Author

Jad Jebara

Published

8 September 2026

Estimated Read time

6Mins

Jad Jebara, Founder and President at Hyperview explains why the infrastructure that powers AI deserves just as much attention as trends such as tokenmaxxing.

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.

By Jad Jebara, Founder and President at Hyperview

Author

Simon Hayward

Published

7 August 2026

Estimated Read time

4Mins

Simon Hayward, GM & VP Sales International at Freshworks explains why AI needs to work effectively for mid-sized organisations to truly succeed.

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.

Written by Simon Hayward, GM & VP Sales International at Freshworks

Author

Dan Brightmore

Published

22 July 2026

Estimated Read time

9Mins

CPOstrategy spoke with some of the key speakers and leaders in attendance at DPW in New York… From AI and operating models to talent and strategic influence, procurement leaders gathered with a shared message: the profession isn’t simply adopting new technology, it is redefining what procurement itself should become

The theme of DPW New York 2026 – Recode – could hardly have been more appropriate. Across conversations with procurement leaders representing industries as diverse as financial services, media, pharmaceuticals, luxury retail, technology, industrial manufacturing and commercial real estate, one message emerged repeatedly: procurement is entering the most significant period of transformation in its history.

Artificial intelligence may dominate the headlines, but for practitioners leading transformation programmes inside global organisations, the conversation has already moved beyond the technology itself. Instead, attention is turning towards operating models, organisational design, talent, governance and the role procurement will play as businesses navigate increasingly complex commercial environments.

Rather than viewing AI as the destination, many see it as the catalyst for fundamentally redesigning procurement.

For several of the speakers CPOstrategy spoke to, ‘Recode’ wasn’t simply about software, it was about rethinking the function from the ground up.

Rina Patel, SVP – Chief Procurement Officer at Versant Media, described the company’s recent spin-off from Comcast NBCUniversal as an opportunity to reshape procurement into a trusted advisory function involved in deciding whether initiatives should happen in the first place, rather than simply executing purchasing decisions.

Others echoed that sentiment. Danielle Salyers, VP for Strategic Sourcing & Enterprise Contracting, at Allied Solutions, who has built procurement organisations from scratch on multiple occasions, viewed the theme through the lens of establishing entirely new operating models. At Semrush, VP for Global Procurement Alejandro Fernandez is living through a different kind of recode as the company’s procurement organisation becomes integrated into Adobe, forcing a rethink of how teams, processes and technologies come together.

Despite the different business contexts, the conclusion was remarkably consistent: procurement’s traditional operating model no longer reflects the realities of modern business.

Beyond Cost Savings

If there was one topic that united almost everyone we spoke to, it was the growing belief that procurement has outgrown its historical identity as a cost-cutting function.

Savings remain important, but few leaders now see them as sufficient for measuring success.

Patel argued that procurement should instead be judged on whether supplier decisions generate genuine business value, improve return on investment, enable revenue and support broader organisational objectives. Salyers similarly described cost savings as an output of procurement rather than its defining purpose, pointing instead to resilience, supplier strategy, risk management and business enablement as the measures that matter most.

Mercury’s Head of Procurement Bobbi Bachynski perhaps captured the changing mindset most directly. Working in a fast-growing fintech business, she sees procurement less as a savings function and more as business development tool, measuring success through the speed at which the organisation can launch products, enable teams and support growth.

That broader definition of value reflects the changing pressures organisations face today.

From geopolitical instability and tariffs to ongoing supply chain disruption, procurement has increasingly become central to helping organisations manage uncertainty. Angela Zou, Chief Procurement Officer at Cushman & Wakefield, noted that global disruption has elevated procurement’s importance within executive discussions, while Marc Behring, Director – Procurement Excellence at Messer Americas, explained that procurement’s ability to respond quickly to changing market conditions has become just as valuable as negotiating favourable contracts.

The profession is steadily moving away from being measured purely on how much money it saves towards how effectively it enables organisations to operate.

AI Starts with Better Processes

Despite the excitement surrounding artificial intelligence throughout DPW, one point generated almost universal agreement. AI cannot repair broken procurement.

Again and again, the executives we spoke to stressed that organisations must first simplify processes, improve governance and clean their data before expecting technology to deliver meaningful transformation.

Fernandez described AI as a magnifying glass that simply exposes existing weaknesses. Deploying sophisticated technology on top of poor-quality processes only embeds those problems more deeply into the organisation.

Others used even stronger language. Salyers warned that “if you automate chaos, you just get chaos faster,” while Zou argued organisations must “clean house before you automate or optimise”. Bachynski cautioned against allowing excitement around AI to distract organisations from building strong procurement foundations, preferring what she described as a measured and intentional approach rather than chasing hype.

Several leaders also highlighted the importance of data quality.

Behring believes that process and data remain the essential foundations for successful AI adoption because intelligent systems can only generate meaningful outcomes when they are built on structured, consistent information. Without that foundation, organisations risk investing significant time and money only to conclude that AI itself has failed, when the real issue lies in poor underlying processes.

The message from DPW was clear: successful transformation begins long before organisations deploy their first AI agent.

Humans Remain at the Centre

Although AI dominated almost every conversation, none of the procurement leaders we spoke to suggested technology would replace human expertise. Instead, the future appears to be one of partnership.

Routine, rules-based and transactional work is increasingly expected to migrate towards automation, freeing procurement professionals to focus on judgement, creativity, negotiation, supplier relationships and strategic decision-making.

Fernandez believes relationship management and stakeholder trust remain fundamentally human activities. Salyers described the ideal future as automating repeatable work while preserving human involvement wherever judgement, ethics and commercial trade-offs matter.

Sandeep Dhar, Senior Director – Center Global Category Management Leader at Johnson & Johnson, sees the operating model evolving into one where AI agents perform tactical activities while procurement professionals concentrate on strategy. Sean Park VP – Procurement, AP & Transformation at Arm similarly views AI less as a replacement than as a decision-support capability, enabling procurement teams to analyse suppliers, identify strategic partners and generate insights more rapidly than traditional reporting tools allow.

A Different Kind of Procurement Professional

As technology changes, so too does the profile of the procurement professional.

Several of the leaders we spoke to suggested that tomorrow’s procurement teams will require fundamentally different capabilities from those traditionally associated with category management and sourcing.

Fernandez believes the rise of large language models will reduce dependence on narrow category specialisation, instead rewarding analytical thinkers, creative problem-solvers and builders who are comfortable experimenting with new technologies.

Behring agreed that procurement professionals will increasingly need to understand how AI works, develop stronger technology skills and continuously adapt as new capabilities emerge. For him, the challenge extends beyond technology itself to identifying what the future procurement skillset should actually look like.

That evolution also requires organisations to rethink how they develop talent. Zou spoke about freeing procurement professionals from routine work so they can build stronger judgement and advisory capabilities, while Dhar argued that curiosity, continuous learning and asking better questions will become defining characteristics of successful procurement leaders.

Several executives also highlighted the importance of confidence. Patel encouraged procurement professionals at every level to become bolder, understand the businesses they support more deeply and build the commercial credibility needed to influence decision-making. Rather than waiting to be invited into strategic discussions, procurement leaders should demonstrate why they belong there by speaking the language of growth, revenue and business outcomes.

Technology is Changing, but Leadership Matters More

Despite AI dominating conference agendas, many leaders suggested that technology alone will not transform procurement.

Leadership remains the decisive factor. Gary Levitan, VP – Head of Procurement at Louis Vuitton, argued procurement earns influence through a compelling vision rather than software. Digital tools may strengthen procurement’s ability to execute, but they do not secure executive credibility on their own.

Others made similar observations. Several leaders stressed every organisation faces different priorities, making it dangerous simply to copy another company’s technology roadmap. Bachynski warned against benchmarking blindly, arguing that procurement functions should be designed around the unique commercial realities of their own businesses rather than following industry trends.

For Park, transformation succeeds when stakeholders understand the entire journey rather than experiencing disconnected process changes over time. Bringing employees into the transformation early, explaining the bigger picture and managing change carefully are just as important as selecting the right technology.

That emphasis on governance, communication and organisational change repeatedly surfaced throughout our conversations. AI may accelerate procurement, but successful implementation still depends upon people understanding, trusting and adopting new ways of working.

Why DPW Matters

While technology formed the backdrop to almost every conversation, many attendees described the greatest value of DPW as something far more human. Connection.

Time and again, these leaders spoke about the opportunity to compare experiences with peers facing similar challenges, distinguish genuine innovation from marketing hype and learn from successes as well as failures.

Fernandez described the event as an opportunity to separate “signal from noise” by hearing directly from practitioners rather than relying solely on vendor demonstrations. Zou highlighted the value of seeing collaborative customer and supplier transformation stories while building relationships with peers on similar journeys.

For Bachynski, DPW represents procurement’s “Super Bowl”. Not because of the product demonstrations, but because it creates opportunities for honest conversations about what is really happening inside organisations. Those candid exchanges help procurement leaders avoid repeating mistakes while accelerating successful transformation.

Others shared similar experiences. Behring pointed to the importance of understanding how peers are deploying AI and evaluating emerging technologies, while Park noted discussions with fellow procurement leaders often proved just as valuable as conversations with software providers. Dhar reflected on DPW’s rapid growth over recent years as evidence that procurement itself has become a far more influential discipline than it once was.

