effectively is paramount when communicating consistently and meaningfully with up to 25 million customers annually. David Garcia, CIO for TUI Musement, talks about the tech evolution driving the travel giant’s provision of experiences, transfers and tours. It’s a big part of its operational shift from local to global. “As a CIO, I’ve always been interested in how the tech innovations we drive can support the business and add value.”
Hiscox: making cybersecurity more accessible
Liz Banbury, CISO at Hiscox and president of (ISC)² London Chapter, talks to us about how cybersecurity can become a more accessible, realistic career path for almost anybody. “When I was at school, topics like computer science didn’t even exist,” Banbury explains. “In one of my first jobs, over in Hong Kong, we were still using a typewriter! A lot has changed. My key point here is that there’s a lot of cybersecurity professionals who are really good at their job. They are inspiring, and have come from all walks of life. Crucially, they don’t have a maths, computer science, or technological background at all. But they still make great cybersecurity professionals.
Portland Community College: Risk vs Speed in Cybersecurity
Reet Kaur, former Chief Information Security Officer at Portland Community College, discusses the organisation’s transition to the cloud amid a digital transformation journey. “I don’t want to work with people who just say yes all the time. I want my ideas challenged to help forge the excellence in the security programmes I help build.”
DBHDS: Cybersecurity in healthcare
The Virginia Department of Behavioral Health and Developmental Services (DBHDS) exists to create ‘a life of possibilities for all Virginians’ and transform behavioural health. Its focus is on supporting people across the entire commonwealth. It helps them get the support they need in order to take wellness and recovery into their own hands. In an area like healthcare, sensitive information is all over the place, meaning cybersecurity is a priority – and this is where Glendon Schmitz, CISO at DBHDS, comes in. “The security team exists to help the wider organisation achieve its objectives with data. We’re there to protect the business, not the other way around.”
Also in this issue, we schedule the can’t miss tech events and get the lowdown on IoT security from the Mobile Ecosystem Forum.
Melvin Brown, Deputy CIO at the Office of Personnel Management, explains the organisation’s ‘sprint to the cloud’ and its determination to modernise at every level.
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Our cover story highlights the Office of Personnel Management’s ‘sprint to the cloud’ with technology.
Welcome to the latest issueof Interface magazine!
Interface hears from leaders who champion a people-first approach driving successful technology transformations.
Culture Modernisation at the Office of Personnel Management
The Office of Personnel Management (OPM) is a government entity which manages America’s civil service. This month’s cover story explores how an organisation that prioritises people is taking a human approach to IT. Deputy CIO Melvin Brown oversees a portfolio of $500m in programs and a growing workforce of around 300 federal employees and contractors. OPM is undergoing a major cloud transformation… “We want to be cloud-first and cloud-smart as we move forward,” he explains. “So, we created a two-year sprint to the cloud plan where we take all our major applications and move them to the cloud in order to take advantage of all the benefits that brings, from both a security and a utility perspective.”
International Trade Administration: A strategic vision for technology
The International Trade Administration (ITA) strengthens the competitiveness of U.S. industry, promotes trade and investment, and ensures fair trade through the enforcement of trade laws and agreements. We hear from its CIO Gerald Caron who is passionate about involving all stakeholders in ITA’s transformation… “We’re introducing different ways of thinking to drive innovation at the International Trade Administration (ITA). What is the art of the possible? We’re looking to explore possibilities with technology across our business units and build simple foundations for the development of more complex approaches.”
Irwin Mitchell: Technology with a human touch
Also espousing the importance of a people-centric approach, Graham Thomson, Chief Information Security Officer at Irwin Mitchell, discusses his firm’s transformative legal solutions. “We’re far more than just a law firm,” he says. “I think what sets us apart is that we’re very people focused and an organisation that genuinely cares about not only our customers but our people too. People are your biggest asset, and you have to look after them.”
State of Vermont: Using AI for good
We spoke with Shawn Nailor, Secretary and CIO at State of Vermont, about IT modernisation, tackling cybersecurity state-wide, and how AI is being used for the good of Vermonters. “We’ve got to be practitioners in order to give good guidance on how to use advanced technology and where… We want to establish a practice by which we can lead by example and show good applications or AI tools to advance services and the delivery of products.”
Also in this issue, we round up the must attend tech events; get game-changing AI, Metaverse and ‘moonshot’ insights from Lenovo, and learn why people are at the heart of the decision-making process at energy company newcleo.
Amit Thawani, CIO for Consumer Data & Engagement Platforms at Wells Fargo, on the journey towards becoming a customer-centric company
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This month’s cover story reveals how a customer-centric approach to technology is helping Wells Fargo deliver stable, secure, scalable, and innovative services.
Welcome to the latest issueof Interface magazine!
It’s our biggest issue yet! The common theme this month is the focus on the creation of customer-centric technologies that offer reliable, secure and helpful user journeys from travel and banking to health and business.
Interface dives deep for insights on understanding, planning, implementing and communicating change across industries.
Amit Thawani, Chief Information Officer (CIO) for Consumer Data & Engagement Platforms (CDEP) on the technology journey at Wells Fargo: “All tech employees at Wells Fargo are tasked with working towards delivering stable, secure, scalable, and innovative services at speed that delight and satisfy our customers while unleashing the skills potential of our employees.”
TUI: Developing a technology ecosystem
Kristof Caekebeke, CIO for Product & Engagement, is a member of the leadership team that is driving the transformation of the TUI technical ecosystem which has seen Master Domain Owners taking different blocks of the ecosystem under their control to roll out across the organisation.
TUI Group
Responsible for product and engagement, Caekebeke’s focus is on building products out of the thousands of hotels, flights, experiences and cruises TUI is offering. “I’m responsible for every contact point between the customer and TUI. The websites, the mobile apps, the retail systems – any contact point we have between the customer and TUI. It’s a large team of 1,100 tech people.
A digital bank transformation journey with Banco PAN
“Until 2018 Banco PAN was very much an analogue company reliant on legacy paper processes,” recalls Leandro Marçal. Joining the bank in December 2020, to become Technology & Operations Director (CIO/COO), Marçal was tasked with accelerating a digital transformation journey.
“Banco PAN invested in innovation before I arrived,” says Marçal. “It is my team’s job to formalise the path towards becoming a digital bank. Our legacy operation was digitalising. It was an opportunity to improve the customer experience with our checking account and credit card systems.”
Pohlad Companies: The power of people
A pillar of the community in Minneapolis, Pohlad Companies is well known to Minnesotans for its influence, its charity work, and the opportunities it has created for people since the 1950s.
Alongside significant commercial real estate investments, Pohlad Companies owns a custom engineering and robotics company, a group of automotive dealerships specialising in luxury vehicles, a film production studio, and many more businesses. Famously, the Pohlad family also owns the Minnesota Twins, a Major League Baseball team.
This variety is part of what makes Rachel Lockett’s job so exciting. She’s Pohlad Companies’ CIO and has spent a decade in her current role. Lockett began her career as a programmer over 25 years ago and quickly moved into IT leadership management.
Coalfire: Embracing change in cybersecurity
If you wait for something to happen, then it’s often too late. The art of having a finger on the pulse is an essential ingredient to success. Failure to manage change and implement cybersecurity protocols could mean leaving an organisation vulnerable to hackers.
Sreeveni Kancharla, Coalfire’s first Chief Information Officer, is leading the company’s digital transformation with unwavering determination. As a cybersecurity advisor, Coalfire assists private and public sector organisations in managing threats, closing gaps, and mitigating risks. Kancharla ensures that her team stays up-to-date with the latest technologies to guard against zero-day attacks.
Uni of Kansas Health: Cybersecurity at the heart
Speed versus safety. The two topics are intrinsically linked and vital in their own individual way. But can you have both in healthcare when the risks are so great? Ultimately, there is no higher stake than saving people’s lives – it goes above everything and is why cybersecurity is so vital.
Protecting the healthcare system
“There’s nothing more important to me than patient care,” affirms Michael Meis, Associate Chief Information Security Officer at The University of Kansas Health System. “It is one of the highest callings you can imagine, to be able to help people. While the cybersecurity team and me, individually, do not directly care for patients, we enable a lot of that patient care to continue and to be able to achieve some of the goals that the health system has set to provide that healing, research, and innovation within the healthcare space.”
Also in this issue, we ask ChatGPT what the future holds for AI and learn from Zoom how businesses can leverage analytics for insights from their hybrid events.
Standard Bank CIO Bessy Mahopo on the challenges of operating in a fractured market and how the company overcomes them
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This month’s cover story highlights how technology is helping Standard Bank overcome the challenges of a fractured market to both drive business growth and improve services for customers.
Welcome to the latest issueof Interface magazine!
“Time may change me, but I can’t trace time…” sang David Bowie. Changes can be challenging to manage with the path to positive disruption not always a smooth change management journey.
Interface dives deep for insights on understanding, planning, implementing and communicating change across industries.
Standard Bank CIO (CIB – Transactional Banking) Bessy Mahopo explains how one of South Africa’s largest banks is using its own digital transformation successes as a template to support the country’s ongoing technological evolution by overhauling IT from the inside out. “I believe that once we start moving the curve to fifth and sixth generation technology, we’re going to become even more of a value-producer.”
The art of change management with SAP
Maria Villar, Head of Enterprise Data Strategy and Transformation at SAP, talks about the importance of driving change in the technology space and helping businesses thrive with data from the perspective of one of the world’s leading enterprise resource planning software vendors. “My job is about finding out what a good data strategy looks like and continuing to spend time with customers to look ahead…”
Talent transformation journeys with TUI
We caught up with Cerstin Lang, Director for HR Group IT at TUI. She reveals how it’s global For:ward program is driving digital transformation as the travel giant works with training partner Udacity to upskill IT talent. “Our IT goals are focused on developing a structure that supports new ways of working with the right balance to innovate and grow in the future.”
How TransUnion is enabling consumer trust
Alejandro Reskala, CIO Canada, LATAM, Caribbean at TransUnion, about technology transformation at a leading consumer credit reporting agency, its dedication to people, and how it makes trust possible. “TransUnion has always blazed a trail to use technology and data to generate insights that help support financial inclusion.”
Also in this issue, we ask what the birth of ChatGPT means for businesses leveraging tech and learn from Rivery why organisations need to rethink their data strategy with robust operational analytics.
How Minted is leveraging digital technology to make investment in precious metals, accessible, affordable and simple
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Shahid Munir, co-founder of Minted, discusses how his firm is competing with larger banks for a spot at the top table of investment in fintech.
Few industries have boomed like the fintech space over the past few years. With a plethora of new technology at consumer fingertips like never before, banks are being properly challenged by upcoming startups offering an alternative solution. Among these is Minted, aiming to make the buying, selling, transferring and delivery of physical precious metals simple through flexible monthly plans and one-time purchases. The company was founded in 2018 by three close friends – Shahid Munir, Hamzah Almasyabi and Haroon Siddiq – with a shared passion for entrepreneurship, technology and the opportunities the financial industry presented. Their combined drive led to the creation of Minted.
Shahir Munir, Co-Founder, Minted
The rise of Minted
Munir, co-founder of Minted, admits the journey has been a “rollercoaster” since the trio decided to launch their venture. “It’s certainly been exciting,” he explains. “It’s been a great learning curve and was a case of taking an industry where so many people were so used to doing it one way and offering something new. This has been challenging because we have a great product, but no one understood it. We’ve had to go out and educate people first in what has been a journey of growth, but it’s a constant journey.”
A decade ago, financial technology was considered by many as ring-fenced by bigger banks. But Munir stresses he has tried to change that narrative and offer competition which provides tremendous value. “Previously, a bank was the only way you could provide financial products,” he says. “Technology has allowed more innovative and creative solutions to launch and test the bigger banks and what they became bad at which was the customer experience. Now you see bigger banks adopt a lot of the technology and some of the practices used by challenger banks which can only be a good thing. Being in London has also helped because it is one of the leading hubs for fintechs and really supports the financial technology industry.”
Armed with different skillsets, the three co-founders complement each other with a diverse range of experience. With Almasyabi bringing an operations background and Siddiq bringing business strategy, Munir completes the line-up with finance and technology know-how. “I think it’s what sets us apart and makes us different,” he says. “Our backgrounds mean we’re not tunnel visioned and can see clearly when things aren’t working. We have a great thinktank within the business which helps us come up with ideas.”
Making precious metals accessible, affordable and simple
“I recall seeing a meme about how the price of a Freddo chocolate had changed over the years, no longer being its trademark 10p, it was now 200% more expensive and also smaller in size. This led me down rabbit-hole of trying to understand why most items go up in price as years pass and rarely come back down again. I became fascinated with how the government increases the money supply and the concept of inflation – my money buys me less in the future than it does today.
“I met with the other two founders that same night and the thoughts extended from my mind into an intense conversation about quantitative easing, Brexit, cost of living – snacks were being consumed faster than the rate of government borrowing. Where could we park our money, what was better than money? That was when the penny-dropped (pardon the pun). Hamzah proclaimed: ‘What about gold, guys?’”
Digital disruption
Through Minted, customers will have full legal ownership over their gold and can also request to have their gold delivered to a verified address. The gold and silver are stored in a grade 10 vault in the UK with the highest level of security possible. The products are fully insured by Lloyds of London at the current value while in vaulted storage as well as when being transported.
As a digital disrupter, one of the biggest challenges Minted continues to face is a lack of understanding. Customer assurance is an important priority, and the organisation has established several initiatives to gain trust. Minted is registered and regulated by the Financial Conduct Authority (FCA) which means the firm operates to the highest financial standards and guidelines as determined by the FCA. “I feel like we need to go that extra mile,” stresses Munir. “What I think we underestimated at first was the extent to which people needed to ask questions until we launched a live chat facility on the website. This function helps build our knowledge base and allows us to hold the customer’s hand throughout the process. We’ve also found success when we’ve attended face to face exhibition events and had one-on-one interactions. It’s been brilliant to see first-hand the customer perception and look at what we can do better to meet their needs.”
Munir says he has noticed a trend of people starting with a “flutter” to test the water and check out the process. “I think it’s important that people build their confidence and recognise the value in what we offer,” he explains. “Once this is done, we often see those same customers make larger transactions. We know our difference can be a challenge for some people to accept which is why education is such an important topic to us. We have to keep doing explainer videos, use social media and hold community sessions to be there for customers.”
Scaling up
Minted recently launched its own app which offers customers an even easier way to manage their gold and silver, as well as introducing a tool to partner with businesses called Minted Connect. Munir believes the move has helped showcase an advanced, modern way for people to own physical items. “I love the app as it just makes things so much easier for customers via the platform,” he explains. “It’s been fantastic, a one-stop solution that helps stores the precious metals for free and allows them to be delivered at any time. In a world where everything is so digitally enabled it is nice to offer something physical – people don’t even buy cars anymore. Hopefully via customer feedback we can make improvements to the app that will help us develop new features.”
Munir believes gold is increasingly being seen as an alternative for savings and affirms global pressures like the threat of inflation amid economic uncertainty has helped people to realise the full potential of Minted’s offering. “In the past if you wanted to save money, you simply open a saver account and start adding money but with gold it was often a little trickier,” he says. “But with Minted we’ve simplified the process and tried to make it as automated as possible. Gold is a great alternative which has stood the test of time.”
Looking ahead, Minted is showing no signs of slowing down and is expanding into different territories. Munir remains positive for the next few years and what comes next for his organisation. “We’re working towards expanding the team because I feel like we’re at the stage now where each of our departments needs its own team of people to run each department,” he explains. “We’re scaling up and branching into new markets such as Turkey, and focusing in on developing the business to business side too.”
“Disruption should drive digitalisation and cloud uptake rather than hindering it.”
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Sal Laher, Chief Digital & Information Officer at global enterprise software provider IFS, reveals how a single strategy for cloud and digitalisation helps businesses maximise the rewards of growth.
Digitalisation equals transformation
Digitalisation and the business transformation projects that enable it are again on the radar for many businesses, particularly given the current macro-economics and potential recession being predicted. According to recent data from Research and Markets, The Global Digital Transformation Market size is expected to reach $1,302.9bn by 2027, rising at a compound annual growth rate (CAGR) of 20.8% in the period 2021-2027.
This renewed focus on digitalisation is aligned to businesses accelerating cloud migration, including readily available SaaS solutions. The Flexera 2021 State of the Cloud Report finds 92% of enterprises have a multi-cloud strategy and 80% have a hybrid cloud strategy.
Sal Laher, Chief Digital & Information Officer, IFS
Both trends will go hand in hand as digitalisation and cloud migration continue to drive business efficiencies, process change and consumer service demands. Most organisations are aware of the potential rewards both business models can bring. This is because it is not the first time they are being talked about– this major transformational shift has already been in place for a decade. But some, wary of the disruptive impact of recent global events are holding back from implementing them. However, it is the wrong approach.
Disruption should drive digitalisation and cloud uptake rather than hindering it. Even in isolation, either moving to the cloud, or undertaking digitalisation, will enable faster decision-making, supported by greater compute power and more agile processes, generating faster output and enhancing customer service. Yet, to drive competitive edge, organisations need to combine cloud migration with business transformation and look to maximise those benefits. To do this, they must develop a single strategy covering both elements and move forward with a common approach.
Migrating to the cloud for business transformation
By digitalising, organisations have an opportunity to benefit from faster time to insight, enhanced business and customer connectivity, and operational efficiencies. It allows them to more easily collect and analyse data that they can later turn into actionable, revenue-generating insights.
Over time, they can go further and start to tap into the benefits of artificial intelligence, machine learning, big data analytics, and the Internet of Things (IoT). But it is the additional compute power and scalability of the cloud that helps them to maximise these benefits and fulfil the potential of digital technologies.
Cloud migration also includes adopting evergreen application (business process) solutions in the cloud with the many SaaS solutions that are available today. That’s why it is important that they adopt a single plan to migrate to the cloud and drive business transformation all in one. This tandem approach also avoids unnecessary customisation, making a business much more agile to change based on actionable data insights.
Adopting a single plan will, in itself, drive up efficiencies and drive down costs. But critically, the two must be linked to ensure that businesses maximise the benefits of the migration process.
It is cloud, after all, that helps businesses adapt to the new digital world, enabling them, for instance, to leverage out of the box business applications, digital analytics tools and low code platforms that deliver informed decision-making and reduce costs. But cloud doesn’t just maximise the benefits for businesses, it also accelerates them. Cloud has become the fulcrum of digital transformation, mainly due to its ability to enable innovation at scale and allow businesses that have digitalised to rapidly launch enterprise-ready products.
Without cloud, businesses will struggle to drive through timely updates to systems and processes. The costs of stakeholder management may ramp up. Moreover, moving to the cloud without doing it within the step-by-step structure of digital transformation risks mistakes being made, increasing the likelihood of data loss and security breaches through misconfigurations.
Optimising the benefits of digital transformation in the cloud
We have seen how important it is to adopt a single strategy for cloud migration and digitalisation and to execute them in tandem. But organisations also need to maximise the benefits of the combined approach. So how can they best do this?
First, they need to avoid procrastination and delay. The benefits of digitalisation and cloud migration working together are compelling – and senior leaders need to seize the initiative and kickstart the transformation. To get the ball rolling, they need to conduct a benchmarking exercise to better understand where their business stands in terms of its capabilities or gaps. This will help to decide where efforts and resources should be focused.
They then need to align their business processes with IT. That’s key as modern business models increasingly emphasise the digitalisation of processes.
Cloud computing and network security concept, 3d rendering,conceptual image.
They should begin by determining their goals and the systems, technologies, and processes currently in use to achieve them. Next, they need to brainstorm and document core business objectives before developing a cloud and digitalisation migration roadmap to guide their implementation. Measuring performance will also be crucial to optimising results. In choosing which metrics to analyse, organisations should concentrate on those that will most positively impact their bottom line or user experience.
Ensuring employees buy into the process of cloud-based digitalisation will also be key. Organisations should use cloud-based digitalisation as an opportunity to strengthen business processes and help employees switch to new ways of working which maximise the potential of the new technology.
Digital readiness
Given all this, it is vital businesses don’t delay on their journey to digital and the cloud. Unfortunately, CIOs often struggle to know where to start with a cloud and digital migration strategy.
Before they begin, they often look to put a complete strategy in place up front. The truth is that it is not necessary. Instead, they need to get going and prioritise what’s most important. Pick one area, settle on a use case, digitalise, and move it to the cloud, demonstrate results – and then repeat incrementally. That will enable the business to showcase value and create momentum. Over time also, this single coordinated approach, will allow it to tap into a wide range of cloud and digitalisation related benefits – and ultimately to maximise the rewards.
Ian Povey, CIO – Head of Payments Services & Technology, on the strategic transformation taking place at NatWest benefitting both the bank and its customers
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This month’s cover story reveals how innovation is at the core of change for payments processes at NatWest.
Welcome to the latest issueof Interface magazine!
Charles Darwin famously said: “It is not the strongest of the species that survives, nor the most intelligent; it is the one most adaptable to change.” Technology is helping us to evolve. And that evolution is being driven by innovation.
“It may be a cliché, but a transformation journey really has no end… If you fixate on a constant end state without ‘checking in’ you can, and likely will, fail in your objectives.” A wise outlook from a CIO with three decades of change management experience across banking’s payments panorama.
Ian Povey, CIO – Head of Payments Services & Technology, discusses the strategic transformation taking place at NatWest and how that journey of change and innovation is benefitting both the bank and its customers as it evolves to become a relationship bank for a digital world. “Our environment is always changing – we must be on the back of the ‘Change Dragon’ and steering/influencing as a leader and always learning from our teams for new ideas.”
Customer-Centric transformation at FedEx
We also check in with logistics leader FedEx… Custom Critical CIO Cheryl Bevelle-Orange reveals a “technology-forward yet flexible company” embracing innovation and “paving the way for customers to get more relevant information faster about their packages while delivering with excellence”.
https://www.youtube.com/watch?v=galaZZlrEn0
Continuous Improvement in IT at Mazars
Mazars CIO David Marcelino explains his approach to innovation and leading on a successful IT transformation program at one of the world’s largest audit and advisory firms aiming to improve the digital experience for all its stakeholders. “Change Management, adoption, training and awareness are at the core of every single business technology project we deliver.”
Tech innovation at speed with the US Air Force
We also caught up with George Forbes, Director of Digital Operations Directorate at the United States Air Force, who outlines the importance of innovation within the federal government.
Digital Transformation in healthcare at Avellino
Nancy Selph, Global Head of IT at Avellino Lab, discusses how technology is creating new opportunities to improve health outcomes and the importance of leadership in the industry.
Also in this issue, we round up the key tech events and conferences across the globe; we learn how Minted are making it easy for everyone to invest in gold; and we feature the latest on cloud digitalisation from IFS.
Expert analysis of the tech trends set to make waves this year
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Digital transformation is a continuing journey of change with no set final destination. This makes predicting tomorrow a challenge when no one has a crystal ball to hand.
After a difficult few years for most businesses following a disruptive pandemic and now battling a cost-of-living crisis, many enterprises are increasingly leveraging new types of technology to gain an edge in a disruptive world.
With this in mind, here are what experts predict for the next 12 months…
1. Process Mining
Sam Attias, Director of Product Marketing at Celonis, expects to see a rise in the adoption of process mining as it evolves to incorporate automation capabilities. He says process mining has traditionally been “a data science done in isolation” which helps companies identify hidden inefficiencies by extracting data and visually representing it.
“It is now evolving to become more prescriptive than descriptive and will empower businesses to simulate new methods and processes in order to estimate success and error rates, as well as recommend actions before issues actually occur,” says Attias. “It will fix inefficiencies in real-time through automation and execution management.”
2. The evolution of social robots
Gabriel Aguiar Noury, Robotics Product Manager at Canonical, anticipates social robots to return this year. After companies such as Sony introduced robots like Poiq, Aguiar Noury believes it “sets the stage” for a new wave of social robots.
“Powered by natural language generation models like GPT-3, robots can create new dialogue systems,” he says. “This will improve the robot’s interactivity with humans, allowing robots to answer any question.
“Social robots will also build narratives and rich personalities, making interaction with users more meaningful. GPT-3 also powers Dall-E, an image generator. Combined, these types of technologies will enable robots not only to tell but show dynamic stories.”
3. The rebirth of new data-powered business applications
Christian Kleinerman, Senior Vice President of Product at Snowflake, says there is the beginning of a “renaissance” in software development. He believes developers will bring their applications to central combined sources of data instead of the “traditional approach” of copying data into applications.
“Every single application category, whether it’s horizontal or specific to an industry vertical, will be reinvented by the emergence of new data-powered applications,” affirms Kleinerman. “This rise of data-powered applications will represent massive opportunities for all different types of developers, whether they’re working on a brand-new idea for an application and a business based on that app, or they’re looking for how to expand their existing software operations.”
4. Application development will become a two-way conversation
Adrien Treuille, Head of Streamlit at Snowflake, believes application development will become a two-way conversation between producers and consumers. It is his belief that the advent of easy-to-use low-code or no-code platforms are already “simplifying the building” and sharing of interactive applications for tech-savvy and business users.
“Based on that foundation, the next emerging shift will be a blurring of the lines between two previously distinct roles — the application producer and the consumer of that software.”
He adds that application development will become a collaborative workflow where consumers can weigh in on the work producers are doing in real-time. “Taking this one step further, we’re heading towards a future where app development platforms have mechanisms to gather app requirements from consumers before the producer has even started creating that software.”
5. The Metaverse
Paul Hardy, EMEA Innovation Officer at ServiceNow, says he expects business leaders to adopt technologies such as the metaverse in 2023. The aim of this is to help cultivate and maintain employee engagement as businesses continue working in hybrid environments, in an increasingly challenging macro environment.
“Given the current economic climate, adoption of the metaverse may be slow, but in the future, a network of 3D virtual worlds will be used to foster meaningful social connections, creating new experiences for employees and reinforcing positive culture within organisations,” he says. “Hybrid work has made employee engagement more challenging, as it can be difficult to communicate when employees are not together in the same room.
“Leaders have begun to see the benefit of hosting traditional training and development sessions using VR and AI-enhanced coaching. In the next few years, we will see more workplaces go a step beyond this, for example, offering employees the chance to earn recognition in the form of tokens they can spend in the real or virtual world, gamifying the experience.”
6. The year of ESG?
Cathy Mauzaize, Vice President, EMEA South, at ServiceNow, believes 2023 could be the year that environmental, social and corporate governance (ESG) is vital to every company’s strategy.
“Failure to engage appropriate investment in ESG strategies could plunge any organisation into a crisis,” she says. “Legislation must be respected and so must the expectations of employees, investors and your ecosystem of partners and customers.
“ESG is not just a tick box, one and done, it’s a new way of business that will see us through 2023 and beyond.”
7. Macro Trends and Redeploying Budgets for Efficiency
Ulrik Nehammer, President, EMEA at ServiceNow, says organisations are facing an incredibly complex and volatile macro environment. Nehammer explains as the world is gripped by soaring inflation, intelligent digital investments can be a huge deflationary force.
“Business leaders are already shifting investment focus to technologies that will deliver outcomes faster,” he says. “Going into 2023, technology will become increasingly central to business success – in fact, 95% of CEOs are already pursuing a digital-first strategy according to IDC’s CEO survey, as digital companies deliver revenue growth far faster than non-digital ones.”
8. Organisations will have adopted a NaaS strategy
David Hughes, Aruba’s Chief Product and Technology Officer, believes that by the end of 2023, 20% of organisations will have adopted a network-as-a-service (NaaS) strategy.
“With tightening economic conditions, IT requires flexibility in how network infrastructure is acquired, deployed, and operated to enable network teams to deliver business outcomes rather than just managing devices,” he says. “Migration to a NaaS framework enables IT to accelerate network modernisation yet stay within budget, IT resource, and schedule constraints.
“In addition, adopting a NaaS strategy will help organisations meet sustainability objectives since leading NaaS suppliers have adopted carbon-neutral and recycling manufacturing strategies.”
9. Think like a seasonal business
According to Patrick Bossman, Product Manager at MariaDB corporation, he anticipates 2023 to be the year that the ability to “scale out on command” is going to be at the fore of companies’ thoughts.
“Organisations will need the infrastructure in place to grow on command and scale back once demand lowers,” he says. “The winners in 2023 will be those who understand that all business is seasonal, and all companies need to be ready for fluctuating demand.”
10. Digital platforms need to adapt to avoid falling victim to subscription fatigue
Demed L’Her, Chief Technology Officer at DigitalRoute, suggests what the subscription market is going to look like in 2023 and how businesses can avoid falling victim to ‘subscription fatigue’. L’Her says there has been a significant drop in demand since the pandemic.
“Insider’s latest research shows that as of August, nearly a third (30%) of people reported cancelling an online subscription service in the past six months,” he reveals. “This is largely due to the rising cost of living experienced globally that is leaving households with reduced budgets for luxuries like digital subscriptions. Despite this, the subscription market is far from dead, with most people retaining some despite tightened budgets.
“However, considering the ongoing economic challenges, businesses need to consider adapting if they are to be retained by customers in the long term. The key to this is ensuring that the product adds value to the life of the customer.”
11. Waking up to browser security
Jonathan Lee, Senior Product Manager at Menlo Security, points to the web browser being the biggest attack surface and suggests the industry is “waking up” to the fact of where people spend the most time.
“Vendors are now looking at ways to add security controls directly inside the browser,” explains Lee. “Traditionally, this was done either as a separate endpoint agent or at the network edge, using a firewall or secure web gateway. The big players, Google and Microsoft, are also in on the act, providing built-in controls inside Chrome and Edge to secure at a browser level rather than the network edge.
“But browser attacks are increasing, with attackers exploiting new and old vulnerabilities, and developing new attack methods like HTML Smuggling. Remote browser isolation is becoming one of the key principles of Zero Trust security where no device or user – not even the browser – can be trusted.”
12. The year of quantum-readiness
Tim Callan, Chief Experience Officer at Sectigo, predicts that 2023 will be the year of quantum-readiness. He believes that as a result of the standardisation of new quantum-safe algorithms expected to be in place by 2024, this year will be a year of action for government bodies, technology vendors, and enterprise IT leaders to prepare for the deployment.
“In 2022, the US National Institute of Standards and Technologies (NIST) selected a set of post-quantum algorithms for the industry to standardise on as we move toward our quantum-safe future,” says Callan.
“In 2023, standards bodies like the IETF and many others must work to incorporate these algorithms into their own guidelines to enable secure functional interoperability across broad sets of software, hardware, and digital services. Providers of these hardware, software, and service products must follow the relevant guidelines as they are developed and begin preparing their technology, manufacturing, delivery, and service models to accommodate updated standards and the new algorithms.”
13. AI: fewer keywords, greater understanding
AI expert Dr Pieter Buteneers, Director of AI and Machine Learning at Sinch, expects artificial intelligence to continue to transition away from keywords and move towards an increased level of understanding.
“Language-agnostic AI, already existent within certain AI and chatbot platforms, will understand hundreds of languages — and even interchange them within a single search or conversation — because it’s not learning language like you or I would,” he says. “This advanced AI instead focuses on meaning, and attaches code to words accordingly, so language is more of a finishing touch than the crux of a conversation or search query.
“Language-agnostic AI will power stronger search results — both from external (the internet) and internal (a company database) sources — and less robotic chatbot conversations, enabling companies to lean on automation to reduce resources and strain on staff and truly trust their AI.”
14. Rise in digital twin technology in the enterprise
John Hill, CEO and Founder of Silico, recognises the growing influence digital twin technology is having in the market. Hill predicts that in the next 20 years, there will be a digital twin of every complex enterprise in the world and anticipates the next generation of decision-makers will routinely use forward-looking simulations and scenario analytics to plan and optimise their business outcomes.
“Digital twin technology is one of the fastest-growing facets of industry 4.0 and while we’re still at the dawn of digital twin technology,” he explains. “Digital twins will have huge implications for unlocking our ability to plan and manage the complex organisations so crucial for our continued economic progress and underpin the next generation of Intelligent Enterprise Automation.”
15. Broader tech security
With an exponential amount of data at companies’ fingertips, Tricentis CEO, Kevin Thompson says the need for investment in secure solutions is paramount.
“The general public has become more aware of the access companies have to their personal data, leading to the impending end of third-party cookies, and other similar restrictions on data sharing,” he explains. “However, security issues still persist. The persisting influx of new data across channels and servers introduces greater risk of infiltration by bad actors, especially for enterprise software organisations that have applications in need of consistent testing and updates. The potential for damage increases as iterations are being made with the expanding attack surface.
“Now, the reality is a matter of when, not if, your organisation will be the target of an attack. To combat this rising security concern, organisations will need to integrate security within the development process from the very beginning. Integrating security and compliance testing at the upfront will greatly reduce risk and prevent disruptions.”
16. Increased cyber resilience
Michael Adams, CISO at Zoom, expects an increased focus on cyber resilience over the next 12 months. “While protecting organisations against cyber threats will always be a core focus area for security programs, we can expect an increased focus on cyber resilience, which expands beyond protection to include recovery and continuity in the event of a cyber incident,” explains Adams.
“It’s not only investing resources in protecting against cyber threats; it’s investing in the people, processes, and technology to mitigate impact and continue operations in the event of a cyber incident.”
17. Ransomware threats
As data leaks become increasingly common place in the industry, companies face a very real threat of ransomware. Michal Salat, Threat Intelligence Director at Avast, believes the time is now for businesses to protect themselves or face recovery fees costing millions of dollars.
“Ransomware attacks themselves are already an individual’s and businesses’ nightmare. This year, we saw cybergangs threatening to publicly publish their targets’ data if a ransom isn’t paid, and we expect this trend to only grow in 2023,” says Salat. “This puts people’s personal memories at risk and poses a double risk for businesses. Both the loss of sensitive files, plus a data breach, can have severe consequences for their business and reputation.”
18. Intensified supply chain attacks
Dirk Schrader, VP of security research at Netwrix, believes supply chain attacks are set to increase in the coming year. “Modern organisations rely on complex supply chains, including small and medium businesses (SMBs) and managed service providers (MSPs),” he says.
“Adversaries will increasingly target these suppliers rather than the larger enterprises knowing that they provide a path into multiple partners and customers. To address this threat, organisations of all sizes, while conducting a risk assessment, need to take into account the vulnerabilities of all third-party software or firmware.”
19. A greater need to manage volatility
Paul Milloy, Business Consultant at Intradiem, stresses the importance of managing volatility in an ever-moving market. Milloy believes bosses can utilise data through automation to foresee potential problems before they become issues.
“No one likes surprises. Whilst Ben Franklin suggested nothing can be said to be certain, except death and taxes, businesses will want to automate as many of their processes as possible to help manage volatility in 2023,” he explains. “Data breeds intelligence, and intelligence breeds insight. Managers can use the data available from workforce automation tools to help them manage peaks and troughs better to avoid unexpected resource bottlenecks.”
20. A human AI co-pilot will still be needed
Artem Kroupenev, VP of Strategy at Augury, predicts that within the next few years, every profession will be enhanced with hybrid intelligence, and have an AI co-pilot which will operate alongside human workers to deliver more accurate and nuanced work at a much faster pace.
“These co-pilots are already being deployed with clear use cases in mind to support specific roles and operational needs, like AI-driven solutions that enable reliability engineers to ensure production uptime, safety and sustainability through predictive maintenance,” he says. “However, in 2023, we will see these co-pilots become more accurate, more trusted and more ingrained across the enterprise.
“Executives will better understand the value of AI co-pilots to make critical business decisions, and as a key competitive differentiator, and will drive faster implementation across their operations. The AI co-pilot technology will be more widespread next year, and trust and acceptance will increase as people see the benefits unfold.”
21. Building the right workplace culture
Harnessing a positive workplace culture is no easy task but in 2023 with remote and hybrid working now the norm, it brings with it new challenges. Tony McCandless, Chief Technology Officer at SS&C Blue Prism, is well aware of the role organisational culture can play in any digital transformation journey.
“Workers are the heart of an organisation, so without their buy in, no digital transformation initiative stands a chance of success,” explains McCandless. “Workers drive home business objectives, and when it comes to digital transformation, they are the ones using, implementing, and sometimes building automations. Curiosity, innovation, and the willingness to take risks are essential ingredients to transformative digitalisation.
“Businesses are increasingly recognising that their workers play an instrumental role in determining whether digitalisation initiatives are successful. Fostering the right work environment will be a key focus point for the year ahead – not only to cultivate buy-in but also to improve talent retention and acquisition, as labor supply issues are predicted to continue into 2023 and beyond.”
22. Cloud cover to soften recession concerns
Amid a cost-of-living crisis and concerns over any potential recession as a result, Daniel Thomasson, VP of Engineering and R&D at Keysight Technologies, says more companies will shift data intensive tasks to the cloud to reduce infrastructure and operational costs.
“Moving applications to the cloud will also help organisations deliver greater data-driven customer experiences,” he affirms. “For example, advanced simulation and test data management capabilities such as real-time feature extraction and encryption will enable use of a secure cloud-based data mesh that will accelerate and deepen customer insights through new algorithms operating on a richer data set. In the year ahead, expect the cloud to be a surprising boom for companies as they navigate economic uncertainty.”
23. IoT devices to scale globally
Dr Raullen Chai, CEO and Co-Founder of IoTeX, recognises a growing trend in the usage of IoT devices worldwide and believes connectivity will increase significantly.
“For decades, Big Tech has monopolised user data, but with the advent of Web3, we will see more and more businesses and smart device makers beginning to integrate blockchain for device connectivity as it enables people to also monetise their data in many different ways, including in marketing data pools, medical research pools and more,” he explains. “We will see a growth in decentralised applications that allow users to earn a modest additional revenue from everyday activities, such as walking, sleeping, riding a bike or taking the bus instead of driving, or driving safely in exchange for rewards.
“Living healthy lifestyles will also become more popular via decentralised applications for smart devices, especially smart watches and other health wearables.”
The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now…
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The digital landscape is changing day by day. Ideas like the metaverse that once seemed a futuristic fantasy are now coming to fruition and embedding themselves into our daily lives. The thinking might be there, but is our technology really ready to go meta? Domains and hosting provider, Fasthosts, spoke to the experts to find out…
How the metaverse works
The metaverse is best defined as a virtual 3D universe which combines many virtual places. It allows users to meet, collaborate, play games and interact in virtual environments. It’s usually viewed and accessed from the outside as a mixture of virtual reality (VR), (think of someone in their front room wearing a headset and frantically waving nunchucks around) and augmented reality (AR), but it’s so much more than this…
These technologies are just the external entry points to the metaverse and provide the visuals which allow users to explore and interact with the environment within the metaverse.
This is the ‘front-end’ if you like, which is also reinforced by artificial intelligence and 3D reconstruction. These additional technologies help to provide realistic objects in environments, computer-controlled actions and also avatars for games and other metaverse projects.
So, what stands in the way of this fantastical 3D universe? Here are the six key challenges:
Technology
The most important piece of technology, on which the metaverse is based, is the blockchain. The blockchain is essentially a chain of blocks that contain specific information. They’re a combination of computers linked to each other instead of a central server which means that the whole network is decentralised. This provides the infrastructure for the development of metaverse projects, storage of data and also allows them the capability to be compatible with Web3. Web3 is an upgraded version of the internet which will allow integration of virtual and augmented reality into people’s everyday lives.
Sounds like a lot, right? And it involves a great deal of tech that is alien to the vast majority of us. So, is technology a barrier to widespread metaverse adoption?
Jonothan Hunt, Senior Creative Technologist at Wunderman Thompson, says the tech just isn’t there. Yet.
“Technology’s readiness for the mass adoption of the metaverse depends on how you define the metaverse, but if we’re talking about the future vision that the big tech players are sharing, then not yet. The infrastructure that powers the internet and our devices isn’t ready for such experiences. The best we have right now in terms of shared/simulated spaces are generally very expensive and powered entirely in the cloud, such as big computers like the Nvidia Omniverse, cloud streaming, or games. These rely heavily on instancing and localised grouping. Consumer hardware, especially XR, is still not ready for casual daily use and still not really democratised.
“The technology for this will look like an evolution of the systems above, meaning more distributed infrastructure, better access and updated hardware. Web3 also presents a challenge in and of itself, and questions remain over to what extent big tech will adopt it going forward.”
Storage
Blockchain is the ‘back-end’, where the magic happens, if you will. It’s this that will be the key to the development and growth of the metaverse. There are a lot of elements that make up the blockchain and reinforce its benefits and uses such as storage capabilities, data security and smart contracts.
Due to its decentralised nature, the blockchain has far more storage capacity than the centralised storage systems we have in place today. With data on the metaverse being stored in exabytes, the blockchain works by making use of unutilised hard disk space across the network, which avoids users within the metaverse running out of storage space worldwide.
In terms that might be a bit more relatable, an exabyte is a billion gigabytes. That’s a huge amount of storage, and that doesn’t just exist in the cloud – it’s got to go somewhere – and physical storage servers mean land is taken up, and energy is used. Hunt says: “How long’s a piece of string? The whole of the metaverse will one day be housed in servers and data centres, but the amount or size needed to house all of this storage will beentirely dependent on just how mass adopted the metaverse becomes. Big corporations in the space are starting to build huge data centres – such as Meta purchasing a $1.1 billion campus in Toledo, Spain to house their new Meta lab and data centre – but the storage space is not the only concern. These energy-guzzlers need to stay cool! And what about people and brands who need reliable web hosting for events, gaming or even just meeting up with pals across the world, all that information – albeit virtual – still needs a place to go.
“The current rising cost of electricity worldwide could cause problems for the growth of data centres, and the housing of the metaverse as a whole. However, without knowing the true size of its adoption, it is extremely difficult to truly determine the needed usage. Could we one day see an entire island devoted to data centre storage? Purely for the purposes of holding the metaverse? It seems a little ‘1984’, but who knows?”
Identity
Although the blockchain provides instantaneous verification of transactions with identity through digital wallets, our physical form will be represented by avatars that visually reflect who we are, and how we want to be seen.
The founder of Saxo Bank and the chairman of the Concordium Foundation, Lars Seier Christensen, argues, “I think that if you use an underlying blockchain-based solution where ID is required at the entry point, it is actually very simple and automatically available for relevant purposes. It is also very secure and transparent, in that it would link any transactions or interactions where ID is required to a trackable record on the blockchain.”
Once identity is established, it is true that it could potentially become easier to assess creditworthiness of parties for purchasing and borrowing in the metaverse due to the digital identity and storage of each individual’s data and transactions on the blockchain. However, although it sounds exciting, there must be considerations into how it could impact privacy, and how this amount of data will be recorded on the blockchain.
Security
There are also huge security benefits to this set up. The decentralised blockchain helps to eradicate third-party involvement and data breaches, such as theft and file manipulation, thanks to its powerful data processing and use of validation nodes. Both of these are responsible for verifying and recording transactions on the blockchain. This will be reassuring to many, given the widespread concerns around data privacy and user protection in the metaverse.
To access the blockchain all we will need is an internet connection and a device, such as a laptop or smartphone, this is what makes it so great as it will be so readily available. However, to support the blockchain, we’re relying on a whole different set of technologies. Akash Kayar, CEO of web3-focused software development company Leeway Hertz, had this to say on the readiness of the current technology available: “The metaverse is not yet completely mature in terms of development. Tech experts are researching strategies and
testing the various technologies to develop ideas that provide the world with more feasible and intriguing metaverse projects.
“Projects like Decentraland, Axie Infinity, and Sandbox are popular contemporary live metaverse projects. People behind these projects made perfect use of notable metaverse technologies, from blockchain and cryptos to NFTs.
“As envisioned by top tech futurists, many new technologies will empower the metaverse in the future, which will support the development of a range of prolific use cases that will improve the ability of the metaverse towards offering real-life functionalities. In a nutshell, the metaverse is expected to bring extreme opportunities for enterprises and common users. Hence, it will shape the digital future.”
Currency & Payments
Whilst it’s only considered legal tender in two countries, cryptocurrency is currently a reality and there is a strong likelihood that it will eventually be mass adopted. However, the metaverse is arguably not yet at the same maturity level, meaning cryptocurrency may have to wait before it can finally fully take off.
Golden Bitcoin symbol and finance graph screen. Horizontal composition with copy space. Focused image.
There is no doubt that cryptocurrency and the metaverse will go hand-in-hand as the former will become the tender of the latter with many of the current metaverse platforms each wielding its native currency. For example Decentraland uses $MANA for payments and purchases. However, with the volatility of crypto currencies and the recent collapse of trading platform FTX indicating security lapses, we may not yet be ready for the switch to decentralised payments.
Energy
Some of the world’s largest data centres can each contain many tens of thousands of IT devices which require more than 100 megawatts of power capacity – this is enough to power around 80,000 U.S. households (U.S. DOE 2020) and is equivalent to $1.35bn running cost per data centre with the cost of a megawatt hour averaging $150.
According to Nitin Parekh of Hitachi Energy, the amount of power which takes to process Bitcoin is higher than you might expect: “Bitcoin consumes around 110 Terawatt Hours per year. This is around 0.5% of global electricity generation. This estimate considers combined computational power used to mine bitcoin and process transactions.” With this estimate, we can calculate that the annual energy cost of Bitcoin is around $16.5bn.
However, some bigger corporations are slowly moving towards renewable energy to power their projects in this space, with Google signing close to $2bn worth of wind and solar investments in order to power its data centres in the future and become greener. Amazon has also followed in their footsteps and have become the world’s largest corporate purchaser of renewable energy.
They may have plenty of time yet to get their green processes in place, with Mark Zuckerberg recently predicting it will take nearly a decade for the metaverse to be created: “I don’t think it’s really going to be huge until the second half of this decade at the earliest.”
About Fasthosts
Fasthosts has been a leading technology provider since 1999, offering secure UK data centres, 24/7 support and a highly successful reseller channel. Fasthosts provides everything web professionals need to power and manage their online space, including domains, web hosting, business-class email, dedicated servers, and a next-generation cloud platform. For more information, head to www.fasthosts.co.uk
Todd Salmon, Executive Advisor for Strategic Services at GuidePoint Security, on the cybersecurity challenge of keeping up with the pace of the ever-changing digital world
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This month’s cover story explores how GuidePoint Security, an elite team of highly trained and certified experts, cut through cybersecurity chaos and confusion to put control back in customers’ hands.
Welcome to the latest issueof Interface magazine!
Interface welcomes in 2023 with a need-to-know list of what we can expect from technology this year and how it can allow enterprises to gain a competitive edge in a disruptive and increasingly digital world. Faced with everything from process mining and AI to quantum-readiness and the metaverse we cut through the hype to bring you the facts.
GuidePoint Security: digital transformation in cybersecurity
“Cybersecurity is in such a reactive mode because of the sheer volume of risks and vulnerabilities an organisation faces,” says Todd Salmon, Executive Advisor for Strategic Services at GuidePoint Security. “We see a lot of copycats and repeat attacks happen, but at the end of the day it’s all about creating solutions to help combat those problems.”
GuidePoint’s elite team of highly trained and certified experts, cut through cybersecurity chaos and confusion to put control back in customers’ hands. Helping them make the smartest, most informed cyber risk decisions, and choose and integrate the best-fit solutions to build the most effective cybersecurity program, Salmon discusses the challenge of keeping up with the pace of the ever-changing digital world.
bp: a strategic reinvention
“We are investing in digital to drive process efficiency and improve insights; but also to develop our people with the skills we need for now, and the future at bp. This means we are playing to win while caring for our people through investing in their personal development,” says Head of Strategic Transformation Nick Hales.
“After setting the right foundations through various remediation and compliance initiatives, we embarked on our digital transformation journey,” adds Strategy & Transformation Manager Emmanouela Vlachantoni. “There was a clear opportunity to standardise and streamline our controls environment to reduce complexity and increase insight.”
Fairfax County: winning the IT war with cybersecurity
Meanwhile, across the pond, we learn how Fairfax County in the State of Virginia is reaping the rewards of a cybersecurity program enabling government services and keeping citizens safe. “My role is to educate our leadership to ensure they understand the business value of cybersecurity as it relates to government services. Being accountable for the security of their systems and data is a key factor in developing a successful cyber program,” explains CISO Michael Dent.
Also in this issue, we round up the key tech events and conferences across the globe and, with the help of the experts at Fasthosts, take a deep dive into the metaverse… Can virtual reality become our reality? Read on to find out.
Nick Hales, Head of Strategic Transformation and Emmanouela Vlachantoni, Strategy & Transformation Senior Manager, on the journey to reinvent business processes that are reimagining bp
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This month’s cover story reveals how bp’s Strategic Transformation leaders are on a journey to reinvent business processes that are reimagining the energy giant.
Welcome to the latest issueof Interface magazine!
Our final issue of Interface for 2022 covers some of this year’s hot tech topics: digital transformation, cybersecurity, data & analytics, customer-centricity and more…
“We are investing in digital to drive process efficiency and improve insights; but also to develop our people with the skills we need for now, and the future. This means we are playing to win while caring for our people through investing in their personal development,” says Nick Hales.
“After setting the right foundations through various remediation and compliance initiatives, we embarked on our digital transformation journey,” adds Emmanouela Vlachantoni. “There was a clear opportunity to standardise and streamline our controls environment to reduce complexity and increase insight.”
Fairfax County: winning the IT war with cybersecurity
Meanwhile, across the pond, we learn how Fairfax County in the State of Virginia is reaping the rewards of a cybersecurity program enabling government services and keeping citizens safe. “My role is to educate our leadership to ensure they understand the business value of cybersecurity as it relates to government services. Being accountable for the security of their systems and data is a key factor in developing a successful cyber program,” explains CISO Michael Dent.
Piedmont Healthcare: data & analytics at the heart of growth
The power of data cannot be under-estimated… At Piedmont Healthcare Mark Jackson, Executive Director of Business Intelligence is building a data strategy driving speed to insight at scale. “Tool selection has played an important role in our ability to scale the BI program and deliver rapid insights in a dynamic environment.”
Also in this issue, CalArts CTO Allan Chen explains how an IT strategy based on coordination and collaboration is supporting six schools; Information Tech VP Fausto Sosa de la Fuente reveals the people-centric transformative IT process at construction industry giant CEMEX; and we take a look at the latest insights from McKinsey highlighting the lessons CEOs can learn from successful digital transformations.
John MClure, CISO at Sinclair Group – a diversified media company and America’s leading provider of local sports and news – talks about the evolution of cybersecurity and the cultural shift placing it at the forefront of business change
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This month’s cover story explores how Sinclair Broadcast Group is embracing the evolution of cybersecurity and placing the role of the CISO at the forefront of business transformation.
Welcome to the latest issueof Interface magazine!
Communication, secure and at speed, is a vital component of the transformation journey for both the modern enterprise and its relationship with stakeholders, be they customers or partners. Putting the right building blocks in place to deliver successful change management is at the heart of the inspiring stories in the latest issue of Interface.
Our cover star John McClure progressed from a career in the military and work as a consultant in the intelligence industry to fight a new kind of foe… As CISO for Sinclair Broadcast Group, a diversified media company and America’s leading provider of local sports and news, he talks about the evolution of cybersecurity, the battle to meet the rising velocity and sophistication of cyber-attacks and the cultural shift of the role of CISO placing it at the forefront of business change.
“Sinclair is unique in terms of its different business units and how it operates. It’s my job as CISO leading our cyber team not to be an obstacle for the business; we’re here to help it move faster to keep up with market forces, and to move safely. We’re here to engineer solutions that work for the enterprise but also help us maintain a positive security posture.”
State of Florida: digital government services
We also hear from CIO Jamie Grant who is leading the State of Florida’s Digital Service (FL[DS]) on its charge to transform and modernise the way government is accessed and consumed. He is building a team of talented, goal-oriented and customer-obsessed individuals to drive a digital transformation with innovation at its heart. “Leadership is really about developing the team and investing in the people. And it turns out that when you get their backs, they appreciate it and then you can achieve anything.”
ResultsCX: putting people first
Jamie Vernon, SVP for IT & Infrastructure at AI-powered customer experience solution specialist ResultsCX, discusses what drives customer care in the 21st century, and the part technology has to play.
“We are the custodians of our customers’ customers,” says Vernon. “In this increasingly tenuous relationship with their customers, they trust us. My leadership takes that responsibility very seriously, and charges each of us with doing everything we can to provide a perfect call, or email, or chat, every time, thousands of times a minute, around the clock and around the calendar.”
Jamie Vernon, SVP for IT & Infrastructure at AI-powered customer experience solution specialist ResultsCX, discusses what drives customer care in the 21st century, and the part technology has to play.
“We are the custodians of our customers’ customers,” says Vernon. “In this increasingly tenuous relationship with their customers, they trust us. My leadership takes that responsibility very seriously, and charges each of us with doing everything we can to provide a perfect call, or email, or chat, every time, thousands of times a minute, around the clock and around the calendar.”
Also this month, Sarita Singh, Regional Head & Managing Director for Stripe in Southeast Asia, talks about how the fast-growing payments platform is driving financial inclusion across Asia and supporting SMEs with end-to-end services putting users first, and we get expert advice for the modern CEO from the University of Oxford’s Saïd Business School.
Our cover story this month reveals how Dr Roman Salasznyk, Senior Vice President at Booz Allen Hamilton, and his team are driving innovation at the IT services specialist to deliver digital solutions supporting federal agencies in their quest to drive mission-critical programs
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This month’s cover story charts how IT services specialist Booz Allen Hamilton is delivering digital solutions to support federal agencies in their quest to deliver mission-critical programs.
Welcome to the latest issue of Interface magazine!
Technology is changing lives; from banking to transport and manufacturing to healthcare, the scaling of digital transformation journeys across global industry sectors is enabling and enhancing our lives… Harnessing the power of tech, to manage everything from the evolution of our supply chains to our response to medical emergencies like COVID-19, is changing the game.
Our cover story this month reveals how IT services specialist Booz Allen Hamilton is delivering leading edge solutions to support federal agencies in their quest to deliver mission-critical programs.
“We’ve made a concerted effort to invest and provide leading-edge capabilities to support some of our client’s most pressing public health challenges across the federal government space,” says Salasznyk. “Technology must add value, solve a business problem, and deliver measurable improvements in efficiency and effectiveness.” That efficiency is driven by over 29,000 experts around the world driving digital journeys, developing analytics insights, engineering, and cybersecurity solutions while working shoulder-to-shoulder with clients to choose the right tech to realise their vision and transform.
Nuffield Health: digital transformation for a healthier tomorrow
Nuffield Health is the UK’s largest healthcare charity (independent of the NHS) operating 37 hospitals and 114 Fitness & Wellbeing Centres. IT leaders Jacqs Harper and David Ankers describe the organisation’s incredible digital transformation and how its people-first attitude runs deep. Nuffield’s beneficiary-centric approach means “driving experiences” to be optimal and best-in-class is paramount. “What was really compelling when I joined Nuffield was how much of a difference this business can make to the nation in terms of improving its health,” says Ankers. “And equally, how we as a team can make the lives of practitioners so much easier. There’s a huge amount of value IT can add.”
Also in this issue, we hear from Celonis on why process mining can help companies stop wasting money on tech they don’t need, and we present the latest analysis from consultancy giant McKinsey’s Technology Council highlighting the development, future uses and industry effects of advanced technologies across 14 key trends.
Our cover story this month investigates how Fleur Twohig, Executive Vice President, leading Personalisation & Experimentation across Consumer Data & Engagement Platforms, and her team are executing Wells Fargo’s strategy to promote personalised customer engagement across all consumer banking channels
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This month’s cover story follows Wells Fargo’s journey to deliver personalised customer engagement across all its consumer banking channels.
Welcome to the latest issue of Interface magazine!
Partnerships of all kinds are a key ingredient for organisations intent on achieving their goals… Whether that’s with customers, internal stakeholders or strategic allies across a crowded marketplace, Interface explores the route to success these relationships can help navigate.
Our cover story this month investigates the strategy behind Wells Fargo’s ongoing drive to promote personalised customer engagement across all consumer banking channels.
Fleur Twohig, Executive Vice President, leading Personalisation & Experimentation across the bank’s Consumer Data & Engagement Platforms, explains her commitment to creating a holistic approach to engaging customers in personalised one-to-one conversations that support them on their financial journeys.
“We need to be there for everyone across the spectrum – for both the good and the challenging times. Reaching that goal is a key opportunity for Wells Fargo and I have the pleasure of partnering with our cross-functional teams to help determine the strategic path forward…”
IBM: consolidating growth to drive value
We hear from Kate Woolley, General Manager of IBM Ecosystem, who reveals how the tech leader is making it easier for partners and clients to do business with IBM and succeed. “Honing our corporate strategy around open hybrid cloud and artificial intelligence (AI) and connecting partners to the technical training resources they need to co-create and drive more wins, we are transforming the IBM Ecosystem to be a growth engine for the company and its partners.”
Kate Woolley, IBM
America Televisión: bringing audiences together across platforms
Jose Hernandez, Chief Digital Officer at America Televisión, explains how Peru’s leading TV network is aggregating services to bring audiences together for omni-channel opportunities across its platforms. “Time is the currency with which our audiences pay us, so we need to be constantly improving our offering both through content and user experiences.”
Portland Public Schools: levelling the playing field through technology
Derrick Brown and Don Wolf, tech leaders at Portland Public Schools, talk about modernising the classroom, dismantling systemic racism and the power of teamwork.
Also in this issue, we hear from Lenovo on how high-performance computing (HPC) is driving AI research and report again from London Tech Week where an expert panel examined how tech, fuelled by data, is playing a critical role in solving some of the world’s hardest hitting issues, ranging from supply chain disruptions through to cybersecurity fears.
Our cover story this month reveals how Sarita Singh, Regional Head & Managing Director for Stripe in Southeast Asia, and her team are driving financial inclusion across the region and supporting SMEs with end-to-end services putting users first
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This month’s cover story reveals how Stripe’s payments platform is driving financial inclusion across Asia.