Perhaps the strongest message came from Salyers, who described DPW as a place where people challenge conventional thinking, inspire one another and return to their organisations better equipped to lead change.

Procurement’s Defining Moment

Although each executive represented a different organisation, industry and stage of transformation, they revealed an unusually consistent picture of procurement’s future.

The function is no longer content with measuring success purely through cost reduction. Instead, procurement leaders are redefining their role around business enablement, resilience, commercial insight, supplier innovation and enterprise growth.

Artificial intelligence will undoubtedly accelerate that evolution, but only where organisations first establish strong processes, clean data and effective governance. Automation will increasingly handle transactional work, allowing procurement professionals to concentrate on the uniquely human capabilities that technology cannot replicate: judgement, relationships, creativity and strategic thinking.

The challenge now is not simply adopting AI. It is recoding procurement itself.

That was the unmistakable message running through DPW New York 2026. The organisations that succeed will not necessarily be those deploying the greatest number of AI tools. They will be those prepared to rethink operating models, develop new skills, redefine success and position procurement as an indispensable strategic partner to the business.

For a profession long associated with purchasing and cost control, that represents a profound shift. If the conversations at DPW are any indication, procurement’s next chapter has already begun. And this time it is writing the code rather than simply following it.

Read more of our DPW coverage in the latest issue of CPO Strategy

Author

Nell Walker

Published

2 June 2026

Estimated Read time

6Mins

Zip is delivering the first governed AI platform for finance and procurement

Zip, the AI platform for enterprise procurement, today announced two major launches: Zip Superagents and Zip MCP. Designed to work alongside the humans who handle procurement today, Superagents are an AI platform that takes on real work – reviewing contracts, unblocking approvals, coding invoices, and researching vendors – with every action audited and governed inside Zip. Zip MCP is a procurement-native implementation of the Model Context Protocol that connects Zip’s procurement intelligence directly to AI assistants like Claude and ChatGPT, enabling employees to work in their preferred AI tools without leaving Zip’s controls behind.

Zip is also launching Zip AI Spend Automation, a new enterprise offering that combines platform access, AI consumption credits, and support from Zip’s own forward-deployed engineers to help the most progressive organizations fully automate their intake-to-pay process. Block, UCI Health, and Snowflake are among the first enterprise customers to deploy AI Spend Automation, with UCI Health already reporting $20M in cost avoidance and value recapture from a single project.

The governance gap shadow AI left behind

Most companies don’t have the infrastructure to safely run AI on their procurement data yet, but employees aren’t waiting for it. Across the enterprise, employees are uploading spend data into Claude to analyse it, redlining sensitive contracts inside ChatGPT, and generating internal financial analyses in personal Gemini or Copilot accounts. Every time they do, sensitive enterprise data leaves systems where every action is controlled and audited, entering environments with no oversight, no compliance controls, and no record of what was done.

The consequences for getting this wrong aren’t hypothetical. SOX violations carry fines of up to $25 million. Executives can face prison time. Public companies that fail compliance audits can be delisted from the stock exchange. When an auditor asks how a decision was made six months later, no one can produce a record. When an employee leaves the company, sensitive data lives on in their personal AI history.

That’s why the world’s leading AI companies run their procurement on Zip. Procurement is one of the few business functions where decisions carry direct financial, legal, and compliance consequences, and where every approval needs to be auditable months or years later. To date, Zip’s customers have saved more than $10 billion through its AI suite by running AI inside a procurement-native governance layer rather than alongside one. Today’s launch is how Zip closes that gap: by connecting procurement infrastructure directly to the AI assistants employees already use, and by launching Superagents to take on the procurement workflows no system has been able to fully automate until now.

“After working with hundreds of enterprises – including the world’s leading AI companies – we’ve learned that this kind of work is already happening, with or without governance,” said Lu Cheng, Co-Founder and CTO at Zip. “Even the companies building AI themselves want this work governed. They want the audit trail. They want the controls. They want the integrations to their systems of record. And they want to make sure their employees aren’t uploading sensitive financial, contract, and customer data into general-purpose AI. That’s why we built Zip’s orchestration layer the way we did over the past five years, so that AI doesn’t just operate alongside enterprise procurement, but inside it, where every action is governed and auditable.”

Zip superagents: Governed AI that takes on the work

Zip Superagents are AI agents designed to reason, act, and collaborate inside the workflows where procurement actually happens. Unlike general-purpose AI tools or scripted automation, Superagents are embedded within Zip’s orchestration platform, where each customer’s approval policies, supplier data, ERP integrations, contracts, spend history, and stakeholder workflows already live.

That context is what allows Superagents to do more than generate recommendations. They can determine the right next step, take action across systems, coordinate with employees and stakeholders, and escalate for human review when needed. Every action is governed by the same roles, permissions, and controls that apply to employees, with granular action settings, audit trails, and deterministic logic for high-impact steps like system updates and approvals.

At launch, Zip is introducing five Superagents built around the highest-friction areas of procurement:

  • Procurement Superagent: Unblocks stalled requests, manages tail-spend negotiation, and handles repetitive follow-up within procurement’s approved policies and approval controls.
  • Contract Superagent: Reviews and redlines contracts against company-approved playbooks, flags deviations from standard terms, and routes high-risk issues to legal stakeholders.
  • AP Superagent: Sorts, codes, matches, and routes invoices using existing approval rules, supplier records, and ERP data to reduce manual AP work while maintaining accurate payment controls.
  • Config Superagent: Identifies workflow bottlenecks and drafts configuration improvements for admin review – letting teams continuously optimize processes without uncontrolled changes to critical workflows.
  • Intake Superagent: Guides employees through compliant request creation, routing purchases to the right buying channel, extracting quote details, nudging toward preferred suppliers, and prefilling required fields based on policy and supplier context.

“At Block, we’ve made a fundamental bet on AI,” noted Mithun Sharma, Chief Procurement Officer at Block. “Every team has a mandate to automate, and procurement is no different. This is one of the many reasons we have partnered with Zip. We get the procurement platform our team runs on, fully governed AI agents automating the work, and forward-deployed engineers who specialize in procurement AI and build alongside us.”

Zip MCP: Procurement governance, wherever employees work

Ungoverned AI doesn’t only happen in shadow tools, it also happens when employees do procurement work inside AI assistants that have no connection to enterprise controls. Zip MCP closes that gap.

Zip’s vendor-hosted MCP connects Zip’s AI procurement platform directly to any MCP-compatible AI assistant. An employee researching vendors in Claude can have Zip proactively surface a request submission directly from that conversation, creating earlier visibility for procurement teams without any context switching. Power users can pull aggregated reporting across suppliers, requests, invoices, and payments from within a single AI conversation. Every action respects user permissions through OAuth, runs inside Zip’s compliance controls, and generates a complete audit trail.

Zip MCP is model-agnostic, ensuring procurement governance travels with the work regardless of which AI tool an employee prefers. This is the first time MCP has been implemented natively for enterprise procurement.

Zip AI Spend Automation: How enterprises get there

Superagents are powerful out of the box. But enterprise procurement is not one-size-fits-all. Every organization has unique approval hierarchies, compliance requirements, vendor policies, and edge cases. Zip AI Spend Automation is how the largest enterprises fully deploy governed AI agents for their specific workflows.

AI Spend Automation pairs platform access and AI consumption credits with Zip’s team of forward-deployed engineers (FDEs), who build and deploy custom agents directly inside customer environments:

  • Zip agent builder platform: Access to all Superagent use cases, skills, and tools
  • Custom development: Ongoing support from forward-deployed engineers for agent configuration and optimization
  • Advanced AI governance: Access to additional control and auditability capabilities purpose-built for enterprise needs
  • Consumption credits: Bundled AI credits to supercharge AI usage

“Healthcare operates on a different set of stakes, where delayed decisions and fragmented processes create real consequences for patient care, organizational agility, and financial stewardship,” said Susanna Rustad, Chief Procurement and Supply Chain Officer at UCI Health. “What stood out to us about Zip’s AI Spend Automation was its ability to bring greater visibility, alignment, and discipline to complex enterprise decisions. In one major IT infrastructure initiative, it contributed to more than $20 million in cost avoidance and value recapture.”

Author

Nell Walker

Published

1 June 2026

Estimated Read time

3Mins

Vertice’s acquisition of Vendr will lead autonomous AI negotiation

Vertice, the AI procurement platform built for the modern enterprise, has announced its acquisition of Vendr, the US software pricing leader.

The deal creates the world’s largest procurement intelligence dataset, as Vertice will integrate Vendr’s software insights with its own. The combined data represents more than $75+ billion in global indirect spend across 32,000 vendors, including real-world pricing and human-to-human interactions from 250,000 negotiated contracts, ranging from software to services. The expanded dataset extends Vertice’s leadership in fully autonomous spend negotiation.

Customers including ARM, Brex, Duolingo, Twilio and Santander will be able to access the data directly within the Vertice platform. Insights will be surfaced at the point of decision to help finance and procurement teams evaluate vendors, manage renewals, and plan negotiations with greater speed, confidence, and precision.