Welcome to the latest issue of Interface magazine!
Opportunities for innovation and growth via the adoption of new technologies are everywhere. However, organisations are faced with a bewildering array of choices to help them transform and choosing the best option to drive positive disruption is a tough call. We take a look at some of these fascinating journeys…
Sarita Singh, Regional Head & Managing Director for Southeast Asia, Stripe
This month’s cover story explores the genesis of fast-growing payments platform Stripe. Sarita Singh, Regional Head & Managing Director for Southeast Asia, leads a team driving financial inclusion across the region, supporting SMEs with end-to-end services putting users first.
“We’re building products and the financial infrastructure to help our users go cross-border, beyond their domestic boundaries, to widen their markets and drive efficiencies within their financial services infrastructure. With Stripe under the hood, businesses are able to focus on what they do best without wasting time researching, purchasing, integrating, and maintaining dozens of payment technology point solutions because Stripe is a platform that offers all of them, and is already integrated.”
IAG: tech procurement linked to purpose
We speak with IAG’s CPO & VMO Claire Ledder, who reveals the transformative approach to technology procurement being deployed by an Australian market leader home to several leading insurance brands. “We’re now able to tackle sourcing and contracting with an end-to-end approach capable of measuring the value delivered.”
Portrait Photography
U.S. Department of State: facilitating diplomacy with tech
Todd Cheng Director of IT Customer Service at the U.S. Department of State, talks about the ever-evolving relationship between technology and diplomacy. “We’ve been through the process of updating the IT model at State to a new, more customer centric version of the Information Technology Infrastructure Library (ITIL).” By his calculations, these changes have benefited the organisation by reducing network disruption by some 400,000 hours of diplomacy every month.
Afni
Afni’s CISO Brent Deterding explains how breaking down the traditional and perceived barriers between security and the boardroom can transparently position cyber effectiveness as a critical enabler of improved business outcomes.
Afni’s CISO Brent Deterding
Also in this issue, we hear from Zoom on the future of work and report again from London Tech Week where an expert panel gave advice for businesses on anticipating and preparing for cyber risk against a backdrop of geopolitical uncertainty.
Our cover story this month explores how Wei Li, Vice President & GM for AI & Analytics at Intel, and his team are powering Artificial Intelligence to enable the digital journey from data to insights
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This month’s cover story explores Intel’s AI technologies powering the digital journey from data to insights…
Welcome to the latest issue of Interface magazine!
In this issue of Interface, we speak with a diverse group of tech leaders blazing a trail that others can follow to navigate the journey towards transformation.
We met with this month’s cover star Wei Li at the AI Summit during London Tech Week where Intel’s AI & Analytics leader delivered a compelling keynote speech and explained how the tech leader is powering Artificial Intelligence to enable the digital journey from data to insights.
“AI Everywhere means that anybody should be able to apply and use AI,” says Li, explaining the pledge Intel has made to further democratise the use of technologies such as AI. “We provide not only the hardware for AI, but also AI software and solutions for everyone to accelerate their data to insights journey. Software is the bridge between hardware and the millions of developers and billions of users.”
London Tech Week
During London Tech Week Chris Philp MP, the Parliamentary Under Secretary of State at the Department for Digital, Culture, Media and Sport (DCMS), discussed the launch of the UK’s Digital Strategy with an expert panel. We take a look at what this means for Britain’s approach to expanding the reach of its digital economy to drive growth, boost productivity and create more better-paid jobs.
ENGIE: collaboration through data
We speak with ENGIE’s Group Chief Analytics Officer Thierry Grima, who outlines the extraordinary data transformation the global utility giant is going through, and how the ground-breaking data connection of 170,000 global team members is benefiting the business. “As a business, we need to unlock the value of data because it’s no longer a competitive advantage. It’s just a necessity.”
Elsewhere, Jim Brady from Fairview Health Services reveals how his dual role as CISO and VP Information Security & Infrastructure/Operations is uniting security and operational technology to break down silos and drive a transformation with people power at its heart. “I love people, helping them and interacting with them in a positive way. There are several hundred people on my team, but I still spend time with them one-on-one and in small groups, even now that we’re largely working remotely.”
Also in this issue, S. M. Jaleel’s CIO Teoman Buyan explains how the right company culture can drive a positive technology transformation and Sal Laher, Chief Digital & Information Officer at global enterprise software provider IFS, talks about the importance of developing a more environmentally friendly approach to technology that weaves sustainability into the software fabric.
This month’s cover story reveals the cycles of transformation, being led by CDO Lucho Torres, which are driving the disruptive digital journey at Peru’s second largest financial services group
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This month’s cover story reveals reveals the cycles of transformation driving the disruptive digital journey at Scotiabank Peru, the country’s second largest financial services group.
Welcome to the latest issue of Interface magazine!
A customer-centric vision is often an important factor in the journey towards a digital transformation where a commitment to continuous improvement can bring scalability and lasting growth. Interface taps the brains behind some of the biggest tech successes happening across the globe today…
Lucho Torres, SVP & Chief Digital Officer at Scotiabank Peru is on a mission to leverage the trust in a global banking leader founded in 1832 and lead a transformation to create “the most relevant, simple and fast digital bank for consumers and businesses” across Peru. “The challenge was to build a digital bank with scalability and sustainability. We have created a customer-centric value proposition by building and taking to the market our own digital platforms and financial products to deliver personalised and intuitive customer experiences.”
IBM
We speak with IBM’s AI & Data guru Jean-Philippe Desbiolles who gives us a fascinating overview of his book AI Will be What you Make of It: The 10 Golden Rules of Artificial Intelligence. “I am passionate about the fact that at IBM we are transforming businesses by leveraging technologies in a broad sense of the word. And one of those key technologies is Artificial Intelligence.” Listen to our podcast with Jean-Philippe here or you can watch it below…
Digital Transformation in healthcare, education and telecomms
Also in this issue, Michael Haenelt, CIO at the Weed Army Community Hospital tells us the story of the development of a state-of-the-art medical facility at Ft Irwin, in California’s remote Mojave Desert, where a commitment to digital transformation is at the beating heart of the organisation.
This month’s cover story explores the customer-centric digital transformation journey of leading insurer AXA being led by UK & Ireland CIO Darrell Ryman
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Our cover story this month explores how leading insurer AXA‘s customer-centric digital transformation journey is refining the art of the possible to unite business with technology.
Welcome to the latest issue of Interface magazine!
The opportunity to leverage data & analytics to transform organisations seeking to sharpen their digital focus and better connect with internal and external stakeholders is at the forefront of a revolution in connectivity driving both operational efficiency and growth. In this issue we bring you some inspiring stories that reflect the impact today’s innovations are having on shaping the business journeys of tomorrow…
This month’s cover story explores the customer-centric digital transformation journey being led by AXA’s UK & Ireland CIO Darrell Ryman. “It’s both a challenge and an opportunity for the insurance industry,” he reflects. “Many of the legacy systems firms use are now outdated and based on the nine-to-five business operating model – they’re not designed for the modern digital experience.” Ryman’s IT team is driving that transformation pivot by focusing on three key pillars: developing a digital backbone, becoming a digital business and creating a digital ecosystem.
https://www.youtube.com/watch?v=i6wxgQ2gAmI
XGS
Today’s on demand transactions require custom logistics solutions. We discover how flooring supply chain specialist Xpress Global Systems (XGS) is combining existing data with employee experience to deliver technology solutions that form the core of the company’s humanised approach to digital transformation.
EY
Also in this issue, Ken Priyadarshi CT AI leader of EY Technology, explains how the leading professional services network is developing Digital Twins to deliver big-data and low-latency scenario planning models for financial services: “It’s time for the digital twin to become a mainstream tool for the C-suite and go beyond the traditional manufacturing or operational use-cases.”
Data management driving efficiency and growth
Elsewhere, we learn how specialist insurance broker Howden is achieving success in Asia by establishing a structured, data-driven, engagement and distribution strategy; and reveal the way America’s leading critical infrastructure damage prevention firm, Stake Center Locating, is future-proofing by transferring its expertise from legacy systems to the cloud.
Our cover story examines how Microsoft is accelerating innovation for sustainable growth by providing specialised solutions supporting financial health for enterprises and their customers in the Azure cloud
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Our cover story this month reveals how Microsoft is supporting future-first financial services in the cloud.
Welcome to the latest issue of Interface magazine!
Digital transformation can take many forms, powering the strategies to achieve goals across a diverse range of sectors from education and manufacturing to business development and health. In this issue we explore some of these compelling success stories.
Gracing this cover of Interface is Bill Livezey, Director of Financial Services for Intelligent Cloud at Microsoft. Bringing a quarter century of experience at the tech giant to his latest role, he explains how it is accelerating innovation for sustainable growth by providing specialised solutions supporting financial health for enterprises and their customers. A broad set of data models and tools in Microsoft’s Intelligent Cloud work together and allows for its partners to join in quickly building differentiated experiences in an industry-compliant and secure public cloud.
Virtusa
Today’s businesses require change at a scale and speed that defies traditional ways of working. By delivering deep digital engineering and industry expertise through client-specific and integrated agile approaches, we learn how Virtusa, in conjunction with key partners like Pega, is driving digital transformation with the pace and passion of a startup delivered with expert execution on a global scale.
Bossard
Also in this issue, we hear from Bossard, a leading global provider of product solutions and services in industrial fastening and assembly technology. Chief Information Officer Georg Meyer reveals how IT is supporting its efforts to achieve ‘proven productivity’ while working towards its 200th anniversary strategy goals.
Digital Transformation supporting Sustainability
Elsewhere, we discover how the School District of Oconee County has transformed the lives of its teachers and students through the pursuit of digital transformation; and reveal the way SodaStream is leading the fight against plastic pollution, aligning its operational and digital goals with sustainable solutions and products that truly help to preserve our planet.
Bridewell Consulting has outlined its top 10 cybersecurity predictions for 2022.
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Bridewell Consulting has outlined its top 10 cybersecurity predictions for 2022.
Compiled by its skilled consultants, and coupled with data gathered from its 24/7 security operations centre in 2021, the company warns of the automation of security threats, increased risks for remote workers, and more nation-state attacks on the UK’s critical national infrastructure and supply chains.
“Cyber threats are always evolving and 2022 will be no different. Attackers will use new technologies to launch more sophisticated attacks and remain under the radar, while businesses will use technology to strengthen defences and drive efficiencies. Heading into 2022, organisations need confidence that their systems, data and processes remain protected, regardless of how the landscape evolves, and ultimately that comes down to developing an agile and adaptive security strategy”
MARTIN RILEY, DIRECTOR, MANAGED SECURITY SERVICES, BRIDEWELL CONSULTING
Top 10 cybersecurity predictions for 2022
1.2022 will be the year of remote risk. With remote and hybrid working here to stay, expect to see a large increase in mobile malware attacks. Cybercriminals will evolve and adapt their techniques to exploit the growing reliance on mobile devices and remote working.
Social engineering will remain the initial attack vector for deployments of malware, phishing and ransomware, with an increase in deepfake technology making attacks more technologically convincing in 2022.
Phishing volumes have already surpassed levels seen in 2020, and this year we’ll see a rise of update-themed phishing emails designed to trick remote employees into believing they are legitimate updates, as well as those used to tailgate employees into restricted areas under the guise of being a new employee hired during lockdown.
2. Ransomware will become automated. Human operated ransomware will be the biggest cyber risk for organisations in 2022. Different from traditional commodity ransomware attacks, we’ll see more cybercriminals with a high level of offensive security knowledge gain access to organisations and survey the environment for an extended period before launching a potentially devastating attack on data and systems.
The risk presented by human-operated ransomware will only increase as wormable variants such as WannaCrypt and NotPetva are utilised more. Additionally, automation will play a key part in the evolution of modern ransomware and malware attacks, with machine learning and Artificial Intelligence (AI) used to remove some of the mistakes that allow businesses to respond to current threats.
3. Volume of hackers-for-hire will increase. Over the past few years, groups such as REvil and DarkSide have appeared and disappeared after carrying out very public attacks against numerous industries. In 2021, we saw a number of hacker groups arrive, have a big impact, and then vanish as quickly as they came, only to repeat the same process again a few months later.
In 2022 we can expect more of the same; in particular, large attacks on lucrative targets such as supply chains and cloud providers to maximise ransom value and payments. Managed services and thirdparty suppliers will also be under greater risk. Phishing-as-a-Service will become commonplace on dark web forums, increasing attack volumes.
4. Zero-Trust will become the de facto cyber security approach. With the rise of hybrid working, Zero-Trust will become critical in 2022. Lack of secure cloud configuration will continue to cause security breaches and organisations will seek to separate users and devices from data, applications, infrastructure, and networks, through the Identify, Authenticate, Authorise and Audit model (IAAA).
More CIOs and CISOs will roll out system-wide Multi-Factor Authentication (MFA) with stricter rules around conditional access built-in and supported by session information and telemetry to develop a comprehensive audit trail for real-time detection of a policy breach. Extended Detection and Response (XDR) will also become the technology of choice for Zero-Trust, enabling rapid detection and response of threats across endpoint, network, web and email, cloud and importantly, identity.
5. Organisations will turn to hybrid SOC models to plug skills gaps and aid consolidation. As the cyber skills shortage grows and enterprises lack security professionals with the depth of knowledge and technical skills to develop more advanced capabilities required for running a cloud-native modern Security Operations Centres (SOC), we will see more organisations turn to hybrid SOC models which combine the cyber skills of in-house teams with the expertise of a Managed Security Service Provider (MSSP).
Companies will use providers to plug gaps in defences while developing in-house expertise in tools and techniques including EDR, XDR and intelligence-based threat-hunting. Hybrid SOCs will also be used to facilitate consolidation of security tools, driven by a growing desire from the board to reduce security costs, maximise ROI and improve efficiency.
6. Rise in 5G and connected devices will increase IoT risks. 5G will continue to be rolled out globally in 2022 and increase the number of connected devices within organisations, particularly within industrial IoT. Manufacturing and Critical National Infrastructure (CNI) will remain the sectors most susceptible to security issues, with more factories and facilities becoming connected and more organisations reliant on IoT devices for measuring and monitoring processes remotely. Expect to see the introduction of more government guidance and standards to bolster IoT security as uptake increases.
7. Organisations will shift focus fromprevention to detection and response. As the speed and complexity of attacks continue to grow, demand for managed security services, such as Managed Detection and Response (MDR) will rocket. No longer the luxury of large enterprises, in 2022 expect all companies to seek to shift from prevention to response and look to implement early warning systems to alert on early signs of a potential breach.
Security Orchestration Automated Response (SOAR) solutions, such as Microsoft Sentinel, will be critical alongside MDR to help to improve the efficiency. Traditional tools such as anti-malware software and spam blockers will still be important, but these will increasingly be combined with proactive tactics, such as MDR, threat hunting, and ethical hacking to ensure any vulnerabilities are identified and mitigated immediately.
8. Critical National Infrastructure will face more threats. CNI will face increased activity from nation state groups, which are likely to prioritise green energy targets given the global focus on the development of sustainable infrastructure. The oil and gas sector will also be the subject of more directed attacks from hackers-for-hire as they attempt to target high-value income industries.
9. Cybersecurity transformation will drive digital transformation. Digital transformation became a necessity for businesses in 2021, driven largely by Covid-19. Probably the biggest mistake we saw in 2021 was a reactive approach to security transformation, whereby security was only considered afterwards. In 2022, expect to see this model flipped with a rise in mature companies who seek to use cybersecurity transformation as the driver for digital transformation.
Cybersecurity will shift from a box-ticking exercise to a business enabler, with CISOs and CIOs working directly with the CEO to develop an adaptive and customisable security model to ensure cybersecurity is as strong as possible before broadening the attack surface further.
10. Cybersecurity vendors will start to consolidate. Microsoft and Google willevolve to become leaders in cybersecurity. Microsoft has already announced a huge commitment to growing its cybersecurity offering and given the company’s dominance in the collaboration market and Google has already taken huge steps to bolster its security expertise.
As both companies continue to build their expertise, we expect to see traditional cybersecurity players start to lose market share as they struggle to keep up with the visibility, coverage and collaboration benefits the global giants can offer.
ABOUT BRIDEWELL CONSULTING
Bridewell Consulting is the second-largest and one of the fastest-growing, privately-owned, cybersecurity services firms in the UK, with its security operations centre protecting some of the country’s most critical national infrastructure.
It also delivers a vast number of services across aviation, financial services, government and oil and gas. The company hold a number of industry accreditations including NCSC, CREST, ASSURE, IASME Consortium, Cyber Essentials Plus, ISO27001, ISO9001 and are PCI DSS QSA Company. The company was recently named Cyber Business of the Year in The 2021 National Cyber Awards and won the SME 100 Growth (Under £10M) and Tech Company of the Year awards at the Thames Valley SME Growth Awards 2021.
Our cover story investigates how the latest cybersecurity technologies ensure the Commonwealth Bank and its customers are protected from cybercrime
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Our cover story this month charts how the Commonwealth Bank is strengthening its cybersecurity posture to protect 16 million customers
Welcome to the latest issue of Interface magazine!
Cybersecurity, and the need to share data safely and securely, goes beyond the day to day requirements of one organisation, it’s about enterprises at all levels collaborating to develop an ecosystem for the greater global good.
Our cover star Memo Hayek, General Manager Group Cyber Transformation & Delivery at CommBank, is leading a team on such a journey while executing the technology transformation required to fortify cybersecurity for CommBank. Leveraging the latest cutting-edge technologies from partners including AWS and Palo Alto Networks – in demand as the global attack surface grows – Hayek is flying the flag for women in STEM careers and delivering the strategies to ensure the bank, its Australian community and the wider global economy are protected from cybercrime.
https://www.youtube.com/watch?v=jQNXY2duLZs
Philip Morris International
Also in this issue, we learn how Philip Morris International (PMI) is instigating a digital revolution in the travel retail sector, merging the physical and online worlds by implementing a number of CX-driven initiatives framed around PMI’s IQOS brand which is helping smokers to non-smoke products.
Valtech
We hear again from global business transformation agency Valtech on its efforts to embrace diversity across the length and breadth of its organisation to make it better able to provide solutions that touch all of society. Una Verhoeven, VP Global Technology, gives her perspective on the diversity debate and how that’s further supported in the technological evolution with the rise of composable architecture.
Digital Transformation
Elsewhere, we discover how biotech firm Debiopharm’s digital transformation journey is ushering in a new era for drug development and clinical trials. We also reveal the innovative global IT transformation plans of market-leading tile manufacturer Terreal.
Our exclusive cover story this month explores how IAG Firemark Ventures is disrupting insurance to reimagine the customer journey today…
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Our exclusive cover story this month explores how IAG Firemark Ventures is disrupting insurance to reimagine the customer journey today
Welcome to the latest issue of Interface magazine!
Technology with the capacity to enhance customer journeys and evolve in line with our changing needs is the holy grail that the companies featured in this packed issue of Interface are on a quest to deliver…
Our cover star Scott Gunther, General Partner at IAG Firemark Ventures, embodies that pioneer spirit. Leading the investment arm of Australia and New Zealand’s largest insurer to think like a startup and drive innovation in the FinTech & InsurTech space, Gunther’s vision is being realised… “We not only provide staple financial services but the solutions that can make the world a safer place by reacting to everything from natural disasters to life-changing events.”
Trusted by 95% of Fortune 500 companies, Microsoft Azure is delivering transformative cloud journeys for organisations at all levels. Laurent Pierre Jr, General Manager for Azure Customer Experience Engineering Support (CXP), reveals how by creating a high trust environment, the speed at which you and your team can execute and perform becomes a force multiplier.
Keeping with the theme of transformative tech, BSI talk us through the innovation behind the extraordinary world of immersive auditing, outlining its advantages and the potential for a continuous wave of disruption set to provide deeper client value and change the dynamics of assurance forever.
Also in this issue, we hear from Lockton Re on how its global reinsurance business is benefiting from the deployment of smart solutions that leverage new technologies; speak with the CIO at the Office of Inspector General (a part of the US Department of Health & Human Services); discover advances in the digital approach to identity validation with Okta and get the lowdown from Vodafone on how blockchain has the potential to disrupt telcos.
Our exclusive cover story this month takes a drive down the information superhighway with Auto Club Group and the Automobile…
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Our exclusive cover story this month takes a drive down the information superhighway with Auto Club Group and the Automobile Association of America.
Welcome to the latest issue of Interface magazine!
A customer centric approach to the creation and deployment of digital services is something that unites the business transformation journeys we explore in this issue of Interface.
Our cover story examines how one of the oldest organisations in the US – the Automobile Association of America (AAA) – and Auto Club Group, among its largest affiliates, are building trust in technology through cybersecurity to support more than 14 million members with a range of digital services. Chief Information Security Officer, Gopal Padinjaruveetil, explains: “Cybersecurity can be the brake in the information vehicle so a business doesn’t have to slow down, enabling it to accelerate change with confidence without putting the organisation, and its members, at risk.”
Elsewhere, we discover how insurance giant Generali is leveraging analytics and AI on a global scale for a structured approach to insurance services delivering long term security and peace of mind for its customers as a lifetime partner.
Delivering innovation on a global scale, SAP’s customer-centric business technology platform currently serves 91% of the organisations making up the Forbes Global 2000, while a staggering 70% of all global transactions touch an SAP system. We find out more…
Also in this issue, we hear from Insider on why Apple’s iOS15 update will impact ecommerce and data gathering; we get the lowdown from EY on the four key steps organisation should take to accelerate their digital transformation and learn from Pulsant how to identify and achieve your business transformation goals.
IT heads say data leaks in the home will cause the biggest security headache over the next two years as…
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IT heads say data leaks in the home will cause the biggest security headache over the next two years as hybrid working arrangements see employees buying and installing their own technology, according to new research by Brother UK.
More than a third (34%) of the respondents cited the issue as their top concern as more decentralised purchasing decisions for devices such as laptops, printers and scanners are creating more data vulnerabilities.
The research, which surveyed 500 IT leads working for UK businesses, found that just 13% expect employees to be in the office full time over the next two years.
Work to minimise security risks was signalled by almost a quarter (23%) of respondents anticipating that office technology would be centrally procured with employees purchasing home tech from approved supplier lists over the next two years, up from 19% that currently have this procurement model.
However, 11% of IT leads said they expect all office and home technology to be procured by employees on their own over the same period, compared to 5% that currently operate in this way, which could signal some additional challenges for security in the future.
Other top concerns included data security in the office (27%), network security for remote workers (13%) and accountability (12%).
Mike Mulholland, head of services and solutions at Brother UK, said: “The immediate challenge for IT leads in managing people working from home is ensuring that the technology connected to business systems is secure.
“This is part of a wider opportunity for the channel, as they help customers respond to new challenges from the workforce becoming more dispersed, by providing new solutions and services.
“But it’s important that suppliers consult with clients on balancing the efficiencies gained from decentralised procurement against the security and integration that’s more assured from centralised decision making.
“Helping customers to build lists of approved technology for employees to procure from may pay dividends in productivity and security benefits.
“It will also be important for IT vendors and partners to advise when managed services can offer the best outcomes for businesses. Managed print services, for example, gives IT managers full oversight of print fleets wherever they may be, enabling them to manage security settings, firmware updates, and diagnostics from afar.”
Overall, the research found security to be the top priority for IT heads. Almost two-thirds (63%) saw the issue to be as being ‘very important’ over the next two years, compared to 52% that said the same for productivity, 50% for cost-efficiency and 48% for sustainability. Nearly half (49%) associate security with business resilience, while two-thirds (66%) said they are currently working towards improving their IT security in order to underpin resilience.
Ben Nicklen – chief operating officer for workplace data analytics firm Tiger – explores the range of comms channels that are available and shares when there’s a need to ‘start video’
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Transformation has accelerated on a global scale for organisations throughout 2020. Many businesses and employees who hadn’t previously adopted the latest collaboration technology, are now doing so – and swiftly.
The numbers tell a significant story. For example, Cisco WebEx and Google Meet have seen 100 million meeting participants in a single day, 200 million recorded for Microsoft Teams, and a staggering 300 million for Zoom.
So, while we might feel lucky to have access to all this technology, some of these working practices are maybe taking their toll on individuals that are experiencing ‘Zoom fatigue’.
There has never been a greater requirement for organisations to stay connected. At this moment in time, millions of businesses across the globe will be logging into meetings, answering calls, checking instant messages and clearing inboxes.
With a range of collaborative tools now firmly at a modern-day company’s disposal, it’s no surprise that there has been a rise in certain intuitive technology as colleagues speak to one another while working remotely. For the enterprises that are used to operating from an office, they will have experienced many more video calls compared to pre-pandemic times.
But are some teams prioritising video, when a traditional call might do? Especially when this method can drive conversations to be wrapped up swiftly and ensure urgent matters are handled there and then.
There has, in fact, been a significant shift in traditional telephony throughout 2020. Organisations have also used it as a central component to newly rolled-out customer schemes that are based upon keeping in touch. And for companies that have had to shut physical stores, diverting their phones can mean many are still able to trade.
How communication continues to evolve
Thinking about productive business calls pre-pandemic, these were typically made in their car or on public transport when travelling between meetings. So, when employees who are so used to communicating on the move, are suddenly told to stay put in their home and adopt a more video-friendly approach, it’s no wonder that several may have struggled to transition.
For workforces relatively new to Teams, Zoom and Google Meet calls can bring a sense of apprehension. Colleagues might be worried about Wi-Fi speeds, the flow of the conversation, how they act on screen and what impression their background makes.
There’s a certain level of trust attached to video too, with many employees perhaps feeling as though they always have to be based in an office-style setting when firing up their cameras. And none of these concerns would enter their minds when making an audio call.
However, this isn’t a case for pitting the phone against video – or choosing one over the other. In fact, it’s about understanding the critical role both play in a company’s entire suite of collaborative technology.
To truly know which comms method is required, a good place to start is to consider why a call has to be made in the first place. Is there something visual that’s required? Or does an employee want to replicate those ‘water cooler’ moments to feel better connected and less isolated? If these resonate, then perhaps video is the best course of action.
Once that’s been decided, add an agenda so that individuals know the reasons behind the meeting and where they’re required. For the longer calls, a good tip is to include regular breaks, so employees don’t get distracted or lose focus. Having simple guidelines in place – and communicating them effectively – can help to underline why video is preferred over a quick-fire phone call or less urgent email.
Why more organisations must revisit their suite of comms software
Throughout 2020, there has understandably been a dramatic increase in collaborative tools. It’s anticipated that enterprises have experienced 10 years of remote working transformation – within six months. So, there is a real need to provide an all-around communicative approach to ensure that customer and colleague comms remain of the highest quality.
With human integration and social interaction now a huge priority for teams working in isolation, video is here to stay. And business leaders must utilise a combination of intuitive tech in the right way – understanding how each one positively impacts their workforce’s productivity and well-being, alongside the organisation’s overall bottom line.
That’s where workplace analytics plays a pivotal role. Not only does it support ambitious firms to remain agile and be able to adapt swiftly to economic flux, but it helps their managers to gain visibility of employees’ activities – providing the vital data to make business-critical decisions that truly enhance the colleague and customer experience in both the short and longer-term.
Learn more about emerging trends across the tech panorama in the latest issue of Interface
Oliver Goodman, Head of Engineering at Telehouse, explains the impact AI is having on data centre security and energy efficiency
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Demand for data centre (DC) services has been steadily rising every year, but since the beginning of the COVID-19 pandemic, that demand has skyrocketed with people and businesses more reliant on them than ever before. Despite some operators scrambling to overcome capacity shortages, the sector has coped well with the increased demand and has even achieved greater recognition with the UK government giving the sector a voice on COVID-related matters and DC workers being given key worker status.
Relying on human monitoring and intervention can be problematic when trying to stay on top of three of a DC’s biggest challenges – energy efficiency, electricity costs and cybersecurity – when demand is rapidly rising. This is where AI can help.
Maximising energy efficiency and minimising cost
It’s no secret that DC facilities are power hungry, so it would be easy to assume the sector has a negative environmental impact. However, this simply isn’t the case. A recent survey of UK commercial operators revealed that 76.5% of the electricity they purchased is 100% renewable – 6.5% is between 0 and 50% renewable, 7% is between 50% and 99% renewable and 10% is purchased according to customer demand. But that doesn’t mean DC operators aren’t going further to improve energy efficiency, and this is one area where AI can help.
The load (the amount of energy consumed by servers and network equipment in server halls) can vary at given time depending on the network demand and accommodating the load efficiently is challenging without the intervention of AI. For example, if the load suddenly goes up in one server hall, additional chilling is required to keep the servers cool and running efficiently. Energy efficiency gains can be made by knowing exactly when to switch that additional chiller on and when to switch it off.
By collecting, aggregating and analysing operational data, AI can set certain trigger points and execute actions – such as switching the chiller on or off – at exactly the right moment. Machine Learning can also by deployed to understand load patterns and predict when fluctuations in load will occur, allowing DC operations to react efficiently. In an uninterruptable power supply (UPS), AI can switch between efficiency modes automatically in response to changing load levels, ensuring the system runs as close to the optimum efficiency for the load at any given time.
This can also be applied to reducing electricity overheads. Balancing energy efficiency with the cost of electricity is a constant struggle for DC operators. With loads increasing every year, operators are faced with growing electricity bills. Attempts to keep electricity costs low can impede upon the energy efficiency of the facility. For example, running chillers at 10% of their capacity is one way to minimize electricity costs but this means the chillers will run inefficiently.
IT Programmer Working in Data Center System Control Room.
AI can be used very effectively in control systems to help operators balance cost and efficiency. This is improving over time but there is an onus on the manufacturers to make these developments faster so that operators can build greater levels of automation on top of those systems to help strike the right balance.
Robust cyber security measures
Increasing cyber security in DCs largely comes down to understanding behavioural patterns in the IT infrastructure and reacting immediately when a typical pattern is disrupted by an atypical behavioural event. This is very similar to the way cyber security works in a conventional office-based business. Each company device will have its typical usage pattern and AI can understand how individual devices typically interact with the network. A device logging on to the network outside of regular working hours and extracting data from the system would be an unusual behavioural event and AI can recognise this then disable the device’s network access and notify the business of a possible attempted security breach.
In the context of a DC, AI will monitor the behavioural pattern of every server and will react accordingly to any event that diverges from the typical pattern. These AI capabilities can be leveraged at an extremely granular level to further enhance security. For example, if a server’s behaviour suddenly changes after somebody has been present in its server hall. This kind of granularity offers huge potential for DCs from a cyber security perspective and will continue to improve security as demand for their services grows.
Where humans would typically struggle to make data-informed split-second decisions that could improve energy cost and efficiency or stop a data breach, AI is helping the DC sector to evolve. It’s an exciting time for the sector and we can expect to see decision-making becoming more intelligent and autonomous as AI-driven solutions continue to evolve.
Learn more about emerging trends across the tech panorama in the latest issue of Interface
Local surgical hubs, new technology to speed up diagnosis, and innovative ways of working, will help the NHS to tackle…
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Local surgical hubs, new technology to speed up diagnosis, and innovative ways of working, will help the NHS to tackle growing waiting lists and treat around 30% more patients who need elective care by 2023 to 2024.
Backed by a new £36bn investment in health and social care over the next three years, ‘doing things differently’ and embracing innovation will be the driving force to get the NHS back on track.
The funding will see the NHS deliver an extra nine million checks, scans, and operations for patients across the country, but it’s not enough to simply plug the elective gaps. The NHS will push forward with faster and more streamlined methods of treatments.
Surgical hubs already being piloted in a number of locations are helping fast-track the number of planned operations, including cataract removal, hysterectomies and hip and knee replacements, and will be expanded across the country. Located on existing hospital sites, surgical hubs bring together the skills and resource under one roof while limiting infection risk and providing a COVID-secure environment, with more planned to open in the coming year.
Health and Social Care Secretary, Sajid Javid, said: “This global pandemic has presented enormous challenges for the NHS and led to a growing backlog – we cannot go on with business as usual.
“We are going to harness the latest technology and innovative new ways of working such as surgical hubs to deliver the millions more appointments, treatments and surgeries that are needed over the coming months and years to tackle waiting lists.”
GP surgeries are also using artificial intelligence to help prioritise patients most in need and identify the right level of care and support needed for patients on waiting lists.
Using the latest technology and locally led innovation will increase efficiencies, make every penny count and increase activity levels to tackle rising backlogs.
Martin Riley, Bridewell Consulting’s Director of Managed Services, explains why a cyber security strategy can future proof your business and provide the platform for a successful digital transformation
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Regardless of sector, digital transformation has become a business necessity for organisations in 2021. Described as the most important trend in business today, 65% of the globe’s GDP is expected to be digitalised by the end of 2022. And with promised benefits including improved operational efficiency, agility and employee productivity, it’s no surprise that businesses are going digital.
However, while there’s no denying the importance of digital transformation, different levels of organisational maturity can lead to different approaches and this is particularly apparent when it comes to security. Many organisations often take a reactive approach, whereby business and technology transformation are the priority and security is only considered afterwards. However, the risks from putting security on the backburner can be numerous, including higher costs and extended timelines to retrofit crucial security fixes.
Martin Riley
More mature companies have a different approach – one that puts security transformation first, ahead of digital transformation, to ensure the best possible future-proofed outcome. Their success is now providing a valuable proven blueprint for other firms to follow. So, to reap the benefits of this approach where should you start?
Shift your mindset
Before embarking on any transformation, it’s imperative to get your strategy right. Move away from thinking purely about digital transformation and cyber security as separate strategies and instead develop a cyber security transformation strategy. This will ensure that you can reduce risk and improve your cyber resilience, even as your attack surface grows.
It may be that security transformation becomes the driver of your digital transformation. For example, if you have identified vulnerabilities within your legacy IT infrastructure that necessitates a need to move critical data to the cloud.
Take critical national infrastructure as an example… The convergence of IT and Operational Technology (OT) as well as increased legislative requirements, such as the Network and Information Systems (NIS) Regulation, is driving a clear need for cyber security transformation. Organisations need to adapt to gain a holistic view of cyber security across physical OT and cloud systems before transformation can take place.
Understand your risks
Digitalising your business ultimately introduces new risks. For example, new digital channels can broaden your attack service, while poorly configured cloud-based infrastructure can pose easy targets for cyber attackers. There’s also risks from the internet of Things (IoT) which increases sensitive data proliferation (and by association, vulnerabilities), as well as authentication and access risks posed by remote working and connected supply chains. Before embarking on a transformation plan, you need to understand the security implications of any changes.
Assume zero-trust
In order to ensure that security is front of mind in your transformation you need to adopt a philosophy of a zero trust, where no individual or device is trusted. This involves verification by authenticating and authorising based on all available data points, utilising just-in-time and just-enough-access to limit user access and using analytics to drive threat detection. Not only does this help businesses to be prepared for cyber threats, but also articulates the value of security transformation to other departments.
Embed security from the outset
It can be tempting to simply keep investing in a growing number of security technology tools as and when your transformation takes place. However, all too often there is little integration, overlap and there are gaps in the coverage these tools offer. And while a well-configured set of security tools can provide coverage, many drive threat alerts that are false positives or benign positives, leading to fatigue and alert blindness. Instead, ensuring security is a critical part of the initial design of your transformation strategy.
Use security intelligence to your advantage
Move away from a focus on prevention to response and make security intrinsic throughout the business by implementing proactive measures such as Managed Detection and Response (MDR). By combining human analysis, artificial intelligence and automation to rapidly detect, analyse, investigate and actively respond to threats, MDR can encourage alignment of security transformation with digital transformation.
Cyber Technology Security Protection Monitoring
An adaptive and customisable security model, MDR can be deployed rapidly and cost-effectively as a fully outsourced service or via a hybrid SOC. It helps develop a reference security architecture that enables you to safeguard on-premise and legacy systems, cloud-based infrastructure applications and SaaS solutions, whilst also protecting and responding to new security and user identity threats as well as reducing cyber risk and the dwell time of breaches.
Engage third party support
Finally, don’t neglect to seek help from outside your organisation. By engaging a security architect early on in your project lifecycle, you can benefit from robust and detailed analysis and expertise to ensure the correct decisions are made, tracked and traced from beginning to end. They can also help you understand the interdependencies across your IT estate, identify risks and suggest best practice, as well as legal and regulatory obligations to ensure you continue to be able to withstand a range of cyber attacks throughout your transformation.
Reaping the rewards of cyber security transformation
Every business is on a digital transformation journey, regardless of size or objectives. However, as organisations transform, so do technology and cyber threats. Those that fail to adopt a more proactive and efficient system for mitigating risks and handling, responding, detecting and learning from cyber security attacks will find themselves falling behind and the security function unable to keep up.
Ultimately, cyber and digital security should be thought of as inseparable – and those that can plan and integrate both into their transformation projects from the very beginning will be in the strongest position to succeed and future-proof their business.
By implementing a robust cyber security transformation process and proactive security measures, such as MDR that can support secure digital transformation, you can reap the benefits of a stronger, structured system for managing, isolating and reducing threats and continue to pivot, transition and serve in the new digital economy without leaving security on the side-lines.
Bridewell Consulting
Bridewell Consulting is a specialist cyber security and data privacy consultancy. NCSC Certified and CREST accredited, it provides reliable, high-quality security and risk consulting services; helping its customers protect not just their data, but their reputation, customer trust and bottom line. Providing four core service areas: cyber security, data privacy, penetration testing/red team assessments and managed security services, Bridewell’s expert team of professionals possess specialist industry experience and proven capabilities. They can deliver effective cyber security and data privacy services across financial services, pharmaceutical, manufacturing, technology, retail, media, government, aviation and 24×7 critical services. As a vendor agnostic business, Bridewell is able to effectively and honestly engage with business executives and provide advice, guidance and services in a way that is most appropriate for each organisation, ensuring that proposed solutions are aligned with its clients’ strategy, business objectives and the wider IT architecture.
Learn more about emerging trends across the tech panorama in the latest issue of Interface
we.CONECT offer a virtual and hybrid approach to live events planning delivering tomorrow’s business engineering today
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we.CONECT was founded in 2011 by two self-confessed “passionate event industry geeks” with an entrepreneurial spirit. Henry Fuchs and Daniel Wolter saw an opportunity to meet the need for change within the event industry with a new approach to b2b-conferences within the innovation, enterprise and tech sectors.
Henry Fuchs
“We have grown by more than 50% yearly ever since,” reveals Henry. “Today, we serve engineering and manufacturing, automotive, digital transformation and the IT sectors across DACH, Europe and the US market. Our focus has always been on interactions and creating forums and platforms for meetings and connections. This allows decision-makers to interact and network with their peers and get the latest ideas and industry trends. In our environment, they will be given opportunities to grow their businesses and skill sets.”
A diverse network
we.CONECT boasts a 50,000+ strong network, taking pride in having companies as clients rather than simply defining their attendees as the audience. “Our ambition is to fuel them with new ideas, new connections and new inspiration,” pledges Daniel. “We attract everyone from specialists and strategists to management newbies, geniuses and visionaries to help the world’s biggest brands, most innovative companies, and the most promising start-ups, shape tomorrow´s business.”
Daniel Wolter
The rollcall of clients is impressive… Adidas, Adobe, Amazon, BASF, BMW, Coca-Cola, Daimler, Google, Paypal, Nasa, Tesla, Apple are all part of we.CONECT’s network of business partners enjoying unique event experiences alongside the likes of Bosch, Cisco, IBM, Microsoft, Nvidia, Samsung, Siemens and SAP.
The 1.5 million business users in we.CONECT’s ecosystem demand excellent networking and learning opportunities. “Our events are packed with more than 30 session formats covering different interactivity levels – strongly geared to our customers’ needs,” says Henry. “The problem solving and discussion focused world café-sessions and our ‘Live Tech Take’ are two great examples of formats our clients greatly appreciate.”
Digital ‘managed’ events
we.CONECT’s Digital Managed Event (DME) offering is for exhibitors that don’t want to share their leads with others. “They bring the content and the crowd; we assist with the hosting, event infrastructure and marketing of the event,” explains Daniel. “With a DME, exhibitors have an opportunity to tailor-make an event relevant to their product and solution; it’s a chance to invest in your own exclusive and customised format.”
Hybrid connections
we.CONECT’s hybrid business event portfolio offers business leaders from all over the world exclusive content, leads and an opportunity to be a part of evolving business communities to gather information, share knowledge, network with peers and find solutions for business-critical challenges. “We believe it’s imperative to be part of a new world of networking with other global players and niche businesses both live and fully digital in an ever-changing world,” asserts Henry. “The hybrid format delivers in that regard. It offers total flexibility, is COVID-compliant and enables both the audience and the exhibitors a chance to make the most of their experience.”
hubs101
Daniel and Henry began innovating with the digital transformation of events back in 2016 through the development of their own event app platform and in 2018 with their own first digital events – long before Covid became an issue.
“When the pandemic hit, we were able to react with agility and digitalise our entire event portfolio in 2020,” recalls Daniel. “One of the key enablers was our own virtual event platform, hubs101. It’s a complete platform, built on our event insights and know-how with the latest technology in focus. We’ve gradually developed it over the years, like the company itself, with constant tweaks and improvements. hubs101 has now been road-tested by more than 10,000 customers and hosted over 500 events, which is just the beginning…”
The we.CONECT team continually add new functions to improve usability based on the feedback received from each event. These invaluable insights contribute to the continued innovation of 30 different session formats that inspire attendees to interact and learn from each other’s experiences.
The timing of the public release of hubs101 with the pandemic was a coincidence but the team felt the platform had reached a stage where it could be beneficial for others. “Before Covid, we’d launched the platform to host 12 online events,” remember Henry. “When the lockdowns started, we identified the potential for virtual events and were able to scale up the platform to host most of the used-to-be on-premises events, working on over a hundred in 2020.”
AI matchmaking
hubs101 users can enter their event interests, business goals, and expectations on the platform; that data is sorted and matched with other participants’ entries. The AI matchmaking function enables hubs101 attendees to find the business partners they’re looking for and connect with them immediately. This saves time and avoids the uncertainty to connect with the right person on an on-premises event, and thus helps businesses reach their ROI more quickly.
Germany, Berlin, 18.09.2019 – Industry Of Things conference in Berlin 2019.
Marcel Wogram for WeConect.
“Our goal is to provide event attendees with the best event experience,” adds Daniel. “Therefore, we’re constantly searching for ways to take the current online event experience on hubs101 to the next level. Right now, users can attend a virtual event smoothly and find the right business partners with an AI matchmaking function. And we aim to expand that function to include not only attendee matching but also interest matching. In the future, hubs101 users can expect to meet the right person and get suggestions for the right event, based on their own goals and expectations they provide to the platform.”
The pandemic has accelerated the process of event digitalisation. Henry and Daniel have embraced the challenge and are determined to continuously help define the future of the event industry, and to transform as many events as possible to a full-scale hybrid experience. “In these times when marketers worldwide rank virtual events as a top three method to generate leads, boost revenue and improve brand impact, we.CONECT and hubs101 can help shape and improve any company’s future strategy and tactics for events and meetings.”
Learn more about emerging trends across the tech panorama in the latest issue of Interface
The Mobile Ecosystem Forum’s SMS Protection Registry, which was developed and piloted in the UK, is now being launched in…
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The Mobile Ecosystem Forum’s SMS Protection Registry, which was developed and piloted in the UK, is now being launched in Ireland and Singapore.
The Registry significantly reduces the impact of smishing (SMS phishing) and spoofing by SMS.
In the UK, many major banks and government brands are currently being protected with 352 trusted SenderIDs registered to date. Over 1,500 unauthorised variants are being blocked on an ever-growing list, including 300 senderIDs relating to the government’s coronavirus campaign.
Government agencies, including HMRC and DVLA, are participating in this ecosystem wide anti-fraud solution which is supported by BT/EE, O2, Three and Vodafone, along with the UK’s leading message providers.
The cross-stakeholder working group has seen a significant drop in fraudulent messages being sent to the UK consumers of the participating merchants. Following the success in the UK, The Ireland SMS SenderID Protection Registry is being launched.
The Registry is also launching in Singapore as The Singapore SMS SenderID Protection Registry. With strong interest from numerous other territories, MEF expects new Registries will soon follow.
“There are millions of faked SMS sent by fraudsters trying to steal passwords every day,” says Dario Betti, CEO of the Mobile Ecosystem Forum “We need to help consumers and organisations fight back. Thanks to the collective efforts of the British mobile industry MEF has managed to show a way: a Registry for SMS short-code names.
“The fight against fraudsters is a relentless one, it will never stop. But we are happy to celebrate one successful tool created in the UK.”.
This month’s exclusive cover story focuses on how global digital agency Valtech is on a mission to inspire organisations to…
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This month’s exclusive cover story focuses on how global digital agency Valtech is on a mission to inspire organisations to embrace inclusivity, supporting everyone to succeed in tech…
Welcome to the latest issue of Interface magazine!
Technology and its ability to transform the human experience for all the stakeholders of any business, from customers to employees to partners, is the defining theme of this issue of Interface.
At the heart of this line of inquiry, our cover story reinforces why technology should be for everyone. Valtech, a global digital agency focused on business transformation, is on a mission to encourage organisations to embrace inclusivity, “inspiring everybody to have an authentic voice” by supporting women and people of all walks of life to succeed in tech-based careers. Our interviewee, Sheree Atcheson, Global Director of Diversity & Inclusion, pledges: “We are trying to do something that leaves the world better than we found it.
https://www.youtube.com/watch?v=4W25hWRdDMA
Elsewhere in this issue, we explore the rise of AI in banking and learn how solutions are being deployed by UnionBank of the Philippines. Dr. David Hardoon, Senior Advisor for Data & AI, explains how the bank is better leveraging data to drive financial inclusion with the delivery of services to the underserved and unbanked. We also speak with Alexandre Kozlov, Head of International IT at Kelly Services, and discover how the staffing giant is embracing business relevant IT with tech that puts people – clients, candidates and recruiters – first.
Also in this issue, we.CONECT tell us how they are using technology to bring people together for virtual live events; we explore AI’s influence on data centre management, and discover why security can future-proof your digital transformation journey.
Ericsson and Vodafone have completed the first deployment of a new energy-efficient 5G radio in London as part of their…
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Ericsson and Vodafone have completed the first deployment of a new energy-efficient 5G radio in London as part of their collaboration to improve network energy performance.
Situated on the roof of the Speechmark, Vodafone UK’s central London office, the controlled deployment of Ericsson’s antenna-integrated radio solution (AIR 3227) saw Vodafone’s daily network energy consumption decrease by an average of 43% in direct comparison to previous generations of radio technology, and as much as 55% at off-peak times.
Future-proofing 5G networks
Designed for future-proof and sustainable networks, Ericsson’s new radio is 51% lighter in comparison, and its more compact design and improved energy management features will help to optimize overall site footprint, making 5G rollout and 4G upgrades faster and easier.
1500 of the new radios will now be deployed across Vodafone’s network by April 2022, helping to reduce Vodafone’s forecasted energy consumption of its future 5G network and support a sustainable and responsible 5G rollout.
Vodafone partnering with Ericsson to drive efficiency
Andrea Dona, Chief Network Officer, Vodafone UK, commented: “Our strategy is simple; turn off anything we don’t need, replace legacy equipment with up-to-date alternatives and use the most energy efficient options available. The success of this trial allows us to explore new ways we can more effectively manage the energy consumption of our network with our partner Ericsson.
“There is no silver bullet to manage our network energy consumption – it is about putting sustainability at the heart of every decision and adding up all the small gains to make a material difference.”
Björn Odenhammar, Chief Technology Officer, Networks and Managed Services, Ericsson UK and Ireland, added: “Building on the success of an award-winning 5G network in London, it is another fantastic achievement for Vodafone and Ericsson to reduce network energy consumption by a daily average of 43%.
“Sustainability is central to Ericsson’s purpose and our new radio will help Vodafone to reduce network energy consumption, simplify network rollout and efficiently manage the expected growth in data traffic of both current and future 5G networks. Together we are building the 5G network of the future – one that delivers the highest possible performance with improved resource efficiency and low environmental impacts.”
The global Machine Learning (ML) market is estimated to grow by a CAGR of 43% by 2029, according to a…
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The global Machine Learning (ML) market is estimated to grow by a CAGR of 43% by 2029, according to a new report from ResearchAndMarkets.
The major drivers for the ML market are identified as the proliferation in data generation, technological advancements in ML and the increased adoption of connected devices and their data driven application. Enterprises are now awash in data related to their customers, prospects, internal business processes, suppliers, partners and competitors.
The ResearchAndMarkets report found that, often, businesses can’t control this flood of data and convert it to actionable information for growing revenue, increasing profitability and efficient business operation. Organisations of all disciplines across the globe suffer a serious problem of managing data in the form of data retention, understanding dark data, data integration for proper analytics, data access and others.
Data volumes set to rise exponentially
Machine learning offers a promising solution to gain economic benefits from the increase in data with the help of predictive analysis and reducing fraud. The volume of data collected by businesses worldwide is estimated to double every year with a lack of understanding of data now cited as a primary reason that overruns project costs to the tune of 20-35% of operating revenues.
Big data capabilities can assist in providing constant changing customers preferences helping companies to improve customer satisfaction, enjoy faster decision making and develop strategies for launching new products while exploring new markets.
Machine Learning in BFSI remains indispensable
The global Machine Learning market has been segmented on the basis of verticals, deployment modes, organisation size and service. The vertical segment is further sub-segmented into banking, financial services, and insurance (BFSI), retail, telecommunication, healthcare and life sciences, manufacturing, government and defence, energy and utilities and other verticals. The BFSI segment leads the verticals in terms of revenue in the global ML market with around 21.9% market share in 2020.
BSFI is primarily driven by a growing demand for ML to automate the process of loan approval, for fraud prevention, risk management, investment predictions, marketing and other strategies. Prominent banks across the globe including JPMorgan Chase, Wells Fargo, Bank of America, Citibank, U.S. Bank and others have adopted ML to realise the potential benefits of data driven decision making.
Machine Learning in healthcare promises significant opportunities
The healthcare and life science vertical is anticipated to grow at the highest rate over the forecast period (2021-2029) growing at a CAGR of 44.3% over the forecast period. This high growth rate is attributed to the fact that ML solutions offer wide potential across the healthcare industry. This include patient data & risk analysis, in-patient care and hospital management, medical imaging and diagnosis, drug discovery, life style monitoring and management, medical diagnosis and imaging, precision medicine and more.
Additionally, key companies are providing various ML systems across healthcare; these include Google Deep Mind Health, IBM Watson and others. Moreover, increasing healthcare expenditure also leverages huge adoption opportunities for ML. According to the Institute of Health Metrics and Evaluations, global healthcare expenditure is expected to reach $18.28 trillion globally by 2040.
Learn more about emerging trends across the tech panorama in the latest issue ofInterface
The summer of 2021 has shown a vast variety of extreme weather events around the world and thereby given an…
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The summer of 2021 has shown a vast variety of extreme weather events around the world and thereby given an outlook on the consequences of the climate crisis. To limit global warming to safe levels, we need to do everything we can. The latest report by the UN’s Intergovernmental Panel on Climate Change confirms that it is crucial to reduce our emissions drastically and, on top of that, remove unavoidable and historic carbon emissions from the air permanently. Climeworks’ carbon dioxide removal via direct air capture technology is the only solution that can reduce atmospheric concentration of CO2 in a scalable manner, by capturing CO2 from the air today and storing it permanently underground.
Swiss Re’s pioneering commitment
Swiss Re committed in 2019 to reach net-zero operational emissions by 2030 by reducing their carbon footprint and removing any residual emissions. The company is committing to a unique long-term partnership with Climeworks.
Swiss Re and Climeworks are launching a cutting-edge collaboration by signing the worlds’ first 10-year carbon removal purchase agreement. This first of its kind agreement is worth $10m.
Both the length and the total value of the partnership are, so far, unrivalled in the voluntary carbon market for this type of innovative high-quality carbon removal. The partnership with Swiss Re is of integral importance to Climeworks: the re/insurance industry is at the forefront of assessing complex risk structures including those of climate change. Re/insurers are capable of structuring those risks and allocating them in an efficient way. Swiss Re’s unique long-term commitment sends a strong signal emphasising that a pure climate solution like Climeworks’ technology is important to reach the Paris Agreement climate targets.
Supporting the rapid scale up
This commitment is by its nature providing a structure for interested buyers to enter into similar purchase agreements with Climeworks. Swiss Re is sending a key demand signal to carbon removal solution providers and investors. Pioneering customers like Swiss Re and their long-term commitment prove that a market for measurable and permanent carbon dioxide removal already exists today and will grow significantly in the future.
Bringing climate solutions to scale not only requires the right demand signals, but also de-risking and financing. This is why the partnership between Swiss Re and Climeworks goes beyond the pioneering 10-year carbon removal purchase agreement with further joint activities being assessed together.
About Climeworks’ direct air capture and storage technology
Powered solely by renewable energy, Climeworks’ direct air capture plants capture CO2 from the air. In Iceland, Climeworks’ partner Carbfix mixes the CO2 with water and pumps it deep underground where it reacts with the basaltic rock formations and mineralizes: the CO2 literally turns into stone. Climeworks’ technology is scalable and does not compete with arable land. This September, Climeworks is going to launch its new large-scale direct air capture and storage plant ‘Orca’ in Iceland, bringing large-scale direct air capture technology to reality.
By Robert Hewitt, MB BS, PhD, Biosample Hub The UK has over 150 hospital-associated biobanks, and the function of these…
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By Robert Hewitt, MB BS, PhD, Biosample Hub
The UK has over 150 hospital-associated biobanks, and the function of these biobanks is to provide researchers with consented and carefully processed clinical samples. However, three years ago, the annual report of a UK agency called Medicines Discovery Catapult came up with a shocking finding. A survey conducted by the organisation found that 80% of SMEs (small-to-medium sized biotechs) found accessing samples from the NHS ‘unexpectedly difficult with the result that 75% imported samples from abroad’.
This is not a problem exclusive to the UK. Biotech companies everywhere in the world have great difficulty accessing high quality patient samples to support their research and development. And at the root of the problem is the simple fact that patient samples most often originate in a healthcare setting in the public sector. Biotechnology companies are in the private sector and therefore have reduced access.
Hospital biobanks
Hospital biobanks generally exist in teaching hospitals and academic centres. They are publicly-funded and are established for the purpose of supporting research in associated universities and institutes. They require dedicated staff and expensive equipment—such as liquid nitrogen freezers—so the start-up and maintenance costs are considerable. While the start-up phase may be funded by research grants, it is harder to obtain research funding for the on-going maintenance costs of these unglamorous-yet-essential core facilities. So, many biobanks survive on funding provided by their own institution. A typical hospital biobank may have 2-3 staff working extremely hard within a very tight budget to provide professionally-curated clinical samples for in-house researchers.
One way in which biobanks can develop an independent income stream is to charge a fee for the provision of patient samples. However, this must be approached with caution as it is illegal to make a profit from the sale of human tissue in many countries. So, biobanks are allowed to charge a carefully calculated cost-recovery fee.
Access to a biobank’s samples is decided by scientific and ethical committees that are populated by various institutional members (scientists, clinicians, administrators, ethicists), with the frequent addition of a patient representative. These committees judge the merits of each application for samples, and they operate according to institutional policies.
One issue that sometimes reduces the likelihood that samples will be provided to industry is the concern that some patients may not want their samples to be used by commercial organisations that make a profit from them. Whether patients react in this way is very much dependent on how matters are presented to them and whether or not the societal value of industry research is emphasised.
In many cases these biobanks are open to applications from industry, in theory at least. Biobanks of different specialities can be found in various national and regional biobank directories, but unfortunately their level of interest in working with industry is often obscure. So, we have the problem that useful biobanks are hard to find.
Biotechs and Big Pharma are very different
Sample access problems are bigger for smaller, younger biotech companies than for established pharma companies. For one thing, these pharma companies will have had many years to develop networks of hospitals supplying samples. Additionally, the fact that pharma companies conduct clinical trials gives them access to hospitals, doctors and patients. Many large pharma companies have teams of dedicated clinical sample procurement staff and their own in-house biobanks, which often dwarf those found in typical hospital biobanks.
In contrast, a small biotech company, particularly a start-up, has none of these advantages and certainly cannot afford to have staff dedicated to sample procurement.
Looking ‘abroad’
In general, the easiest way for biotech companies to obtain samples is to get them from a commercial broker. These companies have the sole focus of providing clinical samples for industry, and naturally they are driven by the need to make a profit.
Brokers generally find it difficult to obtain their samples from hospitals and biobanks in western Europe, where ethical concerns about the sale of human tissue are prevalent. Some countries in eastern Europe and parts of Asia provide a more reliable source. The USA is one industrialised country where brokers are much more accepted, with many US hospital biobanks being willing to supply brokers. The majority of brokers are based in the USA, and many of these have sample procurement operations that extend across global networks.
Scientifically-speaking, the main disadvantage of using a broker is that sample provenance may be lacking (brokers tend not to reveal their sources for business reasons) and along with this there may be uncertainty about the quality of the samples and hence the reliability of resulting research.
Encourage some practices, discourage others
It must surely be best practice for any researcher to obtain biosamples direct from source, that is, directly from the hospital biobank that collected the sample from the patient. In this way, they can have the most confidence that samples and data have been collected professionally. So biotechs should ideally obtain their samples direct from hospital biobanks.
To encourage this, we need to make it easier for biotechs and hospital biobanks to find each other. Biotechs can search a number of biobank directories to find suitable partners, but this is often a difficult approach. Many of the biobanks listed may not be open to working with industry, or may give companies a low priority. Use of biobank directories often results in a lot of disappointing false leads.
One initiative that offers a solution is the online platform, Biosample Hub. This international platform is dedicated to bringing biotechs and academic/hospital biobanks together, and its use is restricted to these two groups. It includes a directory of biobank and biotech members, a directory of sample requests and social networking features. The only reason for biobanks to be on the platform is to supply industry, so the problem of false leads is minimised. One other key aspect of the platform is that it is not-for-profit, so this overcomes the ethical concerns of many biobanks.
Another way to encourage this is to make it more attractive for hospital biobanks to work with industry. In other words, there need to be more and bigger incentives. The problem is that for many hospital biobanks, local academic researchers get top priority, other academic researchers get second priority, leaving industry at the end of the queue. This is natural, because these biobanks are established as institutional initiatives, with the purpose of serving their own institution. The focus of academic biobanks is very much on research productivity as measured by publication impact, and unfortunately industry, for reasons of intellectual property, faces restrictions about how much work it can publish and when.
The incentive of funding is certainly the most viable option for getting hospital biobanks to work with industry. Biobanks need funding and often operate on shoestring budgets. Much has been written on the subject of biobank sustainability, especially financial sustainability. One approach is for biobanks to charge industry a cost-recovery fee for its samples and also to charge a fee from additional sample processing services, such as cutting sections and extracting DNA. This approach seems to be especially well understood by French biobanks, who use the term valorisation for the process of adding and yielding value from their samples. Almost half of the biobanks that have joined Biosample Hub are French and most offer additional sample processing services. All French hospital biobanks are certified according to the French norm NF S96-900 which must also make them more attractive to industry.
Another approach is to make external grant funding of biobanks conditional on service to industry. This could be aided by making it mandatory for funded biobanks to make their sample access policies public, by requiring annual reports on sample distribution and perhaps even having industry representatives on sample access committees. Patient representatives are well accepted, so why not industry representatives?
Samples that lack provenance
New regulations are likely to have a major impact on how biotech companies source their clinical samples. An example is provided by the new European regulation governing manufacture of in vitro diagnostic devices, which comes into force on the 26th May 2022. To demonstrate conformity, makers of IVDs must show that the biospecimens used to validate their devices have undergone acceptable pre-analytic processing. This will require the sourcing of samples from biobanks that are certified to meet specific quality management standards. As a result, diagnostics companies will need to obtain samples from known sources that provide full provenance information.
This need for provenance information will put pressure on commercial brokers to change their business practices and reveal the source of their samples. One way in which brokers may mitigate this is by using binding contracts with both the provider and the requestor of samples, to prevent them from interacting independently of the broker. Of course, not all companies or biobanks will be comfortable with such restrictions.
There are technological solutions that can be used to ensure the reliability of provenance information of samples and use of these will be beneficial. The use of blockchain is one example. This digital technology allows tracking of the transfer of biospecimens from the patient donor to the researcher in a secure, transparent and ethical manner, with all transactions documented in an incorruptible shared digital ledger.
What do patients want?
In order to speed up development of new therapies, diagnostics and vaccines, do we want to allow biotech companies to have access to the best quality patient samples? Or do we want this access to be blocked for a variety of possibly short-sighted reasons? The time seems ripe for a major change in the way clinical samples are sourced by industry and by smaller biotech companies in particular. Now more than ever, as a result of the pandemic, the general public understands the importance of biotech and pharma companies.
As reported by the BBC, the UK government spends £2.3bn every year on keeping old technology chugging along. While it…
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As reported by the BBC, the UK government spends £2.3bn every year on keeping old technology chugging along.
While it spends £4.7bn altogether on IT across all departments, almost half of that goes to patching up systems – some of which date back three decades.
The Cabinet Office has stated that it’s taking action to reduce the reliance on outdated technology.
A report that the Office published warns that the spend on obsolete systems over the next five years could each £13bn to £22bn.
Some service, the report says, ‘fail to meet even the minimum cyber-security standards’.
The Home Office spends the most on IT, compared to other government departments, but still relies on 12 legacy systems. Attempts to retire them have repeatedly failed.
The report also reveals that the performance of government systems isn’t being monitored effectively.
A performance management system was implemented nine years ago, but is not only obsolete now, but it soon fell into disuse.
Commenting on the report, Labour’s Shadow Cabinet Office minister Fleur Anderson said Michael Gove had “created a culture of waste and inefficiency”.
“It is unacceptable that taxpayers’ money is being pumped into failing and outdated infrastructure.
“Keeping old and broken systems going is what this Conservative government does best. They desperately need an upgrade.”
A Cabinet Office spokesman said the government had accepted the report’s recommendations in full.
“We are reducing our reliance on legacy IT, moving away from costly, insecure and unreliable technology and laying the foundations for future digital transformation.”
Major car manufacturers are leveraging advanced technology to prioritise a different formulation for electric vehicle (EV) batteries, according to Environmental…
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Major car manufacturers are leveraging advanced technology to prioritise a different formulation for electric vehicle (EV) batteries, according to Environmental Leader. Ford, VW, Tesla and others are looking to replace nickel or cobalt batteries with lithium-iron-phosphate (LFP), as the components are cheaper.
CEO of VW, Herbert Diess, has committed to using LFP in Volkswagen’s entry-level EVs in order to lower costs. Ford has also confirmed that it will be using these new types of batteries in commercial EVs.
Additionally, Tesla founder Elon Musk has announced the company will be making a ‘long-term shift’ towards LFP.
Importantly, making this change also helps to reduce human rights issues over cobalt mining.
LFP isn’t new technology, but it has helped boost EV adoption thanks to lowering battery costs.
In 2020, lithium-ion battery pack prices dropped 89% in real terms to $137/kWh (compared to 2010 prices), and average prices will be close to $100/kWh by 2023, according to BloombergNEF
At the $100/kWh price point, BNEF expects vehicle manufacturers will be able to produce and sell EVs at price parity with non-EV vehicles in some markets.
Ericsson organised a dedicated virtual event, Ericsson Digital Unboxed 2021, for Jazz Pakistan, to share its thoughts on industry leadership…
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Ericsson organised a dedicated virtual event, Ericsson Digital Unboxed 2021, for Jazz Pakistan, to share its thoughts on industry leadership and discuss digital infrastructure.
Ericsson’s global and regional experts and thought leaders showcased the latest insights, use cases and technologies tailored to Jazz Pakistan.
During the virtual event, Ericsson shared its technology vision and updates, and also discussed the possibilities for consumer and enterprise segments. It delved into several topics revolving around creating a differentiated user experience for sports, spectrum strategies, and dedicated networks with a focus on B2B segments.
As part of the event, the latest Ericsson ConsumerLab reports were also presented and discussed. Several demos were also part of the event like Edge Compute Gaming, where low latency access can enable a better gaming experience, and Ericsson Industry Connect, a channel-ready cellular network for factories and warehouses, built to streamline ordering, installation, and management for Enterprise IT.
Abdul R. Usmani, VP of Network, Jazz said: “Digitalisation is everywhere and is now part of our daily lives. At Jazz, we aim to provide state-of-the-art end-to-end services to our customers, focused on data-driven networks as well as the need to accelerate technology advancements in the areas of AI, FinTech and digital content.
“The Ericsson Unboxed event showcased several valuable insights which will accelerate the next phase to meet the evolving demands of connectivity. We are looking forward to more insights and are confident in the next step of the digitalisation journey.”
Ekow Nelson, Vice President of Ericsson Middle East and Africa and Head of Ericsson Pakistan added: “Ericsson’s partnership with Jazz spans over many years with several recent wins and shared successes in the areas of network rollout and digital services. Our world is witnessing challenging times due to COVID-19 and connectivity has never been more critical than ever.
“At Ericsson, we endeavor to automate and accelerate our networks and technology to meet the demands of an ever-changing world. We are working closely with Jazz to provide the best possible connectivity, ensuring that Jazz networks run optimally as demand grows and the need for digitalization expedites.”
Brother UK has partnered with Datalogic to provide technology resellers with the opportunity to buy Auto-ID products on subscription. The…
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Brother UK has partnered with Datalogic to provide technology resellers with the opportunity to buy Auto-ID products on subscription.
The ranges of both vendors will be made available through Brother’s Managed Label Service (MLS) platform, which will give businesses the option of spreading the upfront cost of new labelling and scanning devices, software, services and supplies over a monthly payment plan.
The move will include Datalogic’s barcode scanning hardware and partners supplying the equipment will be able to simply integrate Brother labelling devices into customer deals via MLS, and vice versa.
The vendors say the partnership will make it easier for resellers to specify label printers and barcoding technology for bespoke Auto-ID systems, and provide them with access to a joint technical support team.
Ged Cairns, head of Auto-ID business unit at Brother UK, said: “Customers are increasingly looking to buy all hardware, software and solutions as a service, as they look to simplify purchasing decisions and turn capex into opex for affordability.
“Vendors working side-by-side can help partners responding to these changing customer needs faster, by providing considered guidance and expertise of how technology can work as part of a full system and by supporting one another through shared payment platforms.
“With Datalogic by our side, we’re well positioned to help partners as they handle the growing demand for Auto-ID systems.”
Jonathan Brown, UK&I Channel Country Manager, at Datalogic, added: “Brother’s MLS platform is providing another string to partners’ bows as they target growth in the Auto-ID market, so it’s an excellent platform to open up to the resellers we work closely with too.
“Our new partnership recognises the value that two vendors working together can provide resellers, which is especially helpful for those breaking into the Auto-ID market for the first time.”
The move follows Brother UK’s Auto-ID team striking a new deal with specialist distributor BlueStar, which will now carry the company’s thermal and mobile print range as part of a pan-European arrangement.
UtterBerry, a tech giant whose innovations have been used on some of the largest infrastructure projects in the world, is…
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UtterBerry, a tech giant whose innovations have been used on some of the largest infrastructure projects in the world, is bringing some of its operations to Leeds, Yorkshire, creating 800 jobs – as reported by the Yorkshire Post.
The business’s primary objective is producing sensors which monitor the movements of infrastructure – for example, bridges and tunnels – in real time. It allows those working on the infrastructure to be warned in advance if anything’s wrong, preventing potential accidents.
The new Leeds hub will also design and manufacturer contactless COVID-19 symptom scanners. UtterBerry is aiming to roll these out across the globe.
Heba Bevan, founder and CEO of UtterBerry, is keen to help those who lost their jobs during the pandemic find meaningful work again, and to attract more women into a typically male-dominated industry.
“What attracted me to Leeds was I knew there was a huge amount of talent around Yorkshire because you have got amazing universities,” she said.
“There is a huge pool of undergraduate and graduate talent.
“Engineers want to do good and provide sustainable developments. The pandemic showed us just how much we are lacking in manufacturing.”
Chancellor of the Exchequer, Rishi Sunak, said that the investment was “fantastic news for Leeds”.
As reported by DroneLife, Verizon has launched a Robotics Business Technology Division in a bid to involve itself further in…
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As reported by DroneLife, Verizon has launched a Robotics Business Technology Division in a bid to involve itself further in the unmanned sector.
Verizon states that it “expands enterprise solutions for drones and ground robotics”.
It acquired Skyward, a drone management company, in 2017 and has since used drones for emergency response and the maintenance of its own network.
It has also worked closely with businesses like UPS or delivery projects, and to leverage the power of 5G.
The new division will continue to enable autonomous solutions for Verizon.
“Enterprises in many industries are adopting drones and ground robots to gather data, survey and monitor infrastructure, and automate logistics operations,” says Mariah Scott, Head of Robotics Business Technology.
“By integrating these fleets with one operational platform, and leveraging Verizon’s advanced connectivity solutions, businesses can speed up time to insight, increase automation of their operations and deliver greater value.”
“Robots are a critical aspect of the 5G future. The formation of this new business unit will accelerate the symbiotic relationship between humans and machines, paving the way for Verizon to transform the way businesses approach innovation and the future of work,” adds Elise Neel, VP of New Business Incubation.
“Our talented team of roboticists will leverage the power of Verizon’s network, paired with the sophistication of next-generation software, to orchestrate and unify robotic experiences. This work will help deliver on the promise of making the fourth industrial revolution a reality.”
According to a new study, technology could create a way for indigenous communities in the Amazon to curb deforestation in…
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According to a new study, technology could create a way for indigenous communities in the Amazon to curb deforestation in a major way, as reported by the BBC.
Conservationist groups have supplied indigenous citizens of the Peruvian Amazon with satellite data and smart phones to allow them to monitor the removal of trees. As a result, tree losses have been halved in the first year of the project.
The researchers wanted to see if putting information directly into the hands of those living in the forests themselves could make a difference to the rapid deforestation that has plagued these areas for decades – with great success.
The controlled study was randomised, using 76 remote villages in the Amazon, with 36 randomly-assigned people participating.
Thirty-seven other communities served as a control group, where normal forest management resumed.
When suspected deforestation was picked up by satellite information, coordinates and photos were loaded onto USB drives and delivered up the Amazon river. Then, the data was downloaded onto apps which would show the participants the locations.
It could then be confirmed whether or not the deforestation was unauthorised, and community members would decide on the best approach. If drug dealers were involved, they could decide whether to report to law enforcers. Otherwise, they would intervene directly.
“It’s quite a sizeable impact,” said Jacob Kopas, an independent researcher and an author on the paper. “We saw evidence of fewer instances of tree cover loss in the programme communities compared with control communities.
“On average, those communities managed to avert 8.8 hectares of deforestation within the first year. But the communities that were most threatened, the ones that had more deforestation in the past were the ones pulling more weight and were reducing deforestation more than in others.”
Indigenous groups welcomed the research. “The study provides evidence that supporting our communities with the latest technology and training can help reduce deforestation in our territories,” said Jorge Perez Rubio, the president of the Loreto regional indigenous organization (ORPIO), where the study was carried out.
Welcome to a very special edition of Interface Magazine!
There are few enterprises with a heritage and scale enjoyed by Carrefour. The 63-year-old global grocery and retail giant is undergoing enormous change across its numerous territories and grocery formats, and not before time. Sitting, as it does, at a pivotal moment in its history, Carrefour is facing, and meeting, the challenges of size and legacy as it leverages tech and data to transform into a company ready for the challenges ahead. We caught up with Carrefour’s leadership team across its numerous territories and divisions to find out how it’s transforming its operations on a global scale…
Carrefour has embraced a widespread ongoing transformation, as the retail landscape experiences monumental shifts in behaviour. And the person Carrefour looked to, to deliver this incredible programme of change, was the then rather youthful 45-year-old Alexandre Bompard who joined the Group as Chairman and CEO in July 2017. Bompard has a proven track record in delivering change having been at the helm of French retail chain Fnac-Darty. Bompard’s “Carrefour 2022” transformation plan “embodies the goal of bringing eating well – healthy, fresh, organic, local food – to within everyone’s reach”, said Bompard upon its launch. “To become the world leader in the food transition for everyone”.
Elsewhere in this issue, we speak to Cesar Augusto Dos Santos, Director of IT and CIO of giant Brazilian Communication Service Provider Claro, regarding its digital transformation at scale, as the company enters an exciting new phase of its evolution. Plus, we have some fascinating and insightful content covering digital transformation, business goals versus business purpose and a guide to new working practices that could change your company overnight!
Three in four senior corporate executives believe increasing financial investment is necessary to protect intangible trade secrets, according to new analysis commissioned by global law firm CMS and conducted by The Economist Intelligence Unit…
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A new report released today commissioned by global law firm CMS and conducted by The Economist Intelligence Unit reveals that trade secret protection is rapidly rising up the corporate agenda as firms widely recognise the commercial imperative to protect vulnerable assets in light of more business conducted online and across borders.
With more companies relying on an ever-greater proportion of intangible or ‘secretive’ assets, the findings show a marked shift in how executives are planning to tackle employee leaks, supply chain vulnerability, corporate espionage and cyber-attacks. According to a global survey of 314 senior executives across a range of industries, the three most valuable types of proprietary information held by organisations are customer databases (42%), product technology (40%), and R&D information (23%).
The report, ‘Open secrets? Guarding value in the intangible economy’, reveals that trade secret protection is no longer just a concern for the legal department, but a top priority at the board and C-suite level. The majority (75%) of respondents agree that increasing financial investment was necessary to protect their trade secrets. Measures must be taken to raise awareness of these assets more widely among employees, with 28% of respondents viewing a lack of in-house experience with trade secrets as a safeguarding challenge.
The most significant threats to the security of trade secrets are weaknesses in cybersecurity (49%) and employee leaks (48%). As firms increasingly store and share sensitive information across virtual and distributed workforces, companies face a range of unpredictable insider threats, including intentional leaks from disgruntled employees. This is the biggest concern for the UK, whilst the fear of cybercrime is front-of-mind for business leaders in France, China and the US, worsened by poor internal cybersecurity expertise.
Tom Scourfield, Co-Head of IP Group at CMS said: “Fifty years ago, a company’s value was derived solely from its physical capital. Today, the world’s most successful firms are built on intangible assets that are often secretive by nature – algorithms, customer data, product formulae. This report shows that firms must start taking a more holistic approach to protecting these intangible assets, from computer software to company valuesbalancing restrictions with incentives – and importantly engage every level of their workforce. Without this strategy, protecting trade secrets will remain an uphill battle for many.”
Significantly, four out of five of the top measures that companies are planning to implement over the next two years focus on minimising employee leaks. These range from harsher measures such as closer surveillance of employee’s electronic activity through to more collaborative approaches that centre on improving the company culture and introducing innovative staff incentives.
“Willingness to snoop” is highest in China, Singapore and the United States. It is also a top preferred measure for executives in Technology, Media and Telecommunications, with 36% of respondents planning to implement surveillance over the next two years, reflecting the growing tensions between employers and employees in the technology sector. Efforts to improve work culture are clearly felt more widely in other industries, with almost a third (31%) calling for corporate values to shift towards encouraging trade secret protection.
As companies become increasingly wary of cybercrime and ransomware attacks, the majority (82%) agree that leveraging cybersecurity software is key to protecting their organisation in the long-term. However, only half (53%) believe it is the most effective deterrent or have already restricted digital and physical access to confidential information (55%).
Hannah Netherton, Employment Partner at CMS adds: “It’s overwhelmingly clear that the threat of employee leaks is driving a need for new strategies to guard valuable assets. Companies must find the right balance between perfecting their cybersecurity protections and creating a healthy company culture that incentivises trade secret protection and encourages speaking up through appropriate channels – even the most rigorous of protocols won’t prevent every employee leak or a disgruntled whistleblower.
“The pandemic has opened doors to a digital workspace, where it’s easier for employees to accidentally or purposefully access and expose confidential information. It is impossible to protect trade secrets if employees are not aware of the sensitivities around these assets, so putting the right values and measures in place has never been more important to an organisation’s success.”
Aukje Haan, Co-Head of Commercial at CMS added: “With the introduction of the Directive on Trade Secrets, businesses will get a range of options to safeguard their most prized proprietary information. However, there are prerequisites to be able to invoke those options. Identifying and taking reasonable steps will be crucial, from NDAs, cybersecurity efforts through to employee regulation, as well as specific requirements depending on the nature of the business, e.g., online businesses will need to take more cybersecurity measures whereas manufacturing companies will need to take more physical measures on the factory floor.“
There are seismic changes underway in the automotive world, as the UK gears up to meet its 2030 climate targets. Electric vehicle numbers are going in the right direction – in 9 years, there will be nearly 10 million EVs on Britain’s roads, close to 1 in every 3 cars.
OEMs clearly mean business as Jaguar Land Rover and Ford have already announced that their models will be entirely electric by 2030. However, the journey to electrification is not simply a case of ramping up the numbers of EVs on Britain’s roads. The industry must wake up to the importance of smart tech to make mass adoption possible.
Smart charging, specifically, holds the key to unlocking the EV technology revolution by maximising infrastructure capacity, lowering the cost barrier to adoption, and gathering data on charging patterns and driver behaviour. Without it, Britain’s ability to meet its climate targets hangs in the balance.
How will our infrastructure cope?
Our national grid will struggle to handle such an huge influx of EVs draining its resources, without smart-charging helping us balance the grid. If 10 million EVs plug in at similar times, for example before work in the morning, the unprecedented demand could cause the grid to collapse under the pressure. Ohme’s own calculations show that if numbers of this scale plug in at once using dumb chargers, this could add 70 GW to peak demand. Even if just 30% of these owners plugged in using dumb chargers, it would add 21 GW to peak power requirement – a 33% increase in the power required.
By using smart charging technology, we can prevent such a surge by shifting EV technology demand by time and location to ensure the grid isn’t overwhelmed, allowing electricity to be consumed effectively and sustainably.
At the same time, this smart tech solves the problem of managing renewable energy surplus. At the moment, the industry struggles to harvest and store excess wind power, for example, when demand is low and supply is high – when the wind blows and we’re asleep.
The bottom line is that we can’t afford wastage when confronted with such ambitious climate targets. Today, the industry’s solution to this problem is huge, expensive investment in infrastructure – namely megabatteries, backup generation capacity and grid reinforcements. But by using smarter technology, we can achieve the same goal, without the cost. Smart charging enables drivers to draw surplus energy from the grid into their EV batteries at off peak times, turning the car batteries themselves into the perfect storage solution – effectively utilising our natural resources at all times of the day.
Affordability is key
We will never remove ICEs from Britain’s roads unless we can demonstrate that switching to electric doesn’t have to cost the earth. And while the cost of buying an EV might be falling as more affordable models come on to the market, for many, EV ownership still remains out of reach. Bringing down the running costs of EVs through smart-charging will be critical if EVs are to become mainstream, particularly in a post-pandemic economy.
Smart charging solutions allow consumers to tap into cheap energy by identifying the best times to charge. In fact, in some cases when there is surplus energy on the grid from renewables, drivers can even get paid to charge their vehicles, dramatically reducing running costs over time.
EV owners can additionally unlock a short-cut to huge savings by combining a smart-charging app like Ohme’s with a time-of-use (TOU) tariff. For example, using the two together brings the approximate cost of driving 10,000 miles down by £280 annually for Nissan Leaf drivers, and by a jaw-dropping £350 for Tesla X drivers.
Joining the dots with data
Smart-charging does not only protect the grid and benefit consumers, it can also help energy suppliers. Smart-charging technologies deliver the ability to ‘connect and control’ the nation’s charging infrastructure – providing the data for energy companies to be able to direct power to where it’s needed, when it’s needed.
Smart charging also provides an invaluable connection between energy companies and energy consumers, unlocking the data that will help them better serve their customers by understanding their behaviours. By working with smart charging data platforms, OEMs can unlock powerful insights into driver behaviour. This powerful insight can also shape an OEM’s strategy from vehicle design right through to add-on services such as insurance and after-sales care.
Data is key here – it allows us to build a smart, networked system which is able to manage large fluctuations in energy supply and demand whilst providing powerful insights to help both energy companies and OEMs shape their service offers.
The time is now
The industry is laser focused on production, but the EV revolution can’t be realised in Britain without the right tech to support it. The answer to breaking down the barriers to mass adoption is staring us in the face – smart-charging technologies.
Smart tech improves affordability, protects and preserves our infrastructure, and joins the dots between EV stakeholders. It’s a triple win for EV owners, energy companies and car manufacturers, and its adoption at scale will see us well on our way to meeting our 2030 climate targets.
For the purpose of this podcast, we firmly believe that Kelly Smith, Chief Digital and Information Officer at Hagerty –…
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For the purpose of this podcast, we firmly believe that Kelly Smith, Chief Digital and Information Officer at Hagerty – a brand known for perpetuating the love of driving and North America’s largest classic car insurance provider, would be best suited.
Kelly brings more than 25 years of technology experience to the table and leads Hagerty’s enterprise digital strategy, capitalizing on emerging opportunities to support Hagerty’s rapid growth.
In addition, Kelly champions the integration of information and technology into all aspects of the business including team building, customer experience, development and product management. Prior to joining Hagerty, Kelly served in senior roles at MGM Resorts and Starbucks.
Data analytics is certainly not a new concept. It’s something we have been fascinated with, both personally and professionally, for…
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Data analytics is certainly not a new concept. It’s something we have been fascinated with, both personally and professionally, for decades but its an area which continues to see dramatic change when it comes to our understanding and indeed our application analytics tools. Data is key to transformation. We knew that already. But what we don’t know, as much as we love discussing it, is how far data analytics can truly take us. In order to try and understand where we can go, Transformation Executive Paul Bailo joins the Digital Insight to take a look at where we are. What are we seeing right now in terms of our data analytics maturity and what does it say about the opportunities ahead of us?
Featuring… Swisscom, State of New Jersey and Cementos Pacasmayo, plus much, much more…
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Welcome to another packed issue of Interface Magazine!
Following the success of an exciting B2C portal, we revisit the dynamic partnership between Swisscom and Accenture to find out more about the follow-up: a brand new B2B offering…
In June 2020, Interface Magazine published an in-depth feature on telco giant Swisscom’s new omni-channel platform – created in conjunction with Accenture – which transformed Swisscom’s B2C offering. Accenture delivered the framework for this digital omni-channel platform (DOCP) and, over time, Swisscom was able to run it independently. In the story, we mentioned that the company was also planning a B2B transformation. At the time, the plan was in its infancy.
Now – again, hand-in-hand with Accenture – Swisscom has launched this exciting new element of its business. We spoke with three people directly involved with this next step – Stephan Schneider, MD of Accenture; Anne-Thérèse Morel, Head of Capability Management at Swisscom Business Customers; and Matthias Piller, Solution Train Engineer at Swisscom – to gain a broader insight on what has changed since our last catch-up.
Elsewhere, we sit down with Luis Miguel Soto Valenzuela, CIO of Cementos Pacasmayo, to discuss the company’s digital and customer experience transformation, and its dedication to improving Peru. And we catch up with Poonam Soans, Chief Data Officer of the State of New Jersey, who explores how she is overseeing a data-driven revolution to better serve its citizens.
Sam Holding, Head of International at SparkPost reveals the role of email in enabling marketing teams to be agile and to successfully meet the changing needs of the business and of their target audiences…
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This week, The Digital Insight welcomes Sam Holding, Head of International at SparkPost.
Sam Holding, Sparkpost
Sam reveals the role of email in enabling marketing teams to be agile and to successfully meet the changing needs of the business and of their target audiences…
“So, I’m Sam Holding and I head up the international business for SparkPost. Over the past 20 years, I’ve worked in digital advertising and ad tech and I’ve experienced just how important a really well executed digital program is for a business and seen how email is a key component within that.
I was fortunate enough to be offered an opportunity to join the SparkPost team 18 months ago. SparkPost is an email sending and deliverability platform. What that means is we send a lot of mail. We’re the world’s largest and most reliable email sender. We deliver almost 40% of the commercial email sent globally. To put that into context, that’s about 4 trillion emails that we support our clients to send. We’ve also got the world’s largest email data footprint, which we make available to our customers, for them to use, to make data-driven decisions and drive better performance from their email programs…”
Cierra Dobson, strategy director at design and technology agency, Rufus Leonard, explores how brands of all shapes and sizes can adopt the successful strategies of category-defining service brands to grow their market share and take the lead…
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Cierra Dobson, Strategy Director at design and technology agency, Rufus Leonard
Brands are increasingly building a service wrapper around their core products to unlock new revenue streams and grow or protect profit margins. Accelerated by the pressures of Covid-19 and enabled by digital, brands are trying to respond to the ongoing challenge of commoditisation by moving from transactional to long-term value driven relationships with customers. Service brands – whose primary offer is an intangible outcome rather than a physical product – are naturally better positioned to excel in this new reality, sometimes even redefining the categories in which they operate.
Being a service brand doesn’t automatically inoculate your business from commoditisation. Rather, service brands tend to possess a more customer-centric organisational mindset, a more robust technology infrastructure, and greater operational flexibility due to the inherent nature of delivering outcomes rather than physical products. In effect, service brands tend to have the raw materials to become experience-driven businesses.
The strength and resilience of service brands
Together, these traits affect the relationship service brands have with customers, i.e. the length, breadth and depth. Consider a robo-investment brand like Betterment— the customer journey stretches over years (length), spans numerous touchpoints (breadth) and deepens over time as more customer data is generated (depth). If customer experience is a canvas, service brands tend to have a bigger one, with more opportunities to provide value, delight, educate and entertain. It’s no surprise that service brands tend to have been early adopters of CX principles like personalisation and seamlessness.
Such relationships also necessitate a robust digital ecosystem. From communication, to content, to transactions. Forrester notes organisations that use technology to make a meaningful difference to people’s lives grow 4x faster than their competitors.[1] All brands should consider their tech architecture as the foundation for value-adding CX.
Find inspiration from category-defining leaders
Wise is a service brand that originated in a highly commoditised category.
With 10 million customers, a reported 70% growth in revenue, doubling profits YoY from March 2020, and a recent valuation of $5 billion[2], Wise (formerly TransferWise) is a fintech unicorn truly deserving of the title. Wise combines frictionless customer experience with category-beating low fees and speed for international money transfers. But the brand’s mission statement, “Money without borders”, has acted as a powerful North Star for its recent expansion into new services[3]. The statement describes an outcome, and the company’s newest services—like banking accounts designed for people who live, work and travel all around the world—tightly align to that outcome. Brands looking to strategically expand their services should start with a clear mission; what is the outcome you want to deliver for your customers and the world?
Domino’s is a product brand in a fairly commoditised category
The 2000’s were a rough decade for Domino’s. But a bold move to re-invent their entire offer from ingredients to delivery has since paid off. Besides making the pizza more edible, Domino’s focused on a core need: their customers want to get pizza with as little effort as possible. They pioneered the real time pizza progress tracker, allowing customers to worry less about when it might arrive. Their AnyWare platform allows customers to order from an ever-expanding list of channels with as little as a click of the ‘Easy Order’ button. Designing an effortless, user-centric delivery experience has helped Domino’s revenue grow from $1.6B in 2010 to $4.1B in 2020, (Papa John’s revenue grew from $1.1B to $1.8B in the same period)[4]. Brands should ask themselves, ‘how could we make the experience around our core offer meaningfully better for customers?’
Peloton is a premium brand which straddles both products and services.
Peloton was never just a stationary exercise bike. But now it’s fair to say they’ve created a fitness ecosystem to rival the likes of Nike. The expansiveness of their offer makes them difficult to categorise. It’s digitally enabled exercise equipment, it’s a virtual fitness coach, it’s a streaming service for fitness content, it’s a social platform… Motley Fool contributor Neil Patel sums it up, “Peloton sells hardware that is differentiated by software.”[5] The ecosystem combines data, content and community interaction to make the customer experience feel empowering and addictive[6]. Brands that want to expand their offer should think strategically about their digital ecosystem; is your tech stack fit to deliver truly category-defining experiences?
All three brands have expertly used customer experience design, branding and technology to deepen the relationship they have with customers and win market share.
How to add value to your offer by designing meaningful experiences
Take inspiration from your brand purpose and identity. What outcomes does your brand ultimately hope to deliver for your customers and what tends to get in the way? Brainstorm service experiences that deliver on your promise. Even small changes, like using less jargon in website copy, can make a significant difference.
Take inspiration from your brand purpose and identity. What outcomes does your brand ultimately hope to deliver for your customers and what tends to get in the way? Brainstorm service experiences that deliver on your promise. Even small changes, like using less jargon in website copy, can make a significant difference.
Take inspiration from your brand purpose and identity. What outcomes does your brand ultimately hope to deliver for your customers and what tends to get in the way? Brainstorm service experiences that deliver on your promise. Even small changes, like using less jargon in website copy, can make a significant difference.
All brands have the opportunity to think like a service brand by putting customer experience and outcomes at the heart of their growth strategy. Purpose, empathy, and tech infrastructure are the keys to creating differentiated and meaningful experiences that can come to define a category.
[1] Forrester; Dare To Disrupt With Technology-Driven Innovation Report, 2019
Gayle Carpenter, Founder and Creative Director at Sparkloop, discusses her incredible journey and the way she has smashed– and continues to smash – gender-based barriers in business…
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It seems incredible, in 2021, that female founders remain a rarity – especially when it’s been proven, time and again, that the influence of women entrepreneurs is an incredible force for good. The Treasury recently commissions Alison Rose, CEO of Natwest Group, to lead her own independent review of female entrepreneurship in the UK [LINK: https://www.gov.uk/government/publications/the-alison-rose-review-of-female-entrepreneurship] digging deep into just how influential women can be and exposing the barriers they face.
The goal of the review was to tap into the economic potential of female entrepreneurs; one of its key findings was that up to £250bn of new value would be added to this country’s economy if women started and scaled new businesses at the same rate as men. In response to Rose’s report, the government now has plans in place to increase the number of female entrepreneurs by 50% by 2030 – this is around 600,000 women.
The business case for why this is so important is crystal clear – it’s the much slower march of the way society views women that still needs an overhaul. You’ll hear people claim that sexism no longer exists in the UK because there are no specific laws that bar women from doing anything men do in business, but that’s a deeply short-sighted claim that completely discounts the pervasive nature of negative gender-based stereotypes.
Even the highly successful Gayle Carpenter, Founder and Creative Director at Sparkloop, faced that one-dimensional mindset from her father when she was choosing what to study. While her passion lay in the arts, she initially chose a business degree, because he’d told her, “girls can do art, but if you want to get a proper job, you’ll need to do business”. Carpenter soon realised she’d made a mistake, and switched to art and design – something that didn’t stop her launching her own business 15 years ago, flying in the face of what Carpenter Senior expected.
Challenging perceptions
“The two things – arts and business – are completely united now,” she says. “My father’s viewpoint spurred me on to prove him wrong in the fact that you could be artistic and commercially creative, and make a career out of it.” Carpenter describes Sparkloop as “an ideas business”, a creative agency which specialises in branding, and all the associated channels of delivery. While the fundamentals of what Sparkloop does, as a business, haven’t changed much in a decade and a half, the way it delivers what it creates certainly has.
“The channels in which we deliver our strategy are beyond the imagination, now,” she explains. “You can’t recognise the output from 15 years ago. So, whilst staying true to our core skills and beliefs, we do make sure that we’re just one step ahead in terms of technology.” This has enabled Sparkloop to remain at the top of its game, and, unsurprisingly, the words and attitude of her father have stayed with Carpenter every step of the way, challenging her to continuously prove his perceptions wrong.
“Part of the reason there’s such a gap in female entrepreneurship is the perception of women in leading roles,” she says. “My dad, bless his soul, had a really old-school attitude towards girls in business – but have we actually moved on that much? There’s still that perception that if you were to start a family, you will be at home, potentially, or at least have to take a step back in order to do that. And that’s a real challenge for many women. Sadly, I do genuinely see that kind of ‘old boys network’ idea at play, but I think you can find or start your on network, and what I’m seeing now is a much more diverse network of people who are like-minded, rather than it being a ‘who you know, not what you know’ situation. It’s really, really nice.”
Everyday barriers
Times are indeed a-changing, but Carpenter has still been up against her fair share of barriers – the kind that remain common today. “I’ve been in a lot of male-dominated teams, and even at creative head level, there would be stereotypical response to my opinions; I was seen as ‘feisty’ as opposed to ‘assertive’, yet the ego-driven, crazy creative director who would throw hissy fits constantly was just ‘eccentric’! It’s interesting how we’re labeled, and how that’s so set within the psyche. But I am seeing it change.”
When we talk about those deep-rooted prejudices, language choice is often how they emerge. People are so used to describing powerful women as ‘difficult’ for standing their ground, and praising men for the same behaviour, that they don’t always realise how damaging that can be and how it influences their own viewpoints and actions surrounding women leaders. For Carpenter, personally, the best way around that has been to take what she’s learned and make sure others know they can come to her for guidance and advice.
Creating the change
“I would say I take much more of a mentoring role,” she says. “I like nothing more than when I started to work with, or collaborate with, clients or other people in my sector and they then almost outpace me. It’s a sign of success in terms of how they’ve grown. I never set out to do it in a structured way, but I’ve worked with a lot of clients who have just naturally asked me for advice, or 360 feedback, and that’s turned into more of a conversation and a bit of mentorship, where they’ve then gone onto do really great things with the confidence and the voice to make a difference. That’s really heart-warming for me.”
Carpenter’s team, just by chance, happens to be very diverse, including her ‘right-hand woman’ whom she brought on board as a junior and who is now a great senior creative. And Carpenter herself has been the recipient of a mentor’s sage advice, which – consciously or unconsciously – shapes the way she has worked with juniors now.
“When I was at university, I did some experience at a small agency, headed up by a male and female team, and I later went back to work for them – it was one of the happiest places I’ve worked,” she says. “Looking back on it now, in this particular creative head, who was female and had children, I can identify the qualities I’ve noticed in woman leaders and that I would like to draw on myself – kind, but firm, and with a real tenacity. I actually didn’t realise, until now, how much of an impact that particular personal situation had on me, perhaps because it was the only time within my career where I had been working for a female head. So it enabled me to start as I meant to go on, very early.”
The future’s bright
For Carpenter, it’s important to reiterate the fact that giving women equal opportunities shouldn’t be seen as a threat to men, and opening doors for one doesn’t close any for another. It’s also vital to highlight that diversity isn’t just about men and woman – it’s a far broader conversation including gender, sexuality, race, health, and beyond. But regarding female leadership, the issue still lies within perceptions creating barriers that needn’t, and shouldn’t, be there.
“I’ve got a son, and I want to be a role model for him as much as I do for other women, to know that it’s right and fair to have this diverse attitude going forward,” Carpenter explains. “I certainly see that playing out in him, which is wonderful. He doesn’t see male and female roles in the same way that we ever would have, as kids, so that’s fantastic. Additionally, my other half works in finance, which isn’t the most diverse industry, but some of his favourite roles have been when he’s had female bosses, because he says they often have more divers teams which have been more successful.”
Things are moving in the right direction, from Carpenter’s perspective. The fact that gender is an everyday topic of conversation, now, is a step forward, and she’s seeing a general increase in the numbers of women in business. “It’s a lot more split, now, in terms of who I’m seeing as decision-makers,” she says. “There’s a real blend, and that’s really reassuring. I think you just have to have a certain mindset or ambition, regardless of gender, and if you have that sort of natural instinct it’s hard to let go of it. I’m constantly trying to stay one step ahead of myself, always challenging myself. I talk to other female – and male – leaders and use their mentorship to spur me on.
“Just stay true to yourself, don’t be something you’re not. As a woman, you don’t have to try to be a man to be successful – be who you are and have confidence in that. Never take your eye off the ball, look after your clients, value your team, and that will pay you back in dividends. Most importantly, don’t be afraid of failure. Test, learn, challenge yourself, keep moving forward, and be prepared to make measured risks – it’s the only way you’ll grow.”
After a year in lockdown, the Office for National Statistics has revealed data showing that productivity per worker during the…
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After a year in lockdown, the Office for National Statistics has revealed data showing that productivity per worker during the pandemic has increased by 0.4%.
Businesses have adapted to digital and flexi-working and the benefits they entail have now solidified themselves in our working culture norms. Across the UK, the dialogue has been changed as employers from the Civil Service to PwC have announced official structures for flexible working in the long-term, cutting office space by around 40% to reflect this.
However, many businesses, including some giants such as Goldman Sachs, continue to denounce the idea of flexi-working in the long term, going against the grain of what employees are calling for. As restrictions are eased, employees are now being called back to the office, triggering calls for increased flexibility in order to maintain the increased flexibility they have seen during the pandemic.
This is supported by landmark research by Theta Global Advisors, showing that a lack of flexibility from businesses has resulted in negative impacts on productivity, mental health and working cultures. Workers want to choose how and where to work going forward in order to be more productive, safeguard their mental health, and achieve a better work/life balance.
According to the research, more than half of workers feel that the leaders and decision makers are “out of touch” and do not understand the processes required to ensure efficiency and productivity.
Working from home has also blurred boundaries between work and private life, with bosses messaging and emailing late in the evening and during out-of-hours, leading to employees feeling increasingly drained and unable to relax.
With a third of UK workers seeing their company’s headcounts decrease but workloads increase, a perfect storm is brewing.
Chris Biggs, Partner at consultancy and accounting Theta Global Advisors, says: “To ensure people are at their happiest and most productive, flexibility is needed in both where and when they work. Freedom from the office must also mean freedom to go to the office to account for different experiences, priorities, and conditions.
“With companies adopting new policies and substantial differentiation in the experience of working during COVID-19, it seems working environments will never return to what they were in 2019.”
Technology has played a vital role in changing the way people eat and view their health. The strategy& report, “An appetite for opportunity: How changing dietary goals can drive growth in retail and consumer goods”, explores how…
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The internet as a teacher: COVID-19 has shone a spotlight on health
From the endless memes about inevitable weight gain – glossing over the fact that this has often been caused by illness, depression and anxiety – to the laser-focus on mental health, how we function and what we put into our bodies has become more of an open talking point since the pandemic began. This inevitably means that people have spent more time researching the best options for their personal needs online.’Our research shows the pandemic, and resulting lockdowns, have seen some consumers altering their diets to better support their mental wellbeing’, the strategy& report states. ‘We see indicators of this shift to overall wellbeing when we look at Google Search data. It’s clear there has been sustained interest in ‘vitamins’ over the past five years, with a significant spike in January 2021′. The first lockdown also saw a huge spike in Google Searches for ‘sugar substitute’.
Increased reliance on technology has changed how we acquire food
This shift isn’t new, but COVID-19 has accelerated it. In the UK, many supermarkets had to quickly adjust their online services when the first lockdown caused an enormous surge in the demand for delivery and click-and-collect slots. Additionally, the popularity of takeaway websites and apps has exploded.According to strategy& data, 21% of consumers found they’d increased the amount they spent online during 2020, and 13% expected that to continue for the next 12 months. The data also found that consumers are more interested in spending their money with independent, local food businesses.
People are learning new skills via the internet
While consumption of takeaways has indeed risen, many have also used this time as an opportunity to either learn to cook, or to expand their cooking skills, with the internet to guide them.’Across all consumer segments, the web is the top destination for food information and inspiration, including search engines, recipe websites and videos’, the strategy& report states. Additionally, subscription box services have become increasingly popular. ‘Consumer intent to purchase these has doubled since the pandemic, with a particularly strong take-up among Generation Z’.
Gen Z is leading the way in online health education
The strategy& research found that, by far, Gen Z was the most likely age bracket to change its diet. ‘While they my lack the spending power of older generations… the younger demographic is more likely to change their diet for environmental reasons and they are also looking to become better-informed, turning to digital formats for information about wellbeing and diets. They’re using social media, health tracking apps and podcasts to guide their nutritional choices and meet their health goals’.
Health-based goal-setting has gone digital
Food-tracking websites and apps have also been around for several years already, but an increased focus on health and wellbeing has made them far more commonplace. Additionally, pre-packaged meal plans that focus specifically on health or meeting a certain are on the rise, with online services hurrying to provide. ‘The significant rise in healthy-eating packaged meal plans, delivered to the door, is capturing the attention of consumers whose goals may include a healthier lifestyle or the greater convenience of more hassle-free preparation and cooking’, the strategy& report says. ‘The proliferation of online services and marketplaces means consumers can easily and quickly better understand their choices against their goals, and then satisfy their dietary needs, whatever they are, at the touch of a button’.
Welcome to part two of the Data transformation trilogy with Paul Bailo, a leading digital transformation executive.
In this installment we take a look at Change management, two words that will either unlock your transformation, or block it. Love it or hate it, change management is vital to any transformation, so why is it so polarizing?
Transformation and change are and perhaps always will be, the key topics defining the business conversation.
And for every headline that focuses on a new technology, or indeed a strategic roadmap, how often do people address the elephant in the room that is change management?
Leading executives will tell you about the significance of change management, but what does that mean? What makes change management more than just another trendy buzzword that gets trotted out when you need to try and quantify change? What is wrong with our approach to change management?
It’s all well and good saying change management is necessary and essential to transformation, but what are you doing to address it? What does change management look like for an organisation? As with any journey, there has to be a beginning, so what first steps do you need to take to act on the promise of change management, but also to fully embrace the change in the first place?
We all knot the importance of sponsorship. Get the backing of the board, and the teams around you, and change comes naturally.Leaving you to wonder; what were you even worried about?
Any leading executive will tell you that if you don’t have the sponsorship of those around you, you’ve failed before you’ve started. It makes sense of course,, if you don’t buy into an idea, are you just going to willingly go along with it?
This is where storytelling comes in, obtaining quick wins and achieving results and being able to establish a sense of credibility in what you’re doing.
But, change is different and people aren’t always wired to accept change immediately. You can be the best storyteller in the world, and have all the data in your hands to prove that change is good, but for some, that sponsorship just will not come your way….so the question then becomes; what happens now?
Missed part one? Watch The Data Transformation Trilogy Part 1: C-level talent and leadership; do you have it?
Change is needed – but change is overwhelming. An increase in data is an increase in knowledge. And an increase in knowledge is an increase in power…making change isn’t easy. Make the mistake, and the results could be catastrophic. Remain frozen in fear, and fall away into irrelevance. The only way to succeed is to try.
Change is hard and while isn’t always priority number one, change is necessary to evolve as a business.
So when you are about to embark on a change journey, and you cast your eye over your organization, your processes,, your strategic roadmap and both your existing and future technologies….consider how you’re going to get there. Consider the sponsorship you need, the wins and how you can cultivate the culture that’s required in order to embrace change.
It’s time we reconsidered our love hate relationship with change management….
This month’s exclusive cover story features Anant Adya and Umashankar Lakshmipathy, from Infosys, who dive deep into what cloud means for digital transformation and what the Infosys Cobalt cloud offering brings to the table…
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Welcome to the latest issue of Interface Magazine!
This month’s exclusive cover story features Anant Adya and Umashankar Lakshmipathy, from Infosys, who dive deep into what cloud means for digital transformation and what the Infosys Cobalt cloud offering brings to the table.
A global technology leader, Infosys – headquartered in Bangalore but present and active across the world – is busy not just conquering the cloud services arena, but taking its customers with it. Even at the size it is now, as a multinational tech giant, Infosys continues to hold the hands of its clients and collaborate in order to create bespoke solutions which benefit all parties. And at the heart of the business are brilliant experts pushing the agenda that community is key.
For both Lakshmipathy and Adya, cloud is a way of life, and a foundational pillar in the digital transformation of any business. Digital transformation has never been more important; it was forging forward even without COVID-19, but the pandemic has accelerated its march to a startling degree. So why exactly is cloud so vital? For Lakshmipathy, cloud is no longer something unreachable – it’s fully landed.
Elsewhere, we speak to Jon Walton who is bridging the digital divide in San Mateo County, California and catch up with Boldt Group CIO Miguel DeSantis regarding the massive digital transformation programme at the Argentinian technological services giant. Plus, we ask ‘where are the female founders in tech?’ and list 5 ways in which tech has adapted to our shifting health habits…
The latest episode of The Digital Insight podcast brings you the first in a new three part series with Paul Bailo, Digital Transformation Executive.
We explore how leadership teams must reassess their current operating models, take an honest look at their existing talent pool of both their employees and executive teams and think about how they attract future data and digital leaders.
What changes should they be making today to ensure that they attract the right talent, don’t fall behind or go out of business tomorrow?
At the start of December 2020, new audio-only iPhone app, Clubhouse, had 3,500 members worldwide. Fast forward to the end of February 2021 and the Silicon Valley founded platform surpassed in excess of 10 million downloads, with 2 million weekly users.
Granted, these figures are low in comparison to the 500 million Instagram users that post stories on a daily basis, but it’s clear that Clubhouse is starting to gain traction and fast.
For individuals yet to receive an invite, Clubhouse is a new and exclusive members-only iPhone app that connects users via audio. Once ‘inside’, users can join ‘rooms’ to listen to members talking at any time, providing a space for debates, discussions and even performances. The only rule is that no audio content can be recorded.
Already valued at $100 million despite only marking its first year since launch this April, Clubhouse founders are now in the process of making the app available to the wider public.
The burning question, therefore, is how the app will work on a mass scale? And whether it will provide a new and exciting opportunity for brands to reach and directly engage with their target audiences, following in the footsteps of SnapChat and TikTok.
Let’s explore:
People buy from people
The Instagram era will always be synonymous with the creation of social media influencers, with millions utilised by businesses and brands on a daily basis to help support their latest campaign or promote their newest product.
Since the launch of Instagram stories in 2016, the popularity of the platform has accelerated, where monologues to camera or snippets of ‘behind the scenes’ type content are now the norm.
In essence, Instagram works because people like to engage with and buy from people. As an app that encourages online audio engagement between individuals, Clubhouse, therefore, has the potential to provide a seemingly authentic avenue for target audiences to engage with brand ambassadors online – providing the opportunity for ‘story’ type snippets to be extended into lengthier discussions, debates or even brand masterclasses.
For example, current Clubhouse entrepreneurial discussions amongst the elite could quickly turn into make-up tutorials conducted by an influencer, using the latest Charlotte Tilbury line. You can see how this would work and would bolster brand awareness and product sales as a result.
Interest and Demographics
When joining Clubhouse, the algorithm integrates with your iPhone and shows you what friends or family members are utilising the app. In addition, the app also suggests other people for you to follow and engage with based on your individual preferences.
To ensure you find suitable ‘rooms’, Clubhouse also provides a ‘Find Conversations About…’ option which lets you select and follow relevant topics and interest points.
From a brand perspective, this suggests one clear thing: Clubhouse already has a growing dataset on user demographics and interests, which means there is scope to create advertising opportunities within the app.
Just as we have seen with TikTok, a dedicated Clubhouse advertising model seems a clear and obvious move and if the app continues to gain traction at the same rate, it is likely to work – providing another digital platform for brands to utilise to directly engage with target audiences, increase brand awareness and drive sales.
The negatives?
Clubhouse came out of the starting blocks at a time when consumers were faced with the sheer destruction caused by the COVID-19 pandemic, which resulted in brands shifting their focus to remain relevant and continue to resonate with their target audiences.
Essentially, brands with purpose won in 2020 and you can’t but help think despite the clear genius behind Clubhouse that its exclusive ‘celebrity only’ approach was ill-timed, particularly as people across the globe were sat in their homes under lockdown restrictions and very likely to engage with a platform that promised open conversation.
It will, therefore, be interesting to see public response to Clubhouse as it removes its barriers and tries to engage a wider audience. What we do know, however, is that if mass users sign-up to Clubhouse, it won’t be long until brands follow… So, watch this space.
We take a look at 5 apps that have underscored the new necessities of remote work: collaboration, security, employee engagement… and a well-equipped home office, as identified in Okta 2021 Business at Work report.
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Many of us have adapted seamlessly to working from home over the last 12 months. Technology, and the way software organisations have stepped up to the plate to supply the tools we needed most, has been key to this. We take a look at 5 apps that have underscored the new necessities of remote work: collaboration, security, employee engagement… and a well-equipped home office, as identified in Okta 2021 Business at Work report.
While it now feels utterly normal to join a professional video chat and see the inside of people’s home offices, kitchens, or sheds, the fact is that it’s only been normal for less than a year. Many people thrive on home working, although some did struggle with the shift, and numerous reports have explored the clear benefits of a more flexible working situation than most of us had pre-pandemic.
One of the main reasons why many of us have adapted so seamlessly is the role technology has played, and the way software organisations stepped up to the plate to supply the tools we needed most. ‘A shakeup in our top apps underscores the new necessities of remote work: collaboration, security, employee engagement… and a well-equipped home office’, states the Okta 2021 Business at Work report.
As well as a rise in the use – and choice – of tools that enable us to better work with our colleagues, clients, and peers, remote workers have required additional protection that their employers would normally take responsibility for, hence the rise in security-related apps. Additionally, HR teams are busy investing in whatever will give them the best employee engagement, in order to ensure staff feel happy and supported at a time when they’re separated from their co-workers.
Interestingly, the Okta report shows that 90% of the fastest-growing apps are brand new to the top 10 – the first time in the report’s history. ‘Companies needed to enable remote work, which means supporting at-home workspaces and virtual collaboration, and these apps helped them do it. Also, for the first time, security tools claim four top spots in the fastest growing category, and an HR-centric tool appears for the first time since 2016’.
Microsoft 365
The real heavyweight app of 2020/21 was Microsoft 365, which is no surprise considering most office workers need to use at least one element of the app every day, and many of them haven’t invested in it for their personal computers. In the words of the Okta report, ‘Since our first report in 2015, Microsoft 265, Salesforce, and Google Workspace have held three of our top four spots. They may have rebranded once or twice, but they are embedded in our desktops and our work lives’.
AWS
Amazon Web Services is a cloud computing service that works on a pay-what-you-use basis – it’s not surprising, then, that it’s such a popular choice, particularly at a time when the way we work has changed so drastically. ‘We’ve seen some exciting changes in out top rank’, the report states. ‘Cloud platform AWS has risen steadily from sixth place five years ago to become this year’s second most popular app by number of customers’.
‘The new second-place global rank for AWS is driven by its strong growth in EMEA and APAC, where it has seen over 25% growth since April 2020, compared to 16% growth in North America during the same time period’.
Salesforce
A CRM platform and cloud computing service, Salesforce’s popularity has remained steadfastly near the top of the list. This is thanks, in part, to its usage in the US: ‘Salesforce and Zoom’s global ranks are underpinned by their popularity in North America’, the report states. In APAC and EMEA, Salesforce is several spots lower, but this hasn’t affected its appreciation elsewhere.
Google Workspace
Formerly known as G Suite, Google Workspace combines collaboration and productivity tools, and cloud computing. Its broad appeal has brought it to the top four spot, regardless of how it overlaps with other apps. ‘While companies may splurge on a few best-of-breed apps, we might expect they would tighten their belts where they see clear redundancy. However, 36% of Okta’s Microsoft 365 customers now also deploy Google Workspace, the largest jump in the past three years. Top collaboration tools have never been more important for productivity’.
Zoom
Zoom is no longer simply a name – it’s a verb. “Shall we Zoom later?” is the latest “Google it”, thanks to the video call app’s usability, stability, and business-friendly features like the ability to record meetings and set a photo of the Taj Mahal as your background. ‘Tools enabling collaboration, including Zoom, have jumped in the ranks’, the report states.
‘[It] had only joined the top apps by unique users for the first time in 2019, ended this current data period in sixth place. In our Businesses at Work (from Home) report in April, when we highlighted apps that had seen significant growth in numbers of corporate and personal users in March, Zoom was our fastest growing app by number of unique users. While unique users dipped a bit over summer, by the end of September they were reaching new highs, likely related to Zoom’s extensive efforts to support distance learning’.
But this is all future talk. Lets think less about 2025, 2030 and 2035, and think about 2021 and the paths we are on right now.
What has the last ten years brought in terms of EV development, and where are we right now when it comes to the EV market?
Paul Loustalan, a partner with Reddie & Grose, a provider of patents, trade marks and designs and particularly patents coming from the EV market, sits down with Dale Benton to explore the significant advancements made in the global EV market.
The next ten years will be an interesting time for the automotive industry:
But much like any other industry, the larger players dominate the headlines (and the market) but the smaller players bring about true disruption. In the financial space, the larger incumbents were once upon a time disinterested in what the start ups and fintechs were doing, but now they are making radical changes in order to catch up to them and cater to the new financial customers of today. So is it fair to assume that the smaller start-ups and disruptors in the EV and automotive space, are forcing the bigger companies to not only look over their shoulders, but think about their own futures?
If you were to look around the world right now EVs are here. As noted already, global EV and Plug in hybrid sales soared to 3,24 million in 2020. But for some, EVs remain just out of reach. We were lead to believe we’d all be driving fully automated EVs by now, and yet we aren’t.
EVs are something that we’ve spoken about for many years as coming soon. But as we can see they’re here right now. So why is there still a perception that, despite the promises and government mandates, EVs will always remain a technology of the future?
We know the benefits, we see what it can and will and already is doing in terms of carbon emissions and energy consumption, but as with any technology there will always be the challenge of; do the customers want it? For every customer who wants a new, energy efficient car, there will be one who is happy to continue using what works best for them – and why shouldn’t they?
It can never be as black as white as saying; there are those who want the new and those who don’t, and companies need to cater to all consumers and ease those who are reluctant into the new era of the automotive industry.
As with any technology, when it works, it sells itself. We as consumers can see it operating successfully and the benefits it will bring to our lives. In the automotive industry, we think of a car and outside of cosmetics – we simply ask that it works and that it allows us to go about our daily lives with relative ease.
If it can save us some money, and reduce our carbon footprint, then even better. Success stories sell. But what significance is there in focusing on failure? Can that actually be a good thing in terms of the conversation surrounding EV technology? Can we gain more from hearing about those failures than we would by simply focusing on the successes?
As we speak in 2021, the next 10 years are going to see huge shifts in the EV market and we will start to see them in the next four. We don’t know for sure what’s going to happen and how well its going to pan out. But we can see trends and see data and anticipate the next wave of innovation.
Whatever the future has in store for us all, EVs are here. People are driving them right now. And there’s going to be more of them appearing on the roads and parked up on the driveways as the world moves away from diesel and petrol combustion engine vehicles.
The Vaccine Administration Management solution can help organisations rapidly administer COVID vaccines at scale…
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ServiceNow, which is supporting vaccinations for more than 20 million people with the Now Platform and its Vaccine Administration Management solution, has released further product enhancements to its Vaccine Administration Management solution to help organisations quickly meet the “last-mile” challenges of vaccinating and protecting people at scale. The latest enhancements make it easier for people to schedule vaccination appointments and for providers to manage vaccine inventory.
With the Biden administration directing states to make all U.S. adults eligible for vaccinations by May 1, ServiceNow is committed to leveraging the Now Platform to help states and healthcare providers convert vaccines into vaccinations as quickly as possible. The Now Platform and Vaccine Administration Management solution are being deployed in just days by some providers, using ServiceNow’s workflow technology to rapidly improve vaccine distribution, administration, and monitoring. The NHS National Services Scotland, for example, is using ServiceNow to help quickly vaccinate Scottish citizens.