Roy Tuvey, Founder and CEO, Vertice, said: “Vertice and Vendr have shared a vision for AI in procurement: to build purpose-designed AI agents trained on real-world data and tailored to specific procurement use cases. By bringing these teams together, we can accelerate everything – from the breadth of agents we can build, to the commercial impact we deliver for customers. We are setting a new benchmark for what procurement teams should expect from AI procurement platforms.

“Our combined software pricing data and vendor intelligence has 2M+ price points and surpasses that of our nearest competitors by an order of magnitude. With deeper insight into vendor pricing, commercial terms, sales tactics and risk, our customers will consistently achieve stronger procurement outcomes.

“Training our AI – including ‘Ana’, our autonomous negotiation agent – on this same rich, procurement-specific dataset makes it even more powerful. Our agents work around the clock helping customers reduce manual effort while delivering best-in-class savings.”

The benefits of Ana

Ana is Vertice’s autonomous negotiation agent which has been trained on hundreds of thousands of real-world negotiations. Procurement buyers can now scale their coverage and minimise effort by using Ana to negotiate on their behalf. Buyers set their priorities, policies and thresholds and Ana engages with the vendor directly to optimise outcomes, such as cost savings, payment terms or policy compliance.

Vertice and Vendr together operate more than 60 procurement AI agents, all used regularly by over 1,000 customers worldwide. These agents support customers across key procurement workflows, including intelligent intake, pricing optimisation, workflow efficiency and third-party risk assessment.

Customers will immediately benefit from a stronger offering and Vendr customers will also gain access to Vertice’s award-winning Intake-to-Procure platform.

Ryan Neu, CEO of Vendr, commented: “Vendr was founded on a simple observation: buyers were making million-dollar purchasing decisions with only a fraction of the information available to the vendor across the table. We spent years closing that gap – building the data, tooling, and negotiation expertise to rebalance that dynamic.

“Joining Vertice means that intelligence is now significantly richer – by far the most comprehensive available – and embedded directly within the platform where procurement decisions are made. I’m proud of what we built independently, and even more excited about what our two organisations can build together.”

This year, Vertice has been recognised by Lionfish Tech Advisors, a global analyst advisory firm, as the Leader in Intake-to-Procure platforms, and as the Leader in Procurement Orchestration in G2’s Summer 2026 Grid Report. Forrester also named Vertice as a Notable Vendor in its 2026 Landscape report on Supplier Value Management. 

Tuvey added: “Vertice has become the clear choice for enterprises seeking to move beyond fragmented, reactive procurement toward a model where every purchasing decision is intelligently orchestrated, executed quickly, and grounded in robust market intelligence.” 

Author

Tom Lanaway

Published

2 March 2026

Estimated Read time

4Mins

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.

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. 

Learn more at connective3.com

  • AI in Procurement
  • Artificial Intelligence in FinTech
  • Data & AI
  • Digital Strategy
  • People & Culture

Author

Nell Walker

Published

25 November 2025

Estimated Read time

2Mins

BeNeering’s MD and CRO dig into the company’s history with AI, and the necessity of seeing beyond the hype of new technologies

A privately-owned company with over 20 years of procurement digitalisation experience fueling it, BeNeering is at the forefront of the AI-powered revolution in its sector. BeNeering was founded in 2007. At the time, Christoph Moll, BeNeering founder and Managing Director, was busy implementing SAP SRM systems for large European multinationals. While this provided great experience, Moll could see the limitations – and he wanted to move beyond them. He wanted to do something more.

“That’s how BeNeering was founded,” he says. “We focused on consulting until 2013, at which point we transitioned to being a solutions provider. I cherry-picked a great development team, and I’m happy to say that the same strong team is with us still today. Stability is our value.”

Natalia Parmenova, Chief Revenue Officer, is an example of one such strong team member, who has enormous faith in the business. “From my perspective, BeNeering is a super special solution provider for a few reasons,” she states. “First of all, we believe in co-innovation. Everything we develop is built together with very large and advanced customers. We try to stay close to those customers, to people who are forward-thinking and developing their procurement functions, so we can develop solutions for them with them. We are not just inventing things we think are useful – we are basing our development on customer needs. That’s really important.”

Simplify and optimise

Many people fall into procurement accidentally. It’s a common story among procurement professionals, and a source of amusement considering how passionate many of them become about it. For Parmenova and Moll, however, it was a case of seeing the way the wind was blowing and following the scent of change.

“In 2001, when I was employed by SAP, I wanted to do things better to help users in procurement,” says Moll. “That was how it started for me. My vision was really to simplify and optimise steps and processes for both requestors and buyers.” 

Read the full story here.

Author

Nell Walker

Published

Estimated Read time

3Mins

Dafydd Llewellyn digs into why businesses need to be deliberate about how they use AI

Taking on a new leadership role can be both exciting and daunting. Dafydd Llewellyn is the CEO of HICX, having taken up the mantle in September. In fact, by the time we spoke with him, he’d only been at his post for five weeks – but he was buzzing with nothing but pure enthusiasm about it. At this crucial juncture, when the pace of change is faster than ever before, strong leadership is vital. As such, Llewellyn has his hand on the tiller as he guides HICX on the next part of its journey.

“We’re a supplier management platform,” he says. “Companies work with us because they want to transform their supplier management to become more unified, more strategic, and more intelligent. Ultimately, what that means is our customers’ businesses are really able to make the most and harness the power of the suppliers.”

AI in the real world

Being competitive in the modern day means being not just au fait with artificial intelligence, but having a deeper understanding of it. The theme of DPW Amsterdam this year, as with the New York event in June, was ‘Put AI to work’. While AI has been a topic of discussion for several years now, planning (and bracing) for its impact is a different matter. But HICX, led by Llewellyn, is ready.

“It’s great that DPW is focusing on AI,” he says. “At HICX, we are being very deliberate about the way we approach AI. The way we’re looking at it is really about using AI to allow procurement professionals to be more value-added in the tasks they do, and remove all the repetitive tasks that they really don’t want to be doing. They can drive more value for the business that way.

“So, we are looking at things around business processes and automation, right through to document capture, through to compliance checks; using AI agents enables us to do that,” Llewellyn continues. “I can give you a real-life example. If you think about the workflow for a new supplier in the old days, you’d have to have them involved to create that workflow. Now, we can use AI to create that workflow just by writing it in natural language.”

Read the full story here.

Author

Nell Walker

Published

17 September 2025

Estimated Read time

6Mins

The proof, as they say, is in the pudding – and the evidence of TealBook’s increasingly-successful evolution lies in its client relationships

We talked endlessly about data and AI at DPW New York 2025. A universal truth is that the successful implementation of AI requires clean data; it doesn’t have to be perfect, but businesses certainly need to have a decent handle on their data before adopting AI tools successfully. 

To help make this a reality, North American data and software company TealBook has recently announced a legal entity-based data model. It’s designed to resolve supplier records to the correct legal entities, map parent-child relationships, and enrich profiles with verifiable attributes, enabling accurate supplier data to flow seamlessly into procurement systems and AI applications. “This is part of a 12-year journey for TealBook,” says Stephany Lapierre, the company’s Founder and CEO. “Our vision has always been to build a way to enable procurement organisations to have high quality data with a lot of integrity, in order to give them the trust they need to put data directly into their systems. 

“Twelve years ago, we underestimated the complexity of getting large enterprises to trust a third-party data solution. As part of our journey, we started using AI early on to find information where it exists on supplier websites and databases, and start creating digital profiles in a structured way for procurement to access it, match it to their vendor master, and use it.”

TealBook’s evolution

But, again, at the beginning, TealBook couldn’t be sure whether the data was high enough quality. In 2017, the company was primarily known as a supplier discovery application, positioned as a pre-sourcing engine to help procurement teams identify alternative suppliers. At the time, TealBook’s data and models enabled it to determine which companies were similar to others, allowing users to search and find comparable suppliers to expand their sourcing options.

“But that was just a way for us to deliver something that was underserved in the market,” Lapierre continues. “Then our customers started asking for certificates, which are hard to collect and match. They needed cleaner data. They felt they were under-reporting. So in 2018, we started to see whether our technology could refine the data more, and focused on certificates and supplier diversity. We collected great use cases along this journey, and the vision never wavered.

“Just last year we released a new technology – completely different, really sophisticated – allowing us to pull from a lot more data sources, and we have provenance so our customers can actually verify where the data’s coming from. We can match it to vendor masters. And now, we also have this new model that includes 230 million verifiable global legal entities from across 145 countries’ registries. We marry this with global parent and child hierarchy, which is really hard for our customers to match themselves.”

Partnership with Kraft Heinz

Now, after 12 years of that vision, TealBook is deeply proud of what it’s achieved. Part of its ability to get to this point is due to early adoption from key customers. Kraft Heinz is a business which Lapierre describes as a “co-innovation partner”, and has been invaluable in helping TealBook achieve its recent goals.

From the perspective of Stefanie Fink, Head of Global Data and Digital Procurement at Kraft Heinz, the partnership has been an immediately valuable one. “It really started with having a visionary, like-minded relationship,” she says. “That’s an important piece of it, because my vision for procurement is that we are partners in our enterprise. 