Additionally, Children’s Minnesota, one of the largest pediatric health care systems in the U.S., recently went live with ServiceNow Vaccine Administration Management in just five days. When Children’s Minnesota expanded its vaccination rollout beyond staff, to patient caregivers and the most vulnerable members of the community, it experienced similar challenges as those faced by other organizations across the country. With its new system, Children’s Minnesota has reduced wait times from three hours in a walk-in model to 20 minutes with an appointment and successfully vaccinated nearly 1,400 staff members, caregivers and the community in 11 hours.
“At Children’s Minnesota, our mission is to champion the health needs of children and families. Right now, that means ensuring our vaccine management process is efficient and able to get our community vaccinated as quickly as possible. After all, one arm at a time is how we can get out of this pandemic,” said Patsy Stinchfield, MS, CPNP, Nurse Practitioner, senior director of infection prevention at Children’s Minnesota and head of the health care system’s COVID-19 incident command center. “We’re thrilled that we are efficiently vaccinating our staff, caregivers and our most vulnerable patients.” #
ServiceNow is helping organisations across healthcare, government, education, and the private sector distribute COVID-19 vaccines and get people vaccinated quickly, including:
The Department of Homeland Security is facilitating vaccinations for its 240,000 employees via ServiceNow for vaccination eligibility checks, communication management, and coordinating mass vaccinations at Veterans Affairs facilities.
The University of Central Florida is leveraging ServiceNow to coordinate and schedule first and second dose vaccinations for its faculty and staff.
The State of North Carolina Department of Health and Human Services (NCDHHS) is relying on ServiceNow’s technology as the foundation for its command center for healthcare providers, clinicians administering the vaccine, and supporting NCDHHS staff to access the latest information related to state vaccine requirements and to get their vaccine‑related questions answered.
Outside the U.S., The NHS National Services Scotland using ServiceNow’s Now Platform as the digital backbone of its program to rapidly roll out the vaccine to protect citizen health in the fight against COVID‑19. Over 220,000 vaccination appointments were booked in the first 12 hours of the Now Platform going live.
Introducing more control and visibility for vaccination scheduling
The latest updates to the ServiceNow Vaccine Administration Management solution improve the vaccination scheduling process for vaccine recipients, administrators, and clinicians, providing increased visibility into inventory, to help convert all available vaccines into vaccinations.
New capabilities announced today offer increased control and visibility over available vaccine doses to help match vaccine appointments with inventory supply to minimise waste and avoid overbooking appointments. This has been a challenge for many organisations, leading to long wait times and leaving many recipients in line with cancelled appointments. New capabilities include:
The ability to schedule and cancel appointments based on vaccine inventory as vaccines are distributed. Organizations can automatically track vaccine inventory in real-time and open, close, and reschedule appointments based on the number of vaccines they have available.
Location-level configuration capabilities enable organisations managing multiple vaccination sites to specify inventory, available hours, and appointment slots by location.
Additionally, new capabilities announced today give vaccine recipients more control over the scheduling process for a seamless booking experience, including:
The ability to select a specific day and time for appointments and independently book second appointments. Previously, users were automatically booked into the first available spot.
The ability for contact center agents to book appointments on behalf of recipients.
Options for family scheduling will be available soon, allowing families to book appointments together and at the same time, rather than signing up individually with different accounts at varying times.
These updates will support smoother and more efficient experiences for both those receiving and administering vaccinations as more people become eligible and vaccines are made widely available.
“The rapid distribution of the COVID-19 vaccine is one of the greatest workflow challenges of our time,” said Mike Luessi, AVP and GM, Healthcare and Life Sciences Industry at ServiceNow. “We are working closely with organizations to rapidly ramp their vaccination efforts and adding new capabilities to our Vaccine Administration Management solution twice a month as the landscape evolves and more vaccines become available.”
Workflow a healthier future
The recently passed U.S. stimulus package has prioritized helping state and local governments recover from the challenges of COVID-19 to get people back to work and to restart the economy.
ServiceNow also continues to innovate its previously announced Safe Workplace suite to allow governments and organizations to safely return to work. ServiceNow’s Safe Workplace Solutions support all aspects of creating a safe and efficient return to work for governments, campuses, and companies. This now includes Vaccination Status, an app that helps public and private sector companies track the status of vaccinations in the workplace.
With the ServiceNow Vaccination Status app, employees and stakeholders in an organization can easily submit documentation of completed health vaccinations to meet return to workplace requirements, where permissible by law. Organisations can also collect vaccination data to assess when it’s safe to bring employees and stakeholders back to a workplace and provide benefits to employees who received vaccinations, in accordance with their respective policies.
To date, more than 1,000 organisations globally have downloaded the Safe Workplace suite apps with over 12,000 unique installations.
“When educators became eligible for the COVID-19 vaccine in Florida, we quickly began working with the Florida Department of Health in Orange County to coordinate the safe and efficient vaccination of faculty and staff,” said Dr. Michael Deichen, Associate Vice President of UCF Student Health Services, University of Central Florida. “We knew we needed a solution to seamlessly manage the vaccine scheduling process.”
“We worked diligently with ServiceNow to build a solution that would meet our goal of safely vaccinating more than 2,000 faculty and staff in just five days,” said Scott Baron, Associate Director, Performance and Service Management, University of Central Florida. “This is a continuation of the work we’ve done with ServiceNow throughout the pandemic to build solutions that support faculty, staff and students.”
It sounds like a strange parallel to draw, but when it comes to the implementation of a digital transformation project – specifically the automation of business processes – Chief Technology Officers (CTOs) and their senior counterparts could learn a lot from the Great Britain Cycling Team.
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Digital transformation, big data and Artificial Intelligence and like phrases used before them, ‘automation’ has grown to become quite the buzzword in the world of business. In fact, there’s now so much talk about the use of technology to ‘streamline operations’, that automation is almost an unattainable panacea in the eyes of many – even in the tech sector where organisations should perhaps know better.
Yes, at an enterprise level, there are some corporate giants thinking big and really nailing it. Likewise, there are some vast organisations with dedicated project teams and six or seven-figure budgets, that become so shackled with scope creep that their automation aspirations remain nothing more than pipedreams.
There are also smaller – and often nimbler – businesses that would be ideally placed to implement automation-led initiatives large and small, but they simply don’t know where to start. Their CTO may have an articulate vision and the ‘toolkit’ to achieve it, but the all-important buy-in from the wider management team – if not the rest of the organisation – doesn’t exist.
It’s certainly a mixed bag, but it needn’t be such a minefield. This narrative will be ‘preaching to the converted’, for many CTOs. So what’s the answer and what will finally stop holding digital transformation projects back?
The aggregation of marginal gains
Organisations embarking, from scratch, on a quest for greater automation, need to stop worrying about moving mountains from day one. Instead of focusing on the entirety of what’s possible, there is arguably more value in breaking the job down into actionable and achievable component parts.
In this respect, much can be learned from Sir Dave Brailsford, head of British cycling, who took the long-suffering team from winning only one gold medal in 76 years, to seven at the 2008 Beijing Olympics – an achievement mirrored in London four years later.
Aware that aiming for gold felt like a daunting and perhaps even impossible plight, he applied the theory of marginal gains to the sport. In other words, he deconstructed everything to create a checklist of micro tasks and concentrated on improving each element by just 1% to secure a significant aggregated performance increase. The mentality centred on progression, not perfection.
Likening this to automation in business may seem like a stretch, but the same principle applies. The possibilities that automation can unlock are almost endless, so to cover everything will probably never be feasible. But by making individual systems and processes more ‘joined up’ with digital transformation – as well as quicker and slicker to execute, with an eye on best practice throughout – means even 1% efficiency gains will soon add up.
Removing digital silos
Some businesses may have far to travel on their automation journey, whereas others may have already made a start by ‘thinking digitally’.
This is something at least, because the digitisation of processes represents an important step. But what happens if these tools and technologies continue to exist on ‘digital islands’, with varying degrees of customisation and few – if any – ‘bridges’ between them to enable the data to do what it needs to. If someone must pull all the strings to make multiple products work together – with a questionable degree of effectiveness – there remains much to do.
The key to automation is to define the process that will spontaneously enable widget A to press buzzer B that activates application C and produces data point D – and so on – digital transformation!
Everything needs to work together, much like a team. And it’s OK to start small.
In simplistic terms, a business may decide to outsource its mailing so it’s saving time – and money – that would otherwise be spent licking stamps! This soon outweighs the cost involved.
But automation can be far more sophisticated too, of course. An email marketing platform can talk intuitively to a CRM tool as a sales pipeline advances, for example, before auto-updating a billing engine when a deal converts and triggering a conversion report to better understand ROI.
Without this automation, people involved in any one part of the process would still have confidence the data existed in there. However, the time otherwise required to uncover it, and then manually push it through the system, could mean the insight soon becomes obsolete and the associated opportunity is consequently lost. The real-time nature of the intel is where the value lies – much like the of-the-moment performance of the GB Cycling Team – hence the beauty of triangulating these multiple elements to create a truly integrated eco-system.
Is Digital Transformation only for big players?
In saying all this, one of the most important points to perhaps note is that automation shouldn’t be feared. Digital transformation is not necessarily a complex process that lies only within the reach of gigantic corporations with equally large budgets. Yes, data volume makes an investment in automation easier to justify. And a degree of technical competence is needed to orchestrate the integration of tools that lead to a super-slick outcome. But it needn’t cost the earth. For senior professionals who have perhaps worn the t-shirt a couple of times over, it’s better to communicate that – making it relatively easy to move forward as a result.
Secondly, automation is not trying to rid people of their jobs and replace them with ‘robots’ – a fear that seemingly shows no sign of fading. On the contrary, at a time when employees are becoming increasingly discerning about their workplace fulfilment levels, it can liberate them from burdensome, administration-centric tasks, and free up their time to focus on activities that make better use of their skills – boosting both productivity and engagement as a result.
Thirdly, the benefits associated with automation aren’t isolated solely to staff motivation and workplace efficiencies. Automation – or certainly, an automation-savvy mindset – can become the lifeblood of a firm’s scale-up strategy, which empowers the business to grow at speed, with a constant eye on cost control and service levels too. In the current economic climate, this agility – not to mention bottom line protection – has arguably never been so important.
by Terry Daniell, Operations Director at Trenches Law
Innovation and change when fighting legacy infrastructure and an antiquated operating model…
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As a market leader in a world of continuous change and digital disruption? What more could you be doing to embrace true digital disruption and deliver on the promise of tomorrow to an ever evolving customer base?
Amanda Heintz, Devops and IT Automation Release Manager at Schneider, joins us to talk about what it’s like to work in an industry that is still perceived to be lagging behind in the digital conversation due to legacy infrastructure and an antiquated operating model…
The question then is, what is Schneider doing to define and redefine the technology market of transportation?
The benefits of embracing innovation and implementing new technologies are clear to see and yet as we speak in 2021 one could argue that there is still evidence to suggest that there is resistance and hesitance to take the risk of digital transformation. It stands to reason that many organisations could be too afraid to embark on a digital transformation journey, despite the seemingly endless cases of major success for those that have done so already.
Listen to Amanda on the Bitsize episode of The Digital Insight podcast below:
With transformation, there are common challenges that come with legacy infrastructure, and with transition and change, so how can businesses cope with such a major shift?
There s no such thing as a guarantee of success. As much as we’d love it. We often speak of successes and looking at what went right, but perhaps more importantly should we explore the importance of admitting that things have not worked out according to plan.
It is no secret that change comes from recognising that there is a need to adapt and to evolve, so the greatest lessons can come from the smallest of missteps.
Digital transformation, disruption, and embracing innovation and change, is no easy task. It is no secret that we all look to other organisations, other industries for inspiration and we look for the big companies that are recognised as the benchmark for innovation, but when you are one of these companies, and you are in an industry that has that label of falling behind the pace, how aware of you of your responsibility to help drive the industry forward?How much do you recognize yourself as a benchmark for others to follow?
Schneider is but one example of the many organisations (big or small( that are truly embracing innovation and disruption and doing so in a way that will help propel the industry forward.
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Why not check out some of our recent episodes of The Digital Insight below:
The new update gives all users tailored access to relevant market research and reports based on their role in their organisation. The update was implemented to prevent an ‘information overload’ from deterring workers and teams from utilising market research – something which can be a real problem for large enterprises who have vast amounts of data and insights available for different teams spread across business units, countries and product lines.
Workspaces & Teams also allows organisations to create separate Workspaces (for example, one for the B2C business unit and one for the B2B business unit) within their Stravito platform. This helps large enterprises give employees direct and easy access to relevant insights, while limiting improper use of the wrong insights, leading to time savings and improved decision-making across business units.
Within each Workspace, organisations can also create Teams to further fine-tune access and relevancy of insights within their business unit, enabling enterprises to customise their experience and access to information in the platform.
In addition to improving user experience, Workspaces & Teams makes it easier for administrators to tailor confidentiality for sensitive research documents.
Thor Olof Philogene, CEO of Stravito, commented: “We are always looking for new ways to combine insights relevance and security to enhance customer engagement with our platform. This Workplace and Teams update is purpose-built for large organisations with distributed units and branches, but as the business landscape continues to change against the backdrop of the pandemic, we also see increased demand for this type of services to suit organisations of all sizes.”
The Workspaces & Teams update follows another recent development targeted towards enterprise customers: ISO 27001 certification.
Stravito’s ISO 27001 certification recognises that the development and delivery of the Stravito SaaS are done in accordance with global information security best practices.
To receive the certification, an in-depth audit testing all security processes and frameworks was undertaken. This included incident management, risk management, employee management, secure software development, and the management of information from third parties – giving customers full peace of mind that their data and information is secure.
Notable aspects of Stravito’s security, which was commended, include its information security policy, which covers all aspects and employees of the organisation, an incident management process, which allows Stravito to triage and resolve any incidents promptly, a secure software development life cycle, ensuring they deliver secure and bug-free code, and a solid risk management framework, which is used to identify and mitigate risk throughout the organisation.
Marcus Södervall, head of Security at Stravito, commented: “Receiving the ISO 27001 certification is a huge accomplishment for Stravito, reinforcing our commitment to implementing best-in-class security that truly protects our customers and their data.”
“Not only does ISO 27001 test the maturity of Stravito’s processes, but it also embeds security into our company’s DNA, shining a light on the trusted and reliable platform we have built.”
By doubling down on essential capabilities for enterprises, like customisation and security, Stravito aims to continue its mission to simplify knowledge discovery for global organisations.
Google, BT and DCMS among over 1,000 organisations offering free mentorship to independent organisations through Digital Boost
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Digital Boost, a new platform connecting organisations with digital skills founded by serial entrepreneur Sherry Coutu CBE, has today set out a bold ambition to digitally upskill 500,000 women from female-led organisations by January 2022, with 200,000 of those from BAME backgrounds. This comes as recent research revealed that 97% of charities feel insecure about their command of digital skills, while a survey conducted by BT and Small Business Britain found that 63% of small businesses lack confidence in future-proofing their business.
Digital Boost helps small organisations access digital skills through unlimited free one-to-one mentorships delivered by volunteers at some of the world’s most respected organisations including Google, DCMS, Visa, BT and The Big Lottery. Digital Boost is also working with its partners to offer specialised workshops and access to short online courses to its learners.
Since its launch in June 2020, Digital Boost has mentored more than 2,000 small businesses and charities. It currently has 1,600 partners listed on the platform and has successfully delivered multiple one-to-one mentoring sessions.
Sherry Coutu CBE, founder of Digital Boost, said, “We’re proud to work alongside our valued partners to mentor at least 1 million people who work for small businesses and charities by 31st January 2022, of which 20% will identify themselves as BAME and 50% will identify themselves as female. With our enhanced digital platform that offers unlimited mentoring support as well as commercial partnerships for potential corporates, we believe we can significantly boost the revenues of female-led businesses”.
As a beneficiary of multiple mentoring sessions, Amanda Mann, founder of Mann’s Cookies, said: “Mine is a Covid-19 business. I couldn’t imagine I would have so much fun and meet such amazing people but I didn’t have any business experience so I am so grateful I found Digital Boost. They were brilliant on our mentoring calls and they were great at helping me get to grips with the mechanics of business, showing me how to deliver great customer service and sharing tips on keeping up my social media presence.”
Three years on from Open Banking launched in the UK, let’s look at what we’ve done and where we can go from here…
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Earlier this year, UK Open Banking celebrated three years. Since 13 January 2018, regulated third-party providers have been able to integrate with bank APIs to access customers’ financial data, in an effort to break down the barriers standing in the way of seamless data sharing.
The overarching goal of this new regime was to give consumers and businesses greater visibility and control over their finances, with technology at the forefront of this mission. Specifically, the pioneering Open Banking initiative was created to enable financial technology (fintech) providers to bring innovative new propositions to the SME and consumer market.
By extension, the users of Open Banking would benefit from products that were better suited to their unique financial situation, enabling them to compare available products in order to find the best deals on the market. So, as we reflect on three years of Open Banking, the question is: how much progress has been made, and what’s in store for the future?
Increasing collaboration through innovation
The introduction of a new requirement for all UK-regulated banks to allow customers to share their financial data with authorised third-party providers introduced a new era of collaboration within a previously segregated market.
Joined by one overarching mission – namely, to drive innovation and deliver the best possible customer experience – large banks and fintech startups began forming valuable partnerships. Thanks to more efficient data sharing, incumbents, for instance, have been able to integrate propositions developed by fintechs into their own platforms, in an effort to better meet the evolving needs of the customer.
The benefits to the customer are evident: a more interconnected and open financial ecosystem, which enables them to browse available products and access the right services for their needs.
Since its inception, Open Banking has served to shift the power to the customer and increase competition within the sector. By utilising new apps and digital platforms, banking customers now have access to a fuller and clearer view of their finances. This allows individuals to budget more effectively, switch products more easily, and generally make more informed decisions.
Increasing uptake
Since the initiative was launched in 2018, Open Banking adoption among UK consumers and businesses has surged. While generating awareness about its benefits has been a slow process (a recent PwC study found that only 18% of consumers were aware of what Open Banking means for them), the COVID-19 pandemic has driven Open Banking usage.
Today, over two million users utilise Open Banking-enabled applications and services. This number has doubled since January 2020, with the pandemic likely having a strong influence on the rate of uptake.
As disruption took hold and personal finances took a hit, many people turned towards online banking and money management apps, in search of tech solutions that could bolster their financial confidence. Since the first lockdown in March 2020, almost one in five (17%) of UK adults have started using an online banking service to help with their money management goals, with this figure rising to 45% among 25-34-year-olds.
Without the advent of Open Banking, the accessibility and value of such solutions would be questionable. After all, many of these fintech solutions use Open Banking to connect directly to users’ bank accounts to provide a more tailored service.
At the same time, it has also enabled financial services providers to obtain an accurate and up-to-date view of an individual’s financial situation, as well as their past and present behaviours, in order to deliver more personalised guidance.
How will Open Banking develop?
Open Banking today generally covers personal and business current accounts, credit cards and online e-money accounts. In the future, the concept will extend to cover all financial markets – from pensions to investments and insurance.
Now that we have built the underlying infrastructure, it will become easier to build on top of this. More complicated use-cases of Open Banking will begin to develop, with competition from non-traditional players such as fintechs and challenger banks stepping in to provide a range of new services – particularly within industries that previously strayed away from large scale digital transformation.
As the ability to let information flow between applications continues to improve, new products and iterations of existing offerings will be built, integrated and modified at a much greater speed than before. We will shift away from a closed banking system to one that encourages new aggregators, service partners, and payment providers to add value to existing businesses models, and in doing so, create a range of new customer-centred financial services.
Examples of innovations that we are already seeing include services that provide personalised advice to banking customers looking to improve their credit score, and applications that enable employees to save directly from their salary.
We’ve come a long way in the Open Banking revolution, giving consumers and businesses greater control over their financial lives and the ability to choose products and services that work best for them. As we progress further towards Open Finance, this initiative will give customers greater influence over a wider range of their financial data, and offer access to enriched financial services.
Ammar Akhtar is the co-founder and CEO of Yobota, a London-based technology company. Founded in 2016, Yobota has built a fast, flexible, cloud-native core banking platform, which allows clients to create and run innovative financial products. You can follow Yobota on LinkedIn and Twitter.
Our exclusive cover story this month is an in-depth look behind the scenes at Cisco…
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Welcome to issue 20 of Interface Magazine!
Our exclusive cover story this month is an in-depth look behind the scenes at Cisco; the company that helps its clients adapt to an ever-changing world by providing the building blocks of a digital ecosystem that allows more agile and efficient communication alongside operational prowess. But what about Cisco itself? What does transformation look like inside this Silicon Valley giant, and how does itsuccessfully harness data-driven, digital technologies to improve its own operations to boost growth and profitability?
We caught up with Dr. Christian Vogt, Cisco’s Chief Innovation Officer of Data & Analytics at his Silicon Valley office. Christian’s mission is to drive the adoption of digital, advanced analytics, and artificial intelligence at Cisco, and to incubate and scale the capabilities needed to accomplish this, both inside his organization and across the company. Some of these technologies are developed by Cisco’s own engineers, while others are the result of partnering. To achieve the latter, Christian has established an open-innovation arm that partners closely with world-class startups and venture capital firms in Silicon Valley and beyond. “My goal is to make us a more data-driven, digitally enabled, and AI-powered company,” Christian explains.
Elsewhere, we also meet up with Aviva Italy to see how a cloud-native ecosystem will help the company address the new paradigma of insurance. Plus, we look at the past, present and future of Open Banking and examine how CTOs could learn so much from the GB Cycling Team!
As people began to spend more time online in 2020, it resulted in a boom of DDoS attacks…
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The number of DDoS attacks detected by Kaspersky DDoS Prevention in Q4 2020 increased slightly in comparison to the same period of 2019. However, it is 31% less compared to Q3 2020. This drop can be connected to the growing interest in cryptocurrency mining.
However, in Q4 2020 there were only 10% more attacks than in Q4 2019. And compared to Q3 2020, the number of attacks in Q4 2020 fell by 31%, while Q3 2020 also saw a drop compared to Q2.
Experts suggest that this can be caused by a surge in cryptocurrency costs. As a result, cybercriminals may have had to ‘re-profile’ some botnets so that C&C servers, that are typically used in DDoS attacks, could repurpose infected devices and use their computing power to mine cryptocurrencies instead.
This is further proved by KSN statistics[1]. Throughout 2019, as well as in the beginning of 2020, the number of cryptominers was dropping. However, from August 2020 the trend changed, with the amount of this form of malware increasing slightly and reaching a plateau in Q4.
“The DDoS attack market is currently affected by two opposite trends. On the one hand, people still highly rely on stable work of online resources, which can make DDoS attacks a common choice for malefactors. However, with a spike in cryptocurrency prices, it may be more profitable for them to infect some devices with miners. As a result, we see that the total number of DDoS attacks in Q4 remained quite stable. And we can predict that this trend will continue in 2021,” comments Alexey Kiselev, Business Development Manager on the Kaspersky DDoS Protection team.
To stay protected against DDoS attacks, Kaspersky experts offer the following recommendations:
Maintain web resource operations by assigning specialists who understand how to respond to DDoS attacks
Validate third-party agreements and contact information, including those made with internet service providers. This helps teams quickly access agreements in case of an attack
Implement professional solutions to safeguard your organisation against DDoS attacks. For example, Kaspersky DDoS Protection combines Kaspersky’s extensive expertise in combating cyberthreats and the company’s unique in-house developments
With industrial organisations ramping connectivity to accelerate digital transformation and remote work, threat actors are weaponising the software supply chain and ransomware attacks are growing in number, sophistication and persistence.
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A new report from Nozomi Networks Labs finds cyber threats to industrial and critical infrastructure have reached new heights as threat actors double down on high value targets. With industrial organisations ramping connectivity to accelerate digital transformation and remote work, threat actors are weaponising the software supply chain and ransomware attacks are growing in number, sophistication and persistence.
“This report leaves no doubt that the time for action is now,” said Nozomi Networks Co-founder and CTO Moreno Carullo. “The recent Oldsmar, Florida, water system attack and the ongoing SolarWinds investigation are dramatic reminders that the critical infrastructure and other systems that we rely on are vulnerable and at constant risk of attack. Understanding the effectiveness of defenses against the emerging threat and vulnerability landscape is vital to success.”
Nozomi Networks’ latest “OT/IoT Security Report,” gives cybersecurity professionals an overview of the OT and IoT threats analysed by Nozomi Networks Labs security research team. The report found:
Ransomware activity continues to dominate the threat landscape, growing in sophistication and persistence. In addition to demanding financial payments, Ryuk, Netwalker, Egregor and other ransomware gangs are exfiltrating data and deeply compromising networks for future nefarious activities.
Supply chain threats and vulnerabilities show no signs of slowing. The unprecedented SolarWinds attack not only infected thousands of organisations including U.S. Government agencies and critical infrastructure, but it also demonstrates the massive potential for attack via supply chain weaknesses.
Threat actors are targeting healthcare. Nation states are using off-the-shelf red team tools to execute attacks and perform cyber espionage against facilities involved with COVID-19 research. Ransomware crews are targeting healthcare providers and hospitals, in some cases disrupting patient treatment.
Analysis of 151 ICS- CERTs published in the last six months found memory corruption errors are the dominant vulnerability type for industrial devices.
“Urgency has never been higher. As industrial organisations race toward digital transformation, threat actors are taking advantage of greater OT connectivity to create attacks that aim to disrupt operations and threaten the safety, profitability and reputation of enterprises around the globe,” said Nozomi Networks CEO Edgard Capdevielle. “While threats may be on the rise, the technologies and practices to defeat them are available today. We encourage organisation to act quickly to implement the recommendations in this report. It’s never been more important or more possible to take the necessary steps to detect and defend critical infrastructure and industrial operations.”
Nozomi Networks’ “OT/IoT Security Report” summarises the biggest threats and risks to OT and IoT environments. The report provides information on 18 specific threats that IT and OT security teams should study as they model threat vectors and evaluate risks across operational technology systems. It includes 10 key recommendations and actionable insights to improve defenses against the current threat landscape.
The adoption of smart building systems has become a case of “when”, not “if”
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More than half of organisations plan to increase their investment in renewable energy, energy efficiency, and smart building technology in 2021. This is according to Johnson Controls’ annual Energy Efficiency Indicator survey. Interestingly enough, these business plans are comparable with investment trends that came after the 2010 recession; now likely a result of preparation for the post-pandemic world.
As people begin returning to shared spaces once herd immunity has been reached, the health of building occupants and energy efficiency will continue to be top of mind—and an investment priority for facilities managers around the world.
What are the drivers?
– Health and safety concerns.
– Reducing energy use and working towards net-zero targets.
– New awareness around reducing the spread of infection as a result of the COVID-19 pandemic.
– The need to increase the ability to operate under different conditions, both planned and unforeseen.
In this article, we’ll delve further into the survey and reflect on the conclusions drawn. It is important to note that while the report reflects an analysis of the US market, many of the themes are appropriate to the European property industry, and the research opinions are likely shared by the majority.
Net zero is the new hero
As Paris Agreement obligations edge closer, facilities managers are under increasing pressure to reach net-zero targets.
– 70% of organisations are very or extremely likely to have one or more facilities that are nearly zero, net zero or positive energy or carbon status in the next 10 years (an increase of 7% from 2019).
– 66% are very or extremely likely to have one or more facilities able to operate off the grid in the next 10 years (an increase of 3% from 2019).
– 63% invested in onsite renewable energy in 2020 (a 22% increase from 2019).
How smart tech can help:
The key to harnessing energy efficiencies is having access to accurate, real-time energy consumption data. By knowing how energy is used in your facility (and when), you can identify an “energy action plan” that works for you. This is the role of a smart energy meter; using these will put you in control of your consumption.
Other smart, sensor-based technologies can help reduce energy consumption. For example, occupancy sensors can control lighting and heating so that energy is only being used when someone is in the room.
A breath of fresh air
With the evidence strongly indicating that COVID-19 is spread through aerosol transmission, indoor air quality is set to become tantamount to facility safety for facilities managers.
According to the survey:
– 79% are planning to or have already increased air filtration.
– 75% are planning to or have already installed an air treatment system.
– 72% are planning to or have already increased outdoor air ventilation rates.
How smart tech can help:
New technology is enabling better air quality by observing and monitoring air quality in real time. Indoor air quality sensors can continually measure the air quality within a given area and send an immediate alert if the air quality or ventilation is compromised in any way.
Simple, smart management systems
According to 81% of survey respondents, increasing the flexibility of facilities and buildings to quickly respond to a variety of emergency conditions was a “very” or “extremely important” driver of investment.
Managers are looking for multi-faceted, ‘all-in-one’ solutions that can streamline workflows and business operations at a glance.
– 75% have invested in the integration of security systems with other building monitoring systems (an increase of 36% from the 2019 study).
– 33% plan to invest in the integration of building technology systems with distributed energy resources in the next year (an increase of 15% from the previous study).
– 79% say that data analytics and machine learning will have an extremely or very significant impact on buildings.
How smart tech can help:
From occupant health to energy efficiency, having an interconnected smart building system is fast becoming the norm rather than the exception. The ability to monitor, maintain and control various aspects of a building remotely via a single dashboard allows the facility manager to—quite literally—ensure a safe, efficient, energy-saving environment at all times, from anywhere.
The future is here; and, as evidenced by the survey, the adoption of these smart systems has become a case of “when”, not “if”.
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About the author
Matthew Margetts is Director of Sales and Marketing at Smarter Technologies. His background includes working for blue-chip companies such as AppNexus, AOL/ Verizon, and Microsoft in the UK, Far East and Australia.
About Smarter Technologies
Smarter Technologies tracks, monitors and recovers assets across the globe in real time, providing asset tracking systems to the open market and fulfilling the world’s most complex asset tracking requirements. Our services cover a vast array of business sectors, products and equipment from container or pallet tracking to military-grade devices; and can be used across a broad spectrum of industries.
As a leading IoT company, we also provide smart building solutions for modern businesses, offering wire-free, battery-powered and low-cost IoT smart sensor technology. Our solutions will put an end to scheduled maintenance and help businesses utilise their building’s efficiency, benefitting from real-time alerts and facilities management tools that will bring them into the 21st century.
Conventional robots, like giant industrial robots used in the car industry, are set to reach $14.9bn value this year, up from $12bn in 2018.
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Robotics play a huge role in the manufacturing landscape today. A growing number of businesses use manufacturing robots to automate repetitive tasks, reduce errors, and enable their employees to focus on innovation and efficiency, causing the entire sector’s impressive growth.
According to data presented by AksjeBloggen.com, the global market value of conventional and advanced robotics in the manufacturing industry is expected to continue rising and hit $18.6bn in 2021, a 40% increase in three years.
Market Value Jumped by $5.4B in Three Years
Robots have numerous roles in manufacturing. They are mainly used for high-volume, repetitive processes where their speed and accuracy offer tremendous advantages. Other manufacturing automation solutions include robots used to help people with more complex tasks, like lifting, holding, and moving heavy pieces.
Companies turn to robotics process automation to cut manufacturing costs, solve the shortage of skilled labor and keep their cost advantage in the market.
In 2018, the global market value of conventional and advanced robotics in the manufacturing industry amounted to $13.2bn, revealed the BCG survey. In 2019, this figure rose to $14.8bn and continued growing. Statistics show the market value of manufacturing robots hit $16.6bn in 2020. This figure is expected to jump by $2bn and hit $18.6bn in 2021.
Conventional robots, like giant industrial robots used in the car industry, are set to reach $14.9bn value this year, up from $12bn in 2018.
The market value of advanced manufacturing robots, which have a superior perception, adaptability, and mobility, tripled in the last three years and is expected to hit $3.7bn in 2021. Combined with big data analytics, advanced manufacturing robots allow companies to make intelligent decisions based on real-time data, which leads to lower costs and faster turnaround times.
The BCG survey also showed most manufacturers believe advanced robotic systems will have a massive role in the factory of the future and plan to increase their use. More than 70% of respondents defined robotics as a significant productivity driver in production and logistics.
European and Asian Companies Lead in the Use of Advanced Manufacturing Robots
Analyzed by regions, European and Asian companies lead in the use of advanced robots, while manufacturers from North America lag behind. However, the survey showed 80% of respondents from the US plan to implement advanced robotics in the next few years.
The survey also revealed that manufacturers in emerging markets, especially China and India, are more enthusiastic about using advanced robots than those in industrialized countries. These companies may be looking to automation as a way to overcome a skilled labor shortage and improve their ability to compete in international markets.
Germany had the largest robot density in the manufacturing industry among European countries, with 346 installations per 10,000 employees in 2019. Sweden, Denmark, and Italy followed with 277, 243, and 212 installations per 10,000 employees, respectively.
Statistics also show that companies in the transportation and logistics and technology sector lead in implementing advanced robotics, with 54% and 53% of manufacturers who already use such solutions. The automotive industry and consumer goods sector follow with 49% and 44% share, respectively.
Manufacturers in the engineered products, process, and health care industries lag behind, with 42%, 41%, and 30% of companies that use advanced manufacturing robots. However, around 85% of manufacturers in these sectors plan to start using advanced robotic systems by 2022.
Mark Wright, Director of Climb Online discusses the importance of speaking the right business language when operating in a crowded digital marketing sector…
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Mark Wright, Director of Climb Online and a successful entrepreneur with a passion for business and a love of digital marketing (and the winner of Apprentice UK back in 2014) discusses the importance of speaking the right business language when operating in a crowded digital marketing sector. We also explore how, as long as you have the passion, the drive, the knowledge and a brutal honesty, then you have what it takes to succeed.
Marketing is something that everyone thinks they’re an expert on, so how do you cut through that?
It’s an excellent question. It comes back to understanding the customer’s industry and business that you’re dealing with. No digital marketing campaign is ever the same, and that’s because no business is ever the same. The fundamental flaw most digital marketers make, or most people in the online world, is taking a cookie cutter approach, treating every business like the same, and every campaign should be the same, when every business needs to be displayed and understood differently. What I did very, very well early on is personally get to know the individual that I’m dealing with, and their personalities and the personalities of their business to understand which marketing strategy would be most appropriate for this business.
For example, if you’re working with a plumber that’s got a great personality, looks great on camera, something like YouTube ads or social media marketing ads with video of that guy talking about his products and services could be phenomenal because he’s got something his competition doesn’t, which is him, his personality. Then, you might have someone that’s shy or hates being in front of the camera, but is very creative, and that person could do great testimonials, great imagery, and case studies on their website and boost it out through blogs or whatever it might be, their way.
It’s understanding what’s going to work for the customer and what works best for that industry. That’s why these cheap, outsourcing it to India, cookie cutter approach businesses don’t work. 99 times out of 100, I go and meet a business and they tell me, “I tried marketing. It didn’t work,” but they’ve tried marketing that’s worked for everyone else, but hasn’t had anyone understand what they should be doing.
You work with clients, for example, Emirates, but also the local dentist. That’s going to be different conversations but both are wanting the same outcome, so how do you communicate with them?
Well, I am a very direct person. A was very upset with me because she didn’t feel the marketing approach I was displaying for her business was right for her business. I said to her; “You’ve been with other marketing companies before, and you failed every single time. Now, if I presented you the same strategy and the same approach that you’ve done over, and over again, we will fail again.
“You have come to me and paid me very hard-earned money to come to me to let me do your marketing. Then, you’re going to ring me up and tell me how to do your marketing. Then, if I listen to you, we’ll fail, because I am the expert. I am the person that is the best marketer, is the best company to go to, and I’m charging you. Now, if I was to listen to you and do your strategy, why would you pay me good money to do that for you? You must listen to me.”
I don’t ring you up, if you’re a dentist, and tell you how to fit a crown, or whiten my teeth, or do this, because I don’t really know. I might have watched a couple of YouTube videos or heard about it down at the pub, but I don’t really know what I’m doing because I haven’t got the experience, I haven’t got the expertise. The funny thing about marketing is everyone is a bit of a bedroom DJ. They think they know their onions, so to speak, but the truth is that I’ve worked 11 years every day, as you say, day-in, day-out, working with thousands of companies. I get it. I understand what to do.
I have to be quite blunt with people sometimes and just say, “Just leave me to it.” Because you don’t put your car in the garage with the mechanics and stand over him and tell him which wrench to use and which filters to change. You understand that that person has experience, qualifications, and the understanding of what to do. Generally, the biggest problems I’ve ever seen in marketing campaigns is owner-operators dipping their wick in, and going in and making changes and putting their two bucks worth in, or not spending enough money. Then, they tell us that marketing doesn’t work.
If you hire experts, if you work with people, you’ve got to let them do their jobs and not tell them how to do their jobs. Because Steve Jobs was a great advocate for if you hire A-players, you need them to let them be A-players. Let them be creative. Let them do the things that you hired them for, and that’s when you get the best results.
Forgive me if I’m wrong, there are thousands of marketing companies that could say and promise the world to clients, but what do you do to ensure that you stay ahead of them?
Yeah, there’s thousands of companies that do. This is the million pound question. Any company, any entrepreneur or any business person that stops innovating starts dying. The day you start standing still, you start moving backwards, so you’ve got to constantly challenge yourself to stay ahead of the market. That’s listening to your customers, that’s listening to technology. Understanding what the next Facebook’s going to be, what the next video content’s going to be. Is it going to be augmented reality? Is it going to be VR? Is it going to be UX? What is it going to be that’s going to be the next Google AdWords for our sector?
Our job is constantly investing in research, constantly investing in new products and new markets to make sure that we’re ahead of every other marketing agency out there. Once upon a time, you used to walk into a phone shop and there were hundreds of phones on the wall. You’d go into a carphone warehouse, and you could pick up to 150 phones off the wall to be your handset. Now, you walk into the shop, there’s three. You’ve probably got a Galaxy, you’ve got an iPhone, and maybe whatever the third-party of the day is. There have been people that have come into that market, that their products have been so good, it killed the other competitors.
My job at Climb Online is making sure that our product and our technology gets our customers such good results that there’s no other option than to go with us, and it kills those other thousand competitors. That’s what I think about every day as I’m getting up and I’m going into work; “What am I doing today for my customers that’s going to make me so essential to their business that everyone has to use me?”
What are some of the current trends you are seeing in the industry?
We’re living in just the most fascinating time in human history. The advances in technology that we’re seeing are just unbelievable. You go back 70 years ago, they didn’t have the TV. We now have the Internet. I still remember, in my time, when we had dial-up Internet, and you would have to sit there for 10 minutes while the box made all that noise, and it’d take five minutes for a website to sort of click down the browser. We’re living in a time where machine learning, algorithms, analytics are just changing the game.
Some of the stuff I’m seeing in analytics, things are being done online using data and analytics that we cannot even dream of. I’m seeing technology, that just blows your mind in terms of data prediction and output that is just breathtaking. The stuff that the companies are collecting in terms of data, and using to segment audiences, supply advertising data, but also control what we’re seeing, and feeling through the media that we’re consuming, is just really intelligent stuff.
I think we’re moving really quickly, and the thing that I’d want to back is being on top of analytics and data. That’s the thing that I’ve seen over the last couple of years that’s really impressed me, and the thing that I think is going to be the big game changer moving forward. If you’re in business right now, understanding your customers and what they want to see, what they’re feeling, how to talk to them is really important. There is technology out there to do that much better than you’re doing it right now. It’s the customers that are understanding that technology and how important analytics are that are the ones that are going to be successful over the next few years.
What have you seen in terms of the impact of COVID on the business landscape?
It’s been a very challenging period. At the same time, when I’ve reflected on it recently, I’m very grateful for where we are and what we’ve learned. I mean, for example, the amount of money that we’ve discovered we were wasting on going to face-to-face meetings all around the country, getting on a plane here, a train here, a hotel there, when our sales process is now improved. It’s now shorter. We’re doing more things by Teams, Zoom, et cetera, like this, saving the company money. We’re closing bigger deals. We’re closing them faster, all using technology.
COVID has changed the world. Now, the health side of it is terrible. The business side has really sorted out the men from the boys, shall we say. It’s sorted out the skilled sailors from the people that were just floating around on a wooden door. There’s businesses that are going under right now, and they’re saying it’s because of coronavirus. Jamie’s Italian went under about a year ago, 12 months ago, right before coronavirus. If they went bankrupt right now, they would blame coronavirus. They didn’t go bad because of coronavirus. They were just a bad business. There are many companies that were over-leveraged, that had poor market share, that had too many employees, that had bad technology, and now they’re blaming coronavirus.
On the flip side, there are some companies like airlines that are just affected, holiday companies that are really affected by coronavirus, and I get that. Our job, as business people, is to understand who it is affecting and who it isn’t. At the start of this, it did affect my business a little bit, but we’ve improved our processes, we’ve learned from it, and we’ve understood what we can do better through technology, through working with different industries, different niches, to make sure that we’re more protected for the future. We’ve also understood that there was wastage in our business that we could improve on.
Tough times are always going to be around. This year, it’s coronavirus. In the future, it will be something else. We can either sit back, furlough ourselves, furlough our employees and blame the environment for failure, or you can tackle it head-on and you can learn from it. If you can run a business right now, if you can thrive right now, you’ve got an incredible business. If your business makes it through this, you have something for the future. If it doesn’t, you probably didn’t have a great business anyway, and your job is to be serious. It comes back to that honesty.
Look at yourself and say, “Is this coronavirus, or is this a bad business? Is this a bad employee, or is this a coronavirus problem?” I think this period has been a great time for really true reflection. Looking at yourself, looking at your business in the mirror and understanding what is good and what is bad. What do I want to change, and what do I want to keep? There’s been a lot of natural cleansing in this period. I think a lot of people, whilst right now it feels really ugly, in 12 months time, they’re going to have made some decisions or be in a totally different business or career, and be really happy and glad this happened because sometimes, things always have a natural way of working themselves out.
Mark Wright
What is your key to success?
Find whatever it is you love to do, and then get obsessed with it. If you want to be successful, you have to be obsessed with being successful in whatever it is. That’s the best advice I could give anyone. I learned, very early on, what it is I was going to do, and I focused on that, day-in, day-out. I watched You-Tube videos about it at lunchtime. I worked until midnight about it, day-in and day-out. It is really finding something that you enjoy, finding something you’re good at and passionate about, and then just really working at it like crazy. If you do that, it doesn’t matter what tools you have behind you, what mentor you’ve got, this, that, and the other, you’ll get there eventually if you stick at it long enough.
Research reveals that millennials would be willing to take a pay cut to work in a nicer office; and also consider quitting if their workplace is either outdated or inefficient…
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Today, smart buildings are becoming more dynamic and tailored to individual requirements, specifically within the office space. And with Gartner predicting that the greatest source of competitive advantage for 30% of organisations over the next few years will be their ability to creatively exploit the digital workplace, the pressure is on for businesses and building owners alike to invest in the latest technologies and techniques to provide even better user experiences.
Employee Expectations
Research reveals that millennials would be willing to take a pay cut to work in a nicer office; and also consider quitting if their workplace is either outdated or inefficient. Employers need to keep up with the rapidly changing demands of employees in order to stay competitive when attracting and retaining talent.
To achieve this, workspaces are now becoming more ‘aware’ through an ecosystem that allows buildings to dynamically adjust to the requirements of users through the convergence of IT and Operational Technology (OT) such as building management systems, energy and space management. There is an expectation in place that facilities and building management firms will adapt to meet employee expectations; if not, then they will fall behind.
Collaboration and Productivity
Many companies are leading the way with shared office facilities and hot desks on a part-time or multi-lease basis. With desk layouts developed by algorithms, companies are responding to the demand for mobility and flexible consumption in the modern digital workspace. By configuring open and closed spaces through noise-absorbing fabrics and glass doors, buildings are providing the privacy of individual offices within an open plan setup, meaning that staff no longer need to be confined by physical walls.
Furthermore, data can be collected about user movements, machinery condition, energy usage and other activities within the building that can be used to optimise the user experience and enhance collaborative processes further. For example, mobile phone controlled AV screens, wafer-thin sensors that can detect occupancy and trigger the air conditioning system, ongoing measurement of internal environmental conditions including temperature, humidity and CO2, and indoor mapping and navigation platforms.
Sustainability
With 72% of office workers revealing that a sustainable environment is important to them, embracing this new movement has become a competitive necessity. Through clever environmental design which optimises space, consumption and resources, smart offices can reduce the overall environmental impact and save money and resources along the way. From autonomous energy systems that shut off heating and lighting when rooms are vacant to systems that monitor and optimise the use of water and electricity, these offices can identify their most wasteful aspects and also lessen the pressure on the national grid.
Making the Business Case
Smart buildings in themselves are opening up new revenue streams. But the cost of IoT implementation may be perceived as a barrier to its adoption and development. Many smart offices are built from scratch so existing workplaces need to be retrofitted with technology. And although there is an upfront investment or cost to retrofit an existing building, once installed, additions such as optimised lighting make running these spaces much more cost-effective to the building owner.
The Role of the MSP
Managed Service Providers have a valuable potential role to play beyond providing Digital Communications and collaborative infrastructure including high speed internet lines, Wi-Fi and cloud based collaboration technology such as Microsoft Teams. The MSP can work with an emerging ecosystem of expert IoT infrastructure, device and applications companies to deploy IoT sensor devices, capture and flow data to cloud based applications for insight and action. The MSP can become the agent of new efficiency gains for buildings and their users, generating new income streams and increasing user satisfaction.
Conclusion
People are the largest investment of an organisation, and as new technologies evolve to make their lives easier and safer, it is important to look at which technologies, strategies and approaches will create the most positive, productive and efficient impact for your office and users. IoT technologies, effectively overlayed and combined with existing digital infrastructure and collaboration initiatives, potentially deliver new data insight to further improve and enhance the intelligent workspace and productivity. An ecosystem of expert IoT companies working with incumbent MSPs can be an effective design, deployment and management mechanism for tapping into the intelligent workspace opportunity.
Interface Magazine talks to James Shanahan, CEO Revolut Singapore, regarding an exciting new dawn of digital banking…
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The banking sector has experienced so much disruption in recent years, hasn’t it?
My background is in banking and insurance for many years. One of my observations ever since has been the emergence of internet banking where the operating models of banks are very much outdated and customer experience is lagging behind what customers expect and experience in other industries. One of the opportunities that Revolut brings to the table or has built, in fact, is that we continue to expand on a new perspective on customer experience and a new perspective on the underlying operating model of banks. We’ve built, and continue to expand on, a global operating model. It’s a contemporary approach with a single underlying infrastructure; one that makes the business highly scalable. And I think in order of magnitude, less costly and more efficient than your run-of-the-mill bank.
Why is this so important?
This is important because when you take a zero off the cost of pretty much anything, you can change the world. And we’ve seen that in many industries in the past and as we move down that path with Revolut, we can see that as we bring ourselves into more and more markets. The difference that makes to our customers and the difference that makes to our ability to scale the business very rapidly is immense. The fundamental business model of banking is the balance sheet, leveraging the balance sheet, taking in deposits, lending those deposits out, and essentially, making a margin on that business. That business is not being disintermediated. The balance sheet business of a bank is intact and sound and will continue on for hundreds of years into the future, is my expectation. However, the surrounding systems, the surrounding protective systems, whether they’re credit systems, whether they’re profit and loss generating platforms or new product platforms, you will want to cut the G and L platform: the credit scoring, the risk engines, all of these are designed to protect those balance sheets. And then, of course, we get to the distribution where the high cost of branches, the high cost of ATM networks, are the millstone around the neck of banks that no longer performs the way it has done in the past. I mean, with the advent of technology, we can disintermediate at that level.
How does a restructuring of a platform help?
Looking at it from a more holistic perspective, the business model of a bank is intact, but the way it is carried out is dramatically or vastly inefficient to what’s possible using the kind of technology we have available today. And so, when you reimagine that from the perspective of an organisation like Revolut, you can conceive of a global bank that operates on a single common platform. You can conceive of a global bank that shares the same operating model universally. And when you start to do that, you are able to scale the business far more rapidly than any bank. Most banks, if you look in their scaled markets, are going to be individual stacks. The stack we have in one country is different from the stack that we have in another country. And that leads, obviously, to very high cost and the inability to move rapidly and to act in a very agile manner. So, by re-conceiving the infrastructure of a bank, if you like, the way that a bank delivers its services, you can take an order of magnitude off the cost, number one, and you can bring a level of experience to the customer that’s not hamstrung by old tech, by old thinking, by siloed approaches, and even a silo at a country level. Because frankly, that school of thinking, that style of thinking is really what’s held banks back and continues to do so, today.
I guess changing is coming to many banking enterprises?
There are some banks starting to move out of that mindset, but it’s like turning the ocean liner. And we’re coming along in perhaps not a speed boat anymore, but in a fast-moving, rapidly expanding boat that can move quickly, can turn quickly and can speed past, some of the incumbents in the market. In any market, we always overestimate what can be achieved in one year, but we dramatically underestimate what can be achieved in 10 years. So, Revolut is five years into its existence. I mean, ask me that question in five years or 15 years, and I hope to show you that Revolut is a global bank with tens, if not hundreds, of millions of customers on board able to operate at margins which put banks in their current form to shame.
Security issues obviously increase with these transformations…
Well, look, security is a war, and a war that will continuously wage. I think there’ll be no end to that. The good guys versus the bad guys will go on forever. What I see is this is increasingly… What we all see is a tech battle as we move to technology as a way to distribute financial services. I think a company that has a stronger tech underpinning and is digitally native, if you like, in its understanding of that technology, will always fight a better battle than those who have to learn the tools of war and have to bring their approaches to a new battlefield, if you like. I think there’s a second part of it as well. So, not only the ability to leverage technology more completely and with more modern and up-to-date tools, if you like, but also the usability factor here. So, a lot of security issues are not driven by weaknesses in the underlying security, but rather weaknesses in customers’ behaviour or lack of understanding on the part of protagonist in the transaction as to what might represent a less secure way of doing things. By having a lot of agility and flexibility on the front end with this customer experience, we can make it easier for customers to stay secure. We can educate them through the way that the application is laid out, through the way the customer journey moves. And we can avoid situations by running, if you like, a rule set or machine learning, or some artificial intelligence tools around the transactions, in addition to the usual transaction monitoring tools and protection tools to guide customers and to help them in a way that many, I think, less contemporary organisations don’t have the flexibility to do. That allows us to do, build in a level of customer awareness of security right from the beginning, and to adjust that on the fly. We can adjust our front ends very, very quickly and lead customers to a better position.
Does this inevitably lead to lower fraud rates?
We find our fraud rates, for example, to be significantly lower than industry standards right across the board. And I think this does reflect the fact that we have a more agile and more technologically-sound understanding of what’s going on, and we can apply it more completely. There’s also something to be said for the ability to manage customers’ expectations in this regard. So, it’s quite clear coming onto a digital-only platform from a financial services perspective, that customers need to be educated, need to be made secure, need to be reminded, if you like, or nudged in the right directions. And that’s easy to achieve with a digital front end much more so than, in a branch or an ATM machine or other offline kinds of environments. So, I think the opportunity to be vastly more secure is built into the operating nature of what we’re doing here with Revolut and other technology platforms.
I guess Covid has driven some of these changes…
You could argue that, absolutely. I think a lot of our customers are driven by convenience, less so than an age demographic. And I think convenience also raises a question in people’s mind, “Whilst this is easier to achieve, am I being safe? Is my bank, A, being responsible, and B, do I inherently understand the change in risk profile that I’m taking on with moving to this platform?” I think in the end… I don’t know. Maybe let’s leave it at that now. Obviously, there’s been some changes in customer behaviours. I mean, despite all the best intentions, travel has evaporated around the world, as we’ve come to see. So, spending has been affected, but I would say that it’s more muted than we expected. We saw a change in our customers’ behaviour and a dip in spending, but we’ve also seen a rapid recovery from that, in particular as people moved online. So, an acceleration in the tendency of people to move online occurred. Perhaps we saw three to five years’ worth of growth in several months in some markets. And then, secondly, I think it creates almost like a pendulum effect. When people are unable to spend, particularly in their disposable income, a demand builds up. And as we saw in various markets now, as lockdowns were eased or removed, we’ve seen spending bounce back, and again, with the pendulum effect, in some cases higher than it was before we went into the COVID period.
According to a recent report from ABI Research, the digital twin market is expected to grow from $3.8bn , as of 2019, to $35.8bn per year by 2025, with more than 500 urban digital twins expected to be in use.
So what’s behind this expected growth? Well, perhaps unsurprisingly, COVID19 has meant that now more than ever before we need to increase resilience and optimise resource management.
Michael Jansen, CEO of Cityzenith, sits down with us to explore the booming digital twin market and what role digital twins could play in tackling a global pandemic…
A business that’s fully and passionately dedicated to ¨promote beauty to achieve personal fulfilment¨, Belcorp is creating something new for itself that’s not a cultural reset, per se, but a cultural reboot. The message behind this Latin American beauty corporation, which operates across 14 countries, remains the same – but it’s now better, stronger, even more deeply ingrained in each and every fiber of the business. What is, on the face of it, a digital transformation for Belcorp has actually been a full people-centric makeover from the inside-out – it just happens to have been driven by technology. With his hand on the tiller is Venkat Gopalan, Chief Technology, Data & Digital Officer for Belcorp, who stepped in 18 months ago to help push the digital plan, resulting in a hard press on the fast-forward button for the company’s development.
Elsewhere, we catch up with Lori Snyder CIO, Information Systems & Technology at the State of Nebraska for the Department of Health and Human Services, to see how the state is using digital strategies to battle COVID-19. Plus, we have exclusive interviews with former Apprentice winner Mark Wright, Director of Climb Online and James Shanahan, CEO Revolut Singapore. We also list 5 essential tips to building an intelligent workplace.
Engaging members virtually and competing in the fast-developing digital fitness market…
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One of the UK’s leading technology developers, which works with operators to deliver virtual fitness content to their customers via livestream classes and premium on demand fitness channels, connecting over 300,000 activity users with over 6000 providers, has partnered with a global health and fitness giant.
Move and Les Mills are partnering up to provide a key element of Les Mills’ new digital content solution empowering health and fitness operators to engage their members virtually and compete in the fast-developing digital fitness market.
The turnkey platform means operators can host Les Mills Content in their own branded ecosystem (web and app) which can be seamlessly integrated into their existing membership system, as well as livestream their own content.
Commercial Director at Move, Justin Mendleton, explains how the partnership helps solve the challenges that the fitness industry faces:
“The demand for virtual fitness products and services continues to accelerate at light speed. It’s going to be a critical part of every operator’s offering long after the pandemic has receded.
We know that operators face huge operational and technical challenges launching and sustaining a high quality digital solution. That’s why we’re thrilled to partner with Les Mills to deliver world class fitness content and world class digital technology that all operators can benefit from.
Read our exclusive interview with Jean-Michel Fournier, CEO of Les Mills Media:
Locking down a virtual strategy now is essential: according to a recent paper from Allied Market Research the global digital fitness industry is now expected to grow by nearly £4bn between 2020 and 2024.
Some of our partners taking advantage of our digital engagement expertise are already using Virtual Studio and seeing retention rates as high as 79%. Having a high quality digital solution during these lockdowns has been an absolute lifeline for them.
If you want to continue to engage and retain your members, it’s pretty clear what you need to do.”
Physical stores do not offer the same browsing experience as we would usually expect…
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There is no doubt that the coronavirus pandemic has changed the landscape of the retail sector. Social distancing regulations and civil anxiety surrounding the virus mean that physical stores do not offer the same browsing experience as we would usually expect. Meanwhile, a growing reliance on online shopping has been boosted by instructions to remain at home as much as possible.
The impact of COVID-19 and our new shopping behaviours have a profound effect on retailers. Changed buying experiences, falling and rising sales, and new consumer demands have defined an adverse year in retail. Here, we look at how customers and businesses have been affected by these changes.
Rising and falling sales
The Office for National Statistics points to eight key industries within the retail sector to define its overall performance since the start of the pandemic. Only two industries managed to increase their sales in the immediate months following lockdown. Unsurprisingly, these were food stores and non-store retailing (otherwise known as businesses which do not utilise a traditional brick-and-mortar location). All other industries within the retail sector saw their figures drop the most in April.
While most industries have since recovered and now show high sales figures when compared to February, two still fall behind their historic performance. Clothing and fuel saw sales drop by 67.6% and 60.7% respectively. This is significantly lower than the 22.2% drop the entire retail sector experienced. The latest figures indicate that the pandemic’s impact is still damaging. In October, clothing was still 13.8% below February sales. Fuel was still 8.8% down.
The reasons for these fallings are a consequence of reduced demand. Limited social activities reduced the need for new clothing. Working from home, furlough, and further travel restrictions also reduced the need for fuel.
However, there are some promising industries within the sector. Household goods now achieve sales 14.4% above what they achieved in February, despite falling 50.5% in April. In fact, this recovery is seen across the board. Total retail in October achieved 6.7% more sales than it did in February. This indicates that the sector should remain optimistic for a stimulating recovery and boost when restrictions are eased, and normal consumer behaviour resumes.
An online boost
During the initial national lockdown, non-essential stores closed to prioritise the public health crisis. Unsurprisingly, consumers became more reliant on online shopping services as reflected in the rise of none-store retailing sales. But the lockdown changed more than the shopping experience, the limitations on public activities changed the demand for some products and services. For example, where social activities were limited, exercise was encouraged. In-store clothing retailers felt the force of lockdown, but for online sport sales companies, sales saw a significant boost. Cycling saw an increased popularity during lockdown, with many searching for more isolated ways to exercise and commute to work. For example, Google searches for ‘mountain bikes’ increased by 522% between February and April in 2020.
One bike sales company, Leisure Lakes Bikes, shared how their online activity grew during the pandemic. Demand for bicycles increased. In fact, visits to their website increased by 295% between March and April — only one month. By May, visits to their website had increased by 580% compared to March. The appeal of cycling during the lockdown was strong.
Time on their website also increased. Between March and April, the average time spent on the website increased by 57%. This shows that consumers are spending longer online, researching products and showing a real intention of making a purchase. One consumer survey found that 55% of customers prefer to visit stores before buying online. COVID-19 is directly responsible for changing this consumer behaviour.
This example reflects changing customer demands and the impact of selling online. Recognising the retail landscape, offering a product which consumers need, and offering an unchallenging buying experience will allow modern retailers to benefit during this period of uncertainty.
Prioritising responsibility
The retail sector is adapting to the changing views of consumers. Customers look towards stores to provide a safe and COVID-secure environment through hand sanitation stations, social distancing recommendations, and PPE equipment and cleanliness among staff. However, the coronavirus pandemic has not just pointed towards an improved health awareness in businesses. Other aspects, including the environment and social contributions, are a focus of consumer choices.
The pandemic has created a sense of ‘mindful retail’. One consumer index suggests that during the pandemic, 55% of people are shopping in local stores in their community or are buying more locally sourced products.
In the same manner, 61% of consumers say they are making more environmentally friendly or sustainable choices when shopping. Even more, 89%, of these people intend to continue this habit when the crisis ends. This means that a majority of people intend to prioritise sustainability in the future through their shopping choices.
Retail businesses have responded to these changing behaviours, promising to ‘build back better’ in the future. While the pandemic may have impacted the affectability of sustainable strategies, there is a clear drive to improve the retail sector in the future in this respect. One study of the largest businesses in the retail sector shows this intention. Retail giants, including Dunelm, B&Q, and IKEA lead among companies which mention sustainability most through their social media and professional platforms. Measures may include recycling, limiting waste, and utilising renewable energy.
The retail sector has been irreversibly impacted by the coronavirus pandemic. Whether looking towards consumer behaviour, e-commerce rises, or company culture, retail businesses must reflect on their potential recovery in the future and understand how they can improve on their services going forward. As the pandemic recovery continues, businesses must adapt to the constantly changing landscape of retail
Almost two thirds received additional funding to accelerate initiatives…
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Coeus Consulting, an award-winning independent IT advisory, today announced findings from its annual CIO and IT Leadership Survey 2021. The survey of senior IT leaders explored how they have had to urgently prioritise and accelerate programmes during the pandemic over the past 12 months.
Remarkably, over half (53%) claimed they were able to implement a strategic shift of their entire business operations to digital and almost three quarters (68%) of respondents either strongly, or generally agreed, that acceleration helped them to digitalise more of their operations.
Half of organisations were still amid their digital journeys or in the planning stages when they had to re-prioritise and pause non-urgent initiatives to focus on operational continuity during the pandemic. In fact, 70 per cent of organisations surveyed prioritised end user solutions (EUS) such as remote working, 52 per cent prioritised operational stability, closely followed by cost optimisation (50%).
“The proficiency that businesses have demonstrated in their prioritisation and acceleration of critical initiatives is a huge triumph. Being able to re-direct resources and cutting down their time to market in digitalising the organisation is no easy feat, particularly in the throes of a global pandemic” said Ben Barry, Director, Coeus Consulting.
Despite this, the speed at which organisations were forced to adapt meant that short term and tactical business decisions had to be made, with over three-quarters (78%) of respondents stating they had implemented ‘quick fix’ solutions.
“Businesses will need to revisit these over the coming months to build on these capabilities with more permanent solutions for the future and ensure that all changes made in response to the pandemic are assessed to identify any tactical risks accepted and create a plan to mitigate, update or accept all of them” Barry continued.
As a result of deploying ‘quick-fix’ solutions, organisations were confronted with operational, as well as strategic difficulties including agreeing priority changes, implementing the solution and post implementation, each of which encompassed numerous challenges.
Challenges in agreeing the priorities for 2020 included security, which was key for over half of the respondents. This was followed by governance constraints (44%), business risk aversion (37%), employee reluctance/education (32%) and board level resistance (22%).
Fifty per cent of respondents cited cost of implementation as the biggest challenge, followed by delivery of bandwidth (42%), integration difficulties (41%) and lack of skills and expertise (37%).
Post implementation challenges included respondents experiencing negative process impacts (53%) and increased operating costs (45%). Customer and user perceptions were also adversely affected for almost 40 per cent as organisations tackled uncertainty and their own internal changes.
These factors were likely exacerbated by the fact that business and IT leaders had to make these decisions rapidly and in a short time frame, having to balance risk with maintaining operational continuity.
Additionally, 82 per cent agreed that business and IT leadership played a key role in improving ways of working and minimising disruption across the business. Furthermore, almost 70 per cent of respondents stated that IT leaders were crucial in accelerating large scale deployments in EUS and about a third prioritised initiatives in improving customer experience, increasing revenues and developing or changing products.
Almost two-thirds of organisations noted they had received additional funding to help accelerate priority projects, but a large majority of those surveyed (63%) agreed that re-scoping, undoing projects, renegotiating and stalling contracts, as well as redeploying resources, will likely cause ongoing business impacts, and we would expect the cost of doing so to be significantly high.
Despite challenges with costs, the IT budget expectations show that CIOs across all sectors are expecting their budgets to remain untouched (28.6%) or increase (22.1%) as businesses recognise that IT is a critical part of delivery in all sectors.
Barry concluded – “As we move forward, organisations must reflect on these implementations, challenges and the role of IT as they look to establish a more permanent shift to a new hybrid workforce in the future.
IT Leaders and their teams have had a great opportunity to show their value and will continue to drive the strategic agenda in 2021 and beyond. This increased visibility and the business’ dependence on IT has given them an opportunity to demonstrate that IT leads in terms of business transformation, and should be funded accordingly.”
IoT data set to unlock significant innovation over the coming years…
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What organisations can do with data is set to dramatically shift in 2021 and beyond, according to IoT connectivity specialist Eseye, as more IoT devices are deployed and the data they generate dwarfs that collected through traditional online channels. Eseye predicts that data mined from user interactions with things rather than digital services will create a wealth of rich data, bigger and more detailed than online data ever was, enabling new business models, the creation of new products and services and new levels of understanding of human behaviour.
Services like Amazon, Facebook and Netflix capture a wealth of consumer usage and behaviour data which is stored, analysed and used to digitise and reinvent shopping, social interactions and entertainment as custom personalised, data-driven services. This has had an extraordinary effect on the creation of new personalised services and new disruptive business models. As radical a change as this was, now IoT data is set to power unprecedented levels of innovation over the coming years.
According to Eseye, this innovation will be seen not just in the next generation of classic IoT devices, which will become much more interactive and personalised to real time behaviour, but also in the development of a new set of devices created through the fusion of multiple sensors, cellular connectivity to the cloud and advanced AI techniques. This combination will enable near real time predictions of what services should be dynamically configured into those devices to maximise revenue and collect even more data and deliver huge value.
“IoT companies that see the potential, not just in the device but also in the data collected, will be the big winners,” comments Nick Earle, CEO, Eseye. “As we come out of the pandemic, organisations will be looking for new ways to innovate, and IoT data has the potential to disrupt business models and processes in practically every industry. Disruption, by its nature, comes from places we haven’t even dreamed of, but it can be radical. For example, the people who invented the internet could never have predicted the emergence of services such as Uber and Netflix. Likewise, we can only speculate around what IoT entrepreneurs will come up with once they have access to data from billions of devices capturing rich intelligence on every aspect of our lives and businesses. We predict it will be an even bigger wave of innovation than the first wave of IoT adoption.”
One of Eseye’s customers is already using rich data to predict diseases before they happen. A leading digital therapeutics provider manufactures and sells a next-generation clinical-grade wearable, which delivers actionable insights powered by machine learning, deep neural networks and AI on real time disease trajectory. This helps clinicians predict and prevent serious medical events. For example, chronic diseases, like heart failure, can lead to billions of pounds of unnecessary hospitalisations and re-admissions. Therefore, the potential benefits across the healthcare sector if this model becomes widely adopted are enormous.
Another example is how IoT is helping vulnerable people remain independent through condition monitoring, whereby such devices use personal health data combined with behavioural patterns, and analytics predict when changes in care regimes might be required. These are just two examples of millions of potential applications.
“In 2020 the pandemic has accelerated many of the IoT trends we predicted last year. That’s because an economic slowdown, like we are experiencing, puts enormous pressure on enterprises to reduce costs and increase customer delivered value. IoT does both of these things, and so the pressure for adoption is growing. This sudden need for new technological approaches has happened at a time when IoT is reaching a level of cost and maturity that allows for mainstream adoption. This will increase the ability to collect rich data from these next generation IoT devices, delivering unimaginable insights to power innovation in years to come,” adds Earle.
This is just one of 10 IoT predictions that Eseye is forecasting for 2021 and beyond. Others include how IoT can deliver real time visibility into the food supply chain with technology advances such as printing IoT circuits, batteries, and cellular connectivity onto flexible labels. It’s exploring how IoT – as it becomes more integrated into consumer and industrial products – can provide brands with a direct line to customers, collapsing supply chains to bring original equipment manufacturers closer to consumers.
Furthermore, Eseye is also analysing how mobile network operators (MNOs) are adapting to compete globally and why a federation approach creates a more viable economic model for MNOs to deliver IoT, as well as the emergence of virtual MNOs. Eseye announced its global alliance of MNOs, The AnyNet Federation, in 2019 and over the last year the AnyNet Federation has grown to 12 MNO members, a number which Eseye expects to further grow in 2021.
To find out more about Eseye’s 2021 IoT predictions, download the report here.
How investing in your workspace could improve your business and the bottom line…
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The past year has been an experiment in different working environments. Workers are again being asked to work from home during the third national lockdown in England while similar restrictions are advised in Scotland. However, the dramatic shift to working from home flexibility has outlined the importance of a good working environment.
If working from home showed very little difference in the productivity of your business, you may want to consider how you can make your office space more productive in 2021. The vaccine drive throughout the UK raises optimism that a return to normal working arrangements can resume in the close future. When returning to working space after restrictions are eased, to protect yourself from company liquidation, you may want to consider how investing in your workspace can improve your business and the bottom line.
Build it and they will come… to work
How does your office space define your branding? While a unique office space can be superficial and potentially unnecessary to complete real work, you must consider the benefits of creating a space that people want to work in. Using the period where workers cannot visit the office is the perfect time for refurbishments. Construction and maintenance work is permitted during this lockdown, meaning you can create a refreshed space for when your staff return to the site.
A great working environment can boost worker morale, promote motivation, and improve your staff’s quality of life. One report found that an overwhelming 87 per cent of workers would like their employers to offer healthier workspace environments. These include wellness rooms, fitness benefits, ergonomic seating, and adjustable sit-stand desks. The appeal to make investments and create this type of space is not purely for your staff morale scores. It can help attract the best talent in your sector.
In fact, 93 per cent of workers in the tech industry said that they would stay longer at a company that offered this type of workspace. In the UK, the average cost of replacing a staff member is £12,000. The retention of your staff is important as trained staff carry the experience of your organisation, and keeping them prevents the costs of training new team members. Investing in your office space may prevent you from spending more money on losing staff.
A defined workspace
Working from home has been a unique experience for many people that were not placed on furlough during the coronavirus lockdown. However, some may have found that the novelty wore off quickly. Having a defined workspace away from home is an important investment for creating a focused environment.
When you consider that with an eight-hour working day, workers spend over one-third of their waking life in the workplace. A defined workspace is as important as a defined bedroom or kitchen.
There’s a big difference between preparing yourself for office work compared to falling out of bed and sitting in front of a laptop screen.
Promoting collaboration and innovation
Again, as important as it is to have a defined workspace, it’s also important to be surrounded by your colleagues and like-minded people. Office space can help new ideas float about easily, as opposed to the online group-chat messages that we’ve become accustomed to.
When restricted to small teams, staff will create a tunnel vision of their task, with little regard for the effects on the rest of the organisation. An open office space can help create routes of communication between your staff and departmental teams. Your task may be specific, but the final goal of your organisation is encompassing.
A sociable workspace is essential for innovation and productivity, but it also helps to prevent sick days. Nicole Fink writes that the economy loses money through “lost productivity including absenteeism, illness, and other problems that result when employees are unhappy at work.”
According to reports, absences cost the UK economy £77.5 billion per year. The need to boost morale and reduce absence can be achieved through the creation of an enjoyable working environment. A working space that creates a sense of community and wellness goes a long way to recover the cost of absenteeism.
Make efficiency quickly
An organised working space has more benefits than you may think. Investing in office furniture can help prevent clutter and make important information easier to find.
One survey found that 13.5 per cent of workers believe that they would be more productive in an organised and decluttered space. Decluttering is an easy fix with low investment costs, and the effect of using cable ties and efficient file storage will improve your business dramatically.
34 per cent of people believe that a cluttered workspace is the most likely reason to have a negative first impression of a company. This is important for clients and potential employees. If a business does not look like it is prepared for organised work, then other clients and staff will not want to work with them.
When considering the most viable investments that your business can make now, the return to work experience should be a priority. Office spaces are at the heart of your organisation and the foundation for all things creative. When workers return to the office following the easing of lockdown restrictions, the workspace can revive enthusiasm in your business. Workers will enjoy reuniting with their colleagues in a productive environment.
Whether it’s to create a space where workers feel happy or productive, for clients to recognise your value, or to increase the efficiency of work, you can profit in more ways than one from creating an office space that works for everyone.
Chris Horner is Insolvency Director at Business Rescue Expert
A global shift to remote working has accelerated digital transformation and prompted a higher degree of focus on cybersecurity, according to Kaspersky’s latest report.
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A global shift to remote working has accelerated digital transformation and prompted a higher degree of focus on cybersecurity, according to Kaspersky’s latest report.
Transitioning from a corporate office environment to working from home, coupled with financial restraints due to economic recession, has seen challenges presented to cybersecurity experts not many had seen before.
From February to March 2020, a 569% growth in malicious website registrations was detected and reported to INTERPOL, including malware and phishing. In April, there was a huge spike in ransomware attacks by multiple threat groups that had been previously dormant for months.
Cybercrime threats are expected to rise as more opportunities present themselves in the coming months. Fake vaccine registration websites will aim to steal data, whilst business email compromise schemes aim to take advantage of the economic downturn and shift in the business landscape.
Protecting the perimeter of a company is no longer enough: there is a desperate need now for home office assessment with tools to scan the level of security. Discouraging poor internet practices such as connecting to an unprotected Wi-Fi hotspot should be top of the list, with VPNs and multifactor authentification systems being offered as a solution.
With an increased reliance on cloud technology and services, dedicated management and protection measures are now a necessity for businesses. Around 90% of employees use non-corporate software and cloud services, such as messaging apps, and this is unlikely to change any time soon.
To ensure that any corporate data is kept under control, better visibility over cloud access will be necessary. IT security managers will need to align themselves with this cloud paradigm and develop skills for cloud management and protection.
This is why, according to Kaspersky, the quality of protection is “no longer up for discussion.”
“Quality protection is now a must have,” report Alexander Moiseev, Chief Business Officer at Kaspersky.
“Another major trend is that deep integration between various components of corporate security, ideally from a single vendor, now plays a bigger role. For instance, there was a long-held belief in the industry that various specialised solutions from various vendors can help create the best combination for protection.
“Now, organisations are looking for a more unified approach with maximum integration between different security technologies.”
You can read Ksapersky’s “Plugging the gaps: 2021 corporate IT security predictions” report in full HERE.
According to the latest ONS figures, the impact of Covid-19 restrictions on the physical retail sector has been mixed. Stores…
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According to the latest ONS figures, the impact of Covid-19 restrictions on the physical retail sector has been mixed. Stores selling hardware, paints and glass, for example, saw a 13% increase in the value of retail sales compared to last year. Others have been hit particularly hard – with clothes store sales down by more than a quarter (26%) in the same time frame.
The forthcoming wave of vaccinations promises to restore the UK’s economy to a more stable position. Nonetheless, we must consider the possibility that changes in consumer behaviour may linger even when lockdowns and social distancing are a thing of the past, as well as how different sub-sectors within the industry will be affected.
Let’s therefore look at two opposing, but equally possible scenarios on the road ahead.
Scenario A – Opening the floodgates
After months of being cooped up at home, customers flock to town centres, industrial parks and shopping centres to exercise their freedom to purchase goods in-person. Sales volumes increase, but supply chains become stretched due to spikes in product demand and store inventories become more difficult to effectively manage.
In addition, disruption to both the need and availability of workers in the months prior leaves stores understaffed, leading to long queues and disgruntled customers. Finally, customers who for months have been encouraged to go cashless are now making far more card and contactless payments, leaving some POS systems struggling with the uptick in data traffic and leading to more frustration for staff and customers alike.
Scenario B – The high street ghost town
For many, shopping online during the pandemic switched from something people wanted to do to something people needed to do. As a result, those who were previously sceptical or unfamiliar with technology (or who simply preferred shopping in-person) had to familiarise themselves with the process. Of course, although many within this group may still be averse to e-commerce today, we must assume that at least some will use their newfound familiarity to continue shopping online in the post-Covid era.
In this scenario, customers new to e-commerce have been swayed by the user-friendliness, low prices and fast delivery on offer online. As a result, footfall on the high street struggles to recover to pre-pandemic levels, creating a tough environment for the small independent retailers who compete with the online giants.
Preparing for every outcome
While these two scenarios are diametrically opposed, the Internet of Things (IoT) could help address some of the issues described in both situations. Comprising a dynamic network of sensors, devices and equipment, the IoT makes it possible to view and interact with physical objects as easily as files and folders on a computer. In other words, the IoT creates a digital overlay that sits across the physical infrastructure of retail stores, effectively facilitating the agility of online shopping in a physical space.
It will require investment, but securing the future is a goal that pays dividends. Here we look at the solutions the IoT has to offer in these two scenarios.
Solution A – Unlocking efficiency at every stage of the supply chain
Preparing to mitigate the negative outcomes in this scenario requires retailers to take a hard look at the systems they have in place, identify areas in urgent need of greater efficiency, and implement new IoT tools to address them:
Real-time supply chain – inventory sensors and POS data are integrated into a direct communication system with supply chain partners, triggering automated manufacturing and production systems and adjusting stock delivery schedules accordingly.
Data-driven decisioning – capacity sensors linked to data analytics platforms not only track the number of customers in-store, but analyse seasonally-adjusted data relating to the length of time customers spend in the aisles and predict where and when staff will be needed.
Robotic process automation (RPA) – from processing supplier deliveries to quarterly stock counts, RPA systems automate time-consuming tasks that happen behind the scenes, freeing up staff time for better workforce scheduling and more focus on customers.
Solution B – In-store customer experience unmatched by online retailers
Innovations such as live product tracking and same day delivery have recently tipped the customer experience race in online retailers’ favour. To attract new customers and retain their business, brick-and-mortar stores must emulate the dynamic, digital and personalised experience offered by their online counterparts:
Interactive digital displays & kiosks – positioned at the store entry, customers can benefit from an optimised in-store journey and a highly personalised experience by viewing commonly bought items, their location within the store and in-the-moment marketing offers based on purchase history.
Roaming POS – queuing is eliminated as tablets carried by staff process customer payments anywhere in the store. In addition, RFID scanners built into trolleys and baskets can total large volume purchases in real-time, without needing to take a single item out to scan.
Customer application integration – in-store geotargeting systems can link via Bluetooth to customer-facing smartphone applications to help locate specific items and provide other useful pieces of information, such as stock levels, current offers and the location of staff.
LTE & SD-WAN branch networking: laying the foundations for the future of physical retail
Regardless of which scenario becomes a reality, any subsequent IoT strategy must begin with a reliable, secure and agile network. The first step is cutting the cord with fixed broadband connectivity and setting up a private in-store network running on LTE. Also known as wireless WAN (WWAN), this solution offers retailers greater levels of flexibility thanks to out-of-the-box connectivity and unparalleled reliability through multiple network channel management.
The second foundational requirement for retail IoT is SD-WAN. With the sheer quantity of network applications running in most branches, cloud monitoring and troubleshooting features – including automated alerts – SD-WAN enables retailers to cost-effectively manage WAN conditions at widespread locations. Crucially, SD-WAN also allows secure VPNs to be established in a matter of minutes, providing robust protection for devices and sensitive information, such as customer payment data.
Survive and thrive in the future of retail
The past year has been an uphill struggle, not least for retailers contending with limited footfall in their physical stores. Investing in new technology may not be top of mind for all retail businesses in the immediate future. But for those who are able and willing to make small adjustments to innovate may find they are able to unlock efficiencies in their supply chain, improve their in-store experience and attract and retain new customers once lockdown restrictions start to ease.
74% of businesses are boosting their marketing and consumer research budgets this year, to better reach potential customers.
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74% of businesses are boosting their marketing and consumer research budgets this year, to better reach potential customers, according to new research from Stravito, a leading provider of knowledge management software for insights.
The research, which was conducted by independent polling company Censuswide, surveyed 200 business decision makers in large and medium sized UK companies in the last week of December 2020.
It revealed that 76 per cent of business are set to overhaul their customer engagement strategy in response to the disruption and dispersal caused by the Covid-19 pandemic, suggesting that many companies are already anticipating 2021 to be the year that they ‘bounce-back’ from the difficult period caused by the crisis.
Interestingly, 82 per cent of surveyed decision makers agreed that data-driven insights are a top priority for them in 2021, and a whopping 83 per cent agreed that improving communication and relationships with customers will be critical to their business growing this year.
Similarly, 72 per cent of business decision makers agreed that their company needs to improve its knowledge and research sharing capabilities in order to improve sales in 2021.
Thor Olof Philogène, CEO and co-founder of Stravito, commented:
“In this pandemic era, connecting to consumers on a ‘human level’ is more important than ever, and demonstrating empathy and understanding with customer concerns and needs is imperative.
“This process must start with comprehensive market and consumer research to help inform business strategy and understand exactly how consumer behaviour and expectations has adapted over the course of the very eventful last 12 months. With workforces still distributed, and remote working here to stay for the foreseeable future, it is essential that research and business insights are made available to all departments and workers in a given company, so that there is no misalignment in knowledge or customer acquisition strategies. Getting instant access to all available market research at the touch of a button will also go a long way to preventing knowledge silos developing between already distributed workforces and departments.”
Deal volumes up 18% and deal values increase 94% in second half of 2020
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M&A valuations are soaring, with rich valuations and intense competition for many digital or technology-based assets driving global deals activity, according to PwC’s latest Global M&A Industry Trends analysis.
Covering the last six months of 2020, the analysis examines global deals activity and incorporates insights from PwC’s deals industry specialists to identify the key trends driving M&A activity, and anticipated investment hotspots in 2021.
In spite of the uncertainty created by COVID-19, the second half of 2020 saw a surge in M&A activity.
“COVID-19 gave companies a rare glimpse into their future, and many did not like what they saw. An acceleration of digitalisation and transformation of their businesses instantly became a top priority, with M&A the fastest way to make that happen — creating a highly competitive landscape for the right deals,” says Brian Levy, PwC’s Global Deals Industries Leader, Partner, PwC US.
Key insights from the second half of 2020 deals activity include:
Dealmaking jumped in the second half of the year with total global deal volumes and values increasing by 18% and 94%, respectively compared to the first half of the year. In addition, both deal volumes and deal values were up compared to the last six months of 2019.
The higher deal values in the second half of 2020 were partly due to an increase in megadeals ($5 billion+). Overall, 56 megadeals were announced in the second half of 2020, compared to 27 in the first half of the year.
The technology and telecom sub-sectors saw the highest growth in deal volumes and values in the second half of 2020, with technology deal volumes up 34% and values up 118%. Telecom deal volumes were up 15% and values significantly up by almost 300% due to three telecom megadeals.
On a regional basis, deal volumes increased by 20% in the Americas, 17% in EMEA and 17% in Asia Pacific between the first and second half of 2020. The Americas saw the biggest growth in deal values of over 200%, primarily due to some significant megadeals in the second half of the year.
COVID-19 accelerates deals activity for digital and technology assets in a highly competitive market
In demand assets have commanded high valuations and fierce competition, driven by macroeconomic factors. These include low interest rates, a desire to acquire innovative, digital or technology-enabled businesses and an abundance of available capital from both corporate (over $7.6 trillion in cash and marketable securities) and private equity buyers ($1.7 trillion).
By comparison, assets in sectors that have been hardest hit by the pandemic like industrial manufacturing or those being shaped by factors such as the transformation to net zero carbon emissions are creating structural changes that companies will need to address. Where the future viability of their business models are challenged, companies may look to distressed M&A opportunities or restructuring to preserve value.
Deal makers widen assessment of value creation to non-traditional sources
Non-traditional sources of value creation such as the impact of environmental, social and governance factors (ESG) are increasingly being considered by deal makers and factored into strategic decision-making and due diligence, as they focus on protecting and maximising returns from high valuations and fierce demand.
“With so much capital out there, good businesses are commanding high multiples and achieving them. If this continues – and I believe it will – then the need to double down on value creation is now more relevant than ever for successful M&A,” says Malcolm Lloyd, Global Deals Leader, Partner, PwC Spain.
The impact of a hot IPO market on M&A
The last six months saw the prevalence of the use of special-purpose acquisition companies (SPACs) to pool investor capital for acquisition opportunities in a highly active IPO market. In 2020, SPACs raised about $70 billion in capital and accounted for more than half of all US IPOs. Private equity firms have been key players in the recent SPAC boom, finding them a useful alternative source of capital. More SPAC activity is expected in 2021, especially involving assets such as electric vehicle charging infrastructure, power storage, and healthcare technology.
Canonical’s Charmed OpenStack will enable industry-leading cloud-based online charging system
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Canonical, the publisher of Ubuntu, today announced that its Charmed OpenStack has been selected by Telefonica Brazil to – in a first for the region – migrate its online charging system (OCS) to its private cloud, Unica Next. The transformation project will see eight private clouds built on Charmed OpenStack, geographically distributed to service Telefonica’s customers in Brazil.
As the country’s biggest mobile operator with 76 MM mobile subscribers, Telefonica uses its OCS to give B2C & B2B customers real-time control and visibility of their precise usage across voice and data calls.
Instead of selecting a conventional virtualised environment, Telefonica opted for Charmed OpenStack for future scalability on which to build a long term roadmap. With new market trends such as 5G, this migration will give Telefonica the agility to develop new features at scale, staying ahead of customer demand by providing more advanced offerings with a faster time to market.
“Migrating our OCS application to the cloud will give us the base and agility we need in order to consistently offer best-in-class solutions for our customers,” commented Flavio Matiello, Head of PrePaid Platforms & OCS at Telefonica Brazil. “This selection was an obvious choice to enable us to scale our charging capabilities to a future-proofed private cloud platform.”
As the OCS requires close proximity to the network, the clouds will be geographically distributed in Brazil. This architecture will consistently deliver the low latency needed to meet the needs of Telefonica’s wide customer base and was a key factor in the selection of a private cloud infrastructure.
“Canonical is dedicated to enabling customers to drive new innovations and we’re pleased to have collaborated with Telefonica Brazil on its OCS migration,” said Nicholas Dimotakis, VP of Field Engineering at Canonical. “This represents a growing trend of telecoms companies moving towards OpenStack, and we’re excited to see what other cloud-based services this could open up across the industry.”
Telefonica’s OCS cloud will be built on Canonical’s Charmed OpenStack, and utilise Canonical’s open source tools to automate the deployment and operations of their infrastructure. Telefonica will benefit from Canonical’s Managed OpenStack offering for the ongoing maintenance and support of operations. The project’s initial phase was successfully rolled out in early August 2020.
“Canonical has been an important community member in helping make OpenStack among the most widely deployed open infrastructure software for telecom in new markets. We’re proud to see Telefonica Brazil choose OpenStack for its flexibility to support a fast-changing telecom landscape. But more importantly, we’re thrilled to welcome their team to the community, representing a growing user base in Latin America,” said Mark Collier, COO, Open Infrastructure Foundation.
Connected technology is of critical importance in this process, and is likely to be one of the key economic drivers going forward.
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Although we have bid a grateful farewell to 2020, the disruption and uncertainty we experienced are spilling over into 2021. If there is one thing that we learnt last year, however, it’s that we need to accelerate the pace of transformative change. Connected technology is of critical importance in this process, and is likely to be one of the key economic drivers going forward.
The digital and physical world continue to converge
2020 symbolises a turning point of adaptation to digital interactions in everyday life, be it working from home, ordering groceries or online schooling. Consumers in 2021 and beyond expect to experience a seamless blend of intertwined in-person and online interactions along the customer journey.
In the manufacturing world, we can expect the rapid growth of AI, IoT and other industrial automation technology, especially since human resources become less accessible and reliable.
Technology’s place in the boardroom
In 2020, technology proved to be a competitive advantage for some companies and a threat to the survival of others. In particular, the failure to have a genuine eCommerce presence cost many companies dearly. As a result of this, the lines between technology strategy and corporate strategy are beginning to blur. In order to survive and thrive, organisations need to assess their current tech capabilities and expand on future possibilities.
Data-driven decision making
To prepare for current changes and an unknown future, corporate and technology strategists need to have access to accurate data to analyse, identify trends, reduce wastage and inform their strategies.
The first step in this process is accurate data collection. This is enabled by Internet of Things (IoT) sensors and networks that are able to report on virtually anything, 24/7. The next step is the ability to analyse this data. Again, technology platforms with advanced analytics capabilities, automation and artificial intelligence (AI) are making meaningful analytics a possibility. By using tools such as cloud-based dashboards, organisations have the ability to:
– Identify internal and external strategic forces
– Inform decisions
– Monitor outcomes
– Develop strategies continuously and dynamically
Information technology accessed by everyone, but trusts no-one
Cloud-first, cloud-only
One of the first steps in digital transformation is modernising legacy enterprise systems and migrating them to the cloud. The adoption of cloud-based applications became particularly important in 2021, with a large proportion of the office-based workforce operating from home. In order to continue with business as usual, employees needed access to critical software and collaborative working. In 2021, organisations will adopt a cloud-first mentality when it comes to building or upgrading technology infrastructure.\
Zero trust is a must
In an increasingly digital world, cybersecurity is high up on the list of organisational risks. Zero trust security (which involves security measures that require everything to be verified) is shaping cybersecurity initiatives. In a zero trust architecture, there is no inherent trust, and every access request should be validated based on:
– User identity
– Device
– Location
– Any other variables that provide context to each connection
Access to data, applications and workloads is provided based on the principle of least privilege.
For most companies, the creation of a zero trust architecture will require third-party assistance from digital transformation experts in IoT spheres.
Supply chains move to the front office
Supply chains were once seen as ‘behind-the-scenes’ necessities. When COVID-19 hit, it quickly became evident that even the most resilient and agile supply chains were only as strong as the weakest links.
A recent survey of supply chain professionals found that 97% of respondents said that their organisations experienced disruptions related to COVID-19. The same survey found that 73% of respondents are now planning major shifts in the way they approach procurement and supply chain management.
In 2021, more and more organisations are realising that the way they conduct their supply chains can actually become a competitive differentiator. Accelerated by the COVID-19 pandemic, customers are increasingly looking for more streamlined supply chains, fast, contactless delivery and greater traceability. In addition, organisations are realising the value of data extracted through the supply chain network.
There is a growing trend to fit products with IoT-enabled sensors that provide 24/7 asset visibility from the source to the hands of the consumer. The ability to capture larger volumes of real-time data allows supply chain operators to mine this data for operational insights.
In addition, the use of drones, condition monitoring, robots and image recognition are making physical supply chains more effective, efficient and safer.
Contactless customer service
Delivery and shipping
Born out of customer desire to minimise physical contact, contactless delivery options will continue to develop in 2021. Contactless delivery is made possible by artificial intelligence-based applications and robotics.
Telemedicine
To minimise the risk of COVID-19 exposure in the healthcare sector, practices have started implementing more telehealth offerings. These include:
– Remote/video consultations
– A.I-based diagnostics
– No-contact medication delivery
Autonomous vehicles
Autonomous driving technology is set to make significant progress during 2021, with major manufacturers such as Honda and Ford announcing plans to mass-produce autonomous vehicles and launch autonomous driving ridesharing services.
Zero food waste
Food security came to light in the midst of supply and demand challenges brought about by the coronavirus in 2020. In 2021, reducing food waste is moving higher up the agenda.
The UN’s Food and Agriculture Organisation reports that more than 30% of the world’s food is lost or wasted every year. Smart technology can be used to reduce food waste, increase food security, and assist with better distribution of food resources worldwide. For example, automated, sensor-based inventory management and replenishment ensures that the correct quantities of food are ordered at the right time, completed without human intervention and inaccuracies.
Blockchain
And, finally, no series of predictions would be complete without a quick comment on blockchain technology. For the most part, the application of blockchain tech is overshadowed by its “poster boy” application—Bitcoin and other crypto currencies. However, as we move into a smarter age, the process accountability distributed ledger technology guarantees will ensure that 2021 will see greater transparency on ordering, delivery and workstream management, along with a host of tradable asset ledgers coming online. All of which will improve efficiency across operating lines and help cut waste.
Technology and transformation 2.0.2.1
These trends predicted for 2021 are connected by the thread of digitalisation and connected technology. The need for this transformation was accelerated by the ‘new normal’ necessitated by the coronavirus pandemic, which set the world on a course towards powerful new digital capabilities. Daunting as this may seem, having the right technology partners on board helps organisations take advantage of the critical technology trends of today.
A look at some of the most innovative advancements in the use of AI in healthcare…
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Technology has impacted every area of our lives, but arguably none more than healthcare. Thanks to advancements in diagnoses and treatments, we’re living longer, healthier lives.
One technology in particular that has revolutionised healthcare is artificial intelligence (AI). The machine-learning technology is used across the spectrum of healthcare, from robotic surgery assistance to virtual nursing assistants and image analysis. It’s even being utilised in drug research to streamline the discovery and repurposing phases.
As with many sectors, the application of artificial intelligence is perceived as a threat by some. Its ability to eliminate admin tasks and even take care of end-to-end processes has caused concern amongst healthcare workers. But it’s important to note the technology is an enabler and helps workers to be smarter and more efficient.
The use of artificial intelligence in healthcare has increased exponentially in the past year, with more intelligent applications than ever before. Here, we cover the most innovative advancements in the use of AI in healthcare recently.
Efficient drug development and testing
UK-based artificial intelligence firm Exscientia has used AI to develop a drug molecule from scratch. That’s right, AI is being used to create new drugs. The molecule forms part of a new drug aimed at treating patients with obsessive-compulsive disorder (OCD), which has entered into human trials in record time. The drug was available for clinical trials within 12 months, compared to the average of four-and-a-half years for the entire lifecycle of drug development.
Similarly, UK biotech company Healx has secured millions in funding to research and develop new drugs for rare conditions using artificial intelligence. Not only does artificial intelligence dramatically reduce the time between drug development and clinical trials, but it’s also projected to save millions on the research and development phases of creating new drugs thanks to how efficient it makes the process.
Processing cancer scans
The National Health Service (NHS) is using Microsoft’s InnerEye technology to automate the process of scans for prostate cancer. Once the scan is taken, the AI gets to work. It outlines the prostate in the scan and marks up any tumours. By automating this manual, laborious process, NHS staff can act faster and speed up prostate cancer treatment.
This technology is also being used to analyse scans from breast cancer screenings, outlining potential tumours. Experimental technology is currently being developed by the University of Nottingham to predict a patient’s response to chemotherapy. This combines breast cancer patient MRI scans, clinical data and advanced computational modelling to help clinicians to deliver personalised, right-first-time treatments.
Virtual GPs powered by artificial intelligence and machine learning are no longer a new innovation. But virtual patients have been introduced in the past year to train NHS staff. Because patients are currently advised to only attend the surgery in urgent situations, in-person training has been limited. The virtual patients utilise mixed reality, allowing trainees to role-play with a virtual patient via video instead of actors in-person.
Using this technology allows learners to build the soft skills required to deal with patients, including providing comfort along with bad news. Users also develop knowledge around building treatment plans and explaining diagnoses. The AI gives the user feedback in real-time so they can continually learn and improve.
Faster stroke detection equalling a lower impact
Viz.ai is a stroke detection solution which uses deep machine learning to identify patterns in a patient’s brain activity and accurately identify large vessel occlusions (LVO), which account for up to 46% of ischemic strokes. The AI will send a radiological image to the clinician’s smartphone, allowing medical staff to quickly triage patients and prevent the irreversible loss of the patient’s brain cells.
Medical professionals who specialise in stroke treatment and care will know that when it comes to treatment, every second counts. In fact, for every minute of additional time-to-treatment, 1.9 million patient brain cells are lost. One study shows that Viz.ai, on average, could prevent patients from being bedridden and requiring 24/7 care, and instead able to walk out of the hospital with no further care required.
Thanks to the utilisation of technologies like artificial intelligence and machine learning, the future of healthcare is bright. Not only can these advances take away laborious but important administrative tasks from clinicians, doctors and nurses, they can be used to create brand-new treatments, allow staff to train without the requirement of in-person actors, and even prevent stroke-induced disabilities.
Charities in the UK are reaping the rewards from GoPoolit – the world’s first social media for good
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GoPoolit, which was founded in the United Kingdom over the COVID-19 lockdown by fundraising professionals with decades of experience, provides a new income stream for charities through the thing the world engages with the most: social media.
Instead of prompting users to post ‘asks’ and lobby for funds on behalf of charities, GoPoolit users are encouraged to show off the creativity that they do on their usual social networks.
Users will talk about their lives, celebrate their achievements, and most likely, post adorable photos of their pets. When doing so, users nominate a charity to their post and share it across all their usual social networks from the GoPoolit platform.
Instead of a ‘like’, their friends, family and followers on GoPoolit have the opportunity to pool between 1-10p to that post, and therefore, that charity.
The more viral users go, the more opportunity there is to raise hundreds of thousands in pocket-sized donations for causes close to their hearts – simply by doing what they already do.
During these uncertain times, like most industries, charities and the third sector have been feeling an immense amount of pressure. In previous years, conventional methods of fundraising have faltered. A new, innovative approach has struggled to fill that void – until now.
There is an equal demand from social media users for a new platform focused on social good. According to the Pew Research Center, almost two-thirds of Americans think that social media has a mostly negative impact on the state of their country.
With users becoming increasingly disengaged with the policies and practices of many platforms, GoPoolit is the perfect chance to hit the reset button on their digital lives and use social media for good.
On the GoPoolit website and app, users can post their usual social media content in support of charities such as World Vision, SOS Children’s Villages, Habitat for Humanity and many more.
Matt Turner, Director of Communications for GoPoolit…
“Imagine if every post you ever made on Facebook or Twitter could be monetised into micro-donations for a cause you care deeply about.
In the months and years to come, we are confident that GoPoolit will become a part of millions of people’s everyday lives – and joining today means you’ll be able to say that you were there from the start.
Sometimes, the smallest gestures can collectively have the biggest impact – so join thousands of others who believe that their social media posts can be a cause for good in the world today!”
The beauty industry is hopping on the trend of the digital world…
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The year 2020 has changed the way we shop forever. The pandemic has driven online sales, for example. Now, over 25 per cent of the world’s population shops on e-commerce websites. The dramatic shift from the high street to online landing pages is set to continue. But while COVID-19 has changed many brands’ focus on retail, the beauty industry has continued to innovate.
There are more factors involved in our changing shopping habits. From consumer demand to understanding the customer experience, beauty brands are opening up to further technological and social innovation. Here we look at how shopping for beauty products will change in the future.
Technology
Technology and the makeup industry are becoming more interwoven. This is already evident in some makeup retailers who offer customers the ability to match their makeup with their skin type and colour by using intelligent scanners. However, innovations may further integrate intelligent technology into our buying decisions, helping us to make smarter decisions about the types of products we buy. 80 per cent of online consumers state that new tech is improving their shopping experience.
Using artificial intelligence (AI), some makeup companies can indicate your skin age and advise which tone of foundation and concealer should be used. Previously, the makeup market had often made it difficult for women of colour to find a matching foundation or concealer. However, this technique allows correct decisions to be made and products to be custom produced for specific customers.
Technology even allows us to test out makeup looks and help guide our purchases. Smartphone filters, the likes of which have been popularised by Snapchat and Instagram, can show us what we look like with a variety of fashionable options. Customers can try on a variety of fashion and beauty products, from clothes, ladies shoes, and makeup. When deciding which colour looks best, choosing from swatches may become the old technique. Instead, seeing the makeup we may buy on our faces without having to apply it may make cosmetic buying a walk in the park. The benefits of this include being able to view multiple makeup looks and colours, avoiding cross-contamination by using testers, and being cleaner overall.
Authenticity
One survey by Ipsos shows that consumers are influenced by the people closest to them over any other group. This means that beauty influencers may not be as effective as first thought. The survey suggests that 50 per cent of people’s beauty choices are influenced by friends, while Instagram and social media influencers only influence 25 per cent of people when it comes to buying beauty products.
Beauty businesses are recognising this and are seeking out more authentic ways to demonstrate and promote their products. Instead of aspirational advertising, where a particular standard of beauty is pedestalled, the future of shopping in the beauty industry will celebrate difference. Diversifying the beauty industry will create a better image for the market, where different body sizes, skin colours, ethnicities, and distinguishable features will be celebrated. Even gender will be a less considerable measure in the industry. The US edition of Vogue recently featured Harry Styles as the first solo-male on the magazine’s cover. Wearing a flowing dress, the singer is taking another step in proving that beauty has no limitations.
Functional
The beauty market has a strong focus on aestheticism. After all, makeup should be used to make us look stronger and feel more confident. But we may be looking for more than colour shades and texture when we go shopping in the future. Instead, makeup is becoming less of a covering tool, and more something which can benefit and rejuvenate the skin underneath.
Gone are the days of clogged pores and heavy chemicals which we would normally associate with makeup. In the future, we can expect natural vitamins, oils, and extracts in our makeup to boost our skincare.
One ingredient in health-boosting makeup is vitamin A. This vitamin can be found in many foundations and base layer cosmetics and can benefit your skin greatly. Vitamin A helps promote and maintain healthy dermis and epidermis. The top two layers of skin can benefit from this health boost which adds natural moisture and can prevent breakouts.
The move is being adopted by more cosmetic companies who understand that, in the future, beauty shopping will focus more on the long-term benefits of cosmetics as opposed to the short-term boost that a new shade of eyeshadow can give us.
The beauty industry is hopping on the trend of the digital world. But the biggest changes will not impose on how we shop, but why we shop. The message of the beauty industry will become one of acceptance and utility, where cosmetics serve a purpose of confidence and change. When we shop for beauty products, we will think about the impact of our buying choices.
Two-thirds of accounting departments still process invoices manually: only 15% are fully paperless
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Despite the increasing need to process invoices remotely as more employees are urged to work from home, the majority of companies are still lagging behind in automation implementation. Accounts payable departments are still largely processing invoices manually, according to a survey of accounting and finance professionals released today by Ephesoft, Inc.
The survey gathered responses from 200 accounting and finance professionals from 26 countries. Key findings include:
Distributing or processing paper documents
Businesses are shifting to automation of their processes – especially for high-value, high-volume documents such as invoices. However, the survey results indicate that companies are slow to change when it comes to digitally transforming invoice processing and other financial documents.
● Only 15% of respondents said that their organisation is fully paperless, which means the majority of businesses (85%) are not.
● Of those who are not, just slightly over 50% are actively pursuing a paperless environment.
● One-third (33%) of companies are predominantly paper-heavy, still far from intelligent automation.
With an average cost to process per invoice at about £11, a lack of automation is likely to keep company growth limited, leaving room for a significant increase in productivity. Modern automation has been proven to cut costs significantly, often by 80% or more, which can be reinvested in other areas.
Current technologies
When asked whether their businesses currently have document management, workflow, AP automation, RPA or artificial intelligence technologies in place, a majority of companies report having some type of document management and workflow tools system in place, but AI applications are still under-utilised. Here’s the breakdown, further showing a lack of current automation tools:
● Less than one-third (30%) employ accounts payable automation.
● Only 12% utilise RPA tools and just slightly less (11%) report using AI.
While these findings are understandable and relatable, Ephesoft predicts that new AI-powered low-code/no-code, cloud technology, which is evolving at a rapid pace, will remove barriers to entry into AI.
The AI Journey
When the question was posed, “What is your organisation’s location on the AI journey?” responses were split, with 42% saying they were in the planning stage and 40% saying they were not planning on implementing AI tools at all.
We can conclude from the data that AI has still not been widely adopted, but many organisations have plans to invest in it.
“This survey confirms that the accounting profession has lagged in adoption of newer technologies such as AI/ML, cloud and low-code/no-code architecture likely impacted by traditionally long implementation cycles and complex integrations,” said Naren Goel, chief financial officer, Ephesoft. “The accounts payable space is an ideal example where manual steps like entering invoices into an ERP system can greatly impact efficiency, so it’s exciting that we are finally starting to see innovation in this space with point solutions that are up and running in hours, eliminate manual tasks and allow accounting professionals to focus on higher value-add functions.”
The survey on digital transformation, AI, technology and automation was conducted on Nov. 5, 2020, by Accounting Today on behalf of Ephesoft. Responses are from 200 accounting and finance professionals from 26 countries, including CEOs, CFOs Partners, CIOs, CTOs, CPAs, accountants, controllers, auditors and consultants in a variety of industries, including banks, energy, government, healthcare, technology, accounting services, airlines, auto, education, large global consultancies and many others.
Most businesses have a website. Fact. But what role does it play in the overall strategy of your business? Now…
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Most businesses have a website. Fact. But what role does it play in the overall strategy of your business? Now that global business is going through one of the toughest and most challenging times, you might need to blow the cobwebs off your website as it could be what actually saves your business.
2020 has been the economic sledgehammer that many of us were not prepared for and has damaged or destroyed companies around the globe in a few short months. But there are ways of salvaging your business from the wreckage if you are prepared to pivot your strategy and stick your neck out and re-evaluate your e-commerce and social media marketing.
Re-invent yourself as an e-commerce site
Over the last few months we have worked closely with a couple of businesses which have had to completely shut down as a direct result of the lockdown, but they have significantly pivoted their strategy and re-invented themselves as an e-commerce site and reaped the benefits.
Although you don’t get the face to face customer relationship, being online still allows you to communicate with customers and develop a ‘virtual’ relationship with them. Via a range of social media channels, you keep them in the loop with what your business is doing, you reassure them that you are still there, you keep talking to them and in doing this, you will build and maintain their trust in you.
This adds value to your customers and by staying active on social media, they still feel connected with you. Now is as good a time as any to reflect that you are probably moving online to stay online as customer retail habits may not return to how they were before the pandemic.
Play on ‘support local’ messaging
Local businesses have been affected a lot more than the big corporates as they don’t usually have the bank role and the ‘padding’ or reserve funds to make it through something as hard hitting as the pandemic.
When it comes to local business, there has always been an almost tribal sense of people trying to support them. If you are able to play on that from a messaging perspective, that’s a great way to make people stop and think and could work really well in winning customer support.
For some of you, it will be fight or flight, and you have to do what is best for you, but if you can reach out to your community there is a good chance that they will buy local. The retail inconvenience caused by the pandemic has made people realise what the value of a local business really is, and if it wasn’t there, how difficult life would be.
Get customers involved – get them to follow you, like your posts, comment, share etc By encouraging this they will feel they are still part of a community, albeit a virtual one!
There is a mini economy in local business, and it needs to be maximised.
Add value to customers lives instead of focussing on direct response marketing
We have definitely seen a shift in behavioural trends over the last few months, be it wearing masks, standing on circles in a queue, keeping our distance from people, but also in the way consumers are engaging with brands.
Those brands offering some kind of value, help or reassurance are leading the pack. Joe Wicks work outs were a prime example of this. The fitness guru wasn’t just pushing his book sales or the growth of his social media channel, his focus was to provide value to parents and young children and to help them to exercise at home, and his growth and popularity came by default.
Ensuring you push a strategy out there that adds value and helps first, typically earns massive dividends but a word of caution: Whatever comfort blanket you offer during these tricky times, make sure you maintain this as part of your strategy moving forwards or customers will lose faith in your integrity.
Your plans also need to be both flexible and scalable, can be turned on and off and with a tone of voice to fit more cautious consumers who are newer to the whole digital experience.
Generate trackable returns
Paid media, in whatever guise, ensures that your brand and your content is seen by a targeted audience compared to many other marketing channels and a big benefit is that it is also scalable.
You don’t have to fork out big money for a billboard and then hope that you make a return from it; paid media means that you can categorically see that, for example, you spend £1K and you made £5K. In an era where we are all being a little tighter and more conscious of the ins and outs of our cash flow, it really is essential that you can track your spend to the nearest pound/pence and see that your returns are on your actual marketing endeavours.
It doesn’t have to look perfect
When it comes to content, brand and comms in general, especially when it is your own business and something you are passionate about, of course you want your platform to look amazing, sound amazing and to be really polished; but it costs to achieve this perfection.
Right now, most businesses don’t have the budget or the time to do that and customers are much more forgiving.
If your proposition is so enticing that people are going to focus on that, the image, the USB and your amazing content, you will already be in a strong position to be successful.
E-commerce/Social Media marketing can save your business if you make it an integral part of your strategy. You need to think fast, be creative and importantly, stay true to your loyal customer base and keep your brand message consistent.
Tim Hyde, Founder and Director of Social Media Marketing Agency, TWH Media
Having commenced his career in leading the Facebook strategy for Lad Bible, Tim Hyde boasts an impressive track record of helping businesses and brands scale online through effective social media marketing strategies.
One of the industry’s leading social media gurus, Tim founded TWH Media in September 2017 and now works with large brands globally ranging from Adidas to Apple Music.
Industry experts say that INSTANDA’s no code platform and ADROSONIC’s insurance domain expertise will empower insurers with the agility to price risk in ways that meet the client’s needs in a changing post-Covid-19 world.
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In a significant development to accelerate the ongoing digital transformation in the insurance industry, INSTANDA, a UK-based SaaS Insurance software platform has entered a partnership with ADROSONIC, a digital consulting firm. Industry experts say that INSTANDA’s no code platform and ADROSONIC’s insurance domain expertise will empower insurers with the agility to price risk in ways that meet the client’s needs in a changing post-Covid-19 world.
Delighted over the tie-up, Tim Hardcastle, the CEO & Founder of INSTANDA, said: “Partnerships play a key role in the insurance industry, not merely for the growth and expansion of the business involved, but also for the transformation of the industry. The new partnership with ADROSONIC is exciting as it provides capability to new markets in North America, India, Middle East as well as Europe.”
Mayank, CEO & MD, ADROSONIC, said that the tie-up would provide insurers with innovative digital product and customer propositions for new markets as well as liberate insurers from inflexible legacy tech and from high-risk, high-cost and multi-year change programs.
“Given the paradigm shift that the market is undergoing, partnership models need to demonstrate not just agility and flexibility but to do so with high quality execution. ADROSONIC and INSTANDA have an outstanding track record of delivery so I am excited at what we can offer insurers to realise their ambitions and bring new ideas to market.” Hardcastle added.
“An unprecedented event like Covid-19 has left a sudden yet profound impact on the Insurance Industry and their IT Systems, as they are now subject to rigorous scrutiny following the rapid shifting of entire workplaces online that was forced due to the pandemic,” Mayank said.
“As the key decision-makers respond to the new market demands and opportunities, they are starting to question the limitations of their existing processes and legacy systems, they also had to reassess the cost base turning to a more cost-effective and agile platform which enables them to provide quicker and more responsive service to their customers and clients. In such a scenario, INSTANDA’s no code platform coupled with ADROSONIC’s domain expertise along with a wide range of digital accelerators including RPA, Data Analytics, & CRM are key in liberating insurers from inflexible legacy technologies.
These accelerators will power transformation across organisations looking at improving their ROI by dramatically reduced product launch times, underwriting and distribution costs and an unrivalled customer experience,” he concluded.
INSTANDA works with the leading carriers, MGAs and brokers in UK, Europe, North America, LATAM, Africa, Middle East and Australia. INSTANDA is the Insurance Industry’s first no-code business platform and allows insurers to break into new markets as well as overcome the drawbacks of legacy IT systems and embrace the benefits of digital transformation.
After a growth in alert volumes, and unpredictable spikes driven by global volatility, its time to close alerts quickly and accurately…
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Silent Eight today announced a multi-year partnership with HSBC that will support the bank in enhancing its industry-leading compliance operations. A recognized leader in technology innovation, HSBC sought a financial crime partner that could successfully improve its manual processes and existing statistical models to decrease risk while simultaneously increasing efficiency.
Silent Eight Alert Resolution investigates, and resolves cases in the same way an analyst would; with greater speed, precision and consistency. Following a successful trial period, the solution is set to be integrated into HSBC’s existing infrastructure to provide case adjudications that are explained and auditable.
“Given the growth in alert volumes, and unpredictable spikes driven by global volatility, we saw an opportunity with Silent Eight that would give us the ability to close alerts quickly and accurately,” said HSBC’s Group Head of Compliance Services, Matt Brown.
Silent Eight CEO and co-founder, Martin Markiewicz, said, “We’re delighted to find a partner that shares our focus on eliminating financial crime. HSBC’s dedication to this project is just one aspect of their tireless commitment to improvement, and to helping drive AI innovation across the industry. We’re proud to partner with them on their mission to make the world safer.”
“Silent Eight’s business case was extremely compelling,” said Ben Rayner, HSBC’s Global Head of AML and Sanctions Screening. “We have chosen their solution as we believe it will provide significant business benefits across all our success metrics.”
Silent Eight is a technology company leveraging AI to create custom compliance models for the world’s leading financial institutions. Our mission is to empower our clients in their fight to eliminate financial crime. Founded in Singapore and with global hubs in New York, London, and Warsaw, we are deployed in over 150 markets. For more information, visit: www.silenteight.com
Our fitness habits have changed dramatically in 2020…
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ClassPass, the world’s leading fitness and wellness membership and a global provider of corporate wellness benefits, has released their annual data-driven trends report. ClassPass has the most robust database in the world of fitness, wellness and beauty search behavior, with insights compiled from 30,000 boutique studios, gyms, spas and wellness partners across 30 countries.
This year’s report focuses on the impact of the pandemic on fitness, wellness and beauty, the trends that have emerged post-lockdown and where these industries are headed in 2021.
The data is broken out into the following categories:
● Top Workouts of 2020 – Digital ● Top Workouts of 2020 – Studio Fitness ● Most Popular Days and Times to Sweat ● How Your City Is Working Out ● Social Trends in Fitness ● Beauty and Wellness Trends During COVID-19 ● The Future of Fitness: 2021 Trend Forecasting
As 95% of studios around the world closed their physical spaces, ClassPass helped 5,000 top studios to add livestream and on-demand workouts, and 81% of ClassPass customers reported that they worked out using digital options. Here’s how they got their sweat on:
Top digital workouts of 2020:
Yoga
HIIT
Pilates
Strength Training
Barre
Dance
Stretching
Boxing
● HIIT’s share of all workouts increased by 26% and Pilates’ share of all workouts increased by 16%. ● *Restorative fitness is also very popular in 2020. Meditation and Stretching both rank in the top 10 on-demand activities booked through ClassPass. ● At home classes that require less equipment are more popular. Classes that require bodyweight only pulled in double the number of bookings as classes that require equipment. ● When you find a strength training workout you love, you’ll repeat it. Strength training is the on-demand workout most likely to be replayed. Fitness travel is in: ● More than half of members have tuned in for classes taught in other cities. ● UK fitness fans are likely to “travel” to NYC and Amsterdam. ● North America fitness fans are likely to “travel” to London, Sydney and Amsterdam. ● APAC fitness fans are likely to “travel” to NYC, London and Los Angeles.
UK TOP WORKOUTS OF 2020 – STUDIO FITNESS
It has been an extremely tough year for studios, with many being forced to close for months, and some having a second round of lockdowns. However, the global data has been promising:
Top in-person workouts of 2020 as studios have reopened:
HIIT
Indoor Cycling
Reformer Pilates
Vinyasa Yoga
Bootcamp
Circuit Training
TRX
Hot Yoga
Additional insights:
● Members are booking equipment-heavy classes such as HIIT, Cycling, Pilates and Boxing classes. It’s likely that many members will continue with some combination of digital workouts, but rely on studio classes for the workouts that are tough to do at home.
● Since studios have been able to reopen, two underperforming genres during lockdowns have climbed back to the top: Indoor Cycling bookings have increased by 30% and Reformer Pilates bookings have increased by 18%.
● There was a 400% increase in the number of outdoor classes being offered by studios this year as many closed studios moved outside, taking advantage of fresh air and room to socially distance. 4 in 5 surveyed members reported a willingness to attend these classes, and we anticipate this will be a lasting trend into 2021.
● Transparent safety information is a key factor in the decision to return to studios, according to more than half of ClassPass members. To help, ClassPass added a feature that allows members to preview the specific safety and sanitation precautions of every studio, from distanced bikes to contactless check-in.
MOST POPULAR DAYS AND TIMES TO SWEAT
Most Popular Time To Take a Weekday Class: 12pm
For the first time ever, lunchtime is the most popular time to workout.
Most Popular Time On Weekends To Take a Class: 10am
Most Popular Times For Professionals on a Company-Sponsored Plan: 8am-3pm
Professionals are now much more likely to take a lunch class instead of an after work class. 89% of professionals say they feel more productive during the work day after exercising.
Most Popular Day Of The Week To Work Out: Wednesday
Workouts used to be stacked earlier in the week. Due to limited end-of-week happy hours and more time spent at home, there is less of a rush to get workouts done before the weekend.
FITNESS HAS STAYED SOCIAL, EVEN WHEN SOCIALLY DISTANT
Fitness fans have gotten creative with distant happy hours and remote meetups, inviting friends and colleagues to join them in a class.