“In order for us to do our jobs, we have to bring in the right data for use. This is where Stephany’s partnership and vision really resonated. We were really looking for diversity and we could make things easier for our partners, while making sure we had the right people in our ecosystem. We also had to lift up the hood and see what was underneath everything we’ve got. Stephany brought our vision to life. TealBook has evolved too, as we’ve seen; it’s more about orchestration and software-as-a-service. It has been a partnership of need and we cannot continue to do other things without this kind of partnership around data.”

When initially dabbling with this relationship, Fink was clear that Kraft Heinz had no desire to be taking care of more stuff. What she wanted from TealBook was a strong focus on good quality data. After last year’s product release from TealBook, Kraft Heinz already saw its data enriched by 25%. The recently-announced new data model gives the business and TealBook’s other customers the right structure tied to a legal entity, which is a highly credible anchor. “We’re able to do entity resolution – all automated – remove all the duplicates, and then you start with a clean, digitised vendor master,” says Lapierre. “That’s what brings further enrichment.”

The challenge of assessing data quality

Assessing its data before involving TealBook was important for Kraft Heinz, but challenging for such a large organisation. “We had to fail first and fail fast,” says Fink. “We tried some AI around fixing things early, but that didn’t work for us. It was a real eye-opener, realising where this next evolution could take us regarding focusing on AI and agents for the right things, not the meaningless things. Before, we were asking agents to tell us if things were duplicates, when we should have been asking: what do these suppliers offer? Where is the innovation? Where is the value?”

What surprised Fink most when looking under Kraft Heinz’s hood was the lack of attention that was being paid to what the business was doing. “It was amazing that nobody had questioned it sooner,” she says. “So I said, let’s take this as a crawl, walk, run approach, and I have a wonderful CPO who really understands where we want procurement to go as a function. She was excited about us just getting it done and getting people involved, and that’s what it takes: real pride in ownership of the data.”

Getting engrossed in GenAI

True partnership and an all-in approach has enabled Kraft Heinz to work successfully with AI – something some businesses are struggling with as the conversation around artificial intelligence grows louder. For Lapierre, as the CEO of a tech company, adopting AI successfully has meant trying and failing and being fully entrenched in AI as it has evolved.

“We’ve been using AI in our technology since 2016,” she states. “We’re an early adopter. We’d be talking about scraping data, and data in the cloud, and AI models, and our customers’ pupils would widen in surprise. We’ve come a long way and the market has come a long way. 

“The technology we deliver today wouldn’t be possible without the AI tools now at our disposal. We used to build models; we don’t do that anymore. We spend a lot of time investing in engineers to build and test models, and that’s made us so much more efficient. I use GenAI every day for so many things now, and I’m encouraging my team to be so involved in AI. That’s how you build expertise, and you need really strong expertise to use GenAI well. 

“Getting good with AI is about taking risks and having a leadership team that pushes for new things, and suddenly the successful use of AI becomes a habit.”

Author

Nell Walker

Published

16 September 2025

Estimated Read time

7Mins

The march towards agentic AI can be a daunting thing, but it’s important to get over that fear in order to make strides

A common question when discussing AI is ‘where do humans fit in?’. The fear of technological advancements stealing our jobs is an old one, but the conclusion is always the same and always true: there will never be a time when human judgement and teamwork isn’t required.

At DPW New York 2025, we sat down with Rinus Strydom, Chief Revenue Officer at Pactum AI, and Steven Velte, Executive Director Procurement Transformation at Honeywell – a customer of Pactum AI – to discuss AI’s evolution and the human connection. As AI develops, for Strydom, Pactum’s focus is on agentic, rather than generative. There’s a key difference there, especially for initial adoption at large enterprises. 

“A lot of enterprises feel a little bit afraid, because generative AI can go a little off the rails,” he explains. “But when you put agents to work, they’re always within the rails that are defined by the customers. Once we get over that hurdle and can make clients see that they can take their procurement operating model and have it just run at scale with agents, rather than being afraid that their image will get tarnished, AI can be put to work much faster.”

Putting AI to work

When it comes to strategies procurement leaders can adopt to make AI work for them, it’s a major discussion point for Strydom and Velte. As a customer, it’s important for Honeywell to feel like its work with Pactum AI is a collaboration; it’s part of what makes its strides into AI work successfully. “This collaboration goes deeper than what we’ve typically had in the past,” says Velte. 

“When we go through organisational changes, we need a true partner, And when that partner gets into the elevator with you, they don’t just push the button with you – they go up to the next floor with you and sit at the table to talk about what’s happening. So a barrier to AI adoption is not having that deep collaboration and partnership.” 

“I think another thing leaders can do today is really help with that psychological change management to make it feel like a safe thing,” Strydom adds. Mindset shift is such a vital part of this change, especially when it comes to successful collaboration. “It’s important to embrace agentic AI, to encourage people to become managers of agents and not run away or become fearful.”

Identifying the opportunities

The true benefits of AI are now beginning to present themselves, as people increasingly embrace AI. For Velte, businesses have to get going with their AI plans in order to realise where the real opportunities lie. “I can make a business case with tons of ROI, potential productivity gains, revenue uplift, bottom line, profit line – all of that. But the real benefits that come from AI are those hidden benefits we don’t realise. When you start looking at it, there’s a common theme of saving time, and time becomes the real benefit. Unlocking better use of time gives you more potential to work on other creative aspects of the business.”

For Strydom, the true value lies in achieving things that used to be extremely difficult to achieve. Pactum AI’s customer base is broadly looking at 10X ROI, which, now, is easily done thanks to the use of AI agents. Agents also allow procurement teams to scale extremely fast, which is something that has, historically, been hard-won. 

“For example, if you need to change payment terms across your entire supply base, you can do that with thousands of agents in parallel. You could never do that before. It gives you the agility to react to global macro risk issues, like tariffs.”

Start now; perfection comes later

One of the loudest topics of conversation at DPW New York 2025 was data quality and the challenge of cleaning that data up. It’s a huge topic, and a daunting one. Many businesses fall into the trap of thinking their data has to be perfect before they can get fully involved with AI, but the conclusion many procurement leaders are coming to is that getting started is more important than perfection.

“Data quality is always the holy grail going forward,” says Velte. “Everyone’s going to look for it, and try to attain it. When you start implementing within an AI framework, you just need to go in there and know that you’re going to constantly evolve in a good way, thanks to the agents, AI programs, and initiatives. They’re going to uncover and unlock a lot of data and inconsistencies that you have. You won’t get there unless you start looking into them as an opportunity area. Data perfection is not the way to go; it’s about getting in there, starting to look at the opportunities, and being willing to be creative, disruptive, and innovating quickly.

“There’s never going to be a time when everything is 100% correct and accurate, because data is always evolving,” adds Strydom. “Start now. The data can be enriched over time with the agents’ help.” 

Maximum savings, maximum momentum

Pactum is using AI specifically to enable it to be a strategic advisor for customers like Honeywell. The use cases coming out are very new, and changing fast. What Strydom and his team want is to be able to guide customers on the right strategies for them, how to get maximum savings, and maximum momentum. As this landscape becomes more complex, human intervention and guidance is more important than ever, which links back to the topic of mindset and change management. 

There’s been a lot of debate within Pactum AI as to how the business embraces this. “From a marketing perspective, too, there’s the question of whether we should make our agents look human,” says Strydom. “Actually, what we’re seeing is that suppliers actually enjoy interfacing with a bot. Walmart, one of our customers, did a survey where they found that 85% of their suppliers actually prefer to negotiate with Pactum than with a human. It’s more efficient, fair, and unbiased.”

Speaking of humans, shortage of talent has been a talking point within procurement for some time. That was, until advanced tech became more widely adopted, and bringing in procurement experts became less important than bringing in technology experts who are willing to learn. With the advent of agentic AI, according to Strydom, procurement leaders are now acting as managers of agents.

“All the analyst surveys say that procurement organisations are being asked to do more with less every year,” he says. “So the type of talent is definitely transforming. What we see is that the procurement organisations of the future are much more strategic. They’re focusing on creating strategy and procurement policies and procedures, and then having the agents actually go out and do the menial day-to-day work – entering things into ERP, turning requisitions into purchase orders, onboarding suppliers, and so on. All of that can now be done very quickly and efficiently by agents. This really elevates the role, and allows procurement to become a partner to the business.”

Velte adds: “When you talk about talent shortage, it’s also that shift in the mindset we’re going through right now. The expertise is changing, and we want to be able to bring in talented people with that technology flare. When we look at the next generation of leaders coming out of university and college, they’re AI enabled already. They’re expecting AI to be available to them to accelerate their development, career goals, and ambitions.”

Making sense of the landscape

As DPW New York 2025 unfolded around us, the discussion inevitably turned to the ways in which DPW helps procurement make sense of the AI landscape. Pactum AI is actually a perfect example of how useful DPW is. Only four years ago, the business was a startup, and won a pitch contest at DPW Amsterdam. “That catapulted the business, and got us a lot of visibility,” says Strydom. “It’s a great place for visibility with practitioners, investors, and partners.”

Again, it comes back to people. Being able to meet them in real life, communicate face-to-face, and learn from one another. “It’s about reconnecting with a lot of our partners,” says Velte. “But it’s also about seeing what is out there on the forefront that’s becoming available. It’s an amazing opportunity for us to really benchmark ourselves, while also getting a glimpse of what’s coming around the corner.”

Author

Jess Shanahan

Published

12 September 2025

Estimated Read time

7Mins

From automating decisions to redefining procurement talent, AlixPartners lays out why risk-takers lead the way.

The use of artificial intelligence (AI) in procurement is gaining traction with many organisations already looking at how the technology can improve processes. However, there’s scope to go beyond efficiency and instead focus on transforming value delivery. 

At DPW New York, we spoke to Amit Mahajan and Aaron Addicoat from AlixPartners, a management consultancy firm doing things a little differently. The organisation is advising its clients on how to implement AI to drive value, but it’s also using AI internally, too. 

“AlixPartners has a unique business model,” explains Addicoat. “We have a very senior model, very few junior resources. So now you imagine taking people with 10 or 15 years experience and now you equip them with AI… For us, it’s a huge unlock.”

This is about more than just productivity gains. AlixPartners focuses on using AI to transform the way procurement teams work, while crucially, maintaining the human touch.

How procurement professionals are using AI

With the support of technology, it’s possible to shift procurement from a cost-saving exercise to a potential revenue driver. Procurement teams are already looking for these opportunities, as Mahajan explains. “They’re starting to think about new ways of doing things,” he says. “It’s not just automation, but asking how do I leapfrog and do something differently?”

There are plenty of use cases where AI is helping with automation. This is a great place to start as it frees up human workers to do more valuable jobs that need a personal touch. “I have a client who’s using AI every day,” says Addicoat. “This allows them to review documents and contracts rapidly, to find key clauses and termination dates. They’re also using it in spend control processes to identify which things need to be reviewed more thoroughly.”

Many organisations are also using AI agentically to create their own bots. This gives teams a more accessible way to review information. “One example is a client who’s using AI for their business to help with acronyms,” says Addicoat. “They built it as an acronym tool to help break down the language barrier between different functions using different terms. This led to better engagement.”

This empowers employees across an organisation to be more autonomous while still getting the full picture. Agentic AI, especially, allows them to interact with information in a way that previously would’ve required specialist technical knowledge. Now, it’s possible to query information within a contract directly. 

“It’s about using agents and AI to look at anomalies within your procurement contracts,” explains Mahajan, “and be able to help the category analysts, the category specialists, and others to get more of those insights.”

While generative AI might be a hot topic, it’s not the only way to use the technology. In combining several sources of data and using AI to spot trends, it’s possible to create workflows tailored to the current environment. Addicoat explains: “We take a series of data inputs, such as weather patterns, lead times, contractual terms, inventory, and forecast. Then the AI generates the purchase order, queues it for review, and upon approval, places the order.”

This can help an organisation to place orders with the right supplier in the most timely fashion to avoid delays, and optimise for cost, for example. This fully automates the end-to-end process, using AI to interpret those important data signals.

While this is useful for procurement teams, it’s only the start. “Using AI in this way is really cool,” says Addicoat, “but what I found most fascinating is that you’re building a data model, and with AI layered into it, that over time can tell you how to optimise itself.”

This has huge implications for procurement teams looking to save money and drive revenue. “For example, it could tell us the commodity price at a certain point in time was low,” says Addicoat, “but because inventory capacity to hold resin was maxed out the client could only buy so much at that low price. So now investing in a new storage unit at a cost of a few hundred thousand dollars could, under the same scenario in the future, save millions of dollars..Data quality challenges

A roadblock that can stop procurement teams from fully embracing AI is a lack of quality data. With so many sources of information, often including paper-based documents, some might think it’s difficult to get the data AI needs to be truly useful.

“Don’t wait for everything to be perfect before you get started,” says Addicoat. 

This is a sentiment echoed by Mahajan: “Use AI to solve your data problem before solving your business problems.”

This requires a mindset shift. While AI can help cleanse, enrich, and structure existing unstructured data, it’s important to take the right approach. Shift from asking ‘what can we do with our data?’ to ‘what value do we need to create?’ and work backwards from there.

With this approach, the questions are less about the data and more about the business problem. This then allows you to use AI to work with the information you have to help answer those questions.

“Start with the value proposition in mind and work backwards,” explains Addicoat. “You can get data from anywhere — it has to serve a purpose.”

Bringing back the human touch

AI can free up procurement teams to focus on tasks that need more nuance and expertise. Using technology to automate workflows and make information more accessible has a huge impact on employee productivity. “It’s fundamentally transforming the way they work, the amount of work they can do, and the type of work they’re able to do,” says Addicoat.

There’s always the worry that with any new technology, the human element will be forgotten. “With every new advancement that comes in,” says Mahajan, “whether that was a steam engine or when computers came along, everybody wondered what they were going to do. But as humans, we always find ways to start doing higher-level work.”

This means that many professionals will find new ways of doing things. “Imagine all the mundane tasks you have to do in your daily job now,” Addicoat continues. “With these new ways of working, imagine the speed with which you can turn an idea into something real. All that time you free up allows you to go talk to people and build relationships that mean something.”

On the other side of things, the sheer volume of AI-generated content out there is going to drive people towards those more meaningful interactions. “You don’t know what to trust and what to believe anymore,” Addicoat says. “That’s going to lead to a resurgence in face-to-face content, being at the office, and being at events.”

AI’s impact on procurement talent

The talent landscape is changing. With technology playing a larger part than ever before, organisations don’t just need procurement professionals, they need adaptable, tech-savvy people. The nature of the job means that those in procurement need a wide range of skills. 

“We do everything,” says Addicoat, “legal, operations, supply chain, negotiation, analytics. Procurement professionals are generalists.” 

Tech plays into every element of that skillset, which means tech skills are becoming even more important for candidates applying for procurement roles. “Nobody goes to college thinking they’ll be a procurement professional,” says Mahajan, “but with AI and tech, that’s changing.”

With procurement often seen as a proving ground for leadership, embedding these tech-minded generalists could have a huge impact on the future. “We have a shortage of talent,” explains Addicoat. “But with more and more CEOs and COOs coming from procurement, that speaks volumes to what procurement does and the value it brings, as well as what the future holds.”

At AlixPartners, the passion for procurement is very clear with Addicoat saying: “There are only two kinds of people in the world: those who love procurement and those who don’t know it yet.”

Change is coming

With AI of all forms steadily gaining traction, procurement could change dramatically in the coming years. It’s the organisations that are willing to take risks and embrace change that will come out on top.

“AI has the potential to disrupt the whole management consulting world,” says Mahajan. “Firms focused on transformation will thrive.” 

With AI’s capabilities increasing rapidly, it’s difficult to predict what comes next. However, adaptability is key. “Hold onto your hat. In a year and a half, the world’s going to look very different,” concludes Addicoat.

Author

Jess Shanahan

Published

Estimated Read time

8Mins

AI is already transforming procurement, but meaningful value depends on more than just tools. At Beroe, that starts with aligning AI to real business problems

As AI continues to dominate conference stages and boardroom discussions, the pressure to use it is everywhere. As this technology becomes further embedded in enterprise strategy, many organisations are still grappling with how to apply it in a way that delivers real, measurable value.

Rather than focusing on AI for the sake of innovation, the question now is how to align new tools with real business problems. That means looking beyond dashboards and pilots to deploy AI where it can simplify decision-making and improve processes.

At Beroe, this principle is central to how AI solutions are developed, deployed, and scaled. As the company behind the world’s leading procurement intelligence platform, Beroe provides real-time market data, cost analysis, and supplier risk assessments, empowering thousands of organisations globally to streamline operations and mitigate risks. Its latest advances in autonomous negotiation, supplier discovery, and predictive analytics show what it means to align AI with business objectives.

Speaking with Prerna Dhawan, Chief Product Officer at Beroe, during this year’s DPW New York conference, the discussion explored how procurement leaders can move beyond hype and start unlocking the full potential of AI.

Misalignment with business needs

There are plenty of real-world examples of how AI can improve efficiency within a business, from automating manual tasks like invoice processing to identifying new suppliers based on complex sourcing criteria. Accessing this technology is easier than ever with a wide range of tools available to procurement professionals. It can be tempting to jump on the bandwagon and integrate AI across every area of an organisation, but success requires a more nuanced approach.

The key is to ask the right questions, Dhawan explains: “We talk about all the latest and greatest technology out there, but what does it mean in practical terms? We need to ask, ‘How can I apply it today in the work I am doing as a head of product or as a procurement professional?’”

The allure of generative AI is especially strong, but business leaders should ask whether that’s the right solution for their needs. As with any decision, it’s important to consider the business problem. “It starts with a little bit of knowledge about what you’re looking for,” says Dhawan. “What are some of your biggest challenges, and which of those challenges could AI technology solve?”

Matching the right tool to the job

Once an organisation has identified a specific problem, it’s possible to find the AI solution that fits. While generative AI gets a lot of attention, other AI technologies and machine learning based systems might be more appropriate. 

In some cases, prescriptive, rule-based, or predictive AI could be a better choice to solve a problem without the need for a large language model. For example, forecasting commodity prices doesn’t require generative AI, just strong, contextual machine learning. 

“We are looking at AI across two dimensions,” says Dhawan. “Firstly, what is our offering to customers, in terms of procurement intelligence and autonomous negotiation technology. Second, we are looking at AI internally. Let’s say in product development, how do we use the latest AI solutions to accelerate our product development cycles so we can release new modules and capabilities more quickly.”