● Most popular digital workout to take with friends based in other cities: HIIT
● Digital happy hour – most common time to take a digital class with friends: 12pm
● Most popular time to meet up at a studio with friends: 6pm
● Most popular studio workout to meet friends at as restrictions lift: Cycling
● Most popular workout to take with a colleague: Strength Training
THE FUTURE OF FITNESS: 2021 TREND FORECASTING
Taking A Crunch Break For Lunch Break:
● For the first time ever, 12pm is the most popular time to work out during the week.
● Lunchtime workouts have seen a 67% increase in popularity. This shift can largely be attributed to a rise in remote work, and the ease of no shower required virtual meetings. Even as people have returned to studios, the 12pm weekday time slot for in-person classes is more popular now than it was before lockdowns.
● Bristol, London, Edinburgh, Dublin, Manchester and Brighton have all leaned into this trend, becoming this year’s Lunchtime Warriors, or the cities more likely to book a lunchtime class.
Open Air Gyms Are a Breath of Fresh Air:
● Outdoor workouts first emerged in Europe and have continued to grow in demand throughout the US. 4 in 5 surveyed ClassPass members are willing to try outdoor classes — ClassPass has added a search for “Outdoors” classes to support this trend and the number of outdoor class options has increased by 400% in 2020.
● Many studios are getting creative with outdoor classes including using beautiful city backdrops for class. One studio in Amsterdam even rented out an underutilized wedding venue! Los Angeles is the most likely city to book an outdoor class in the US. Edinburgh is the most likely city to book an outdoor class in the UK.
● For members who feel more comfortable with 1:1 instead of group workouts, ClassPass has also added personal training options through a new partnership with Fyt.
Corporate Wellness Benefits Have Become a Must-Have for Companies:
● 25% of professionals are exercising more now than at the start of COVID-19, with 1 in 5 using their previous commute time to exercise
● 4 in 5 professionals say fitness activities have been crucial to establishing a new work-from-home routine. 96% of professionals say they feel more motivated and less stressed after exercising, with 89% of professionals saying they feel more productive during the work day after exercising.
● 3 in 5 professionals who have participated in a team workout report feeling more connected to their team afterwards. Teams are most likely to book a private HIIT or yoga class to stay engaged and workout together, and hundreds of private classes have been booked.
● Since the start of the pandemic, ClassPass has offered remote fitness benefits to one million employees across companies of all sizes. The interest from companies is continuing to grow, and we expect fitness and wellness benefits to be more important than ever in attracting and retaining talent.
People Will Head Back To Studios Once They Feel Safe
● 92% of professionals hope to return to fitness studios and gyms in 2021, with 40% planning to return exclusively to in-studio workouts when they feel safe to do so (source: Nov 2020 study of 2,185 professionals from 19 countries)
● After attending their first indoor class since the start of the pandemic, 89% of subscribers responded they would go back as or more frequently to future classes
Cities are increasingly, and massively, depending on water technology as sea levels continue to rise…
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Water is the elephant in the room. As the IDTechEx report, “Smart Cities Market 2021-2041: Energy, Food, Water, Materials, Transportation Forecasts”, explains, cities increasingly and massively depend on water technology as sea levels rise and for other reasons. They will eliminate sewage systems by treating it where it is produced. Gone are thirsty, traditional agriculture systems, and their global supply chains.
Stop killing the sea
Currently, cities are killing the sea that is increasingly near to them. Dead ocean areas are spreading. They do this with untreated sewerage, salt from desalination plants, chemicals from factories, leisure activities, marine vessels, and farm runoff of toxins and fertilizer. Instead, they must farm the sea and maintain biodiversity and create benign marine tourism and leisure activities. Methods of distributing salt from desalination without killing anything do now exist, but deployment is slow.
Cities on the sea
Smart cities are planned at sea and on reclaimed land as at Forest City Malaysia, which promises a veritable jungle with “sounds of nature” and all that greenery self-watering. You can buy a DND house on and under the sea in Dubai.
Independence
Cities will make all their own food, fresh water, and electricity for reasons of empowerment, security, and cost. That electricity-making is even pivoting to water with tidal turbines installed from Scotland to the Hudson River in New York and wave power, both being almost continuous and using almost none of the steel and concrete that produces 16% of global warming. Take a few hours to drop them in – not 10 years as for hydro dams. Part of the reason for water power is that there is less and less land for wind turbines and solar farms. Indeed, silicon solar works better cold, so it is migrating to sea or lake as floatavoltaics. New photovoltaic materials are even useful underwater, and photovoltaic paint is on the way, as explained in the IDTechEx report, “Materials Opportunities in Emerging Photovoltaics 2020-2040”.
Leaders in tidal power such as Simec Atlantis and Verdant Power have more and more companies chasing them. You can say the same for wave power leaders such as Seabased, Wello, and Eco Wave. Even ORPC RivGen horizontal axis water turbines are proving viable in shallow rivers, and they do not disturb fish. Most water power is virtually continuous – no massive batteries. See the IDTechEx report, “Distributed Generation: Off-Grid Zero-Emission kW-MW 2020-2040”.
Leisure and freight on water
Obviously, cities will focus more of their leisure industry and freight transport on the water. See the IDTechEx report, “Electric Leisure & Sea-going Boats and Ships 2021-2040”. IDTechEx sees several ways that even large ships can become zero-emission when today they each pollute as much as millions of cars. At the other extreme, Swiss Seabubble aquaplaning water taxis are zero-emission, charged by small river turbines under the landing platform. They are planned for Paris.
Smart agriculture
Today’s farming systems on land gulp water and boost global warming. They are replaced by vertical farming (see the IDTechEx report, “Vertical Farming 2020-2030”), solar greenhouses, hydroponics in buildings, aquaponics and saline agriculture in marshes as sea levels rise. Genetic agriculture will save water. See the IDTechEx report, “Genetic Technologies in Agriculture 2020-2030: Forecasts, Markets, Technologies”. Meat and milk will be grown in city laboratories, and managing with one percent of the fresh water will become commonplace. See the IDTechEx report, “Plant-based and Cultivated Meat 2020-2030”.
Soliculture greenhouses on rooftops and elsewhere are adopting smart glass that provides electricity for the robots as well as optimally growing the plants again with almost no water. Robotic food cultivation is integrated with human facilities in parts of China, saving space and water.
Fish farming and barley, samphire, seaweed, and other vegetable growing in saline water is a done deal back to the ancient Sumerians, but it is necessarily broadening in scope as global warming and people moving to cities makes land even more scarce. The amazing thing is that there is a roadmap of many options to go even further. For example, aquaponics uses even less land than hydroponics, and it costs less. This is growing fish and vegetables in one closed system, the fish excrement feeding the plants.
Smart gardening
Some are planning turf that produces electricity as well as tapping and filtering rainwater for use. Xeriscaping is appearing in smart cities. It is the process of landscaping or gardening that reduces or eliminates the need for supplemental water from irrigation. It is promoted in regions that do not have accessible, plentiful, or reliable supplies of fresh water and is gaining acceptance in other regions as access to irrigation water is becoming limited. Xeriscaping is an alternative to various types of traditional gardening in necessarily frugal smart cities.
On the other hand, the trend to multi-purposing even extends to damp turf, vegetation, and soil. Plant-e is a company that develops products that can generate electricity from living plants, and Harvard University has biofuel cells using such fuels.
Smart water transport
Transport systems are reinvented for smart cities, and necessarily, Hyperloop shooting passengers from city to city by magnetic levitation in a vacuum and Boring Company Loop shooting autonomous cars at high speed across cities will increasingly be tubes in sea, lake or river for at least part of the way. That even saves money. Autonomous underwater vehicles are zero-emission and they monitor offshore wind turbines, sea-floor mining, fish stocks, and more. Leisure submarines anyone – as taxis too?
Thirsty desert cities
The largest challenge of the $0.5 trillion NEOM smart city in the Saudi Arabian desert is drinking water – all desalinated from the sea. See the IDTechEx report, “Desalination: Off Grid Zero Emission 2018-2028”. The Bill Gates Belmont desert city in Arizona is nowhere near the sea, and the state gets its water from the Colorado River, which is drying up. By far its biggest challenge is water. It has to guarantee 100 years’ supply to be allowed to start. Arizona-based startup Zero Mass Water’s SOURCE photovoltaic panels make electricity but also use the sun’s rays to pull water from the air. Each panel has the potential to draw up to 10 litres (2.64 gallons) of water per day. That will help, but all the sources still leave that city with severe water conservation requirements.
Here is one. Bill Gates has proven from his investments that the elimination of sewage distribution and treatment farms is coming when it is treated at the source. That saves huge amounts of water. One new toilet has an electrochemical reactor that can break down water and human waste into fertilizer for fields and hydrogen, which can be stored in hydrogen fuel cells as a green energy source. Even the little water used is treated enough to reuse for flushing or for irrigation.
IDTechEx guides your strategic business decisions through its Research, Subscription and Consultancy products, helping you profit from emerging technologies. For more information, contact research@IDTechEx.com or visit www.IDTechEx.com.
Gurpreet Purewal, Associate Vice President, Business Development, iResearch Services, explores how organisations can overcome the challenges presented by AI in 2021.
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2020 has been a year of tumultuous change and 2021 isn’t set to slow down. Technology has been the saving grace of the waves of turbulence this year, and next year as the use of technology continues to boom, we will see new systems and processes emerge and others join forces to make a bigger impact. From assistive technology to biometrics, ‘agritech’ and the rise in self-driving vehicles, tech acceleration will be here to stay, with COVID-19 seemingly just the catalyst for what’s to come. Of course, the increased use of technology will also bring its challenges, from cybersecurity and white-collar crime to the need to instil trust in not just those investing in the technology, but those using it, and artificial intelligence (AI) will be at the heart of this.
1. Instilling a longer-term vision
New AI and automation innovations have led to additional challenges such as big data requirements for the value of these new technologies to be effectively shown. For future technology to learn from the challenges already faced, a comprehensive technology backbone needs to be built and businesses need to take stock and begin rolling out priority technologies that can be continuously deployed and developed.
Furthermore, organisations must have a longer-term vision of implementation rather than the need for immediacy and short-term gains. Ultimately, these technologies aim to create more intelligence in the business to better serve their customers. As a result, new groups of business stakeholders will be created to implement change, including technologists, business strategists, product specialists and others to cohesively work through these challenges, but these groups will need to be carefully managed to ensure a consistent and coherent approach and long-term vision is achieved.
2. Overcoming the data challenge
AI and automation continue to be at the forefront of business strategy. The biggest challenge, however, is that automation is still in its infancy, in the form of bots, which have limited capabilities without being layered with AI and machine learning. For these to work cohesively, businesses need huge pools of data. AI can only begin to understand trends and nuances by having this data to begin with, which is a real challenge. Only some of the largest organisations with huge data sets have been able to reap the rewards, so other smaller businesses will need to watch closely and learn from the bigger players in order to overcome the data challenge.
3. Controlling compliance and governance
One of the critical challenges of increased AI adoption is technology governance. Businesses are acutely aware that these issues must be addressed but orchestrating such change can lead to huge costs, which can spiral out of control. For example, cloud governance should be high on the agenda; the cloud offers new architecture and platforms for business agility and innovation, but who has ownership once cloud infrastructures are implemented? What is added and what isn’t?
AI and automation can make a huge difference to compliance, data quality and security. The rules of the compliance game are always changing, and technology should enable companies not just to comply with ever-evolving regulatory requirements, but to leverage their data and analytics across the business to show breadth and depth of insight and knowledge of the workings of their business, inside and out.
In the past, companies struggled to get access and oversight over the right data across their business to comply with the vast quantities of MI needed for regulatory reporting. Now they are expected to not only collate the correct data but to be able to analyse it efficiently and effectively for regulatory reporting purposes and strategic business planning. There are no longer the time-honoured excuses of not having enough information, or data gaps from reliance on third parties, for example, so organisations need to ensure they are adhering to regulatory requirements in 2021.
4. Eliminating bias
AI governance is business-critical, not just for regulatory compliance and cybersecurity, but also in diversity and equity. There are fears that AI programming will lead to natural bias based on the type of programmer and the current datasets available and used. For example, most computer scientists are predominantly male and Caucasian, which can lead to conscious/unconscious bias, and datasets can be unrepresentative leading to discriminatory feedback loops.
Gender bias in AI programming has been a hot topic for some years and has come to the fore in 2020 again within wider conversations on diversity. By only having narrow representation within AI programmers, it will lead to their own bias being programmed into systems, which will have huge implications on how AI interprets data, not just now but far into the future. As a result, new roles will emerge to try and prevent these biases and build a more equitable future, alongside new regulations being driven by companies and specialist technology firms.
5. Balancing humans with AI
As AI and automation come into play, workforces fear employee levels will diminish, as roles become redundant. There is also inherent suspicion of AI among consumers and certain business sectors. But this fear is over-estimated, and, according to leading academics and business leaders, unfounded. While technology can take away specific jobs, it also creates them. In responding to change and uncertainty, technology can be a force for good and source of considerable opportunity, leading to, in the longer-term, more jobs for humans with specialist skillsets.
Automation is an example of helping people to do their jobs better, speeding up business processes and taking care of the time-intensive, repetitive tasks that could be completed far quicker by using technology. There remain just as many tasks within the workforce and the wider economy that cannot be automated, where a human being is required.
Businesses need to review and put initiatives in place to upskill and augment workforces. Reflecting this, a survey on the future of work found that 67% of businesses plan to invest in robotic process automation, 68% in machine learning, and 80% investing in perhaps more mainstream business process management software. There is clearly an appetite to invest strongly in this technology, so organisations must work hard to achieve harmony between humans and technology to make the investment successful.
6. Putting customers first
There is growing recognition of the difference AI can make in providing better service and creating more meaningful interactions with customers. Another recent report examining empathy in AI saw 68% of survey respondents declare they trust a human more than AI to approve bank loans. Furthermore, 69% felt they were more likely to tell the truth to a human than AI, yet 48% of those surveyed see the potential for improved customer service and interactions with the use of AI technologies.
2020 has taught us about uncertainty and risk as a catalyst for digital disruption, technological innovation and more human interactions with colleagues and clients, despite face-to-face interaction no longer being an option. 2021 will see continued development across businesses to address the changing world of work and the evolving needs of customers and stakeholders in fast-moving, transitional markets. The firms that look forward, think fast and embrace agility of both technology and strategy, anticipating further challenges and opportunities through better take-up of technology, will reap the benefits.
Digital health passport providers must also work to address any potential data privacy issues…
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Digital health passports should not be introduced on a mass basis until coronavirus tests are available and affordable to everyone in the country, a new report warns. The same considerations apply to vaccines once these are approved and ready for widespread use.
Failing to address issues with the availability and affordability of tests and vaccines risks excluding already vulnerable populations from protection against the virus, according to the research. This could also restrict people’s legal rights.
Digital health passports, sometimes also referred to as ‘immunity passports’, are digital credentials that, combined with identity verification, allow individuals to prove their health status (such as the results of COVID-19 tests, and eventually, digital vaccination records).
The report also urges digital health passport providers to work to address any potential data privacy issues. It calls for policymakers to strike an adequate balance between protecting the rights and freedoms of all individuals and safeguarding public interests while managing the effects of the pandemic.
The research was carried out by Dr Ana Beduschi, from the University of Exeter Law School and is funded by the Economic & Social Research Council (ESRC), as part of UK Research & Innovation’s rapid response to Covid-19.
The report warns that deployment of digital health passports may interfere with several fundamental rights, including the right to privacy, the freedoms of movement and peaceful assembly. It also warns that the use of digital health passports may have an impact on equality and non-discrimination. If some people cannot access or afford COVID-19 tests and vaccines, they will not be able to prove their health status, thus having their freedoms de facto restricted.
Dr Beduschi said: “Digital health passports may contribute to the long-term management of the COVID-19 pandemic, but their introduction poses essential questions for the protection of data privacy and human rights. They build on sensitive personal health information to create a new distinction between individuals based on their health status, which can then be used to determine the degree of freedoms and rights individuals may enjoy.
“Given that digital health passports contain sensitive personal information, domestic laws and policies should carefully consider the conditions of collection, storage and uses of the data by private sector providers.
“It is also crucial that the communities that have already been badly impacted by the pandemic have swift access to affordable tests and, eventually, vaccines. Otherwise, deploying digital health passports could further deepen the existing inequalities in society.”
Multiple initiatives to develop and deploy digital health passports are currently underway in the UK and abroad, to facilitate the return to work, travel, and live-audience large sports events. The World Health Organisation (WHO) and Estonia have recently agreed to develop a digital vaccination certificate that could be used for COVID-19 once a vaccine is available. Rapid antigen tests for COVID-19 are increasingly offered by private sector providers and results are often managed through digital platforms. Vaccine trials have shown promising early results, raising hopes for vaccine availability and widespread vaccination by next year.
The aim of the report is to inform decision-makers at an early stage, before large-scale deployment of digital health passports, about the risks they pose to the protection of these rights, and to recommend effective strategies for potential risk mitigation. The research analysed the existing legal framework, including UK laws, judicial decisions and international human rights law.
Significant Investment Growth of 200% over the Next 5 Years
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A new study from Juniper Research has found that network operator spend on MEC (Multi-access Edge Computing) will grow from $2.7 billion in 2020 to $8.3 billion in 2025, as operators invest heavily in upgrading network capacities and infrastructure to support the increasing data generated by 5G networks.
The study also revealed that by 2025, the number of deployed MEC nodes will reach 2 million globally in 2025, up from 230,000 in 2020. These devices, which take the form of access points, base stations, and routers, will play a vital role in managing the vast quantities of data generated by connected vehicles, smart city systems and other emerging data-intensive services.
The new report, Edge Computing: Use Cases, Innovation Opportunities & Market Forecasts 2020-2025, notes that this increase in investment is a result of network operators enhancing key network functions, by moving infrastructure used for processing data from core network locations, to base stations at the edge of their networks. It anticipates that the capabilities of 5G technologies, such as high throughput, low latencies and high device densities, will necessitate roll-outs of MEC nodes in urban areas.
The research identified smart cities as a key industry that will benefit from MEC node roll-outs, as operators and planning authorities identify how best to install 5G-compatible edge nodes. It suggests that these parties explore utilising existing city structures, such as street lighting and sidewalks, to mitigate issues of space limitation inherent to densely-populated areas.
Consumers to Benefit from Operators’ Take-up of Edge
The research forecasts that over 920 million individuals will benefit from edge‑enhanced Internet connectivity by 2025; rising from 100 million individuals in 2020. Services, such as music streaming, digital TV services and cloud gaming, will be the biggest beneficiaries of the ultra-low latency provided by operators’ increasing roll-outs of MEC nodes over the next 5 years.
CoinCorner’s CEO, Danny Scott, explains why he believes there is more positive growth set for Bitcoin in 2021
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“As we come to the end of what has been an iconic year for Bitcoin, I can only see more positive growth in 2021 and here’s why…
By CoinCorner’s CEO, Danny Scott
Eggs with currency signs in wooden packing on a blue background. Golden egg with a bitcoin sign. Investment concept
“Living and breathing this extremely fast-paced industry and soaking up global bullish news daily means that I’ve forgotten more good news from this week alone than Bitcoin had in years back in its early days.
“Here are a few of the reasons why I’m incredibly bullish on Bitcoin for 2021.”
“Starting simply, Bitcoin is finite and there will only ever be 21 million. Back in May, we celebrated Bitcoin’s third halving —an event that happens roughly every 4 years, halving the supply of Bitcoin coming into circulation —and this year saw it go from 12.5 Bitcoin to 6.25 Bitcoin per block (every 10 or so minutes). There are expectations for what might come after, with history telling us that the Bitcoin price will typically begin to rise significantly (20x+) within the 18 months following a halving — often simply put down to supply and demand.
“While we know the supply is fixed, what about the dynamic demand? This is the part that I feel has been underestimated at each halving, including by ourselves at CoinCorner following the 2016 halving which led to the bull run of 2017. During the bull run, we were signing up a record number of registrations but our system and processes weren’t ready for this, and we weren’t alone. Some of the larger exchanges had to freeze registrations as they couldn’t handle the throughput, while others experienced technical issues with their trading engines locking up and websites going down due to overload.
“This time around though the industry as a whole is better prepared for the predicted 2021 bull run… it’s not perfect, but it’s better.”
Where’s the current demand coming from?
“Compared to 2017 when demand came from the retail market (this will eventually happen again, of course), the current demand is coming from an institutional level completely flying under the radar for many people and it looks set to continue through 2021.
“Roughly 27,000 Bitcoin are mined (brought into circulation) each month and although this may sound like a lot, it’s really not. For context, Grayscale added 32,000 Bitcoin to their portfolio in October, CashApp received $1.6 billion worth of revenue from their customers buying Bitcoin in Q3 2020 and PayPal has entered the cryptocurrency market, allowing customers to buy Bitcoin with full global roll out planned for next year.”
“In October, Microstrategy became the first publicly traded company to add roughly 38,250 Bitcoin to their balance sheet, with Square closely following in their footsteps with a purchase of 4,709. I fully expect to see this trend continue through 2021 as more companies look for the best place to exit their fiat positions and choosing Bitcoin as their inflation hedge asset.
“At CoinCorner, our balance sheet (like many other Bitcoin companies) already holds Bitcoin and this is likely to be a growing trend as inflation begins to kick in due to the current financial climate.”
What about traditional investment?
“Companies aside, traditional investors are also beginning to make their moves. The well-respected Rauol Pal has this year become more and more bullish on Bitcoin and his position, even more recently mentioning that he was going to sell his gold to buy more Bitcoin.
“Another example is Stan Druckenmiller and Paul Tudor Jones — two high-profile billionaires who recently opened up about their Bitcoin investments and how bullish they are for the coming years.
Stan is yet another person to compare Bitcoin to gold as an investment, stating he owns both but believes Bitcoin should outperform gold. He was quoted saying:
“…so I own many, many more times gold than I own Bitcoin, but, frankly, if the gold bet works, the Bitcoin bet will probably work better because it’s thinner and more illiquid and has a lot more beta to it.” — Daily Hodl
“Again, this is a trend we can expect to see continuing as wealthy individuals look to inflation hedge assets.”
“There are lots of price models and predictions coming out, with Stock-to-Flow (S2F) from PlanB being one of the more popular ones, all ranging in price from $50,000 to $288,000 per Bitcoin in 2021.
“The chart below shows the previous halvings, with the red line indicating our current progress since the halving earlier this year. If it continues to follow the previous trends, we can expect to see the S2F model being somewhat accurate — meaning that $288,000 may not be an unrealistic target price.”
“Touching briefly on the unfortunate situation the world has suffered this year, the coronavirus crisis had the knock-on effect of causing a long-awaited financial crash in March. This resulted in Government bailouts: the U.S. FED printing $3 trillion (plus another $2 trillion on the way), the Bank of England likely printing towards £1 trillion and many more around the world following suit. Not to forget the introduction of negative interest rates which look to become the norm. Although this may be necessary in their eyes to stimulate the economy and its future protection, this comes with a huge risk of inflation on a scale unseen in these territories before.
“Putting this into perspective, the FED printed $3.9 trillion between 2008 and 2014 during the 2008 financial crisis, and they’ve already surpassed this in 2020 alone, with more likely to come.
“When it comes to financial uncertainty, people look for a safe haven and Bitcoin is becoming this.”
“61.71% of all Bitcoin in circulation hasn’t moved within the last 12 months. Bitcoin investors have stomached sharp drops greater than 50% this year and still didn’t sell. Bitcoin’s sitting comfortably around the $15,000 — $16,000 region right now and still those coins aren’t moving. Bitcoin investors are here for the long-term, they have strong hands and are preparing for the next 20x.
“This Bitcoiner crowd is also continuing to accumulate and hodl more every day, leaving less liquidity available for newcomers. In turn, this will drive the price. Once Bitcoin pushes past the $20,000 previous all-time high and starts hitting mainstream media again, retail investors will enter just as they did in 2017, but this time with the backing of public global companies, billionaires and hedge funds.”
Online searches for Bitcoin
“A quick look on Google trends for the search term “Bitcoin” shows that interest today isn’t anywhere close to that of 2017, sitting at only 13%. Yet, the Bitcoin price is hovering around 75% and looks likely to hit that $20,000 before the interest spikes again.
“Interest during the 2013 bull run was only 10% of what 2017 became and so, I fully expect the 2021 bull run to peak “Bitcoin” interest in excess of 5x, maybe towards 15x, of what we saw in 2017.”
“Bitcoin’s history shows that after a halving (2012 and 2016), the price sees an incredible increase in the following year, with the year after that being the only negative years (2014 and 2018).”
2010: 𝟵,𝟵𝟬𝟬%
2011: 𝟭,𝟰𝟳𝟯%
2012: 𝟭𝟴𝟲%
2013: 𝟱,𝟰𝟴𝟭%
2014: -𝟱𝟳%
2015: 𝟯𝟰%
2016: 𝟭𝟮𝟯%
2017: 𝟭,𝟯𝟲𝟴%
2018: -𝟳𝟯%
2019: 𝟵𝟮%
2020: 𝟭𝟮𝟭% (so far)
Is Bitcoin a success?
“The industry has been challenged by a lot of negativity over the years, but as time has passed, its reputation and sentiment has grown stronger.
“At what point do we call something a success? 10 years? 20 years? What if it fails in 70 years time? Would that make Bitcoin a failure? No, it would mean that it’s had its time and something better has surfaced.
“Personally, I’ve gone past the stage of treating Bitcoin like an experiment, or wondering when it will be considered a success — I already see Bitcoin as a success.
“The Bitcoin community is continuing to build a decentralised monetary future and this is only the beginning.”
Comments on millennial wealth often focus on unfavourable comparisons to Baby Boomer prosperity. But while Boomer affluence remains indisputable, millennials’ control of global assets continues to rise. With millennial wealth already topping $24trn, financial institutions have not ignored this shift in fortunes. Instead, those institutions have already worked to attract millennial attention with ESG options that recognise millennial concerns about the Climate Crisis.
To continue adapting, financial institutions can offer similar options for clients to support not-for-profit climate solutions. Normalising that support gives millennials another powerful mechanism to mobilise their assets for climate action.
Millennials’ economic influence and interests
The ‘millennial’ generation has long been plagued by perceptions of financial frivolity or misfortune. From failing to save effectively to drowning in student debt, millennials are often imagined as a global cohort incapable of economic heft.
A recent report from UBS calls many of these assumptions into question. Estimating millennials’ combined wealth at approximately $24trn, the report identifies the younger generation as an emerging powerbroker in the global economy. Driven already by income growth and entrepreneurial activity, this accumulation of assets will only increase in the wake of ‘one of the largest intergenerational wealth transfers ever’. A report from Accenture suggests that in North America alone, inheritance from Baby Boomers may top $30trn by 2050.
Rounding out this portrait of millennials’ financial power is a generational stereotype that has held true. Millennials pay attention to purpose: acting personally and professionally with a set of values in mind.
As a purpose for taking action, tackling the Climate Crisis consistently tops the list of millennials’ global concerns. Deloitte’s most recent Millennial Survey identified the durability of this climate concern even in the wake of COVID-19. Despite the ongoing pandemic, the issue of climate change and protecting the environment remained essentially tied with health care and disease prevention for millennial respondents in mid-2020.
Sustainable options from financial institutions
Faced with millennial wealth and climate consciousness, financial institutions have already adapted their outreach. Sustainable investing and ESG options offer important opportunities for savers and investors to protect the planet. A recent report suggests that global sustainable investment had reached $30.7trn in 2018, up 34% from 2016 levels.
Millennials already make up a significant portion of that total. 95% of millennials report interest in sustainable investing, and a staggering 67% have been involved with one or more sustainable investment activity. In the coming years, this engagement will only increase.
The need for climate not-for-profits
To further adapt to millennials’ economic influence and interests, financial institutions can also offer opportunities to support not-for-profit climate solutions.
ESG and sustainable investing allow market forces to encourage important climate action. But markets are not all-powerful. No market solutions exist for suing polluters, protecting rainforests, or accelerating clean energy to the billion people with no power. Not-for-profit organisations perform these critical tasks.
Take the environmental charity ClientEarth as an example. In September, the organisation was instrumental in accelerating the closure of Poland’s Belchatow power plant: the single largest greenhouse gas-emitter in Europe. This victory reminds us that not-for-profits play a key role in climate action – a role that for-profit organisations cannot fulfil.
In their effort to engage with millennials, financial institutions can acknowledge the role played by climate not-for-profits and provide their clients with simple ways to support them. Climate-conscious millennials will take advantage of an opportunity to channel their assets into issues beyond the reach of ESG initiatives.
An option to Reinvest in Earth
The Global Returns Project has coined the term ‘Reinvesting in Earth’ to describe that simple way for individuals with assets to support climate not-for-profits. When an individual Reinvests in Earth, they commit at least 0.25% of their savings and investments annually to funding not-for-profit climate solutions.
Financial institutions could make Reinvesting in Earth normal and easy by offering it as a tick-the-box option for clients. In addition to attracting millennials, normalising this regular, proportional funding could raise remarkable sums for the climate.
Globally, private individuals hold approximately $140trn in assets. If just 3% of those individuals Reinvested in Earth, they would raise $10bn every year for critical climate solutions.
Despite stereotypes to the contrary, millennials play an increasingly powerful role in the global economy. While ESG initiatives have proven popular with this younger demographic, financial institutions can also incorporate climate not-for-profits into their options for clients. Normalising the practice of Reinvesting in Earth gives millennials the ability to support non-market climate solutions with their assets.
The Global Returns Project:
The Global Returns Project (GRP) is an initiative from the Climate Crisis Foundation which seeks to transform the way we use private assets, by normalising “Reinvestment” in Earth.
It was founded in 2019 by finance gurus Yan Swiderski and Jasper Judd, after they grew frustrated by the lack of support being given to climate-initiatives.
With its unique funding structure depending on the commitment of assets rather than income, the organisation hopes to turn the table on traditional philanthropy and make it easy for individuals to fund not for profit climate solutions, whilst also encouraging financial institutions to make such reinvestment normal and easy for their clients.
Now that the COVID-19 pandemic has moved the Overton window for what we understand as achievable social and policy change, the next decade could prove fertile ground for climate change initiatives. As such, the Global Returns Project has set itself a target to raise 10 billion dollars per year for environmental causes. These funds will then be divided between the organisation’s partners, all of whom are identified via a rigorous selection process as the most highly effective climate solutions. Current partners include Ashden, Client Earth, Global Canopy, Rainforest Trust and Trillion Trees.
Jasper Judd Biography:
Jasper Judd is co-founder of the Global Returns Project. A Cambridge graduate and Chartered Accountant, he has held several senior finance, strategy and innovation roles in large listed global business throughout his career.
In recent years, however, Jasper has been increasingly focused on the Climate Crisis and what people with professional backgrounds can do to make a difference. Spurred by the desire to build a brighter future for his children, he decided to co-launch the Global Returns Project where he uses his financial expertise to empower people to easily fund not for profit climate solutions.
Tim Hardcastle, CEO and Co-Founder of INSTANDA, on what will be top of mind for insurers in 2021 and why technology will be critical
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“Insurance is the industry of risk. But the depth and breadth of COVID-19 – its impact on society and the economy – was not in insurers’ near-term planning models this year. Insurers and their customers enter 2021 in a world transformed. Physical and mental barriers have deteriorated. Walls separating businesses from customers have collapsed, with the discovery that digital can strengthen customer relationships.
ByTim Hardcastle, CEO and Co-Founder of INSTANDA
“As we enter this new world, insurance must reboot and reenergise. Reboot their business development plans, by investing in sophisticated digital tools and partnering with organisations that accelerate innovation. Reenergise their propositions and offerings, so their products continue to excite and stimulate customers.
“In practice, this means focusing on two areas: personalisation at scale and differentiation through digital engagement. Think Netflix and Disney plus, but in insurance.
“There is a more urgent pressure behind this need: cost. To avert another drop in earnings, insurers need to accelerate their digitalisation plans so they can take full advantage of reducing costs to industry leading levels of less than $1 per policy.
“What surprises could 2021 have in store? A potentially unavoidable one is the rapid acceleration of contextual or immersed insurance. Where customers buy insurance through another retail or business interaction – say, a new TV in Tesco – and insurance is embedded and sold through that. This not-so-surprise will bring new businesses challenges that only digital platforms can help solve.
“Another area which is exciting in the year ahead is the industry’s appetite to develop wider service-based offerings, such as pet and cyber insurance which provide extensive service wrappers. A pet wrapper, for example, may include advice on pet health and best practise to keep your pet healthy, with the aim to reduce bills and the insurance claim. This reflects the recognition of serving customers with a wider proposition than simply the claim pay-out.
“Our own business has adapted to respond to the challenge’s insurers faced this year. We’ve accelerated our plans to add more capability to the platform, such as launching our integration marketplace and digital billing and claims. We’ve done so in anticipation of a greater need from insurers to be braver in their approach to meet customer demand.
“Finally, I think the industry can expect a rebounding next year. There has been a downgrade in analysts’ predictions of 2020 results for several major players, as revenues slipped and claims increased. But we are also seeing rate increases in other segments so we anticipate 2021 earnings will rebound.
“2020 has brought a year of surprises to an industry that has dealt with some of the worst kinds of surprises, for centuries. A lesson it has taught – as surprises often do – is the necessity of adaptability; to be able to respond to customer demand and regulation, quickly.
“To prepare for this new year, organisations need to look at their existing infrastructure and business models and ask themselves: am I ready?”
James McLeod, EMEA Director, Faethm, the article looks at how AI and automation have come to be perceived as a threat to human employability much more than any other revolution-driving technology
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Technology, AI and societal change are the two major hallmarks of industrial revolutions. It would be remiss to discuss the first industrial revolution, for example, without reference to steam power and the migration of the workforce from the country to the city, or the third industrial revolution without reference to the internet and rapid globalisation.
Today, as AI/automation and the decentralisation of labour push the world toward the fourth industrial revolution, a core characteristic of these changes has become clear: an acceleration in the speed at which specific skills rise and fall in demand. Over the past 100 years or more, the length of these cycles has dropped from decades to just a matter of years, creating one of the biggest employability challenges for businesses and individuals alike moving forward.
To stay abreast of change, companies must fundamentally change the way in which they look at skills, training and career development. This isn’t just another story about technology and AI creating as many jobs as it invalidates, but rather a need to consider how existing roles will evolve and how people in at-risk jobs can easily transition into roles where they continue to add value on top of technology:
– What needs to happen? Career development must no longer be seen as horizontal (i.e. whereby individual workers refine a particular set of specific skills over the course of their careers and/or lives). Instead, careers must also follow a lateral trajectory, expanding not just upward, but outward into new skill areas.
– How can this be achieved? Each role will have a set of transferable and non-transferable skills. By identifying which skills sit across different roles, employers can corridor existing employees into new roles lessening the need to search for brand new talent.
– Why should employers do this? Trying to keep abreast of demand for new skills by constantly hiring new talent is a costly and unsustainable strategy. Moreover, by looking at how individual processes translate to value can help eliminate bloated processes and release capacity, making roles not only more relevant, but more efficient.
Enterprises that gather customer data also suffer 62% more financial damage due to data breaches…
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Customer data is a valuable commodity to businesses, which they use to improve and market their products. However, some companies profit from selling your data to other businesses.
According to data presented by the Atlas VPN team, one in ten businesses globally sell customer data to third parties.
The numbers are based on The Kaspersky Global Corporate IT Security Risks Survey, which features data from interviews with 5,266 IT business decision-makers from 31 countries globally. The interviews took place in June 2020 and were released in November 2020.
The survey reveals that around half of businesses worldwide collect client data. A total of 48% of small and medium businesses (SMBs) and 52% of enterprise representatives reported that their companies gather information about their clients. One-fifth of these businesses (18% of SMBs and 21% of enterprises) also sell that data to third parties.
Rachel Welch, COO of Atlas VPN, shares her thoughts on how people can protect better protect their data online:
“Nowadays, people face a challenge of balancing privacy and usability. They cannot control how securely companies store their information or in whose hands their data might end up. However, people can make sure that they limit the information they reveal online.
Using a VPN, reconfiguring your device’s privacy settings, and reading Privacy Policy before you sign up for a new service are just some of the things I would recommend to protect your personal data better.”
While 24% of SMBs and 21% of corporations do not currently gather customer data, they plan to do so in the upcoming 12 months. A quarter (25%) of small and medium businesses and 23% of enterprises do not collect any customer data. The remaining 3% of SMBs and 4% of corporations do not know whether they collect client data.
Companies that do not collect client data suffer less from data breaches
Companies that collect client data are attractive targets to cybercriminals and, therefore, always at risk of a data breach. Naturally, they also have more to lose if they get hacked.
SMBs that collect customer data typically lose around $117 thousand per data breach — 37% more than their counterparts that do not collect user data. Enterprises that gather customer data also suffer 62% more financial damage due to data breaches. On average such enterprises lose $1.3 million per data breach.
The ‘Financial Sector, Threat Landscape 2020’ report revealed five top security challenges that the financial sector are currently facing, the risks of future threats, and how to spot these risks before it is too late. Here, CPOstrategy takes a closer look…
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We are no stranger to the notion of cyber security, but one industry that suffers the most from cyber security threats is the financial secretary. Key security measures within the sector have evolved dramatically with the likes of key codes, two factor authentication, voice ID, behavioural analysis, one-time passcodes, protective messaging and digital fingerprinting.
1. Ransomware
Amazingly, the term “ransomware” was only added to the dictionary three years ago. In that time however, ransomware has increased dramatically in terms of the frequency of incidents and the range of methods used to conduct them. Let it be known that the attackers are extremely sophisticated. Once they have your data, who’s to say that your data will be given back or decrypted even if you pay up. Worse still what’s stopping them coming back to attack you again? The report found that once an attack is made, the bad actor will sell the details on to their associates to go after the victim again after deployment, because the payload can still be there, activated and deactivated.
2. Internal Threats
The report takes a look at the Verizon, 2020 Data Breach Investigations Report (DBIR) where it shows that ‘employees’ mistakes account for roughly the same number of breaches as external parties who are actively attacking’ the organisation. Now isn’t that terrifying? Misdelivery within the company, by which information has inadvertently been sent to the wrong person, stands tall as one of the most common issues when it comes to the notion of insider threats. Next time you forward an email or send one to the wrong person/recipient, click on the wrong mailing list, that’s a misdelivery. In the interests of fairness, misdelivery is almost always accidental and non-malicious, but the effects can be devastating. Especially if sensitive data is inadvertently shared to the wrong recipient.
3) App Developments
There’s an app for that. There really is. Apps in the investment and finance space have grown substantially in 2020 which is of course a good thing, as the ability to invest online is quick and easy, and accessible to all. But, with demand comes rushed development. Many of these apps were developed quickly and quite frankly are not ready for cyber-attacks. So that means no two-factor authentication, no protection from appropriate regulations, are not patched or maintained properly, and do not have contingency plans in place to mitigate the effects of a cyber-attack. What that means then is personal information of app users is relatively easy to steal and sell. This can be done by creating duplicate fraudulent apps to trick the user. On these duplicate apps, the imagery and language of the genuine app is mirrored. Once the personal information is supplied, all the money involved (real and virtual) is up for grabs. And so begins the circle of ransomware life.
4) Third-Party Risks
Few organisations work on their own. Quite rightly too. Think about third parties that they use. Vendors, partners, email providers, service providers, web hosting companies, law firms, data management companies, subcontractors. The list goes on. They are all essential to business operations and a lot of these third parties share IT systems and even sensitive information through legal teams so it goes without saying that third parties may very well be an open backdoor into your financial systems for attackers to infiltrate.
5) COVID-19
Yep, even cyber crime has been affected by COVID. It is that unavoidable. Cyber criminals are continuing to target the financial sector even during the pandemic. There has been quite the spike in cyber attacks on banks, financial organisations and the third parties connected to them. Going back to simpler times before COVID-19, if an attacker wanted to sabotage a company or steal data, they would target the business itself. They’d aim their sights at the website, the social accounts, the logins and all their vulnerabilities. In response, organisations had counter measures in place. But now, you just need to target a single remote worker and the house of cards comes tumbling down.
The Collaboration Progress Monitor, the National Centre for Universities and Business’ (NCUB) annual tracking of long-term trends in UK university-business collaboration, shows the number of interactions increased across the board in 2017/18. The Monitor forms part of the State of the Relationship report 2020.
The Collaboration Progress Monitor revealed that 2017/18 saw:
Almost 113,000 interactions between universities and businesses, with the number increasing by 10.2% from 2017 to 2018;
Investment by UK businesses in university research and development (R&D) soar by 8.7% in real terms in just one year – taking the total investment to £389m, between 2017/18;
In just one year, 2017/18, the number of interactions between universities and SMEs grew by 11.9% to 85,218, and interactions with large businesses grew in the same period, by 5.5% to 27,645.
Dr Joe Marshall, Chief Executive of the National Centre for Universities and Business (NCUB), said: “New analysis, published today, shows that collaborations and partnerships between universities and businesses were soaring before the Covid-19 pandemic. Between 2017 and 2018 the numbers of collaborations increased by more than 10 per cent on the previous year. It is hugely positive that these partnerships were becoming deeper and better embedded into the working practices of business and university actors across the ecosystem. Undoubtedly, working together helped universities and businesses to build the resilience to help carry them through the Covid-19 crisis.”
Marshall continued: “Although we have seen a rise in collaborations between universities and businesses for many years, the future looks challenging for collaboration as organisations respond to unprecedented change and uncertainty. Although university-business collaboration in the UK had been deepening, we need, now more than ever, to see collaborations continue to rise. Now is not the time for complacency. These vibrant, and productive partnerships that create lifesaving, innovative products and processes and develop our skilled graduates, are the lifeblood of the UK economy.”
David Sweeney, Executive Chair of Research England, which commissioned the report, said: “This report showcases how universities and business have worked together effectively across the UK and the benefits of that collaboration locally, nationally and internationally. Continuing and deepening university-business collaboration will be essential to help the country recover from the impact of the pandemic and to thrive in the future. Support for university knowledge exchange is a key element in regional resilience, as described in the report, and UK Research and Innovation is now working with the Government on a Place R&D Strategy to deliver improved local R&D outcomes in regions which currently face investment and capacity constraints.”
In the Cambridge Dictionary Machine Learning is referred to as ‘The process of computers changing the way they carry out tasks by learning from new data, without a human being needing to give instructions in the form of a program’. And, in the Oxford Lexico, it is used to describe ‘The use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data’.
Generally speaking, ML relies on mathematical models which are built by analysing patterns in datasets. These patterns are then used to make predictions on new input data. Similar to the way Netflix offers recommendations for new TV series, based on previous viewing experiences, ML is one of the many approaches to AI that uses a system that is capable of learning from experience, and builds upon what has been learnt.
Misconceptions
People are often scared or apprehensive about what they do not understand. Although ML is not a new concept for experts in the field, many are only just getting to grips with what it is and how it can be used. Because the term ML is associated with depictions portrayed in the media of power-hungry robots with a thirst for human destruction, many recoil at the thought of utilizing it in business or private use. But the truth is that these portrayals are not accurate representations, and ML is used by the majority of us, on a daily basis, without us even fully recognizing how or where.
Examples of daily ML in action includes the use of portrait mode on your smart phone, social media feeds on applications such as Facebook or Instagram, music and media streaming including BBC iPlayer or Netflix, online adverts tailored to the user journey, pretty much every online game, banking apps, smart devices… the list is endless.
From reinforcement learning, semi-supervised learning, self-learning, feature learning, sparse dictionary learning, anomaly detection and robot learning, there are many different approaches and techniques used. But, on the whole, machine learning can be broadly classified into two classes, known as supervised and unsupervised learning.
Supervised Learning
Supervised Learning is where a machine learns from training data, and maps out inputs and outputs, based on rules provided in said training data, and from inferred functions. In Supervised Learning, the dataset is labelled, wherein there is a target variable. The value of which the ML model learns to predict, using different algorithms. For instance, it may do this based on IP address location, frequency of web requests and so on. From this, an ML model can then predict if the IP was part of say a Distributed Denial-of-service (DDoS) attack, and more.
The main goal is for the machine to extract the information from the unlabelled data sets, that could aid performance and increase productivity.
Unsupervised Learning
In Unsupervised Learning, there is no labelled data, thereby, no prediction of a target variable. Unsupervised Learning tries to find interesting associations, or patterns, within a dataset. For instance, clustering can be applied in user analytics where application users can be grouped together. By doing this, it is possible to see what data should belong to a specific group, or not.
Machine learning is about developing patterns and manipulating those patterns with algorithms. In order to develop patterns, we need a lot of data that has complete, relevant and rich context. It is not just about the quantity of the data, but also the quality.
Essentially, accurate and rapid security depends on the initial data collection. There are many systems out there, buzzing away, both on-premise and on the Cloud. You need to be able to get the data from those systems, process it, correlate, and analyse those systems. Whether via traditional Syslog, Cloud API, AWS, Azure, Statistical Analysis Systems (SAS) services, or something else, you need to get that data, and have it presented in a way that can be processed quickly and efficiently.
And, once you have the right logs, they need to be validated. You can start to standardise and normalise them. Start with basic correlation. By contextualising the traffic logs against threat intelligence data, analysts can see where risky user activity might be present. This, very quickly, moves along to advanced analytics.
Which is why Data Cleansing is an important part of machine learning, and helps analysts make sense of the raw data captured from multiple sources.
‘If intelligence is a cake, the bulk of the cake is unsupervised learning, the icing on the cake is supervised learning, and the cherry on the cake is reinforcement learning (RL).’ – Facebook AI Chief Yann LeCun
Applications of Machine Learning in Cyber Security
To better understand previous cyber-attacks, and develop respective defense responses, ML can be leveraged in various domains within Cyber Security to enhance security processes, and make it easier for security analysts to quickly identify, prioritise, deal with and remediate new attacks.
Automating Tasks
A great benefit of ML in cyber security is its capacity to automate repetitive and time-consuming tasks, such as triaging intelligence, malware analysis, network log analysis and vulnerability assessments. By incorporating ML into the security workflow, organisations can accomplish tasks faster, and act on and remediate threats at a rate that would not be possible with manual human capability alone. Automating repetitive processes means that clients can up or down scale easily, without changing the manpower needed, thus reducing costs in the process.
The method of automating practices via ML is sometimes referred to as AutoML. AutoML signifies when repetitive tasks involved in development are automated to specifically aid the productivity of the analysts, data scientists and developers.
Threat Detection and Classification
Machine learning algorithms are used in applications to detect and respond to attacks. This can be achieved by analysing big data sets of security events and identifying patterns of malicious activities. ML works so that when similar events are detected, they are automatically dealt with by the trained ML model.
For instance, the dataset to feed a machine learning model can be created by using Indicators of Compromise (IOCs). These can help monitor, identify, and respond to threats in real time. ML classification algorithms can be used using IOC data sets to classify the behaviour of malwares.
Traditional phishing detection techniques alone lacks the speed and accuracy to detect and differentiate between harmless and malicious URLs. Latest ML algorithm predictive URL classification models can identify patterns that reveal malicious emails. To do this, the models are trained on features such as email headers, body-data, punctuation patterns, and more to classify and differentiate the malicious from the harmless.
WebShell
WebShell is a piece of code that is maliciously loaded into a website to provide access to make modifications on the web root directory of the server. This allows attackers to gain access of the database. Which, in turn, enables the bad actor to collect personal information. By using ML, a normal shopping cart behaviour can be detected, and the model can be trained to differentiate between normal and malicious behaviour.
The same goes for User Behaviour Analytics (UBA), which forms a supplementary layer to standard security measures, to provide complete visibility, detect account compromises, and mitigate and detect malicious or anomalous insider activity. By using ML algorithms, patterns of user behaviour are categorised, to understand what constitutes normal behaviour, and to detect abnormal activity. If an unusual action is made on a device on a given network, such as an employee login late at night, inconsistent remote access, or an unusually high number of downloads, the action and user is given a risk score based on their activity, patterns and time.
Network Risk Scoring
Use of quantitative measures to assign risk scores to sections of networks, help organisations to prioritise resources. ML can be used to analyze previous cyber-attack datasets and determine which areas of networks were mostly involved in particular attacks. This score can help quantify the likelihood, and impact of an attack, with respect to a given network area. Thus, helping organisations to reduce the risk of being victimized by further attacks.
When you are doing business profiling, you have to decipher what area, if compromised, is going to destroy your business. It could be a Customer Relationship Management (CRM) system, your accounting system, or your sales system. It’s about knowing, within your specific business environment, what area is most vulnerable. Say, for instance, HR goes down, this may have a low risk score within your company. But if your oil trading platform goes down, that could bring down your entire business. Every company has a different way of doing security. And once you understand the specifics of an organisation, you know what to really protect. And if there is a hack, you know what to prioritise.
The Future of ML
ML is a powerful tool. There is no denying that. But it is no silver bullet. It is important to remember that, while technology is developing, and advancements in AI and ML are evolving at a significant rate, technology is only as good, or as bad, as the minds of the analysts controlling and using it.
There will always be bad actors developing their skills and technology to find and exploit weaknesses. Which is why it is crucial to combine the best technology and processes with industry experts, to be able to detect and respond to cyber threats accurately and rapidly.
To learn more about the use of Machine Learning (ML) and Artificial Intelligence (AI) within security analytics, and to debunk some of the common misconceptions and myths surrounding what constitutes AI and ML, view our video on ‘Using Machine Learning & AI to Hunt Risk in the Real World’ here.
With virtually all companies looking at AI, what are some of the key risks they need to consider before implementation?
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Today virtually all companies are forced to innovate and many are excited about AI. Yet since implementation cuts across organisational boundaries, shifting to an AI-driven strategy requires new thinking about managing risks, both internally and externally. This blog will cover “the seven sins of enterprise AI strategies”, which are governance issues at the board and executive levels that block companies from moving ahead with AI. by By Jeremy Barnes, Element AI
1- Disowning the AI strategy
This is probably the most important sin. In this case, a CEO and board will say that AI is a priority, but delegate it to a different department or an innovation lab. However, success is not based on whether or not a company uses an innovation lab—it’s whether they are truly invested in it. The bottom line is that the CEO and board need to actively lead an AI strategy.
2- Ignoring the unknowns
This happens when companies say they believe in AI, but don’t reach a level of proficiency where it’s possible to identify, characterise and model the threats that emerge with new advances. Even if it is decided not to go all-in on AI innovation, it’s still important that there is a hypothesis for how to address AI within a company and an early warning system so the decision can be re-evaluated early enough to act. Being a fast follower requires as much organizational preparation and lead time as leadership.
3- Not enabling the culture
The ability to implement AI is about an experimentation mindset. That and an openness to failure need to be adopted across the company. Organisations need to keep in mind that AI doesn’t respect organisational boundaries. Most companies want high-impact, low-risk solutions that could simply lead to optimising, rather than advancing new value streams. It is hard to accept increased risk in exchange for impact but it will come as part of the continuous cultural enablement of an experimental mindset.
4- Starting with the solution
This is the most common sin. It’s important to be able to understand the specific problems you’re trying to solve, because AI is unlikely to be a solution for all of them, and especially not blindly implementing a horizontal AI platform. Have the conversation at board level to ensure that an overarching AI strategy, and not simply quick-fix solutions, is the priority.
5- Lose risk, keep reward
As mentioned in the third sin, it is natural for companies to want to implement AI without any risk. But there is no reward without risk. A vendor motivated to decrease risk will also decrease innovation and ultimately impact by making successes small and failures non-existent. AI creates differentiation only for companies that are willing to learn from both their successes and their failures. A company that doesn’t effectively balance risk in AI will ultimately increase its risk of disruption.
6- Vintage accounting
Attempting to fit AI into traditional financial governance structures causes problems. It doesn’t fit nicely into budget categories and it’s hard to value the output. The link between what you put in and what you get out can be less tangible or predictable, which often makes it harder to square with existing plans or structures. Model the rate of return on AI activities and all data-related activities. This demands that these activities affect profit (not just loss) and assets (not just liabilities).
7- Treating data as a commodity
The final sin concerns data and its treatment as a commodity. Data is fundamental to AI. If data is poorly handled, it can lead to negative impacts on decision-making. Data should be treated as an asset. The stronger, deeper and more accurate the dataset, the better models that you can train and more intelligent insights you can generate. But, at the same time, when personally identifiable information is stored about customers, it can be stolen, risking heavy penalties in some jurisdictions. You need to build towards data from a use case rather than invest blindly in data centralisation projects. So, now you know what not to do. Here are some of the simple things that you can do to move ahead. First, talk to your board about how long it will take to become an AI innovator, modelling it out, rather than simply discussing it conceptually.
Second, prepare for change and put in place monitoring. AI shifts all the time, so you’ll want to regularly check in to adjust and pivot your strategy. It’s important to develop a basic skill set so you can redo planning exercises with your board. Third, model out risks in both action and inaction. But don’t model them in a traditional approach, which is to push risk down to different business units and then compensate those units for reducing risk rather than managing trade-offs. Instead, view those trade-offs in terms of risks and rewards, and start to think about how you are accounting for the assets and liabilities of AI. Ultimately, you want to start to model what is the actual rate of return for all these activities that you are doing. Then benchmark it against what you see in other companies from across the industry, and that will give you a good picture of the current situation and where to go.
With a rise in immersive training and workouts on demand, connectedness matter most…
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In what is almost a redundant statement, due to the very obvious nature of it, technology has taken over every facet of the modern world. From the way we eat (ordering a takeaway or watching a YouTube cooking tutorial) to the way we purchase the very clothes on our backs (via H&M, Zalando etc.), technology is right there as an enabler. In fact, in 2020, global retail sales are projected to amount to around $26.tn dollars, with an estimated 1.9bn people worldwide purchasing goods (including food) or services online.
Go back just one year to 2019, and e-retail sales surpassed $3.5tn worldwide. The fact of the matter is, technology has made this possible and it will continue to drive these numbers to almost unimaginable levels. The really fascinating thing about this however, particularly in a year beset by lockdowns and restricted movement outdoors, is how many of these transactions were made from home and how much of that $3.5tn has been spent in the palm of our hands?
In all the talk of global markets and industry being disrupted and revolutionised by technology we often focus on those trillion dollar ones because they are the traditional ‘big hitter’ industries. Over the past decade however, one industry sector has seen incredible growth all over the world and technology (to no surprise) has seen that growth take on a whole new level. In 2019, the global fitness and health club industry exceeded $96bn. There are more than 201,000 health and fitness clubs worldwide and more than 174mn global members. It’s clear to see; the health and fitness space is not to be sniffed at. One of the biggest, if not the biggest, ways in which technology has redefined the fitness industry is through on-demand services. Like everything else in our lives, we want it and we want it now. But for Jean-Michel Fournier, CEO of Les Mills Media, it’s important to remember what people want with their fitness experiences before getting lost on working out how to provide that to them through technology.
“We are more and more connected,” he says from his home gym in San Francisco. “Connection in fitness is very important. Being able to be part of a community and believing in something bigger than you is way more motivating than exercising by yourself and not being able to share what you achieve or what you’re doing. It’s about trying to connect with people who have the same objective, or same experience or someone who can advise you. So that community is very important and with technology now you’re able to be engaged and supported by your community, anywhere, anytime.”
That sense of a shared community, through health and fitness, defines the very core of Les Mills. Headquartered in Auckland, New Zealand, Les Mills is on a mission to create a fitter planet not by making people work out but by helping people fall in love with fitness so that they want to work out.
Les Mills provides workouts that are licensed by 19,500 partners in 100 countries around the world and has a tribe of 135,000 certified instructors to deliver the likes of BODYPUMP, BODYCOMBAT and GRIT workouts to millions of members. With the future of fitness merging between physical and digital, the company has led the charge in delivering immersive training and workouts on demand. This is where Fournier, a fitness fanatic and a student of Silicon Valley, looks to continuously drive engagement with members and it starts with that sense of connectedness and love affair with fitness.
“Actually, I don’t really care about technology. Technology for me is an enabler. Technology’s here to help improve the life of our community,” he laughs. “It’s really my very first company where I’ve seen how we help people to live a better life. To feel better when they wake up in the morning, and do the exercise and fall in love with our classes, where people are doing body pump and body combat on a daily basis and they share their pictures, their achievements through the community. It’s so exciting when I see that and that’s what feeds me, honestly.”
The health and fitness space is notoriously costly and often seen as a luxury, pricing people out entirely. So surely technology and on demand services would simply follow suit? Fournier recognises this, recalling the unfortunate passing of his father over the past few years and how that had made him rethink the role of technology in fitness. “Before my father passed away, he told me that he wished he could go back and be in shape and feel proud of his physical fitness,” he says. “That really impacted me. It made me ask one question; how can we help people get better access to fitness services. The answer is through technology.”
Fournier believes that technology is the key to democratising fitness services, making it truly available to everyone. Les Mills offers all of its fitness programs and workouts, together with advice and FAQs, through a simple and easy to use mobile and tablet app. This app will capture all kinds of data from its members and their activity and feed it back to them in a way that is personalised to each user. While we are competitive by our very nature and we do crave the shared community that Fournier speaks of, we all have our own personal goals and our own achievements that we strive for. But how can an app provide personalised experiences for well over a million users all over the world? The answer is, again, technology. Specifically Artificial Intelligence and Machine Learning.
“The technology allows us to think about things that are perhaps within our subconscious that impact our exercise,” says Fournier. “When are we most motivated to exercise? How does our sleeping habits impact our performance? At what point during a day am I going to get the best results? These are all things that AI and Machine Learning will allow us to think about and understand better. It’s really opening everyone’s eyes and making that process of falling in love with fitness that little bit more seamless.”
Machine Learning, while not a new concept, is still in its infancy in terms of global implementation. Fournier believes that we are “at the beginning of a tsunami” when it comes to Machine Learning and that when it does become a norm, personalisation will come naturally. He compares the concept of personalisation in fitness to that of other streaming on-demand services like Netflix. Personalisation in those platforms can only stretch as far as presenting films that you like based on your activity, or personal lists you create. In fitness, the variables are so sparse and unique to each individual that a “one service to many” approach simply will not work.