Regardless of the type of tool chosen, it should cover a high-impact use case. Integrating AI to solve a problem that only surfaces for a small group of people a couple of times a year won’t have a great return on investment. Instead, look for regularly occurring problems that, if fixed, could have a huge impact on productivity or quality. 

Reducing the cognitive load

We’re already bombarded by information, and the use of AI to add to this doesn’t make sense. “I don’t need another dashboard in my life,” says Dhawan. 

When implemented correctly, AI can make data more accessible while reducing cognitive load for users. The result is increased productivity and faster decision-making. 

“I think the power of AI is to simplify access to data. This is why ChatGPT has been a success: it democratises access to information. That’s what our B2B technology world is waiting for. It gives me something simple that allows me to talk to my data. Then I can focus on what insights I need to make a decision or take action.”

For most B2B users, the key is intelligent simplification. Look for ways to simplify access to data through agent AI tools and conversational interfaces. This brings the focus back to action rather than dashboards.

Inside Beroe

While many procurement teams are still exploring AI’s potential, Beroe has already embedded it across both its platform and internal operations. The company, founded in 2006, provides procurement intelligence to thousands of organisations worldwide. Its platform delivers the critical data that professionals need to make informed sourcing decisions, from commodity prices and risk indicators to ESG scores and supplier intelligence.

“We provide all data that procurement needs for decision making, whether it’s cost data, risk data, ESG data or price data,” says Dhawan. “Our reimagination of the future is not just giving access to more data but creating that layer of recommendations that help you make decisions at speed and scale.”

One of the clearest examples of this in action is Beroe’s new ‘autonomous negotiations’ platform resulting from its recent acquisition of negotiation technology business, nnamu.  Delivering a significant evolution in the procurement technology landscape the platform enhances the foundational elements of AI and game theory with Beroe’s industry-leading market intelligence and, according to Dhawan, it’s being deployed successfully in live sourcing scenarios.

“This is a technology that is being used for multilateral negotiations,” Dhawan explained. “It’s no longer just a POC or prototype, it’s live and being used at scale.” These new tools reflect Beroe’s core mission: to help procurement professionals minimise surprises and maximise margins. 

Crucially, Beroe isn’t waiting for perfect data to apply these technologies. Instead, the company is using AI to work with what’s available — cleansing, interpreting, and extracting value from both structured and unstructured sources.

“You can use AI for cleansing data – even paper contracts,” Dhawan says. “Historically, we thought data had to be structured. But now, with vision models and image analytics, that’s no longer the case.”

Rather than striving for 100% accuracy before taking action, Beroe embraces a more agile mindset that balances speed and precision. 

Is mindset holding procurement back?

The technology is ready. The use cases are proven. So why do so many procurement teams still hesitate to embrace AI? “There’s this subconscious fear that I think is a barrier to adoption,” she said. “And to some extent, it’s to do with our friends in Hollywood.”

There’s the myth that AI is a job-threatening black box, especially in industries where trust and experience are the backbone of good decision-making. For procurement, where professional judgement and business context are critical, the idea of handing over tasks to AI can feel risky.

But Dhawan believes this fear is misplaced. At Beroe, AI isn’t replacing procurement professionals, it’s augmenting them. Whether it’s surfacing new suppliers, automating elements of negotiation, or flagging risks earlier in the sourcing cycle, the aim is to enhance human decision-making. She says: “I think with the new kinds of AI technology that’s available to us, it is an opportunity for us in B2B tech to embrace more human-centred design with higher focus on UX.”

Looking ahead

Looking ahead to 2026 and beyond, Dhawan sees procurement evolving into a more personalised and responsive function – one where AI plays a critical role in both strategy and execution.

“We see hyper-personalisation coming, both in supplier relationships and internal stakeholder engagement,” she explains. “AI will be at the centre of that.”

Rather than one-size-fits-all sourcing strategies, AI will enable procurement teams to tailor their approaches to specific business units, categories, or even individual suppliers. This means smarter segmentation, more relevant insights, and stronger commercial outcomes.

Another key shift is the growing ability to connect macro events, such as geopolitical shocks or regulatory changes, with micro actions inside the business. AI can help procurement teams identify these signals earlier, respond faster, and still align with long-term goals such as cost efficiency or sustainability.

“It’s about balancing your fire-fighting reactions to market events with your long term goals and strategy,” says Dhawan. “Procurement needs visibility and flexibility at the same time.”

Beroe is already moving in this direction. Alongside its growing AI capabilities, the company is refining how it delivers intelligence, building agents and recommendation layers that not only inform decisions, but also help teams take action on them. Whether that means automating routine negotiations or proactively flagging supply risks, Beroe is evolving to meet the needs of a procurement function that’s more dynamic than ever.

As Dhawan points out, the goal isn’t to overwhelm teams with more tools, it’s to make their lives easier. “It’s about reducing complexity and giving procurement professionals confidence in what to do next,” she concludes.

For many procurement leaders, AI still feels like a long-term ambition. But the solutions are already here, and through companies like Beroe, they’re already in use. The challenge now is not whether AI can deliver value. It’s whether teams are ready to adopt the mindset and cultural shift that will allow them to unlock that value.

Author

Jess Shanahan

Published

29 July 2025

Estimated Read time

7Mins

We spoke to Chief Product Officer Prerna Dhawan about what it takes to move from experimentation to execution.

As AI continues to dominate conference stages and boardroom discussions, the pressure to use it is everywhere. As this technology becomes further embedded in enterprise strategy, many organisations are still grappling with how to apply it in a way that delivers real, measurable value.

Rather than focusing on AI for the sake of innovation, the question is how to align new tools with real business problems. That means looking beyond dashboards and pilots to deploy AI where it can simplify decision-making and improve processes.

At Beroe, this principle is central to how AI solutions are developed, deployed, and scaled. As the company behind the world’s leading procurement intelligence platform, Beroe provides real-time market data, cost analysis, and supplier risk assessments, empowering thousands of organisations globally to streamline operations and mitigate risks. Its latest advances in autonomous negotiation, supplier discovery, and predictive analytics show what it means to align AI with business objectives.

We spoke with Prerna Dhawan, Chief Product Officer at Beroe, during this year’s DPW New York conference. The discussion explored how procurement leaders can move beyond hype and start unlocking the full potential of AI.

Misalignment with business needs

There are plenty of real-world examples of how AI can improve efficiency within a business, from automating manual tasks like invoice processing to identifying new suppliers based on complex sourcing criteria. Accessing this technology is easier than ever with a wide range of tools available to procurement professionals. It can be tempting to jump on the bandwagon and integrate AI across every area of an organisation, but success requires a more nuanced approach.

The key is to ask the right questions, Dhawan explains: “We talk about all the latest and greatest technology out there, but what does it mean in practical terms? We need to ask, ‘How can I apply it today in the work I am doing as a head of product or as a procurement professional?’”

The allure of generative AI is especially strong, but business leaders should ask whether that’s the right solution for their needs. As with any decision, it’s important to consider the business problem. “It starts with a little bit of knowledge about what you’re looking for,” says Dhawan. “What are some of your biggest challenges, and which of those challenges could AI technology solve?”

Matching the right tool to the job

Once an organisation has identified a specific problem, it’s possible to find the AI solution that fits. While generative AI gets a lot of attention, other AI technologies and machine learning based systems might be more appropriate. 

In some cases, prescriptive, rule-based, or predictive AI could be a better choice to solve a problem without the need for a large language model. For example, forecasting commodity prices doesn’t require generative AI, just strong, contextual machine learning. 

“We are looking at AI across two dimensions,” says Dhawan. “Firstly, what is our offering to customers, in terms of procurement intelligence and autonomous negotiation technology. Second, we are looking at AI internally. Let’s say in product development, how do we use the latest AI solutions to accelerate our product development cycles so we can release new modules and capabilities more quickly.”

Regardless of the type of tool chosen, it should cover a high-impact use case. Integrating AI to solve a problem that only surfaces for a small group of people a couple of times a year won’t have a great return on investment. Instead, look for regularly occurring problems that, if fixed, could have a huge impact on productivity or quality. 

Reducing the cognitive load

We’re already bombarded by information, and the use of AI to add to this doesn’t make sense. “I don’t need another dashboard in my life,” says Dhawan. 

When implemented correctly, AI can make data more accessible while reducing cognitive load for users. The result is increased productivity and faster decision-making. 

“I think the power of AI is to simplify access to data. This is why ChatGPT has been a success: it democratises access to information. That’s what our B2B technology world is waiting for. It gives me something simple that allows me to talk to my data. Then I can focus on what insights I need to make a decision or take action.”

For most B2B users, the key is intelligent simplification. Look for ways to simplify access to data through agent AI tools and conversational interfaces. This brings the focus back to action rather than dashboards.

Inside Beroe

While many procurement teams are still exploring AI’s potential, Beroe has already embedded it across both its platform and internal operations. The company, founded in 2006, provides procurement intelligence to thousands of organisations worldwide. Its platform delivers the critical data that professionals need to make informed sourcing decisions, from commodity prices and risk indicators to ESG scores and supplier intelligence.

“We provide all data that procurement needs for decision making, whether it’s cost data, risk data, ESG data or price data,” says Dhawan. “Our reimagination of the future is not just giving access to more data but creating that layer of recommendations that help you make decisions at speed and scale.”

One of the clearest examples of this in action is Beroe’s new ‘autonomous negotiations’ platform resulting from its recent acquisition of negotiation technology business, nnamu.  Delivering a significant evolution in the procurement technology landscape the platform enhances the foundational elements of AI and game theory with Beroe’s industry-leading market intelligence and, according to Dhawan, it’s being deployed successfully in live sourcing scenarios.

“This is a technology that is being used for multilateral negotiations,” Dhawan explained. “It’s no longer just a POC or prototype, it’s live and being used at scale.” These new tools reflect Beroe’s core mission: to help procurement professionals minimise surprises and maximise margins. 

Crucially, Beroe isn’t waiting for perfect data to apply these technologies. Instead, the company is using AI to work with what’s available — cleansing, interpreting, and extracting value from both structured and unstructured sources.

“You can use AI for cleansing data – even paper contracts,” Dhawan says. “Historically, we thought data had to be structured. But now, with vision models and image analytics, that’s no longer the case.”

Rather than striving for 100% accuracy before taking action, Beroe embraces a more agile mindset that balances speed and precision. 

Is mindset holding procurement back?

The technology is ready. The use cases are proven. So why do so many procurement teams still hesitate to embrace AI? “There’s this subconscious fear that I think is a barrier to adoption,” she said. “And to some extent, it’s to do with our friends in Hollywood.”

There’s the myth that AI is a job-threatening black box, especially in industries where trust and experience are the backbone of good decision-making. For procurement, where professional judgement and business context are critical, the idea of handing over tasks to AI can feel risky.

But Dhawan believes this fear is misplaced. At Beroe, AI isn’t replacing procurement professionals, it’s augmenting them. Whether it’s surfacing new suppliers, automating elements of negotiation, or flagging risks earlier in the sourcing cycle, the aim is to enhance human decision-making. She says: “I think with the new kinds of AI technology that’s available to us, it is an opportunity for us in B2B tech to embrace more human-centred design with higher focus on UX.”

Looking ahead

Looking ahead to 2026 and beyond, Dhawan sees procurement evolving into a more personalised and responsive function – one where AI plays a critical role in both strategy and execution.

“We see hyper-personalisation coming, both in supplier relationships and internal stakeholder engagement,” she explains. “AI will be at the centre of that.”

Rather than one-size-fits-all sourcing strategies, AI will enable procurement teams to tailor their approaches to specific business units, categories, or even individual suppliers. This means smarter segmentation, more relevant insights, and stronger commercial outcomes.

Another key shift is the growing ability to connect macro events, such as geopolitical shocks or regulatory changes, with micro actions inside the business. AI can help procurement teams identify these signals earlier, respond faster, and still align with long-term goals such as cost efficiency or sustainability.

“It’s about balancing your fire-fighting reactions to market events with your long term goals and strategy,” says Dhawan. “Procurement needs visibility and flexibility at the same time.”

Beroe is already moving in this direction. Alongside its growing AI capabilities, the company is refining how it delivers intelligence, building agents and recommendation layers. These not only inform decisions, but also help teams take action on them. Whether that means automating routine negotiations or proactively flagging supply risks, Beroe is evolving to meet the needs of a procurement function that’s more dynamic than ever.

As Dhawan points out, the goal isn’t to overwhelm teams with more tools, it’s to make their lives easier. “It’s about reducing complexity and giving procurement professionals confidence in what to do next,” she concludes.

For many procurement leaders, AI still feels like a long-term ambition. But the solutions are already here, and through companies like Beroe, they’re already in use. The challenge now is not whether AI can deliver value. It’s whether teams are ready to adopt the mindset and cultural shift that will allow them to unlock that value.

Author

Jess Shanahan

Published

Estimated Read time

7Mins

AI’s rapid evolution is creating both opportunity and urgency. AlixPartners lays out what needs to change — and why risk-takers will lead the way.

The use of artificial intelligence (AI) in procurement is gaining traction with many organisations already looking at how the technology can improve processes. However, there’s scope to go beyond efficiency and instead focus on transforming value delivery. 

At DPW New York, we spoke to Amit Mahajan and Aaron Addicoat from AlixPartners, a management consultancy firm doing things a little differently. The organisation is advising its clients on how to implement AI to drive value, but it’s also using AI internally, too. 

“AlixPartners has a unique business model,” explains Addicoat. “We have a very senior model, very few junior resources. So now you imagine taking people with 10 or 15 years experience and now you equip them with AI… for us, it’s a huge unlock.”

This is about more than just productivity gains. AlixPartners focuses on using AI to transform the way procurement teams work, while crucially, maintaining the human touch.

How procurement professionals are using AI

With the support of technology, it’s possible to shift procurement from a cost-saving exercise to a potential revenue driver. Procurement teams are already looking for these opportunities, as Mahajan explains. “They’re starting to think about new ways of doing things,” he says. “It’s not just automation, but asking how do I leapfrog and do something differently?”

There are plenty of use cases where AI is helping with automation. This is a great place to start as it frees up human workers to do more valuable jobs that need a personal touch. “I have a client who’s using AI every day,” says Addicoat. “This allows them to review documents and contracts rapidly, to find key clauses and termination dates. They’re also using it in spend control processes to identify which things need to be reviewed more thoroughly.”

Many organisations are also using AI agentically to create their own bots. This gives teams a more accessible way to review information. “One example is a client who’s using AI for their business to help with acronyms,” says Addicoat. “They built it as an acronym tool to help break down the language barrier between different functions using different terms. This led to better engagement.”

This empowers employees across an organisation to be more autonomous while still getting the full picture. Agentic AI, especially, allows them to interact with information in a way that previously would’ve required specialist technical knowledge. Now, it’s possible to query information within a contract directly. 

“It’s about using agents and AI to look at anomalies within your procurement contracts,” explains Mahajan, “and be able to help the category analysts, the category specialists, and others to get more of those insights.”

While generative AI might be a hot topic, it’s not the only way to use the technology. In combining several sources of data and using AI to spot trends, it’s possible to create workflows tailored to the current environment. Addicoat explains: “We take a series of data inputs, such as weather patterns, lead times, contractual terms, inventory, and forecast. Then the AI generates the purchase order, queues it for review, and upon approval, places the order.”

This can help an organisation to place orders with the right supplier in the most timely fashion to avoid delays, and optimise for cost, for example. This fully automates the end-to-end process, using AI to interpret those important data signals.

While this is useful for procurement teams, it’s only the start. “Using AI in this way is really cool,” says Addicoat, “but what I found most fascinating is that you’re building a data model, and with AI layered into it, that over time can tell you how to optimise itself.”

This has huge implications for procurement teams looking to save money and drive revenue. “For example, it could tell us the commodity price at a certain point in time was low,” says Addicoat, “but because inventory capacity to hold resin was maxed out the client could only buy so much at that low price. So now investing in a new storage unit at a cost of a few hundred thousand dollars could, under the same scenario in the future, save millions of dollars..Data quality challenges

A roadblock that can stop procurement teams from fully embracing AI is a lack of quality data. With so many sources of information, often including paper-based documents, some might think it’s difficult to get the data AI needs to be truly useful.

“Don’t wait for everything to be perfect before you get started,” says Addicoat. 

This is a sentiment echoed by Mahajan: “Use AI to solve your data problem before solving your business problems.”

This requires a mindset shift. While AI can help cleanse, enrich, and structure existing unstructured data, it’s important to take the right approach. Shift from asking ‘what can we do with our data?’ to ‘what value do we need to create?’ and work backwards from there.

With this approach, the questions are less about the data and more about the business problem. This then allows you to use AI to work with the information you have to help answer those questions.

“Start with the value proposition in mind and work backwards,” explains Addicoat. “You can get data from anywhere — it has to serve a purpose.”

Bringing back the human touch

AI can free up procurement teams to focus on tasks that need more nuance and expertise. Using technology to automate workflows and make information more accessible has a huge impact on employee productivity. “It’s fundamentally transforming the way they work, the amount of work they can do, and the type of work they’re able to do,” says Addicoat.

There’s always the worry that with any new technology, the human element will be forgotten. “With every new advancement that comes in,” says Mahajan, “whether that was a steam engine or when computers came along, everybody wondered what they were going to do. But as humans, we always find ways to start doing higher-level work.”

This means that many professionals will find new ways of doing things. “Imagine all the mundane tasks you have to do in your daily job now,” Addicoat continues. “With these new ways of working, imagine the speed with which you can turn an idea into something real. All that time you free up allows you to go talk to people and build relationships that mean something.”

On the other side of things, the sheer volume of AI-generated content out there is going to drive people towards those more meaningful interactions. “You don’t know what to trust and what to believe anymore,” Addicoat says. “That’s going to lead to a resurgence in face-to-face content, being at the office, and being at events.”

AI’s impact on procurement talent

The talent landscape is changing. With technology playing a larger part than ever before, organisations don’t just need procurement professionals, they need adaptable, tech-savvy people. The nature of the job means that those in procurement need a wide range of skills. 

“We do everything,” says Addicoat, “legal, operations, supply chain, negotiation, analytics. Procurement professionals are generalists.” 