“Technology in the fitness spaces creates a sense of accountability with both the community and the coaches” says Fournier. “You are starting to see more and more coaching platforms out there and we are doing some experimentation with this at Les Mills, where people have a coach in their pocket. Now they are connected with the coach and the coach is going to communicate directly and check on your performance. They look at the data and see that you’ve done the workout and congratulate you for it. Then you feel good about it.”
Fournier admits that it also works both ways, thanks to those extremely different variables; “Say you haven’t done it, the coach can ask you why. It’s because you’re tired, or you’ve hurt yourself. The coach can then work with you to adapt the workout. So that’s going to create this accountability and technology is going to help to create this connection between your data and your community. There’s going to be this golden triangle of information here.”
The benefits of technology are clear to see; the personalisation of the user experience comes directly from it, so Les Mills should just go ahead and throw all of its eggs into the technology basket right? Wrong. Les Mills, since the very beginning back in 1968, is a business built on the foundations of family and community. Right from the top with Phillip Mills himself, to his wife Jackie and children Diana and Les Mills Jr, there is a culture that looks at fitness services and exercises and marries that with technology that can spread that culture all over the world. The technology will never drive the business, the community will. This in itself brings an interesting challenge to the table, yes Les Mills wants to serve the world and help each and every one of us, but it’s also a business and a business will also be driven by revenue and bottom line results through innovation. “So how do you innovate? You need to be sure you have a good understanding of the mission,” says Fournier. “At the end of the day if there are people out there fleeting the next best tech thing in fitness and they’re being more successful, good for them. At the end of the day the mission for Les Mills is not to conquer the world, or to be a dominant company. At the end of the day, we are here to really help people.”
Les Mills is driven by people, for people. That is abundantly clear. Personalisation is one challenge that the company faces and for the most part succeeds in, but what about the actual user experience? How easy is it for someone to log in to the CMS, search through the copious amounts of workouts and then stream those workouts in a truly seamless experience? Les Mills, like many businesses right now, works to provide an omnichannel experience for users so they can indeed access it anytime and anywhere. But omnichannel is a word that has fallen into the trappings of many other keywords in technology right now. How does the company look to move away from simply following a trend and offer a true omnichannel experience?
“It’s hard,” laughs Fournier. “Not everybody has an internet connection at 100 or 200 megabytes. Not everyone has the same bandwidth and capabilities to stream. These days there are a number of successful platforms out in the world, which makes it easier. Having streaming capabilities and adding a strong architecture while working with the best CMS platform out there is critical. Around four years ago, coinciding with when I came into the business, we laid down a very strong and robust platform that can support millions of recurrences and millions of subscribers, to be sure we can provide the quality that our users need regardless of their situation.”
The lines between health and fitness and digital are increasingly blurring and reaching a point as to where we may not be able to think about exercise and fitness without a livestream, at home experience. As with any technological shift, there is also a generational shift running alongside it. It isn’t simply a case of older generations of gym users and fitness professionals suddenly pivoting to digital or being alienated as the world around them becomes an increasingly digital one. As we have seen in many other industries, it is not that black and white and it comes as no surprise that this is something that Les Mills understands more than most.
“If someone wants to enjoy our content on an app, they can. If they want to enjoy our content in a live streaming class, they can. If they want to enjoy our content in a live class with a real instructor they can do it as well,” says Fournier. “At the end of the day we are a content provider. What we do is create amazing fitness choreography linked to music and we do so in a way that is truly accessible to all and for all.”
In 2020, the world was forced to stand still as it became gripped by the coronavirus pandemic. With lockdowns and restrictions put in place to protect the lives of people the world over, this closed a lot of doors for the likes of restaurants, retail stores and yes; gyms and fitness centres. One could be forgiven for thinking that Les Mills, pioneers in the streaming on demand space for fitness, were well prepared for this and suffered minimal impact from this. “Our customers are those fitness clubs and the community centres that provide Les Mills classes to their communities,” reflects Fournier. “So we were hurt there. Everybody moved to digital, which was great and thanks to the great work we did in previous years in building a robust platform we were able to absorb the millions of recurrences into our platform and keep the right level of stability.”
For Les Mills, it has always been about the community and when that community is forced to stay indoors and to stay away from the physical connectedness, the focus changes slightly. Connected community has always been a cornerstone of Les Mills, but in these difficult times the company changed tact and became much more connected to its community than ever before. “I’m very proud of the Les Mills team because we really focused on what was important. The focus was really on responding to the customer needs,” beams Fournier.
“People wanted more connection, so we generated some live streaming classes. They wanted to talk with their instructors live, so we did a lot of live Q&As that were pretty amazing.”
Fournier points to one example where the Program Director, Glen Ostergaard, presented a live streaming class to over 25,000 people worldwide. Just a few short years ago, this would have been unprecedented even for Les Mills and yet here it was, leading one of the largest live streaming fitness classes in the world and exceeding all expectations.
Elsewhere, in the absence of being present in classes and under the watchful eye of a trainer, Les Mills needed to think about how it could leverage the 140,000+ fitness instructors around the world and enable them to connect with the people. “These people aren’t just the faces you see on our apps and workouts, they are the community who run the classes in centres and in gyms,” says Fournier. “They understand fitness, they understand health and wellness and they are a part of the whole community so we started to connect and to create a networking effect, connecting the expert to the community that has a need. It has been quite amazing to see this level of engagement and communication with instructors and seeing how they can exercise better.”
Right, the future and what it will look like for many remains uncertain. The last year has taught us to rethink our perceptions of how industries can and should operate and has forced a lot of businesses to rethink their operations. In some cases, this has created great opportunities and change for good. For fitness and exercise, which as we know was already going through it’s own evolution prior to 2020, this evolution and convergence of fitness and technology will continue at an incredible pace. As we talk of new norms, what does that actually mean for Les Mills? Can it ever go back to what it was before? “Some people enjoy exercising from home. Some people are enjoying working out more outdoors and hiking or going to the park and doing their exercise routines there. And you will always have people missing their fitness club,” says Fournier. “Human nature will always go back to convenience and people will want to go back to the convenience of a fitness club or a class.”
“I firmly believe that club operators need to evolve and they need to focus on their members.There are an increasing amount of members who are outside the club as we’ve discussed. You see the evolution right now, more and more are embracing digital, creating some challenges and motivating people to exercise outside of the club. It’s a pretty big shift and one that’s going to continue, so we have to continue to look at our offering and how we can continue to serve our community in the best way possible.”
Our cover story this month is a revealing feature with Microsoft’s Sangya Singh. Plus, we have exclusive executive insights from Moneta, Les Mills and Fiserv, as well as the Top 5 Financial Security Challenges of 2020 and in-depth guide to AI strategies.
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This month’s cover exclusive features Sangya Singh, Chief Experience Officer and Director of Product Management, Dynamics 365 Customer Insights at Microsoft who takes us ‘behind the scenes’ as she reveals how Microsoft achieves design-thinking-driven digital transformation…
“The need for transformation is greater now than ever before. We are facing problems around the world that can be solved only through innovation: whether it is unaffordable and unavailable health care or energy usage that outpaces what we can support, to education systems that fail many students, to companies and organisations whose traditional setup are being disrupted by new emergent technologies or demographic change or global pandemic like COVID-19. All these problems have people at their heart. They require human-centred, creative, iterative and practical approaches to find the best ideas and solutions that will democratise the benefits of technology and bring in equity to all.
Design thinking is just such an approach to innovation. It requires a different type of leadership style and culture in place; an effective innovation culture is one where we are willing to set aside our initial conception or understanding of what the problem is…”
Plus! We have exclusive executive insights from Moneta, Les Mills and Fiserv, as well as the Top 5 Financial Security Challenges of 2020 and in-depth guide to AI strategies.
Leading retailers across the EU and US are running outdated applications, leaving them vulnerable to cyber attacks….
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In another episode of The Digital Insight Bitesize, we take a look at cybersecurity.
With a recent report indicating that leading retailers across the EU and US are running outdated applications, leaving them vulnerable to cyber attacks, we ask:
Can you be complacent when it comes to your approach to cyber security?
Traditionally such matters would be placed on the desk of the CIO and the IT teams, but Is it their responsibility to focus on cyber security? There’s certainly an argument that the wider organization could and should be more involved.
In a year defined by crisis, how has the COVID19 pandemic impacted the cybersecurity conversation moving forward?
Answering these questions for us today is Stephan Kornakowski of Output24, a leading cyber assessment company focused on enabling its customers to achieve maximum value from their evolving technology investments…
By failing to involve more general staff, company leaders hinder DX progress
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While businesses are doubling down on digital transformation (DX), new research from Futurum Research found that organisational leaders are leaving many of their employees behind in the process. The study revealed that 94% of all employees want to be more involved in DX, and almost half (44%) of the general staff say they simply don’t know how to help. This not only disenfranchises some employees, but it can also slow the pace of DX success.
The global study, sponsored by Pegasystems (NASDAQ: PEGA), surveyed executives, technology leaders, and general employees from over 500 enterprises in North America and Europe on the role company culture plays in driving DX success.
As company leaders accelerate the pace of DX in the wake of the pandemic, the research revealed many employees are eager to be part of the solution. But despite this enthusiasm, only 10% of general staff strongly agree they know how to contribute to their company’s digital transformation efforts. Interestingly, there is also still confusion at the top: even 14% of CEOs report they don’t know how to get involved.
The research also uncovered three additional insights on how leaders should infuse DX into the fabric of their business:
Barriers to success must be addressed holistically: A majority of business decision makers (68%) believe improving customer experience is the most important DX driver, followed closely by automating existing processes (67%) and improving or updating processes (65%). While most agree on the ultimate goals, decision makers face a wider variety of roadblocks to reaching them, namely a lack of adequate skills (42%), partnerships (36%), and budget (36%). These holistic operational issues must be addressed – starting with training or hiring for these skills – to ensure DX success at scale.
Effective DX leadership drives top-down results: Who usually leads the DX charge? Only 18% of respondents believe it’s the CEO compared to 47% who identify the CTO or CIO. But when employees cite the CEO as the DX leader, employees report a more positive perception of DX, which can be helpful in building a stronger DX culture. For example, 67% of respondents from organizations with CEO-led DX expect to be ‘very effective’ in technology leadership compared to only 51% in CIO-lead organizations and 34% when the CTO leads.
Digital transformation is a journey on which no one should be left behind: Leaders need to find ways to bring all employees on the DX journey so they feel vested in the outcome – even in the smallest of ways. Respondents cite helping to train others on new technology (50%), being open minded about using new tools (40%), and voicing positivity about DX (35%) as the top ways they believe they can help – which are all relatively achievable. Broader employee participation at any level helps the DX culture permeate through an organization so businesses can ultimately better serve their customers.
Identifying opportunities across people, processes and technology has created significant operational efficiency improvements around complex claims handling…
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Tesco Underwriting has partnered with Netcall, a leading provider of low-code and customer engagement solutions, to significantly enhance its complex claims handling process. Tesco Underwriting, who underwrite Tesco Bank-branded car and home insurance policies and provide claims services to customers, worked with Netcall to evaluate its ways of working, processes and technology for complex claims. Tesco Underwriting then identified and implemented operational efficiencies which led to an improvement and streamlining of customer and colleague journeys around complex claims, and a significant boost to its customer Net Promoter Score (NPS).
Tesco Underwriting wanted to manage complex claims efficiently to give their colleagues and customers the best possible experience. This meant focussing on the improvement of internal processes, including the effective management of workflows, to ensure claims handlers could accurately identify the priority status of work. Tesco Underwriting needed a system that could provide full visibility of all claims, and the handlers assigned to them, as well as displaying the order of priority and providing the ability to adjust as required.
Tesco Underwriting had three of their Continuous Improvement Team trained on Netcall’s Liberty Create low-code platform in just three days. The members of that team then went on to develop a highly customisable application that helps manage internal claim workflows and has significantly improved efficiency. The company is now able to provide its handlers with a visual tool that automatically prioritises each claim – whilst also breaking down individual work queues. The application development process took under three weeks, with full deployment – including the training period – completed in three months. It can take the same period of time for a company to gather requirements for the development of an internal system, demonstrating the efficiency of the low-code platform. By using Create, Tesco Underwriting was able to adopt the desired, agile approach and achieved an even faster time to delivery.
Being able to build a prototype during the training stage and within such a short timeframe enabled Tesco Underwriting to move quickly and show quick time-to-value to stakeholders. What’s more, since implementation, the company has witnessed a significant increase in claim handling efficiency – with the number of claims processed per hour increasing by 57% due to the implementation of the new low-code based application. Using Liberty Create, the company has met its own goals for claims processing within the first six months – and the new system has also contributed to a substantial seven-percentage-point rise in Tesco Underwriting’s customer NPS.
“The speed and agility that the low-code platform has given us has meant we’ve been able to build, iterate and change processes really quickly and effectively. Without the project, I don’t think we’d have been able to achieve the NPS and the efficiency benefits that we have derived – the speed and agility has been fantastic,” commented Neil Arrowsmith, Head of Operational Excellence, Tesco Underwriting.
“We’re thrilled that Netcall has been able to assist Tesco Underwriting in its venture to optimise its business processes in such a short time frame – six times faster than using traditional development tools and methods. The fact that the company has already seen such an increase in efficiency is fantastic and we’re excited to see what further benefits to customer experience Tesco Underwriting uncovers with our platform in the future,” commented Mark Holmes, Chief Sales Officer, Netcall.
England’s first smartphone-enabled vaccination status feature will assist economic recovery and encourage vaccine uptake…
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myGP – the UK’s largest independent GP booking and healthcare management app that connects patients with primary care – has announced its intention to provide the people in England with a simple, clear means of communicating their verified vaccination status, via their Smartphone.
The new vaccination status feature will display, within the patient profile page of the myGP app, whether or not a patient is sufficiently protected from COVID-19; illustrated via a few personal details and a simple green tick, which will appear 21 days following the final vaccine dose, when a patient is considered protected from the virus. This ‘tick’ will act as a clinically assured means of proving one’s vaccination status, displayed in real-time, generated directly from a patient’s medical record.
myGP – home to the myGP TICKet feature – is developed by Hammersmith-based iPLATO Healthcare. Currently available to patients at 97 percent of England’s GP practices, myGP has spent years working alongside the NHS to gain NHS accreditation. As a result, the app already enables around two million patients in England to view their medical records, request repeat prescriptions, request GP appointments, and access other complementary healthcare services. More than 200,000 patients in England have accessed their medical records via the app in just the last two months.
Economic recovery, at capacity
Currently planned for release in February 2021, and dependent upon availability of the clinical data, the myGP TICKet could allow businesses whose viability depends upon operating at capacity – such as the arts and hospitality sectors – the ability to open either full or part-time to vaccinated individuals, without the need to observe strict social distancing rules. In addition, the technology will reduce the administrative burden on GPs, who will likely be inundated with requests for verification of vaccination status as people begin to return to everyday life around the country.
Since the start of the pandemic, myGP has regularly undertaken patient research, to gauge feelings and intentions regarding their health, access to primary care, and their intentions regarding the Covid-19 vaccine. Last week, upon learning that a vaccine had been approved, myGP asked 2,000 adults if they intend to have the new vaccine, of which 31 percent said no. However, of this group, 23 percent said they could be swayed to have the vaccine if it meant they could attend live events and other activities without strict social distancing measures in place.
Tobias Alpsten, the innovator behind myGP TICKet and Founder and CEO of iPLATO Healthcare and myGP comments on why it could be a game-changer for the UK:
“Not only does our research tell us that the public would respond positively to this kind of incentive; we believe that our solution can provide an economic lifeline to industries who have been crippled by the pandemic.
Further, this innovation will absolutely relieve administrative burden on GPs by simplifying an individual’s access to his or her own vaccination status. The myGP TICKet means that patients will not have to contact their GPs, get certificates printed, apply for vaccination passports, or other long-winded solutions. Simply download the myGP app, register, and it’s done.”
Katie Coull, Artistic Director of Charity ‘Artists for Essential Workers’ (AFEW), comments on why the myGP TICKet could be game-changing for the arts:
“Being unable to operate at capacity has been absolutely crippling for artists and arts venues alike. The ability to fill a venue to capacity, even just part of the time, would make a world of difference to the organisations who provide Britain’s cultural lifeblood. We are fully in support of anything that can open our doors earlier than planned.”
James Balfour, CEO of 1Rebel, one of the UK’s leading fitness brands, explains why the myGP TICKet will help bring the country’s fitness industry back:
“The fitness industry has been faced with unique struggles during the pandemic, due to social distancing requirements. Exercise has been a buzz word during the pandemic, but gyms have been one of the casualties of the lockdowns and tier-systems, despite low transmission rates, and the well-known physical and the mental health benefits it brings.
“Any solution that will help group exercise in particular get back to business safely, will be very welcome by 1Rebel. We can’t wait to get back to helping boost the nation’s health; including having a positive impact on England’s economy.”
Register here to be notified when the myGP TICKet technology is live: www.myGP.com/ticket
Technology is key to all businesses in one way or another, so it’s important to adapt a digital twist to our everyday operations…
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After COVID-19 forced the UK to stay at home, we have had no choice but to make some changes to our everyday lives. A lot of us have used our time wisely and come up with some quirky ways to continue life as somewhat normal – just with a virtual take on things. Being blessed with the age of digitalisation, our digital devices do just about everything for us at the click of a button.
The pandemic has seen a digital transformation in everything from online weddings to an an e-commerce takeover. According to a recent Ofcom report, the average daily screen time for TV and online video content increased to six hours 25 minutes per day since April 2020. This is up by almost a third from the year prior.
In this article, we will discuss how COVID-19 has forced the world to digital in recent months.
Virtual vows: The rise of online weddings
After recent announcements reduced the number of guests at wedding ceremonies to 15 people, the big day that many couples have dreamt of might not be as big as they expected. To overcome this issue of crossing names off the guest lists, many couples have favoured an online wedding ceremony instead. So much so, Google search data found that the term ‘virtual marriage’ experienced a 21,900% increase between February 2020 and July 2020 – proving that virtual vows have been the go-to for many couples recently.
Not only that, but for the search term ‘Zoom wedding’ has also experienced an increase of 3,800% between February and July this year. By using video call platforms such as Zoom, the new measures put in place that limit the number of physical attendees is avoided. Although saying your vows over a screen may not be initially what you had in mind, nothing should get in the way of celebrating your big day.
Technological try-ons
As basic luxuries such as being able to go to a store and try on clothing or jewellery have been stopped, many have solved this problem with the help of technology. Since searches for the term ‘virtual engagement ring try on’ experienced an increase of 433% between March and August, jewellery crafter Angelic Diamonds has skilfully implemented a virtual ring try-on service. This helps their customers see how the ring will look before making a purchase.
FaceTime fitness
Since attending our favourite sport and fitness classes in person has been put on hold, virtual classes have become the next best thing. Fitness company Les Mills International experienced a 900% increase in virtual sign-ups over the course of lockdown as more and more of us rely on home workouts to keep fit.
Other than virtual classes, many have taken this a step further and brought the gym to them. In recent news, high-end department store John Lewis & Partners has revealed that sales of fitness machines had increased by 369% during lockdown. Sales of yoga equipment also experienced a staggering increase of 267%.
Digital driving days
Who’s to say you need a car to drive? Since driving lessons were placed on hold, many turned to virtual driving lessons during lockdown. Driver training simulator company Driver Interactive provides customers with a realistic driving experience that allows them to practice driving in hazardous situations from the comfort of their home.
The thriving e-commerce market
As technology advances throughout the years, the e-commerce market continues to thrive. This has been even more apparent during lockdown. Since the start of the first UK lockdown in March, e-commerce market sales increased by a staggering 161%, adding a hefty £5.3 billion extra to the market. Not only that, but more than 85,000 businesses have joined the online marketplace over recent months.
Although industries have financially suffered as a result of restrictions, many have now embraced the digital world as a result. From clothing stores opening online shops to pharmacies offering virtual prescriptions, almost every industry has found a way to continue making profits through these difficult times.
For the likes of Amazon, however, they have seen sales soar over recent months, achieving a 40% increase in sales to $88.9 billion in the second quarter of 2020. Being at an advantage when it comes to already being an entirely e-commerce store that sells everything from clothes to new car parts, there is something that all businesses can learn from Jeff Bezos’ business operations.
We have seen businesses across all industries get creative with digital in 2020. Technology plays advocate to all businesses in one way or another during these difficult times, so it’s important to adapt a digital twist to our everyday operations.
Lack of confidence in long-term ability to implement digital processes is a growing concern…
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ServiceNow research highlights opportunities for organisations to boost productivity as today’s new pace of working creates the perfect environment for innovation
Legacy technology is causing UK businesses additional concerns during lockdown, according to new research by ServiceNow (NYSE: NOW), the leading digital workflow company that makes work, work better for people. Prior to the announcement of a second national lockdown, both C-Level leaders and employees had low confidence that they would be able to adapt to another major business disruption.
The Work Survey gathered opinions from 900 C-suite leaders and 8,100 employees across 11 countries, including 100 C-level executives and 1,000 office workers in the UK. It found that, despite 96% of UK leaders and 87% of UK employees stating that their company transitioned to new ways of working faster than they thought possible during the initial lockdown, many departments would not be able to implement new digital processes within a month in the event of another major disruption, such as the one we are facing now. Only a minority of UK leaders believe that customer service (37%), finance (38%) and IT (39%) could introduce new workflows within 30 days.
This challenge is exacerbated because most businesses still have a digital disadvantage, with 98% of UK C-level leaders admitting to still using offline processes. These include:
Offline workflows such as document approvals (59%)
Security incident reports (41%)
Performance reviews (39%)
Leave requests and processing (37%)
“Organisations innovated rapidly, and initial sprints enabled them to react to the immediate COVID-19 challenges,” said Chris Pope, ServiceNow’s VP Innovation. “Some decisions made were knee-jerk and rapid, but at what cost? There may be good short-term gains, but are they ‘match fit’ for our new ways of working? For organisations still struggling to integrate and implement a fully integrated workflow system, the future of work will not arrive, and soon they’ll fall behind.”
Worker safety is paramount
The survey also showed there are doubts when it comes to workplace safety from both UK leaders and UK employees.
Almost a third (31%) of UK leaders and 51% of UK employees are concerned their company will prioritise business continuity over safety. In addition, over a quarter (26%) of UK leaders and 40% of UK employees agree that their company will not take all the necessary steps to keep employees safe when returning to work in the office.
“The critical challenge for UK organisations will be balancing the immediate need for business continuity with the personal needs of their employees,” said Pope. “2020 has been a difficult year for a lot of people. Many have seen restrictions over the past several months, which look set to continue through the winter. Businesses need to lead with compassion and combine empathy with meaningful action to help their employees navigate the months to come. In this distributed working environment, how organisations handle the moments that matter, from when a hire joins to when they leave, not only determines talent retention but will also contribute to overall business continuity and success.”
Business leaders split on return to office preferences
UK business leaders are also divided on how to keep their company most productive. While 49% want to maintain new ways of operating once the crisis subsides, 51% are keen to return to business as closely as it was prior to COVID-19, indicating a divide in approach.
Despite 57% of UK employees feeling they now have a better work-life balance, both UK leaders (99%) and UK employees (80%) have concerns about how remote work will impact their business moving forward.
The research indicates that leaders are prioritising speed of business while staff care about the human side of working. In terms of the largest challenges posed by remote work, UK leaders are most concerned about extended timelines for new releases or innovations (48%). Conversely, UK employees see reduced collaboration (48%) as their largest worry.
56% of organizations suffered a ransomware attack in the last 12 months costing $1.1M per hack
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According to data acquired by the Atlas VPN team, 56% of organizations worldwide experienced at least one ransomware attack in the past 12 months, with an average ransom costing victims $1.1 million.
The numbers are based on the Global Security Attitude Survey conducted by CrowdStrike, where 2,200 senior IT decision-makers and security professionals were interviewed on questions concerning cybersecurity in their workplace in the last 12 months. The survey took place between August and September of 2020.
Ransomware is malicious software that infects victims’ systems, devices, or files and blocks access to them unless a ransom is paid. A total of six in ten organizations worldwide faced at least one such attack over the past year.
Out of all the countries featured in the survey, businesses in India had the most ransomware events in the last 12 months. A whopping 74% of respondents from India said their organizations had suffered from ransomware attacks in the past year.
In total, 38% of company representatives said their organization faced only one ransomware attack, while 36% reported they endured more than one such attack in that period.
Next up is Australia, where 67% of the respondents reported that their organization had suffered ransomware threats in the last 12 months. While in France, which occupies the third spot in the list, 60% of businesses faced ransomware attacks during the same period.
Rounding out the top five list are Germany and the United States. According to the survey, 59% of organizations in Germany had ransomware events, followed by the United States, where 58% of organizations experienced ransomware attacks in the period of the past 12 months.
Companies in the United Kingdom endured the least amount of ransomware threats. According to the survey, 39% of respondents said their organization was targeted by a ransomware attack in the past 12 months.
Asia Pacific companies pay the biggest ransom
Once attacked, organizations do not always pay ransom to cybercriminals. In fact, only 27% of respondents confirmed their organizations paid the cybercriminals as a result of a ransomware attack, with the average payment being $1.1 million per hack.
Organizations in the Asia Pacific paid most for ransomware attacks. The average ransom payment in this region in the last 12 months was $1.18 million.
Companies in Europe, the Middle East, and Africa regions do not fall far behind with ransomware payments. On average, a single ransom payment in the region cost victims $1.06 million.
Finally, businesses in the United States paid the least per ransom to cyber criminals compared to other regions featured in the survey. An average ransom payment in the United States was $0.99 million.
Tips on protecting organizations from ransomware attacks
With ransomware attacks posing an increasing threat to organizations around the world, it is essential to take all the possible precautions to minimize the risk of falling victim to cybercriminals. Here are some key things to remember:
Keep your software up to date – Regularly update the software you use. The updated software has the latest security patches, making it harder for cybercriminals to exploit system vulnerabilities. Also, do not forget to conduct regular software scans to ensure it operates efficiently.
Minimize administrative privileges – Restrict employees’ ability to install and run software applications on work devices outside of the responsible department.
Back up your data – Keep your data backed offline. This way, even if you experience a ransomware attack, you will not need to pay cybercriminals to get your valuable data back.
Educate employees – The majority of data breaches happen due to human error. Test your employees’ security awareness with phishing tests. This will help educate them on how cyberattacks may look like and keep them vigilant at all times.
If your organization has fallen victim to a ransomware attack, it is generally not advised to pay ransom to cybercriminals. Paying a ransom does not guarantee you will get your data back and also encourages the criminal behavior.
Instead, organizations should prepare an incident response plan, planning what actions need to be taken should the unfortunate event happen. While no organization is infallible to cyberattacks, having a response plan can mean you will come out of the situation with minimum damage.
ServiceNow research highlights opportunities for organisations to boost productivity as today’s new pace of working creates the perfect environment for innovation
The Work Survey gathered opinions from 900 C-suite leaders and 8,100 employees across 11 countries, including 100 C-level executives and 1,000 office workers in the UK. It found that, despite 96% of UK leaders and 87% of UK employees stating that their company transitioned to new ways of working faster than they thought possible during the initial lockdown, many departments would not be able to implement new digital processes within a month in the event of another major disruption, such as the one we are facing now. Only a minority of UK leaders believe that customer service (37%), finance (38%) and IT (39%) could introduce new workflows within 30 days.
This challenge is exacerbated because most businesses still have a digital disadvantage, with 98% of UK C-level leaders admitting to still using offline processes. These include:
“Organisations innovated rapidly, and initial sprints enabled them to react to the immediate COVID-19 challenges,” said Chris Pope, ServiceNow’s VP Innovation. “Some decisions made were knee-jerk and rapid, but at what cost? There may be good short-term gains, but are they ‘match fit’ for our new ways of working? For organisations still struggling to integrate and implement a fully integrated workflow system, the future of work will not arrive, and soon they’ll fall behind.”
Worker safety is paramount
The survey also showed there are doubts when it comes to workplace safety from both UK leaders and UK employees.
“The critical challenge for UK organisations will be balancing the immediate need for business continuity with the personal needs of their employees,” said Pope. “2020 has been a difficult year for a lot of people. Many have seen restrictions over the past several months, which look set to continue through the winter. Businesses need to lead with compassion and combine empathy with meaningful action to help their employees navigate the months to come. In this distributed working environment, how organisations handle the moments that matter, from when a hire joins to when they leave, not only determines talent retention but will also contribute to overall business continuity and success.”
Business leaders split on return to office preferences
UK business leaders are also divided on how to keep their company most productive. While 49% want to maintain new ways of operating once the crisis subsides, 51% are keen to return to business as closely as it was prior to COVID-19, indicating a divide in approach.
Despite 57% of UK employees feeling they now have a better work-life balance, both UK leaders (99%) and UK employees (80%) have concerns about how remote work will impact their business moving forward.
The research indicates that leaders are prioritising speed of business while staff care about the human side of working. In terms of the largest challenges posed by remote work, UK leaders are most concerned about extended timelines for new releases or innovations (48%). Conversely, UK employees see reduced collaboration (48%) as their largest worry.
More information about The Work Survey can be found by accessing the survey findings slide deck and infographic.
Survey Methodology
Wakefield Research fielded an online quantitative survey in September 2020 to 900 C‑level executives and 8,100 office professionals (employees) from companies of 500 or more employees in the following countries: United States, United Kingdom, France, Germany, Ireland, Netherlands, India, Japan, Singapore, Australia, and New Zealand. While Wakefield surveyed across industries, the findings highlight meaningful differences from employees in the following five key industries: financial services, healthcare, manufacturing, telecommunications, and public sector.
iland research reveals hidden pitfalls of hyperscale cloud and low confidence in key features of cloud services, while a lack of resources is holding back cloud migration projects for 83%
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iland, a leading VMware-based cloud services provider for application hosting, data protection and disaster recovery, today released the findings of its research into customer confidence in cloud services. It found that despite the increase in cloud adoption due to the pandemic, three quarters of organisations surveyed say hyperscaler IaaS instance types may not meet their cost and performance needs for mission-critical applications, while more than one in five are not satisfied with key features of cloud provision such as security, performance, availability and support.
The research also found that a lack of migration resources is delaying or preventing cloud projects for more than 80% of organisations surveyed.
The research: The Hidden Pitfalls of Working with Hyperscale Clouds was conducted among 501 senior IT executives, including CIOs, CISOs and CTOs, in the UK and US by independent research organisation, Opinion Matters, in June 2020. Participants were asked for their views on security, performance, compliance and their overall level of confidence in the cloud services they have invested in.
Key research findings include:
83% say lack of migration resources and/or time has delayed cloud migration. Among those, 12% say it has entirely prevented migration.
75% say a T Shirt size or hyperscaler instance type does not meet all their performance and cost requirements.
24% are not confident that hyperscale clouds can meet performance and availability requirements for specific applications.
23% are not confident that production data is protected via backup or disaster recovery in the event of data loss with their cloud service provider.
24% are not confident they can get the support they need from their cloud service provider.
53% say security is the top factor in cloud supplier selection.
76% agree CSPs should assist or actively manage customer data compliance.
Commenting on the research findings, Researcher Charles Moore said: “While cloud adoption has seen a significant uptick due to the pandemic, the lack of migration resources for many customers has delayed or prevented deployment. Customers need to choose a cloud vendor that can fill the internal resource gaps that can hinder success.”
Justin Giardina, iland Chief Technology Officer, added: “The business benefits of moving to the cloud are indisputable, but with 83% of those surveyed saying that migration resources are necessary to achieve those benefits it’s clear that customers need to look beyond just the cloud platform and ensure their vendor can offer the supporting services that can reduce risk and improve time to value.”
“Hyperscale cloud services are missing the mark for a significant proportion of the organisations surveyed,” continues Giardina. “Having trust in critical cloud features is fundamental to realising its benefits, so with more than one in five respondents lacking confidence in aspects such as performance, availability, backup and support points to the hidden pitfalls of hyperscale clouds.”
Security, management, visibility, and control are priority customer requirements for cloud solutions
The study also found that key requirements for cloud service provision include common or unified management across all services; this is a priority for 73% of those adopting multi-cloud solutions. Similarly, infrastructure visibility and control are must-have features for 71% of respondents. Many were looking to the future, with 89% saying it was important or critical that they can write to their CSP’s API for future software development and deployment.
Security is a primary criterion for cloud provider selection, with 53% saying it is the leading consideration and a further 43% saying it is a major factor. Three quarters of customers also want to see cloud service providers helping manage data compliance.
The survey found that the majority (74%) of respondents felt it was important that CSPs preserve their company’s existing networking environment when they move to the cloud. This reflects the current landscape, where many organisations are being forced to accelerate their cloud adoption programmes due to the pressures of supporting large-scale remote working. Giardina notes: “When organisations are being rapidly pushed out of their comfort zones and forced to shrink deployment schedules to the absolute minimum, being able to maintain the familiar networking environment in the cloud is an advantage that is appealing to under-pressure IT departments.”
We catch up with digital strategist Dr Paul J Bailo, who reveals the third part of his digital transformation masterclass…
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I believe that our final chat within the Digital Transformation Trilogy is based around culture…
The first of our trilogy into what constitutes a successful digital transformation centred around leadership and this was followed by planning. But the glue to keeping this all together is the culture. And culture’s very hard to define for a lot of people, but it’s really the essence of what your organization is about.
It’s truly understanding what your value systems are. When we think of who we are and what we believe we bring to an organization – our beliefs, our religions, our upbringing and what mom and dad taught us – we bring in our feelings of how we see the world. These are basic perceptions, deep, embedded thoughts in our minds, shared beliefs, and even unconscious feelings, right? Who we are and what we are as human beings have developed through where we lived, what zip code we lived in, our friends, our family, religion and background. And these are the values we bring into an organization, which are fundamental to this idea of culture. So, you’re mixing all these different values in order to drive a digital culture, in order to set the right mindsets and behaviors that could be shared with all the members of the organization.
When we talk about digital culture, it’s usually about organizational change and transformation…
Historically, organizations talked about siloed use of digital, but now we’re talking about how every department needs to be digital. When you start talking about keeping everything in a small group and collaborating, we’re saying, “No, digital is everywhere in every aspect of the business.” These are traditionally very hard things for organizations to develop in their culture. And it’s rooted in this idea and belief of who this organization is and what they stand for. And this digital culture needs to be reinforced on a daily basis from the executive leadership down to the frontline people. The culture is the foundation for the business’ success in digital. It’s this stable environment in which organizations behave and hold everyone accountable. I think of culture almost like baseball in a sense.
Baseball? How so?
So, baseball is a set of rules and every player knows that these are the rules. There’s a first base man, second base person and third base person. There are rules and regulations on how you behave in the game of baseball, so when people, the players go out in the field, everyone knows what to do. With our digital culture we need to know the norms that we believe in, and the values we hold true, and the actions we expect. These actions have rituals and behaviors and routine processes that are digital, and there’s a digital culture, which basically serves their structure. These structures are a digital structure of org charts, and products, and mission statements that build the digital culture, in order for organizations to be very successful in the execution of digital initiatives. It’s this idea of the digital culture driving the actions, the mindsets, and driving the mindset at the root of the cultural change that must exist, in order for organizations to be successful in this current world that we’re living and the constant change.
The focus of digital is not just about the actions alone, it’s about the actions and the change that must happen in our heart, minds, and souls in these organizations that are transforming to be digital. It’s who we are and what we stand for, and consistently reminding ourselves and the employees, and the team members, and the shareholders of what we stand for in this digital culture. It is the mindset and behaviors that we agree to. and police, to hold everyone accountable. Understand that by doing this in our culture, they will reap the benefits of this digital change and digital landscape by agreeing that this is how we’re going to support each other in our overall digital culture: the values, the behaviors, how we talk to each other, how we behave with each other, how we execute as a team together.
What are the tangible benefits to this cultural approach?
It’s through minimal disparity and a sharing of the high risk of failure. Support is built into the culture. Taking a massive risk is built into the digital culture. It is extremely hard to change the culture because you’re truly trying to rewire people’s minds. And in legacy organizations, most people hate change, so you have to think about the power structure in this idea of digital culture, and this idea that decisions need to be made quickly, efficiently, very fluidly, and to constantly evolve in this idea of continuous improvement, which means that the culture will be evolving with it also. It’s the values and beliefs that the organization hold as one. It also is the emotional piece. It’s truly, how do you want to work? Is this a place that you want to belong to? Are your personal values aligned with the digital values of this organization? What are the values, right? The values that this organization holds true in this digital arena, are a critical part of the culture, absolutely critical.
Digital is forefront and the lifeblood of these organizations that must have a digital culture in order to survive. There’s no way companies are going to survive – banks, financial institutions, insurance companies – if they continue to behave in the way they’re behaving. Clients will not come to them, and will leave them in droves, if they are not bleeding edge digital organizations that have a culture pushing the envelope in transformation and change. Even the idea or ideas of decision-making, in a digital arena, are fast and furious. It’s not this big, long, legacy type of committee, in order to say these are now the decisions. It’s fast and furious in order to keep up with the marketplace. It’s the idea of strategy on a continuous, unending basis. It’s the idea that digital will change the way organizations conduct business.
It’s seeing the power shift within an organization?
Right! This digital culture is driven by the outcomes. And it’s this idea of digital culture which causes this power shift in the organization. And this is very egotistical, right? This idea of digital culture is a power grab for some people. It’s a mindset rewiring. It’s a behavioral rewiring. It’s an adjustment of values and behaviors. It’s a way of policing each other in a way that might make some people very uncomfortable. When we’re thinking about this, it’s this idea of culture which is one of the core pillars of a digital organization, and looking at these digital organizations in order to be much more efficient and effective in this brutal environment we’re currently in. It’s also building relationships, understanding that the idea of digital culture is a never-ending learning environment.
Apple doesn’t have the best products or the best services, but they react to the market extremely quickly. They react to it because they have a culture of learning, both on the soft skills and the hard skills. They understand the challenges of digital technology very quickly because their culture supports this idea of never-ending learning. A true digital culture within the organization is a learning institution. A digital culture in an organization is an organization that takes care of its employees and upskills them. It identifies the skills that employees need to be competitive, identifies the skills that organizations need in order to drive cultural digital change.
When we talk about digital culture, we’re discussing a massive shift in the way organizations think and behave as well as the organizational structure, the power structure, and executive mindset change. It’s really this idea that digital skills are required in every level of leadership, that training is necessary and the best practices of digital are required.
Increased responsibilities are pushing IT to breaking point
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Increasing pressure on IT teams is pushing many IT decision-makers to the brink of burnout, according to new research from Pulsant, a leading UK provider of regional data centre and cloud infrastructure services.
Nearly two-thirds of UK IT decision-makers (65%) have felt under increasing pressure to keep the organisation running effectively over the past 12 months, with 80% of these admitting this has harmed their health and wellbeing.
The research, which was conducted on 201 UK IT decision-makers in mid-market organisations, finds increased pressure on IT has manifested in various ways: 40% of IT decision-makers impacted say they are experiencing anxiety as a result of increased pressure; over a third (35%) are suffering from increased stress which is unsustainable and will result in burn out if not addressed, and nearly a quarter (24%) have experienced burn out which has resulted with absence from the business. Plus worryingly for businesses, 20% have either resigned or started looking for a new job.
The rise in pressure could be due to an increase in expectations with 77% of IT decision-makers saying expectations of IT have risen within their organisation in the past 12 months. The biggest reasons for this increase were noted as a greater focus on security and compliance (45%), the expectation for IT to work with more areas of the business (39%), the expectation for IT to support and have knowledge of a broader range of technologies (38%), increased pressure to update ageing infrastructure (36%) and being expected to deliver projects quicker (35%).
This, in turn, means that IT teams are left stretched across a wide range of responsibilities, with over a third (34%) of IT decision-makers saying too much workload/not enough time is one of the top challenges within their teams.
“An accelerating pace of change means that IT teams are under more pressure than ever to support more critical business initiatives and deliver results faster, while at the same time ensuring business systems remain available, secure and compliant,” says Pulsant CTO, Simon Michie. “This can place IT teams under immense strain which is detrimental to both the success of the business, and more importantly employee wellbeing, with staff left stressed, anxious and having to take time out from the business.”
The research also revealed a divide in opinions on the purpose of IT, with IT seen as both a caretaker of information and technology and also the driver of innovation across the business. Over half of IT decision-makers (58%) and business leaders (55%) believe the primary role of IT is either a help desk or technical support function or to be responsible for maintaining and running business-critical systems, while 40% of IT decision-makers and 45% of business leaders see the main role of the IT department as an enabler of innovation.
IT has also become influential in board-level business decision making with the majority (87%) of IT decision-makers saying IT is involved in setting the business strategy for the year ahead. An overwhelming majority (93%) say their organisation has a representative from the IT team on the board/leadership team, highlighting that IT is now widely regarded as a critical function.
However, while there is clear recognition for the role of IT in driving the business strategy and innovation, IT teams face challenges in delivering on expectations. Nearly two-thirds of IT decision-makers (65%) say their team is under pressure to be more innovative but there is not enough investment for this to be possible. IT decision-makers are also put off from driving new ideas forward by challenges including conflicting priorities (38%), lack of resource (36%) and time (35%).
“It’s hugely positive that both business leaders and IT decision-makers recognise the role of IT in driving innovation, but it’s clear that more attention needs to be paid to providing the IT team with the right support and resources it needs to perform both functions effectively and maintain the wellbeing of IT professionals,” concludes Michie.”
The research was conducted by Censuswide on 201 IT decision-makers and 200 business leaders in UK mid-sized companies (200-2,500 employees). The full report – The IT Paradox: Balancing support and innovation – and further insight into the findings can be found here.
New web application security study found US retailers had a larger attack surface, while EU retailers run more outdated services…
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Outpost24, an innovator in identifying and managing cybersecurity exposure, today announced the results of the 2020 Web Application Security for Retail & E-commerce Report, which analysed the web applications of the top 20 retailers in the US and EU. Research shows exploits targeted at web applications remain one of ecommerce’s most significant threats. Using an average risk exposure score based on Outpost24’s multi-layered attack surface discovery tool, Scout, the findings revealed that web applications used by US retailers were more at risk with an aggregated average risk score of 35 against a maximum score of 42.33, which was higher than their EU counterparts at 31.
On average, the report found US retailers to be running more publicly exposed web applications (3,357) compared to EU retailers, which ran fewer applications (2,799). Yet, despite having a smaller attack surface, EU retailers had a higher percentage of applications using old components that contained vulnerabilities (27%) as opposed to their American rivals (22%). Nonetheless, all retailers had security risks within their web environments that could expose them and their customer data they hold to potential exploitation and compromise.
The list of retailers were chosen based on Deloitte’s Global Powers of Retailing Report 2019 and had their public-facing web security environments analysed against the seven most common attack vectors used by hackers during reconnaissance, to ascertain the risk score, including Security Mechanisms, Page Creations Methods, Degree of Distribution, Authentication, Input Vectors, Active Contents and Cookies (score 1-100 each).
Security Mechanisms was the single biggest attack vector for both EU and US retailers, attaining a risk exposure score of 90.5 and 99 respectively. For retailers using HTTP websites, and not restricting access to adversaries trying to get into unsecured parts of a site without encryption, this will contribute to a higher attack surface score. Active Content, which observed how web applications were running scripts, was the second most dangerous as both US and EU retailers acquired scores of 88 or more. Third highest was Degree of Distribution with all retailers attaining scores higher than 77.9, which is attributed to the high number of product pages commonly found on large ecommerce sites making it difficult to secure everything.
Nicolas Renard, Security Analyst at Outpost24 comments “hackers are masters of reconnaissance and will go to great lengths to identify weak spots in their target. The rather high risk exposure score among the top retailers is a worrying trend, as bigger attack surfaces create more opportunity for bad actors to find holes in their security defense and execute potential exploits.”
Outpost24’s Scout tool also examined the components that were used to develop the web applications and discovered that 90% of EU retailers and 50% of US retailers are currently running outdated jQuery versions on their applications which could expose them to common cross site scripting attacks. Furthermore, the top retailers are found to be using a variety of outdated servers to run their applications, making their shared hosting environments vulnerable to unauthorized access through potential exploitation of known vulnerabilities.
Stephane Konarkowski, Security Analyst at Outpost24 said “how the web application is built and developed is a key risk indicator if you know where to look. Our research shows the complexity of modern-day applications and the need for retail organizations to understand their attack surface and risk levels. To avoid data breach and the loss of customer trust and revenue, retailers must address security hygiene as an essential step to protect their web applications and ensure the attack surface is kept at a minimum through continuous assessment.”
Even before COVID-19, many organisations faced considerable IT challenges. Now, COVID-19 is rapidly pushing companies to operate in new ways…
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Even before COVID-19, many organisations faced considerable IT challenges. Now, COVID-19 is rapidly pushing companies to operate in new ways and IT is being tested as never before. As businesses juggle a range of new systems, priorities and challenges, including business continuity risks, sudden changes in volume, real-time decision-making, workforce productivity, security and customer satisfaction, leaders must act quickly to address immediate systems resilience issues and lay a foundation for the future. If leaders wait until the other side of the pandemic before applying lessons learnt from the experience so far, it will be too late. Long-term strategies for greater resilience need to be determined now; for many, strong technology partnerships will be critical to this.
Here at Babble, we’ve recently been announced as the Five9 EMEA Reseller of the Year for the second consecutive year, so you could say we know a thing or two about successful partnerships. Our relentless strive to build long-term relationships with clients and implement services that guarantee business continuity and eliminate the hassle and expense of traditional on-premise contact centre software, has in turn benefitted our relationship with Five9, driving record European sales for the business.
So, what’s the key to building successful long-term partnerships?
1. Seek seamless integration: Firstly, if you lack the skills or resources in-house to deliver business-critical technology solutions, you must look to a partner that can seamlessly integrate into your business – and quickly. But always remember, the best technology partnerships are those that are worth more than the sum of their parts, and these relationships must be mutually beneficial.
2. Look beyond the costs: Cloud technology negates the need for bulky upfront costs, which can boost digital transformation, especially where financing is an issue. However, leaders should not focus on the partnership costs alone. Businesses must carefully consider the supplementary support they need and will receive when it comes to innovation, digital transformation and engineering. It is crucial that decision makers understand this at the outset to ensure they don’t enter into partnerships that are ultimately disappointing, and short term.
3. Leverage expertise: Business leaders must be prepared to put the innovation and investments being made by cloud and technology experts to good use. Most businesses will choose to work with at least one technology provider as they look to leverage their deep expertise and numerous cloud services, and getting the most out of them is about committing to a partnership. Don’t think about the short-term – you should be committing to a relationship that allows you to leverage expertise for years into future.
4. Remember the basics – check product functionality/offering: Don’t lose sight of what you require the partner for and ensure that the products the chosen partner can deliver align with and provide the functionality that your end users require.
5. Nurture relationships Don’t forget that technology partnerships are no different to any other relationship. The best partnerships are built on a long-term basis, so while it is critical that a strong working relationship exists from the outset, this is not the only consideration. The relationship needs nurturing. Communication is fundamental – and with a global workforce that is now more technologically agile and available than ever before – there really is no excuse.
The new issue features exclusive content from Marsh UK, HPE, and Rim of the World Unified School District…
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Welcome to the latest issue of Interface Magazine!
This week’s cover star is Alistair Fraser the CEO of UK Corporate at Marsh who has given us an exclusive insight into the massive transformational change at the insurance brokerage, that seeks to help enterprises survive and thrive during a global pandemic…
The COVID-19 pandemic’s economic and social impacts are driving significant shifts in global political risk — introducing new dynamics and accelerating existing geopolitical megatrends, such as trade protectionism and the transition to a multipolar world order.
“We segment our service delivery to clients based on their size and needs around risk and insurance,” explains Fraser, from Marsh’s Bristol office. “Our role is to advise our clients on their insurance and risk requirements so that they can manage risk in a more controlled way, helping them to protect their business, roll out new products and services, and continue to thrive.”
Elsewhere, we speak to Erik Vogel, Global Vice President, Customer Experience at HPE to see how the global, edge-to-cloud Platform-as-a-Service company is transforming the customer journey with GreenLake to provide an ‘everything-as-a-service’ offering…
Plus, we have the third and final instalment of digital strategist Paul Bailo’s Digital Transformation masterclass, and an exclusive with Mads Fosselius, CEO and Founder, Dixa who reveals the secrets to succeeding in this ‘new world’. And we speak to Michelle Murphy, Superintendent of Rim of The World Unified School District, who explores how a digitalisation of the classroom begins and ends with the success of the student in mind.
MTS looks to better enable multi-vendor and cross-platform integration…
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Russia’s largest mobile operator and a leading provider of media and digital services, announces the selection of Canonical’s Charmed OpenStack to power the company’s next-generation cloud infrastructure. MTS plans to leverage Charmed OpenStack’s advanced lifecycle management capabilities and flexible cloud-native architecture to better enable multi-vendor and cross-platform integration.
Serving over 77 million subscribers in Russia, MTS has chosen to partner with Canonical, the publisher of Ubuntu, to further its efforts in building out a full-fledged digital ecosystem based on an open source platform. The partnership is aimed at decreasing time-to-market and speeding up deployment of new services — including toward MTS’ expected future 5G deployment — as well as reducing the total cost of ownership (TCO) of cloud infrastructure. MTS also anticipates to enhance its core technology expertise and set up a competence center for developing OpenStack-based solutions.
MTS plans to begin operationally rolling out the project next year, ultimately deploying Canonical’s Charmed OpenStack solution across 11 data centers in Russia.
MTS CTO, Victor Belov, commented: “The selection of OpenStack is another step forward in our strategy to migrate towards open source software. Building an ecosystem based on OpenStack will speed up our technology adoption, lay a foundation for future 5G rollout, and enhance our network’s edge compute capabilities. This solution will also enable us to improve virtualization cost effectiveness, as well as expand our ability to leverage a wide variety of virtual platforms. That will not only help us maintain a technical edge in the Russian telecom industry, but also enhance our IT agility and enable us to tackle complex challenges to better meet the needs of our customers.”
“Canonical is truly excited to partner with MTS and provide a platform on which they can roll out their 5G network,” said Regis Paquette, VP Global Alliances at Canonical. “The partnership will help build an underlying network and IT infrastructure bringing the latest updates in a predictable and automated fashion. With comprehensive security built-in, and unified automation from core to remote edge locations, this partnership places MTS at the forefront of innovation with open source.”
“All around the world, carriers love OpenStack. What started as an agile framework to deploy and manage network functions has grown to become a preferred platform for managing the evolution of networks from LTE to 5G,” said Mark Collier, COO, Open Infrastructure Foundation. ”Canonical has been an important vendor since the earliest days, and we congratulate their team on working with MTS to deliver agile, open infrastructure for the company’s 77 million subscribers.”
For two in five UK consumers, the telephone has replaced face-to-face interactions during the pandemic When many organisations had to…
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For two in five UK consumers, the telephone has replaced face-to-face interactions during the pandemic
When many organisations had to close their doors and restrict face-to-face activities during the pandemic, the telephone has proven to be a vital and effective tool, with two in five consumers saying phoning business and call centres has replaced face-to-face and in-store interactions with brands. In fact, the survey, which was carried out by Netcall in conjunction with Arlington Research, has revealed that more than a third of consumers (34%) have found it vital to phone businesses during the pandemic. That’s despite recent speculation that COVID could spell the end of the call centre.
And, contrary to many popular beliefs, the telephone has been a vital channel for younger consumers as much as it has been for older age groups. 38% of Millennials, 40% of Generation X, 39% of Baby Boomers, and 39% of the Silent Generation all agree that phoning businesses or call centres is one of the main ways they contact a brand. In addition, 36% of 18-24 year olds agreed it has been vital to telephone a business during the pandemic, compared to 27% of 55-64 year olds.
With England now entering its second national lockdown, which will see all non-essential businesses closed to the public once again, society’s reliance on alternative contact methods is set to continue – and could even escalate.
However, it’s not all good news for the contact centre. More than half (55%) have been kept waiting longer on phone calls to brands during the pandemic. Whilst there may be explanations for this in terms of increased demand and challenges with staffing traditional contact centre sites, this still harms brands when it comes to reputation and customer loyalty. Customer experience and the way that companies respond to consumers has never been so important. In fact, 69% agree that bad customer experience/support over the phone negatively impacts the way they feel about a brand, whilst more than one in three (37%) think businesses should be available by phone 24/7.
And, as the demand for round-the-clock services to be delivered remotely increases, self-service channels are rapidly being seen as the solution. Two-in-five (43%) respondents prefer to use self-service channels such as online chatbots, rather than phoning a call centre. And these preferences vary with age: 58% of 25-34 year olds prefer self-service channels, compared to 33% of 55-64 year olds and 28% over 65. That doesn’t mean self-service for all types of interactions; rather, that organisations should focus their efforts on providing customers with the appropriate channels for the complexity and effort of the engagement.
Richard Farrell, Chief Innovation Officer at Netcall commented, “For simple transactions, automated channels, underpinned by low-code software, can provide convenience for users and free up resource in contact centres for more complex, emotional, or high-value interactions. Chatbots are an obvious example, but organisations shouldn’t neglect telephone-based services such as Interactive Voice Response (IVR) and other forms of voice bot for call routing, direct debit creation, and payments. When customers need to call or escalate from an automated channel, there are ways to help manage the experience, such as call centre callback, that removes much of the frustration for callers and delivers more effective staff utilisation.
“Agents must also be empowered with the right tools to do their job, and that means information being readily available, as well as systems and processes that remove friction from customer journeys. Robotic Process Automation can quickly gather information from multiple systems and perform steps once a call completes, improving customer experience and improving efficiency,” Farrell concluded.
Retailers need to rethink their entire sales and marketing strategies…
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Through forced closures, physical restrictions and mitigating measures, the pandemic has posed threats that have forced retailers to rethink their entire sales and marketing strategy, both short and long term.
And the stats are there to support these notions. Ecommerce sales were up some 92.7% in May 2020, and some 60% of consumers plan to maintain these shopping levels post COVID-19.
Of course, health has been the biggest concern, and by no means should that be disregarded. But livelihoods have suffered too, and navigating out of the disruption from a commercial standpoint is going to take some consideration of them both.
At least that’s the view of Nate Burke, CEO and founder of digital marketing and ecommerce specialists Diginius. Having spent recent months helping businesses establish and grow their online offerings, in light of the restrictions in place to contain the spread of the virus, Nate explains his proposition.
“Physical stores have faced unprecedented challenges this year but before we bid farewell to 2020, many are attempting one last claw back of revenue. What they are recognising is a need for change – not only to survive the pandemic, but to come out of it stronger and well-positioned for retail’s evolved landscape.
“Digital offerings and ecommerce, in particular, have provided a much-needed lifeline. But now that they have their online footing, the next step for businesses is to establish themselves in a marketplace that is only getting bigger, more advanced and increasingly competitive. And one of the ways to differentiate and grow is through digital marketing that can in turn, drive online sales.
“Included in this are Artificial Intelligence (AI) and automation – buzzwords in the digital sphere. But unlike human activities, the computerised actions are much less effected by a biological virus outbreak. And therefore, their influence and impact on the industry haven’t slowed like most other factors have.
“Rather, the changes they are causing are inevitable, but by embracing their capabilities, businesses can not only make a commercial breakthrough, but a human one too. And that couldn’t be more important than at a time like this.”
A human touch
Using computers to increase the human nature of your digital offering, although odd, isn’t ineffective. Nate explains how.
“An increasing number of customers are opting to shop online where they are safe from any virus threats. But what this means for retailers is a risk of consumers becoming disconnected from their brand, which can happen quite easily when the physical distance between the two has widened.
“This is where the benefits of automation can really be felt, particularly when used to enhance customer experience.
“For example, automated marketing strategies that serve content tailored to individual interactions, or PPC tactics that automate ad copy to match users’ search queries, for example, all make for a more personal experience.
“And we shouldn’t forget about that most traditional of digital brand communications nowadays, social media – with its ability to schedule and organise ahead of time posts that will enhance digital marketing and brand communication efforts.
“What this creates is positive brand engagement as each customer is getting an experience that is perfectly suited to their requirements. And in this way, the brand feels much less like a simple transaction and more of a value-added experience.”
There is proof that this has commercial benefit too, with figures indicating that 75% of email revenue is generated from personalised campaigns.
A look inside
While focusing on addressing heightened customer sentiments, it’s important to remember that your employees too are people that are facing the same challenges and uncertainties. But luckily, automation can also help make their jobs easier.
“Another benefit of automation is its ability to lessen the admin burden for all businesses, but especially those who are new to ecommerce and those who now have an omnichannel offering with both an online and physical store,” explains Nate.
“For employees, this means less paperwork or order monitoring as the process can instead take place via a centralised digital platform, which not only holds customer and supplier information, but also analyses data to create insight that can then go on to inform business decisions.
“Pressure is taken off employees, who may well be struggling with an increased workload due to the addition of sales channels, which will no doubt improve wellbeing and workplace satisfaction. And commercially speaking, this can reduce costs related to wages and training, allowing budget and resources to be reallocated to other business-critical activities instead, such as digital marketing.”
The financial impact of the pandemic continues to grow, so we anticipate budget saving will be on the minds of many business owners in the coming months. It appears, then, that automation could be a useful technique.
Nate believes that: “When fully integrated into a business’s process, yes, automation can save costs and help to maximise return on spend in other areas. But as with anything, investment into learning, understanding and implementing a strategy are required in the first instance.”
“Despite this, automation and digital transformation are here to stay. Those who are willing to embrace AI technology now will be in a much better position than those who don’t. And with retailers having suffered enough this year, it may well be that automation is what the industry needs to propel it into a whole new era of ecommerce, giving it a fighting chance of survival amid COVID-uncertainty.”