Tech plays into every element of that skillset, which means tech skills are becoming even more important for candidates applying for procurement roles. “Nobody goes to college thinking they’ll be a procurement professional,” says Mahajan, “but with AI and tech, that’s changing.”

With procurement often seen as a proving ground for leadership, embedding these tech-minded generalists could have a huge impact on the future. “We have a shortage of talent,” explains Addicoat. “But with more and more CEOs and COOs coming from procurement, that speaks volumes to what procurement does and the value it brings, as well as what the future holds.”

At AlixPartners, the passion for procurement is very clear with Addicoat saying: “There are only two kinds of people in the world: those who love procurement and those who don’t know it yet.”

Change is coming

With AI of all forms steadily gaining traction, procurement could change dramatically in the coming years. It’s the organisations that are willing to take risks and embrace change that will come out on top.

“AI has the potential to disrupt the whole management consulting world,” says Mahajan. “Firms focused on transformation will thrive.” 

With AI’s capabilities increasing rapidly, it’s difficult to predict what comes next. However, adaptability is key. “Hold onto your hat. In a year and a half, the world’s going to look very different,” concludes Addicoat.

Author

Nell Walker

Published

23 July 2025

Estimated Read time

7Mins

Why businesses should prepare themselves for AI by not getting lost in the whirlwind of hype and focusing only on what works for their needs.

With AI being the topic of conversation for procurement professionals right now, it’s easy to get lost in the maze of conflicting information. Vroozi is a procure-to-pay platform powered by robust AI capabilities to deliver meaningful use cases. CEO and Co-Founder, Shaz Khan, takes approaching AI the right way very seriously. 

For Vroozi, the use of AI is a two-sided coin. It’s an organisation that talks about AI both in production and consumption. AI is a tool that has been a game-changer, because it has enabled Vroozi’s software and technology engineers to be able to rapidly prototype and develop code. And that code is beneficial for creating feature sets and capabilities that the company wants to introduce to the market.

“Similarly, we take steps to look at how a customer interacts with our software for the first time,” Khan explains. “The implementation process is also ripe for consuming and producing great results with AI. Imagine you go through some type of interview wizard where you prompt the system based on your region and industry. The system will self-configure according to your business unit. This is real intelligence that understands your business at a different level, as well as the competitive landscape, and brings in best practices to deliver incredible results.”

Getting the approach right

Having said that, Khan freely admits that we’re in the early innings of AI adoption. For him, leaders should adopt a multi-pronged approach to implement AI. The first move is to assemble a team. “One key area with AI is that a lot of companies are relying on outside experts that don’t know the business and the goals that they’re trying to achieve,” he explains. 

“You should invest in your own people before you invite outside parties in. Bring that education and assemble a use case, before assessing the problems you’re trying to solve and determining whether AI is a good tool set or capability to solve the problem. If these things match up, execute the game plan, bring in the right technologies and the right expertise, and only then bring AI capabilities into your workforce.”

The challenges

With this being the “early innings”, there are also barriers and challenges. The main issue, from Khan’s perspective, is security. “There’s a trust aspect that has to be looked at,” he explains. “There’s also an ethics aspect. Are you delivering the right results? And how much autonomy are you giving AI and its agents to go out and deliver those results for you without any human interaction? I think the companies that get it right will strike a balance between the trifecta of automation, really great AI technologies, and a balance of human interaction to create an overall output.”

There’s also the question of data. If the data isn’t clean, output will be compromised and lead to poor results. We haven’t seen the worst of what can happen, Khan believes, and AI has the potential to create scenarios that are hard to recover from, if used poorly. “We need to prepare ourselves now to prevent those types of potential calamities from happening,” says Khan. Which is the entire point of DPW: for procurement and technology leaders to educate and learn about best AI practice. 

This allows people to cut through the, as Khan puts it, “hysteria” around AI that can cause problems for businesses. They’re rushing to solve problems, and while leveraging AI can be a component of a complete holistic toolkit, it can’t be the only answer. “A lot of companies today still struggle with getting their businesses off spreadsheets,” he states. “AI should be an equaliser and enabler to get it right.”

Structuring unstructured data

For Khan, in order to ready themselves for AI, procurement professionals and practitioners need to be absolutely committed to data management and governance. “What companies often forget is that much of today’s data is unstructured. It’s not neatly stored in databases – it might be a chat, an image of a spec sheet, or a contract never digitised. This unstructured data often can’t be used by AI models today, so companies risk only addressing a small part of the challenge. Data governance has to be an ongoing exercise.”

Having said that, Khan is keen to differentiate between clean data and perfect data. In fact, many procurement professionals we spoke to at DPW New York 2025 said the same. The message is: don’t wait around for everything to be perfect, or you’ll never start.

“Good enough data is just fine,” Khan says. “But if you’re going to continue to feed your AI engines and algorithms bad data, your outputs will be compromised. Companies need to have data governance strategies and upfront policies in place so that they can manage this, independent of the people that offer them.”

AI creating a complete picture

While treading carefully is important, Khan is equally keen to extoll the many virtues of AI for procurement professionals. There are many incredible use cases already, and AI tool sets and algorithms can effectively interrogate a company’s data and give them the answers they require. AI enables these users to have a complete picture of their buying cycle, and allows them to get additional information for where they can pivot.

“This is where the true power of agentic AI will come into play,” says Khan. “When you can fully trust the system inputs, AI will be able to orchestrate those processes autonomously, and present that information to an end user for final decision.”

Khan is very excited about what Vroozi is doing within its own AI layer. The business looks at AI and intelligence as a pervasive thread across its entire tech stack. Every aspect of its platform has some kind of AI enablement, although it’s not an AI-first company. 

“We follow three distinct areas where we are thriving on the AI front,” says Khan. “First is intelligent document processing. Can we take structured and unstructured data such as contracts, quotes, work orders, and invoices, and populate them automatically onto a screen without any human touch? Processing invoices might require an army of people typing in data, and they might not capture it all. But an AI toolset can take millions of records and process them simultaneously. That’s the power of AI.”

The power of hyper-personalisation

The second area is what Vroozi calls hyper-personalisation, where it intensely personalises the platform to meet a company’s preferences and needs. It’s about how AI can find trends and not only predict the user’s needs, but also help take the next steps. This includes finding suppliers and ordering things that are needed, so that workflows aren’t disrupted.

“Then we also have what we call the push economy,” says Khan. “AI’s power is in pushing and giving people head starts. So when you talk about AI algorithms and look at analytics, it’s about how AI can present to companies in the procurement space when they need to lock in favourable pricing on products and services, and predict when you are seeing potential fraud scenarios based on trends and patterns. You need a lot of data for those AI models to train on, which is why I say we’re in the early innings. It takes time, but it’s incredibly powerful when you get to that point.”

The benefits ahead

At such an exciting time for procurement, 2025 and 2026 look bright for leaders in this space. Not only procurement, but also supply chain and FinTech, are set to benefit from what AI can do with data. 

“There’s going to be a focus on how to capture and harness data, and feed it into AI in a way that produces results,” says Khan. “What we’ll see in the next two years is that AI has now learned from the data that’s been fed into it. You’re going to see higher-quality results and better outcomes. Again, I would caution companies to define the problem first. Then determine if AI is an absolute enabler and game changer. We believe AI can be an influencer and supercharger in terms of productivity. However, there needs to be specific use cases that make sense for corporations. 

“In 2025 and beyond, you’re going to see great technologies embedded into organisations that really work.”

Author

Nell Walker

Published

13 May 2025

Estimated Read time

2Mins

DPW is set to hit New York for the second year in a row, bigger and better than in 2024, and with an extensive list of experts set to speak.

After the success of last year’s DPW NYC Summit, Digital Procurement World is making the event bigger and even better for 2025. DPW New York 2025 will take place at the extremely stylish ZeroSpace Brooklyn on the 11th and 12th of June. The theme this year is ‘Put AI to work’, focusing on the practical applications of artificial intelligence, and the opportunities for innovation across procurement.

The speakers have not yet been finalised and more may be added, but the event will include:

  • Brian Solis, Head of Global Innovation, ServiceNow
  • Jennifer Moceri, CPO, Google
  • Al Williams, CPO, Invesco
  • Eva Choe, CPO, The Chlorox Company
  • Kat Devlin, Head of Procure-to-Pay Operations and Travel & Expense, OpenAI
  • Oliver Gall, CPO, Prudential Financial
  • Maria Jesús Saénz, Director Digital Supply Chain Transformation Lab, MIT
  • Victor Miller, Chief Compliance Officer, Honeywell
  • Noah Eisner, Founder & Advisor, Coupa/Rebar Advisors
  • Bawana Radhakrishnan, SVP Global Supply Chain Digital Transformation, Colgate-Palmolive
  • Chris Duffey, Head of GenAI, Adobe
  • Elouise Epstein, Partner, Kearney
  • Sarah Luisi, VP Group Strategic Sourcing & Operations America, LVMH
  • Tony Filippone, Chief Research Officer, HFS Research
  • Lauren Hymen, VP Strategy & Transformation, PepsiCo
  • Adam Brown, Global Director Procurement Technology Platform, Maersk
  • Mitchell Toomey, VP Sustainability & Responsible Care, American