Nate Burke is CEO of Diginius, a software and services provider with a performance based approach designed to grow your sales online.
Lenovo™ and Intel®-sponsored study looks into how updating technology can improve productivity, employee engagement and customer satisfaction…
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A new Lenovo and Intel commissioned study, “Empower Your Employees with the Right Technology,” conducted by Forrester Consulting, has found that the impact of technology in improving the employee experience (EX), or an employee’s full journey in an organisation, is much more than anticipated — highlighting opportunities for organisations’ IT decision makers (ITDMs) in today’s remote and hybrid work environment. The key insight points out that while companies on average see a 5x return on investment in the EX driven by increased productivity, organisational agility and customer satisfaction, ITDMs and employees disagree on technology priorities. While ITDMs are prioritising strategic IT integration, software and service needs, employees are more focused on their fundamental daily technology experience. This suggests that business leaders have room to collaborate more closely with employees on their IT purchase decisions to elevate team engagement, increase customer satisfaction and improve the bottom line.
Bridging the divide between employees and IT decision makers
With organisations now shifting their focus toward remote and hybrid work, ITDMs are upgrading devices, software and services as part of EX initiatives to improve team engagement and satisfaction. Based on the research findings, this has led to more tech spending. IT leaders are reporting a 5x return (USD $1 spent on these programs yields USD $5 of increased staff productivity, organisational agility and customer satisfaction), with many expecting to increase their investment by nearly 25 percent in two years.
Yet employees still report that they’re frustrated with their PC hardware and software experience:
Fifty (50) percent of respondents say their PC devices are out of date or insufficient (e.g. not fast enough, reliable enough or powerful enough)
Forty-six (46) percent note their software frequently malfunctions and disrupts their work
Only 33 percent are extremely satisfied with the current laptop provided by the company
Only 30 percent said their laptops or desktop work well for cross-collaboration.
Importantly, ITDMs and employees both define employee satisfaction with technology as a crucial goal. Satisfaction with technology also has the greatest observable positive impact: nearly 60 percent of ITDM respondents noted a more than 10-percent increase in EX scores by improving employee satisfaction with technology. It’s evident that IT departments and the technologies they offer are instrumental to driving EX, beyond conventional factors such as human resources, worker benefits and more.
Yet again, there is a clear disconnect between employees and these ITDMs, whose primary concerns are the longevity of their technology investments rather than its impact on team engagement. According to the study, whereas 84 percent of ITDMs believe employees can easily switch to a different PC device if their current one needs to be replaced, only half of employees agree that’s an available solution. Ultimately, both ITDMs and employees agree that refresh cycles can be improved and better aligned. In addition, ITDMs believe the integration of hardware and software will impact EX the most, whereas employees simply want devices that work consistently.
Prioritising employees to better leverage technology investments
The study outlines a few key recommendations on how business leaders can better improve employee engagement and business outcomes through technology investments.
Realign investments. While many ITDMs are investing resources into exploring newer, emerging technologies such as 5G, augmented and virtual reality (AR/VR), and artificial intelligence (AI) or machine learning tools, based on worker respondents’ feedback there is an opportunity to focus first on immediate employee priorities—building a strong foundation of collaboration tools and PC devices—while IT departments explore more advanced technology tools in parallel.
Reorganise priorities. Decision-makers should also focus on improving EX vs only focusing on specific productivity metrics. In fact, according to the study nearly 80 percent of ITDMs plan to focus on improving employee engagement over the next few months.
Focus on PCs. PCs have become critically important to employees, with 77 percent of full-time employees saying that PC devices are a critical factor in their daily work and collaboration with one another. A renewed focus on PCs can make the greatest impact on the bottom line and customer satisfaction, with most respondents agreeing that PC devices are critical to increasing customer satisfaction (69 percent), revenue growth (62 percent) and employee retention (55 percent).
Involving employees in PC investment decisions. Overwhelmingly (72 percent) of employees responded that listening to workers or getting clarity on what they need ranks in the top three of what companies should do to improve EX. This feedback is important, as employees understand their work devices’ value in driving business outcomes, based on technology factors such as performance, connectivity, reliability, portability, size/weight, battery life and more. Listening to employee feedback can go a long way towards making the case for better technology options.
“Our new study findings further affirm our belief in the strategic importance of technology as critical investments, and not as simple transaction costs. The right deployment of technologies delivering returns can far exceed the initial expense of new business models and opportunities,” said Christian Teismann, President, Commercial PC and Smart Devices Business, Lenovo.
“Given employees are a company’s greatest asset, the study further maps out opportunities to uplift the return on technology investment by focusing on PC devices and collaboration tools, while better involving employees in purchase decisions. In today’s new remote and hybrid work set-up, these steps are pivotal for companies in yielding opportunities that go far beyond the initial spend on their technology.”
Data revealed as Tech Nation and Dealroom launch the Impact & Innovation database…
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New research from Tech Nation and Dealroom reveals that investment into UK impact startups increased 9.5x between 2014 and 2019. UK impact startups have raised €1.4B so far in 2020 with Cleantech and Climate tech companies raising the most capital of all UK impact startups.
The biggest rounds for UK impact startups in 2020 include Octopus Energy, Arrival, Connexin (Hull), Tokamak Energy (Abingdon), Compass Pathways, Cera, Highview Power, FiveAI (Cambridge), The Meatless Farm Company (Leeds).
It comes as Tech Nation and Dealroom launch the Impact and Innovation database, that catalogues 4,939 startups and scaleups, 7,472 funding rounds, and 232 exits of innovative companies addressing the world’s most pressing challenges.
George Windsor, Head of Insights at Tech Nation, commented: “UK impact tech firms have come on leaps and bounds over the last six years – with nearly 10x more investment made into groundbreaking companies in 2020 than 2014. UK tech must continue to play a key part in tackling some of the world’s toughest challenges, including climate change. This revolution is happening right across the country. Tech Nation is pleased to work with some of the leading companies in this space through our world-first Net Zero programme – ensuring that companies working in this sector can scale to have the greatest impact.”
The data also reveals that European startups are more impact-focussed than their global peers. €6B was invested into European impact startups in 2019, making up over 15% of all VC investment in the region. This research shows that what was once fringe investment and innovation activity is finding traction and proven success in Europe, becoming a core part of European innovation ecosystems.
Climate tech startups, which includes electric vehicles, have attracted the most investment within the Impact sub-sector, with European players emerging as global market leaders. European companies working to tackle climate change and its impacts have attracted €9.8B in VC investment in the last five years.
Impact innovation startups are also fueling growth and job creation. Crucially, these startups are actively hiring, the Impact & Innovation database lists over 2,100 jobs in impact startups that are currently hiring in Europe – over 390 of these are in the UK.
The Impact and Innovation platform will bring together startups, investors, non-profits, governments, and corporates in one open-access data-driven platform. The new mapping of the global impact and innovation ecosystem will facilitate data-driven policy and decision making, the sharing of cross-industry knowledge, and will foster the partnerships required to help next generation innovators succeed on the global stage.
Accenture and ServiceNow have formed a new business group to help private and public sector clients accelerate their digital transformation…
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Accenture and ServiceNow have formed a new business group to help private and public sector clients accelerate their digital transformation and better address today’s dynamic operational challenges. The Accenture ServiceNow Business Group represents a significant multi-million dollar investment from both companies over the next five years.
In the COVID-19 era, organisations are under more pressure than ever to innovate faster, reduce costs, enhance productivity, and meet their customers’ needs. The Accenture ServiceNow Business Group will help organisations rapidly evolve organisational processes and unlock the full value of technology investments by adopting digital workflows that deliver modern, personalised customer and employee experiences. This includes empowering employees and customers with self-service and remote work programs that offer increased flexibility, mobility, and choice. By establishing a more modern workplace with platform-driven, technology-enabled workflows, organisations are better positioned to balance business needs, satisfy customer demands, drive employee engagement, deliver productivity expectations, and realise workplace cost optimisation.
“By further strengthening our strategic alliance with ServiceNow, we will enable our clients to more quickly embrace change,” said Julie Sweet, chief executive officer, Accenture. “With a move to the cloud, they can reimagine their operations, reskill their employees, and become more sustainable. Working together with ServiceNow to automate complex processes and create better experiences across industries, we will help organisations deliver greater 360-degree value that benefits all — their customers, people, shareholders, partners, and communities.”
ServiceNow CEO Bill McDermott said: “Leaders in every organisation know that their 20th century technologies are too slow, too siloed, too stuck in the status quo to meet the dynamic digital demands of employees and customers today. Speed, agility, and resilience are what’s needed now. Our ServiceNow and Accenture partnership brings together world-class teams, expertise, and our modern workflow platform to accelerate every organisation’s digital transformation. The Accenture ServiceNow Business Group will help every organisation become a 21st century digital business.”
The Accenture ServiceNow Business Group will deliver industry- and domain-specific solutions and services to customers. Together, Accenture and ServiceNow will initially help accelerate digital transformation programs for customers in telecommunications, financial services, government, manufacturing, healthcare, and life sciences. Workflow innovation will focus on employee engagement, customer service and operations, artificial intelligence for IT operations, and security and risk. Additional industry solutions will be developed in the future.
Supported by approximately 8,500 Accenture people skilled in ServiceNow, the new group brings together dedicated professionals from both organisations with expertise in transformational workflow and platform development, marketing, sales, and business development across numerous priority industries. The business group will develop advanced industry and domain-focused solutions designed to deliver tangible, positive outcomes for clients at scale.
For example, Boehringer Ingelheim, a leading, research-driven pharmaceutical company with more than 51,000 employees and an Accenture and ServiceNow customer, uses ServiceNow’s technology and Accenture services to create a seamless, consumer-grade experience for global employees and customers.
“Our work with Accenture and ServiceNow has strategically fueled our innovation power. By optimising our global employee experience, we’ve made our work processes across business functions faster and more efficient, ultimately driving better patient outcomes,” said Andreas Henrich, corporate vice president of IT Enterprise Data Services at Boehringer Ingelheim. “We’ve reduced complexity across our disparate bespoke systems and, in doing so, have transformed our business for growth.”
Accenture and ServiceNow also collaborate to serve government entities. Earlier this year, Accenture Federal Services (AFS) announced a $96 million task order to help the Department of Veterans Affairs (VA) modernise its enterprise service management and IT capabilities, using ServiceNow to power the digital transformations end-to-end. Using the Now Platform, AFS will work with the VA to automate its manual workflows and introduce applied intelligence (AI) and machine learning capabilities, allowing the VA workforce to focus on more complex tasks that serve veterans.
“Today, Veterans Affairs is truly running IT like a business,” said Greg Rankin, Service Management Office Director, Department of Veterans Affairs Office of Information & Technology. “We are utilising ServiceNow’s powerful discovery engine and Accenture’s expertise to create top-down business service maps that eliminate the guessing game as to which configuration items underpin which business service. With a mission as critical as providing service to veterans, it’s imperative that we have real-time visibility into the health, availability, and costs of the services we provide – we have that now.”
Accenture’s use of ServiceNow is a strategic enabler of customer-facing innovation at scale and, as a ServiceNow customer, the company uses ServiceNow workflows for employee engagement, invoice processing, asset management, artificial intelligence for IT operations, and its universal service desk. Accenture recently made the Now Mobile app available to its more than 500,000 people.
As a ServiceNow Global Elite Partner, Accenture is one of ServiceNow’s largest global go-to-market partners and winner of its Global Partner of the Year award in 2020.
A new study from Business Fibre reveals the best cities to be a tech student around the world
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A new index by Business Fibre has analysed 34 of the world’s Organisation for Economic Co-operation and Development (OECD) capital cities to find 2020’s best cities to be a tech student. The index has analysed each city according to metrics such as the number of universities offering technology and engineering courses, total tech companies and employees in each city, the monthly living cost and the top cities investing in tech-related research. See the index here.
The top 10 cities to be a tech student
To find the world’s top cities to study technology, we have ranked each city according to a series of metrics to find the overall winners for those looking to start their career in technology.
The metrics explored include budget spent on tech-related research, the number of people employed in professional, scientific and technical sectors, tech companies, monthly living costs as well as the number of top universities offering technology and engineering courses.
Introducing the top 10 cities to be a tech student…
London, UK
Berlin, Germany
Jerusalem, Israel
Bern, Switzerland
Seoul, Korea
Stockholm, Sweden
Paris, France
Canberra, Australia
Rome, Italy
Tokyo, Japan
Top cities contributing to tech research
Exploring Technology research spend, the study also finds the top cities who are consistently investing in technology research. This has been calculated by looking at the % of the total GDP spent on research.
Rank
City
Research Spend (% of total GDP)
1
Jerusalem, Israel
4.8
2
Seoul, Korea
4.3
3
Bern, Switzerland
3.4
4
Stockholm, Sweden
3.4
5
Tokyo, Japan
3.2
6
Berlin, Germany
3.1
7
Copenhagen, Denmark
3.1
8
Vienna, Austria
3
9
Helsinki, Finland
2.7
10
Brussels, Belgium
2.7
The highest-ranking city is Jerusalem, which ranks high across all metrics and is the 3rd best city for tech students overall. The top three cities for tech-related research also include Seoul, spending 4.3% of the GDP, followed by Bern at 3.4. All three cities also rank high for the best universities and overall top cities for tech students.
Top 10 universities to study technology worldwide
Based on the top 10 cities to be a tech student, we wanted to find the best universities in each city for aspiring students. To find the best universities BusinessFibre looked at metrics such as the total number of students, faculty staff and the number of international students. This alongside each universities global subject ranking for Engineering and Technology make up the top 10 tech universities in the world. The monthly cost of living has also been included so that students can be sure they’re studying at the best overall tech university.
Rank
University
Worldwide ranking (Engineering and Tech 2020)
City
1
Imperial College London
7
London, UK
2
Technical University of Munich
25
Berlin, Germany
3
Technion – Israel Institute of Technology
179
Jerusalem, Israel
4
ETH Zurich – Swiss Federal Institute of Technology
4
Bern, Switzerland
5
Seoul National University
22
Seoul, Korea
6
KTH Royal Institute of Technology
30
Stockholm, Sweden
7
Ecole Polytechnique
57
Paris, France
8
The Australian National University
71
Canberra, Australia
9
Sapienza University of Rome
127
Rome, Italy
10
The University of Tokyo
21
Tokyo, Japan
Comment from Ian Wright: “With technology arguably being the fastest growing and most profitable industry in the world, we wanted to find the best cities in the world to be a tech student as well as the top cities funding technology-related research.
It’s clear from the research that London, Berlin and Jerusalem are the best cities for students, while Seoul and Bern join Jerusalem at the top for investing in technology-related research.
For those who don’t want to spend a ton of money on their education, Seoul National University is a great option that offers a lower living cost while still having a good global university ranking.”
With an ever-increasing demand for digital and online payments, Paypal will increase the utility and usability of cryptocurrencies by making…
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With an ever-increasing demand for digital and online payments, Paypal will increase the utility and usability of cryptocurrencies by making them available as a funding source for purchases, with nearly 26 million merchants accepting the currencies.
The service has been enabled by a partnership with Paxos Trust Company and has seen PayPal secure a first-of-its-kind conditional Bitlicense from the New York State Department of Financial Services.
With over 5,300 different types of cryptocurrencies, PayPal has been selective in its choices, and will only offer support to Bitcoin, Ethereum, Litecoin and Bitcoin Cash. Customers will then be able to instantly convert their cryptocurrency balance to fiat currency.
In addition to this, PayPal will offer educational content which aims to help account holders understand more about cryptocurrency and blockchain, as well as the risks and opportunities associated with investing.
Dan Schulman, President and CEO of PayPal, said: “The shift to digital forms of currencies is inevitable.”
“This shift will bring with it clear advantages in terms of financial inclusion and access; efficiency, speed and resilience of the payments system; and the ability for governments to disburse funds to citizens quickly.”
“Our global reach, digital payments expertise, two-sided network, and rigorous security and compliance controls provide us with the opportunity, and the responsibility, to help facilitate the understanding, redemption and interoperability of these new instruments of exchange.”
Bitcoin’s price rise from 15th October to 22nd October
However, there are concerns from the crypto community, as customers currently cannot move the cryptocurrencies to other accounts either on or off PayPal, and PayPal will not provide customers with the private key. There will also be a transaction fee for any purchase or sale, but these have been waived until 2021.
Upon the news, Bitcoin’s price hit a record high for the calendar year, rising 13% to $12,900 on Thursday. PayPal’s share price had a similar reaction, with shares up 7% to $215.
Web scraping can improve your bottom line and competitive positioning if done correctly
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According to BRC-KPMG’s retail sales monitor[1], retail sales in the UK increased by 6.1 per cent in September on a like-for-like basis from the same period last year. However, the same month also saw a dramatic increase of 37 per cent in online non-food sales. As we enter the Golden Quarter, eCommerce operations need to be clear about why they need an ethical approach to web scraping to stay ahead of the pack. This is according to Oxylabs, a proxy and data gathering service provider.
Julius Cerniauskas, CEO at Oxylabs, stated: “It is very clear from the figures released this week that UK consumers are spending online on home improvements and even stockpiling goods in preparation for another tightening of COVID related restrictions. In fact, the British Retail Consortium went one step further claiming Christmas was coming early.”
While this appears to have provided a boost for some retailers, as we move towards Black Friday and into the Christmas trading period, those online or refocusing on eCommerce, need to get ready quickly, and the key to this is having a clearer understanding of their market. Central to this is information and that in turn requires data.
“Information is so readily available today with the advent of the internet and sourcing reliable information can happen incredibly quickly,” added Mr Cerniauskas.
The top five business benefits of ethical web scraping
Competitor analysis
Imagine being able to scrape product and price comparisons within minutes across tens of thousands of eCommerce channels, enabling you in turn to be able to influence consumer-buying decisions via data-driven pricing strategies and attracting price-sensitive customers.
SEO
The main goal of Search Engine Optimisation (SEO) is to increase website traffic and convert leads. With ethical web scraping, you can quickly collect critical data on keywords, PPC and even content. Then, with this data available you can adjust your own online campaigns.
Enhanced lead generation
As a business, for you to reach out to your prospective customers and generate more sales, you need qualified leads. That means getting all their details, such as the name of a company, street address, contact number, emails, and other necessary information.
How data is collected is absolutely critical, but so too is its veracity. This is where ethical web scraping steps in to collect public data from competitors’ websites, portals and forums, so you can find out who is following them and what they are saying. From there, the collected data will have to be aggregated and analysed to provide insights and patterns.
It’s all about brand
Anyone who sells online knows the pivotal importance of brand and how consumers perceive it. Ethical web scraping across multiple online channels can help executives to promptly collect vast amounts of data that can bring tangible insights once analysed. The real value is if this is done in conjunction with measuring your competitors over the same timeframe and that leads us to the final benefit.
Sentiment
From TripAdvisor to eBay, from Amazon to Yelp, the internet is awash with opinions on your business, drafted and posted by consumers on a daily basis. It is all publicly available and that is why you need ethical web scraping to automate this process of intelligence collection, which, once absorbed, can create new opportunities and allow companies to differentiate in highly competitive markets.
Mr Cerniauskas concluded: “Ethical web scraping is a practise whose time has come. When done ethically and correctly within the law, it can identify and extract vital public data which will help any eCommerce operation to maximise the critically important financial and marketing decisions they need to take in the build-up to the Golden Quarter and beyond.”
Oxylabs has been at the forefront of data gathering and extraction for over five years. Driven by an ever-increasing demand to capture and leverage publicly available information, large scale eCommerce providers, as well as businesses working in the information economy, are readily deploying residential and data centre proxies to fuel web data gathering mechanics in-house, as well as outsourcing ready to use solutions to gather business intelligence, support price optimisation, and enhance lead generation over competitors, to name a few.
“Data centre and residential proxies make in-house data scraping possible by acting as intermediaries between the requesting party and the server. The choice of either type depends on the business use case, with residential proxies being most suitable for more challenging data targets and/ or specific geographic locations.
“Not every company has the resources to conduct data extraction in-house. In those cases, outsourcing a trusted solution is ideal because it can free up resources to focus on data insights rather than being overloaded by challenges associated with data acquisition,” concluded Mr Cerniauskas.
Now more than ever before, IT and procurement must come together…
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In a bid to survive and prosper, businesses are either moving forwards through innovation while others are hunkering down to secure initial and long-term survival. Which approach proves more successful remains to be seen, but as we move together, cautiously or optimistically, we need to consider our actions of today. Starting with leadership, IT and working closer with procurement.
Lockdown is a word we all now share. But lockdown means far more than simply staying at home. Lockdown is a behaviour which many companies have adopted in recent months, a behaviour that is required to enable survival.
This lockdown behaviour is, in part, demonstrated by looking at the job market. The first ‘hot’ roles that grew sharply soon into the UK pandemic were in finance, followed by procurement. Across sectors, roles which could ensure structure to finances, conserve immediate cash and renegotiate to save some money in the mid and long term, all grew sharply. Companies were effectively managing their financial risk exposure.
Managing down this risk of exposure by limiting activity to core activities, limiting cash, and cutting spend, gives more financial headroom, but will it provide a future for those same companies? That future is one that will be measured by stakeholders, shareholders and critically the actual teams of employees who need to feel confident that they will get the funding, latitude, investment and accountability to grow again.
Widening the business lens
This, interestingly, is a time when employees who perhaps previously hadn’t really had a wider lens on the businesses in which they work in, are now becoming more aware. The agenda in many businesses has been about customers and that remains as true during these tough times as it ever was. But, perhaps the wider ‘IT’ engine room of the business had been less interesting to some parts of some of our teams.
In addition to finance, bigger constraints came into play as the landscape continued to change. Some organisations have seen a game-changing shift in their competitors and are in defence mode, protecting their businesses from both new and existing competitors in an urgent bid to maintain cash flow, remain solvent and survive the events of 2020.
Radical and sudden operational and supply chains have also been impacted and disrupted. Some companies are struggling to leverage distribution channels and to provide enough product/service availability to keep up with demand. The ability for IT systems to accurately predict customer/client demand for products and services, in the face of competitive disputers taking full advantage of change in customers’ demands due to the pandemic, requires IT platforms capable of balancing short-term focus against long term growth opportunities in a business. This, without overplaying it, is a major challenge for senior technology leaders. The propensity for historic underinvestment in technology, that same technology which now safe-guards the future, might mean any current near-term gains might well become rapidly eroded as today’s tactical gives way to tomorrows’ strategic catch-up.
These company lockdowns are being seen by many of us. So, more than ever, having a responsive IT team with definitive and exemplar leadership driving survival in some technology led companies who are consolidating revenue streams, divesting businesses, rationalising products and reducing proposition of services to help to drive a simpler business, is going need high emotional engagement, experience and intelligence, and exceptional collaboration.
IT and Procurement: hand in hand
Along with simplifying, many companies are reducing their trading risk by diversifying supply chains across multiple vendors and partners, to enable more transparency and security across supply chains. The complexity this adds to IT platforms can in some legacy IT stacks, be exponential.
This technology complexity is overlaid with another major contributor, and key strategic partner to IT, procurement.
Procurement teams are actively reviewing IT and other framework contracts, scrutinising big spend items, and assuring contractual performance with suppliers. Investigating cost reductions due to the scaled back operations of product or services outlined above, as well as removing over-licensed software, matching capacity that was built into contracts with actual need and achieving other low-hanging fruit to reduce ongoing expenditure is a joint collaboration where IT and Procurement will only succeed together.
In recent work I have led ( before the pandemic) I have been able to achieve year-on-year savings in operating expense in excess of 50% through partnering effectively with Procurement. By adopting a focused strategy on what products and enhancements can deliver proper near-term and lasting value, and by challenging and removing legacy IT, outdated working practices and processes, reducing the ‘belt-and braces’ culture and implementing a ‘what matters’ culture.
This ‘what matters’ approach was achieved through a rigorous and transparent process involving team members through the organisation, at all levels, working in collaboration with partners and suppliers to look at creative ways to finance payments, defer spend, extend contractual Terms and to avoid ‘hanging-on’ to platforms which, in the very near term, will become exposed as obsolete. In my recent conversations, one CEO said to me that we have a world class ERP platform but it’s about ten times the size we need – we’re massively over-engineered’. He is acutely aware this needs to be dealt with. In my own recent past, I have taken over 20% out of the cost base for a single large business-wide platform. A reduction of millions of pounds. This was achieved by being focused on right-sizing the platform the business needs for now and not allowing vendors to charge for licenses for future growth when that growth, right now, is uncertain.
A culture of change
In driving this change there is a huge reliance on having the best possible people engagement, exceptionally high amounts of transparency and trust, and a culture which embraces the uncertainty openly, and with empathy. Being transparent and operating with empathy will give businesses more of a license to do the right things and the hard things and get as much support as possible.
Businesses that operate counter to this, with secrecy, obfuscating their thinking and sharing their decision making until as late as possible, will lose trust of their teams, both in the short term and long term. How many of us have seen M&A activity destroy value because of the wrong behaviours of an acquiring company? Good leaders in good companies remove information silos within their organization (including those among leadership roles) and focus on more cross-functional collaboration, but this is not all we need to consider as senior IT leaders.
Our teams, especially in times of immense change, also need support. The investment made in supporting people in time of need pays dividends in the future. The key to this is allowing flexibility within the operations of the business. During the pandemic, a number of my team worked split days, early morning to mid-morning and then evenings. It worked well and was well received, allowing for home schooling and other home life challenges. But, this flexibility is not something for a few months, this is change for the long term. How then, as our businesses rely on being more agile, can IT teams be collaborating yet separate and discontinuous in time? The role of IT leaders going forwards is to provide a far clearer outcome-based approach to working, enabling people to organise themselves not just to meet when needed, but to work when needed. This needs new skills and behaviours. Skills of collaboration, not being afraid to ask for help and readiness to be flexible to expand in tangential roles. This new way of working is going to take time to settle in organisations; employers, leadership, managers and their teams will need help long into the future of how to adjust, while working productively and collaboratively.
Change is necessary
Productively and collaboratively is not enough anymore. We also need to keep everyone safe, both physically and mentally. Leaders and managers, no matter how functional and historically distant from deep rooted emotional intelligence thinking they are, also need to become significantly more aware. Development will be needed as part of basic early-career management education in a range of topics as far ranging as diversity and systemic bias in decision making in the workplace, to building products with sustainability and carbon neutrality in mind; maybe with objectives and performance linked to this more extensively than is found today.
Having recognised that functional skills alone are likely to be a smaller percentage of the competency of the next generation of first-time leaders, what other capabilities are needed in the best of the next generation of leaders?
Characterising these skills has been driven forward by the pandemic, but clear expectations would include critical thinking, creativity, and inclusiveness driven from both curiosity and a growth mindset all deployed in an organisation that shows both flexibility and adaptability. These operations must be prepared to be courageous and challenge the status quo in an empathetic and technology inspired way.
Being a next generation leader in this new and complex world will take some investment. Being a current generation leader living with today and developing teams for tomorrow will require all of us to draw on everything we have learned to date and double it up, This is certainly the case if we want to be the beacons of hope, inspiration and confidence for those we lead, coach, mentor and develop today.
As we all think about the new world with this technology issue showing us some of the possibilities of our future, I think deeply about the ever-growing challenges of being a technology leader in society, both in industry and globally.
The once simple(r) operating model of developing great products, wrapping great service around them and giving great value would likely mean success. Alas, this is a formula that has long since passed and the final bastions of companies that could operate in that way, have, in no small part to Covid, been rapidly eroded.
The future is ours to see
Having started with a conversation about finance, procurement and risk, we return to the conundrum; How do keep the spirit of innovation, effectiveness and efficiency in our teams alive, whilst at the same time cutting cost, driving wastage down and surviving?
Will we see a resurgence of command and control style operating models? Or will waterfall style driven deliveries prevail? For the Agile proponents reading this, will we see a reversion to less iterative, less accountable, less empowered teams of technologists, and arguably less innovative thinking?
Or, as some are demonstrating, will fortune favour the brave and the courageous?
Will we see encouragement to experiment and invest in new ideas, with quick adaptation, pivoting in response to the recent disruptive events?
Will we see a further acceleration of the latest thinking, the use of AI, blockchain, cloud, ML, IoT, edge computing, at every level of our operations from changes in our supply chain to enable better transparency and security?
Will we see changes internally unlocking more efficiency through new models of operations? models that complement new technologies platforms and underpin remote working
Out of the shadows
Regardless of the delivery model, approach and style, it’s clear several companies are pushing forwards on some big-ticket innovation items in readiness for their futures.
Others are hunkering down.
No strategy can yet be judged as right or wrong, it is too early to tell.
Both hunkering down and investing might lead to initial and long-term survival, but as we move together, cautiously or optimistically, we need to consider our actions of today.
Never has the shadow we cast as IT leaders been so evident. Never has IT output, and the trust in IT, been so high. Never has IT been so central to the future, as it is now.
IBM and ServiceNow today announced an expansion to their strategic partnership designed to help companies reduce operational risk and lower…
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IBM and ServiceNow today announced an expansion to their strategic partnership designed to help companies reduce operational risk and lower costs by applying AI to automate IT operations. Available later this year, a new joint solution will combine IBM’s AI-powered hybrid cloud software and professional services to ServiceNow’s intelligent workflow capabilities and market-leading IT service and operations management products.
The solution is engineered to help clients realise deeper, AI-driven insights from their data, create a baseline of a typical IT environment, and take succinct recommended actions on outlying behavior to help prevent and fix IT issues at scale. Together, IBM and ServiceNow can help companies free up valuable time and IT resources from maintenance activities, to focus on driving the transformation projects necessary to support the digital demands of their businesses.
“AI is one of the biggest forces driving change in the IT industry to the extent that every company is swiftly becoming an AI company,” said Arvind Krishna, Chief Executive Officer, IBM. “By partnering with ServiceNow and their market leading Now Platform, clients will be able to use AI to quickly mitigate unforeseen IT incident costs. Watson AIOps with ServiceNow’s Now Platform is a powerful new way for clients to use automation to transform their IT operations.”
“For every CEO, digital transformation has gone from opportunity to necessity,” said ServiceNow CEO Bill McDermott. “As ServiceNow leads the workflow revolution, our partnership with IBM combines the intelligent automation capabilities of the Now Platform with the power of Watson AIOps. We are focused on driving a generational step improvement in productivity, innovation and growth. ServiceNow and IBM are helping customers meet the digital demands of 21st century business.”
Organisations are under pressure to deliver innovation and create great experiences for customers and employees, all while driving efficiencies and keeping costs and IT risks down. Yet in today’s technology-driven organisation, even the smallest outages can cause massive economic impact for both lost revenue and reputation. This partnership will help customers address these challenges and help avoid unnecessary loss of revenue and reputation by automating old, manual IT processes and increasing IT productivity.
IBM and ServiceNow will initially focus on:
Joint Solution: IBM and ServiceNow will deliver a first of its kind joint IT solution that marries IBM Watson AIOps with ServiceNow’s intelligent workflow capabilities and market-leading ITSM and ITOM Visibility products to help customers prevent and fix IT issues at scale. Now, businesses that use ServiceNow ITSM can push historical incident data into the deep machine learning algorithms of Watson AIOps to create a baseline of their normal IT environment, while simultaneously having the ability to help them identify anomalies outside of that normal, which could take a human up to 60% longer to manually identify, according to initial results from specific Watson AIOps early adopter clients. The joint solution will position customers to enhance employee productivity, obtain greater visibility into their operational footprint and respond to incidents and issues faster.
Specific product capabilities will include:
ServiceNow ITSM allows IT to deliver scalable services on a single cloud platform estimated to increase productivity by 20%.
ServiceNow ITOM Visibility automatically delivers near real-time visibility from a native Configuration Management Database, into all resources and the true operational state of all business services.
IBM Watson AIOps uses AI to automate how enterprises detect, diagnose, and respond to, and remediate IT anomalies in real time. The solution is designed to help CIOs make more informed decisions when predicting and shaping future outcomes, focus resources on higher-value work and build more responsive and intelligent applications that can stay up and running longer. Using Watson AIOps, the average time to resolve incidents was reduced by 65 percent, according to one recent initial proof of concept project with a client.
Services: IBM is expanding its global ServiceNow business to include additional capabilities that provide advisory, implementation, and managed services on the Now Platform. Highly-skilled IBM practitioners will apply their expertise to facilitate rapid delivery of valuable insights and innovation to clients. IBM Services professionals also will introduce clients to intelligent workflows to help improve resiliency and reduce IT risk. ServiceNow is co-investing in training and certification of IBM employees and dedicated staff for customer success.
For example, using the IBM and ServiceNow joint solution, a bank will be able to obtain a full view of an incident, from start to finish. With recommendations and deep diagnosis from Watson AIOps, a service agent will be able to quickly understand the incident, without ever leaving the ServiceNow ITSM platform. Leveraging more than an agent’s own knowledge and research, Watson AIOps can provide anomaly detection along with automated recommendations from the historical deep analysis of prior incidents. Using incident management tools from ServiceNow, actions and insights can be recorded for auditing purposes and for leveraging future insights. Watson AIOps can then push important context to tickets, discovered only via AI algorithms and baselining techniques, helping to make the data more useful to agents and retraining the AI over time.
“Businesses are facing increased pressures to match the digital pace of a cloud-first market in order to meet the demands of their customers,” said Stephen Elliot, program vice president, DevOps and Management Software, IDC. “The C- suite is transforming workflows to deliver insights and automation for more efficient customer engagement models and cost containment strategies for the business, while simplifying IT operations and increasing collaboration between IT and business stakeholders.”
Today’s news strengthens the partnership previously announced by IBM and ServiceNow to help enterprises simplify IT operations for multi-cloud environments.
A new ‘smart infrastructure’ and carbon-neutral energy era will see the US state emerge a global leader to fight Climate Change.
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New Mexico is launching a new ‘smart infrastructure’ and carbon-neutral energy era on a grand scale, after its 2019 Energy Transition Act (ETA) positioned the US state as a global leader to fight Climate Change.
Its ambition will be enabled by partnership between The Agile Fractal Grid (AFG), developing a new integrated power and broadband network, and Cityzenith, creator of the revolutionary Digital Twin platform SmartWorldPro.
Digital Twins are virtual replicas of buildings, infrastructure and physical assets, fully interconnected with the data in and around them that optimize project performance, and help predict and visualize future outcomes. Delivering value across multiple functional areas like maintenance, energy consumption, space utilization and traffic management, Cityzenith’s Digital Twin platform, SmartWorldPro, aggregates and analyzes information needed to design, build, and run projects at any scale.
The state and these partners predict the multi-billion-dollar project will transform life and the economy in New Mexico (pop. 2.35m, GDP $104bn) and ripple outwards as other energy operators, states and nations see the benefits: 1,000s of new businesses, 100,000s of new jobs, better and faster data links, higher infrastructure efficiency, and up to six new smart cities.
The 5th largest US state’s fossil fuel power will also be replaced by a cleaner ‘smart’ energy network, featuring North America’s biggest solar and wind array, and generating ample surplus for trading on energy markets.
Those living there will experience ‘smart’ IT benefits in entertainment and hospitality venues, retail, transport hubs, health and hospitals, security, telecoms, power utilities, employment, and manufacturing.
Key to all this potential is Cityzenith’s SmartWorldPro, a breakthrough software able to unify all planning data and diverse software. It speeds hi-res 3D Digital Twin modelling of the replacement infrastructure towards efficient design before construction, and streamlines ongoing operation and development of the new assets.
Cityzenith’s CEO Michael Jansen said: “It’s the kind of visionary project SmartWorldPro was designed for and we are already modelling New Mexico’s biggest city, Albuquerque (915,000) before rolling out across the state over a 10-year program.
“SmartWorldPro can integrate with AFG’s futuristic portfolio of AI, smart building, and other technologies towards a ‘Smart Connected Community’ for cities, large venues, and even whole states.”
AFG CEO John Reynolds said: “The project is a highly efficient deployment of services for 21st century public, commercial, and industrial needs.
“But individuals will also be impressed by Living-as-a-Service™, the emerging bundled entertainment, ticketing, hospitality, housing, transportation, food and beverage, wellness, and utilities platform.
“And Cityzenith’s SmartWorldPro means we can show and deliver this data-rich ‘smart lifestyle’ to everyone in New Mexico – urban and rural. Longer-term, this sustainable power, comms, and lifestyle ‘reset’ could span North America, and national 10GB broadband maybe just 10 years away.
Michael Jansen added: “It’s easy to see the benefits for New Mexico, but this cutting-edge technology can go global, pushing back against urban pollution and Climate Change and trillions in economic and environmental damage.
“Cities occupy less than 2% of the Earth’s surface, yet consume 78% of global energy and pump out 60+% per cent of greenhouse gas emissions* while 100 megacities like New York, Seoul, Hong Kong and Shanghai produce a shocking 18% of those emissions.
“So, partnership with fellow visionaries at AFG also fits our long-term ‘Clean Cities – Clean Future’ mission.”
This follows the recent media coverage across the US where Cityzenith has pledged its SmartWorldPro technology to the worlds most polluted cities
While the virus has presented many challenges, it has also opened up opportunities for increased industry security and customer relationships. Agnė Selemonaitė, Deputy CEO at ConnectPay, explains.
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1. Increased industry security
Banks and other financial institutions have been a major target for scammers since the beginning of the pandemic; in fact, cyberattacks between February and April alone spiked an astonishing 238%. The increased volume of threats has encouraged companies to face the situation head-on and implement new safeguards.
“Putting more safeguards in place will benefit market players long after the crisis has blown over, as market players will be better equipped to deal with the constantly evolving digital threats,” says Selemonaitė.
2. Growth of digital payments market
Alongside the World Health Organization encouraging us to go cashless, the crisis has stimulated the growing amount of e-payments. Selemonaitė notes Sweden’s example: amidst the uncertainty, Sweden’s central bank signed an agreement to gain access to EU TIPS platform, which will act as the basis for the country’s own platform for instant payments.
“Sweden’s approach shows that in order to be in a better spot to satisfy increasing demand for faster, more convenient services – you need to be proactive,” Selemonaitė explains. “We follow this approach too; having realised our clients’ needs for greater options amidst quarantine, we integrated more payment methods into our Merchant API.”
3. Accelerating digital banking development
As banks had to severely limit their working hours during the lockdown, digital banking picked up the slack to accommodate the financial needs of people working from home. “As the new wave of customers sieged the system, faster development of banking services took precedence,” says Selemonaitė. In the US alone, over 45% of people have changed the way they bank amidst the crisis, and according to a European customer survey by McKinsey, there has been a 20% increase in digital engagement.
4. Enhanced customer experience
The aforementioned McKinsey survey showed that people who are highly satisfied with their digital banking experience are two-and-a-half times more likely to open new accounts with their existing bank than those who are just just satisfied. The aftermath of COVID-19 is expected to continue down the path of developing simplified UX to attract and retain clientele.
“Although requiring meticulous work, constant UX evaluation can greatly benefit product credibility and client retention, for instance, our first UX update led to doubling our monthly conversions,” says Selemonaitė. “It is likely that we will see a more customer-focused approach in the post-crisis industry too.”
5. A catalyst for fintech companies
The ’08 financial crisis gave a boost for the fintech industry, as, at the time, people were losing trust in the system, and in legacy financial institutions. In the aftermath, some entrepreneurs parted ways with the concept of traditional banking, aiming to present the market with a more technologically sophisticated solution.
“This time, the crisis could have an even greater impact for fintechs, as well as regtechs, as they rely on solutions fintechs can develop,” adds Selemonaitė. “Unfavourable circumstances drive the need to innovate across interconnected sectors.”
Marius Galdikas, CEO of ConnectPay, explains the role of digital finance during a pandemic, and how it has changed society forever…
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Could you tell us a little about your background?
I originally come from the field of technology. I’m a physicist, and I’ve always marveled at engineering and technology – digital technology, specifically. Through the years, I shifted into products and then into fintech, which was very exciting to me, because fintech is about people and technology. It’s about good people that understand regulation, understand business and understand technology. I am now the CEO of ConnectPay.
Data shows that cyberattacks on financial institutions spiked enormously between February and April this year – why is that?
I think the main reason it happened is actually at the core of the pandemic; the pandemic means people are locked up at home, so you end up with many more users of digital financial services than there usually are. Cash is unusable at this time, when you’re locked up, so you have a lot of new customers in digital finance – some of them are tech savvy and others are not. There’s a lot of people that never used digital financial services, and now they must. So you have this influx of customers into the market, that’s number one. Number two, governments reacted and we had these stimulus programs released, which means there’s a lot of funds being distributed through different programs. And many of those funds are meant for relieving the consequences of joblessness.
So you have a lot of new funds moving around and, because all of it is happening in the digital finance area, I think that stirred up the whole fraudster community. Fraudsters are working hard, now, to try and use the situation to steal funds from people, which results in information security threats and cyber attacks. Cyber attacks are means of achieving the goals for fraudsters.
How has cyber security adapted to combat this issue?
It’s a very big challenge to tackle. Number one is, all of the financial services providers that already operate online, they have their assets online, they have the required technology and so on. Could that have been changed so fast? No. Information security requires a lot of work and insight, and it’s a lengthy process to deploy specific tools to combat that. So I don’t think much has changed, but I think a realisation came that fraud prevention is now a very important area.
As well as increased security, what have been some of the digital baking trends since the emergence of COVID-19? How have people changed the way they handle money?
The stride towards a cashless society has obviously been accelerated, forcefully. Some countries and some companies will do better than others, but I think majority of the change is yet to come, because the pandemic will result in economic hardship and economic hardship will result in changes, in innovation, just like we had in the 2008 crisis. That gave birth to Bitcoin crowdfunding, sharing economies – all of that was an outcome of financial crisis, and I think we will see something come up that we cannot even imagine right now. What is the driver for those changes? Previously in 2008, there was a huge loss in trust towards financial institutions. The financial sector was the reason behind the crash, and so trust was lost, and all of these instruments – crowdfunding, sharing economy, blockchain technology – were targeted specifically at, “Hey, we don’t trust financial institutions anymore; what can we do to exclude them from the economy altogether?”
So what will happen now, I think, will be the same, depending on the size of the downturn. I’ve been hearing that in the Western and European developed markets, countries have been hit very hard, financially, by the pandemic. This will continue; there will be financial problems. It’s different because, previously, everybody lost jobs and salaries went down. Now, there’s a different aspect to what the hardship will be like, and it will result in something new.
What are your thoughts on a cashless society? Do you think it’s inevitable or are there barriers? And if it does happen, how far away do you think it is?
I do think it’s inevitable. I think the entire world is going towards a cashless society at different speeds; for example, the Nordic countries are the biggest cashless societies in the world, whereas the UK is probably five years behind them. In the US, cash is still very important –people love cash in the States – so they’re about 10 years probably behind the Nordics. However, the direction is the same. It’s all going towards cashless. The reasons for it is obviously internet penetration and mobile phone penetration – those are the key factors towards how fast will we get to cashless society, country-by-country. But also, what we need to understand is that cashless society also sort of puts a strain on the society as a general, because elderly people might be excluded from this market or might have trouble or problems adapting to the cashless environment. However, sometime, we will all be there.
The push towards the cashless society is driven by two things: one is the new consumer. These are new people, the new generation, and exchanging funds should be as simple as messaging or using social media. So one driver is this new generation that drives the digital economy and the cashlessness, because they live in the digital world. The other part is the actual financial institutions that drive the cashless society, but their reasoning is different – it’s efficiency. They want to cut costs. They don’t want to have physical retail locations. Nobody wants to transport or count cash. There’s fraud issues related to cash, so the financial institutions are driving it from another perspective.
Do you think it’s safe to say that digital banking is no longer a luxury, but a necessity?
Absolutely. We see that the world is much more fragile than we thought. We are all forced to go online, work from home, access our financial instruments from home, shop online, get government funding and stimulus online without going anywhere, and so on. It is a necessity, it is definitely not a luxury and everybody will have to adapt to that. I just hope it becomes less painful for everybody to transition, and that people don’t lose out on their money through fraud.
We spoke to Carlene Jackson, CEO of Cloud9 Insight, about the transformative power of both technology and company culture…
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What led to you launching your business, Cloud9 Insight?
I started Cloud9 about 10 years ago, and it was an opportunity to support small businesses to deploy CRM in the cloud for the first time, because I saw a trend of more and more clients moving to the cloud. There’s an opportunity to help clients with making the most of their data in the SME space, plus they’re able to use Microsoft technology to get more insights – hence the name Cloud9 Insight. At the time, most of my competitors were still looking to sell on premises-software, but I saw a gap in the market.
Historically, what I’d seen with enterprise clients I had worked with, is that CRM projects had been at least a year long, and often you’d question whether the business had moved on since the definition stage of the project, and if it was still fit for purpose. I think projects these days need to be a lot more agile to support clients with business transformation; for me, working with cloud technology allows that agility.
There’s a quote on your website where you say you have a love of change and disruption – what does that mean to you, as a tech leader and expert?
I think it comes naturally to me. I’m moderately dyslexic, and some say that dyslexics are quite creative people. I find it hard to read anything without having a pen and paper in my hand, because I always got lots of ideas, and I think part of the reason that entrepreneurs have often been so successful as dyslexics is that we often think differently. If you look at tackling problems the same way they’ve always been tackled before, then you’ll probably come up with the same answers – but if you can address things differently, then maybe you might come up with a better opportunity.
When I started my business, I moved almost immediately to the Alps; I hadn’t worked in the Microsoft channel, and I had no preconceptions about what did a Microsoft partner selling CRM did. That meant my business model turned out very different to a lot of others. I also recruit a lot of young people into my business – which is why I’ve set up an apprenticeship programme, called Vantage Academy – and having them involved in the business has helped maintain that creative, disruptive model.
So is company culture very important to you?
Definitely. I used to work at IBM, and it was quite normal to travel around different offices around the country, visit your clients and just pop in and hot desk. Depending on which office you went to, some people were a bit more chatty and you got to hear a little bit more about what they’re doing. But what I noticed about my business, as it was growing, was it was becoming departmentalized and siloed in the same way that many of my clients complain about. I didn’t want that; I don’t want the salespeople not working with the support people, or projects people, and so on. There’s so much opportunity to learn when you have conversations with colleagues across different parts of the organisation, and I really wanted to make sure that we worked as a team.
I know you’re a big advocate for diversity in the workplace, and in the general realm of technology – what are some of the benefits diversity can bring?
First of all, organisations need to make sure that the demographics of who they employ reflects the demographics of who you’re selling to, because it’s difficult to understand them otherwise. Certainly in a B2C market, having representation across age groups in your workforce is really important. What I’ve found is that what really motivates the older generation is the ability to be a mentor and a leader to those that don’t yet have the experience. They want to give back.
As for younger people, they have energy, ambition and hunger to pass on to across the workplace, allowing great things to happen, and I think it increases the performance of my overall team. Diversity could also be gender; certainly in many sectors like tech and oil and gas, it is heavily biased towards males, and a lot of my staff do tell me that it’s nice to have a more balanced workplace.
I’m a lot more people centric than maybe a lot of my peers might be; I like to embrace the people and the value of people in businesses, both within my clients and within my own team. That’s really important to me.
You wrote a piece about how working from home is changing attitudes to work, specifically citing children gatecrashing video calls and how that represents how the life part of work-life balance can no longer just be hidden away – with technology supporting people really successfully to work from home, will things ever go back to ‘normal’?
I think there’s no going back to ‘normal’, for sure. The old way is not going to exist at all. There’s two types of businesses: those who are probably kidding themselves and just about surviving, and those who are probably a lot more agile and forward-thinking, who are going to look at the trends that have been happening, jump onto those trends and allow a lot more flexibility around people working from home.
The other great thing about this mobility of the workforce, is that maybe your team don’t even have to be in the vicinity of your office – maybe not even the vicinity of the UK. Maybe we can tap into where the best talent is.
How do you think female entrepreneurship can be encouraged in tech, and other STEM industries?
I love that question. One of the exciting things about me being able to set up an apprenticeship business is I’m definitely going to use my voice and position to be a great advocate for younger females to come into the tech sector. I think there might be a perception that you need to have technical skills, but having great leadership skills, having creative skills are also very important and greatly valued in the sector. It’s just trying to open the younger generation’s mind, especially for young females, as to the skills that they have inherently, in great abundance, how are they valued, and how can they use those skills to make a difference.
And for me, technology is a great enabler of change and making a difference. I’d like to see schools working more with younger people to help them feel confident about working with technology. When I hire people that are fresh out of school, I’m absolutely dismayed by how few skills they have in using technology. That crosses all genders, but it’s really sad to see the percentage of females attending degree courses that are highly attended by males. However, when you look overseas at places like Poland, they have a much greater balance, so I think we have a lot to learn about what is it that overseas countries are doing that we’re not. I suspect that starts at a young age in school, and if we could create more entrepreneurs, then our economy will be much more successful.
So it’s about encouraging STEM topics in schools, full stop, not just for girls but all genders, in order to fill that skills gap.
Yes, absolutely. I think that if there’s more integration between businesses and their involvement in schools, and that opportunities to learn entrepreneurship and problem-solving using technology exist, that might open their eyes.
Loyal subscribers ‘rejected’ and ‘ignored’ by brands that show favouritism to new customers
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TV subscription brands are their own worst enemy when it comes to losing customers, according to an in-depth report launched today by Singula Decisions, a specialist in subscriber intelligence.
The new findings highlight that while brands obsess about the problem of ‘churn’ they only have themselves to blame for customers cancelling their subscriptions. Respondents are left rejected and ignored by OTT brands that prioritise winning new customers instead of building valuable relationships with existing ones. In addition, brands often avoid customer communication completely for fear of alerting consumers to the fact they are being billed for a service they may have grown tired of, and that futile efforts to retain customers only truly start when they request to cancel.
Speaking about the findings, Bhavesh Vaghela, CEO of Singula Decisions, said: “Brands spend a huge amount of time and effort building predictive models and using analytics to identify potential churners and understand why they are leaving – but what they often don’t consider is that they’re the biggest part of the problem! By the time a subscriber has requested to leave, the damage has been done. To reduce churn, brands must change their mindset; efforts to build a long-term, happy relationship must start at the beginning, not a short burst at the end to try and save a customer that’s cancelling.”
Retain subscribers
The ‘Psychology of a Subscriber’ research has highlighted the need for brands to do more to listen, understand, and engage with customers throughout the entire journey. Learning what makes each individual subscriber tick and responding appropriately – from the moment they join, through the power struggle over billing, and even the pain of cancellation – is essential to the long-term strategy of reducing churn and building positive, long-term relationships with subscribers.
Report author and Director of QualiProjects, Jennifer Whittaker, said: “A lack of focus during the early stages of the customer journey means loyal subscribers can feel rejected by brands, and that they are not getting enough value. It’s disheartening for loyal subscribers to see favouritism shown to new customers who have not yet spent any money with the brand. When brands avoid loyal subscribers due to a fear of losing them if they are reminded too overtly of their monthly spend, they are unconsciously sabotaging what could have been a healthy relationship.”
Make cancellation easy
Those surveyed also commented that communications and marketing offers are rarely personalised – treating all customers with a one-size-fits-all approach instead of individuals with unique desires and needs. The process of cancelling was also flagged as a major problem by consumers who feel there are too many barriers, and that some brands act in a cynical way, using interrogation tactics and pressure to get them to stay or find out why they are leaving.
“Churn is inevitable – and doesn’t have to be viewed negatively. Some cancellations are involuntary, either due to financial difficulty or a change in lifestyle, so it’s important that brands listen and make it easy and painless for customers to go. Giving the subscriber a positive experience at the end – by making it easy for them to leave and rejoin, and providing great customer service – means there’s a strong possibility that they will return in the future,” Vaghela added.
Churn
This is the final paper in a series of three that looks at the ‘Psychology of a Subscriber’. The latest report focuses on ways brands can look to reduce churn and win back customers through better communication and creating positive sentiment with loyal subscribers. The research explores how brands can:
Create valuable engagement with loyal subscribers and give rewards for their commitment
Shift from a cold, transactional relationship to a warm, emotional one
Enable customers’ wishes for flexible subscriptions that offer easy ways to ‘dip in and out’
Make it easy for customers to cancel and rejoin, generating positive sentiment for the brand
Reimpress past subscribers by gaining permission to keep in touch, while maintaining login details and watchlists so they feel remembered and like they’ve ‘come home’ when they rejoin
Download a copy
The ‘Psychology of a Subscriber: Part 3 – Churn’ report explores the psychological and emotional drivers that consumers experience when subscribing to an OTT service and can be downloaded here.
The qualitative study, which was conducted and authored by Qualitative Researcher, Accredited Psychotherapist and Director of QualiProjects, Jennifer Whittaker, and Business Psychologist and Researcher, Katharina Wittgens, explores subscriber attitudes towards OTT TV brands in the UK and US, gaining a deep understanding of how consumers think, feel and behave throughout the customer journey.
Join the webinar
There will be an opportunity to hear the authors of the study discuss the research with Colin Dixon, Founder and Chief Analyst of nScreenMedia in a live webcast on October 19th at noon Pacific Time (8pm BST, 9pm CET). This webinar is part of the Let’s DEW Lunch webinar series from Digital Media Wire and you can register to attend here.
Ray Stanley, CIO and VP of Marian University, tells us how an IT strategy empowers the student to unlock their true potential.
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Our cover story this month is an exclusive look behind the scenes at Indianapolis’ Marian University to see how its unique technology strategy puts the student experience front and centre. Ray Stanley, CIO and VP of Marian University, tells us how an IT strategy empowers the student to unlock their true potential.
“In higher education, we have many different groups of customers. We have the staff, faculty and students and so being a driver of technology is critical,” explains Stanley. “But you also have to make sure that you’re listening to your entire customer base as a whole and that you’re understanding and aligning with the trends in higher education.”
“In higher education, the industry kind of forces you to go where it needs to go in its offerings,” Stanley explains. “You also cannot force technology and expect adoption. You’re not here to support a business to make a profit, your goal is to support the faculty to instruct a student for successful graduation and it’s a completely different mindset and a completely different model.”
Elsewhere, this month, we spoke to Carlene Jackson, CEO of Cloud9 Insight, about the transformative power of both technology and company culture. Marius Galdikas, CEO of ConnectPay, explains the role of digital finance during a pandemic, and how it has changed society forever. Plus, AgnėSelemonaitė, Deputy CEO at ConnectPay reveals five opportunities that COVID-19 has created for the digital banking sector…
How AI-driven technology is gaining momentum in the digital payments market, both in backend operations and customer-facing payment systems…
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Over the past few years, the digital payments market has exhibited steady growth. To keep up with the increasing number of transactions, companies are continuously looking for ways to utilize new tools that would help ensure smooth and efficient processes. Currently at the heart of this lookout is the use of artificial intelligence and its use-cases in reducing the number of false positives in fraud and AML monitoring, and facial recognition-based payment verification.
Marius Galdikas, CEO at ConnectPay, has shared his insights on the current trend of harnessing the power of intelligent systems and their role in fraud prevention and streamlining transactions.
AI-enabled facial recognition
The pandemic gave precedence to AI-driven facial recognition solutions. A group of restaurants and retailers in California combined the need for stemming the spread of Covid-19, and the task of handling payments securely. The effort resulted in a face-powered payment confirmation system, or PopID. According to Marius Galdikas, the pay-by-face idea bears great potential as it requires a lot less engagement from the customer’s perspective, which adds to its appeal.
“Such AI-powered payments decrease the required effort from the customer to the bare minimum,” said Marius Galdikas. “Eliminating the extra steps in the process—taking out the card, entering the required PIN—is likely to improve perceived shopping experience, as customers can focus on a grab-and-go approach and save time. This leaves very little room for hassle, which, in fact, may lead to increased shopping cart values too.”
Interruption-free transactions
While conducting a digital payment transaction, users want one thing above all else – a smooth, glitch-free experience, as unexpected lags are too much of a disruption for the modern-day customer. VISA has already attempted to bridge any possible outages by introducing a Smarter Stand-in Processing (Smarter STIP), which leverages deep learning to analyze past transactions before generating decisions to approve or decline transactions on behalf of issuers. The prototype is set to be released in October, and the smart stand-in solution may push other players in the payment industry to also look for additional measures that could help limit the number of declined transactions.
Listen to Marias on our exclusive episode of The Digital Insight:
“For merchants, a smooth payment process may be the single most important aspect in terms of retaining customers with the ever-decreasing attention span,” said M. Galdikas. “Bypassing issues related to system glitches could help avoid costly failures for both PSPs and merchants. In addition, combining such solutions with AI enables to adopt a more dynamic approach and deal with similar situations in a timely manner, without any noticeable mishaps for the customers.”
Fraud-resilient settlements
The past few months reemphasized the importance of anti-fraud measures, as having more users switching to online shopping instead of brick-and-mortar businesses resulted in skyrocketing levels of scams. The finance sector has already ramped up the cybersecurity spent to keep the fraudsters at bay.
AI can assist with recognizing patterns and exceptions, minimizing fraud for complex, high-volume transactions. Human error is one of the more pronounced weaknesses, so using task-specific AI to recognize dubious transactions will have a significant impact on the overall fraud resistance of digital payment systems. In addition, fraud prevention not only protects against the loss of funds but also saves businesses additional costs for legal settlements, which can add up to above $3 for each dollar lost to scammers.
“The circumstances surrounding Covid-19 and the growth of online fraud adds up to the stressors that urge both merchants and PSPs to deepen their search for novel security tools even more,” explained M. Galdikas, “thus AI-driven solutions are highly likely to become a must-have among tools for ensuring transparency and reducing fraud.”
Without a doubt, the real impact of AI usage in the digital payments market will reveal itself over time. That said, it seems a wider implementation of AI-driven integrations is inevitable, as it carries the promise of next-level actionable solutions that would sustain the growing demand for digital payments.
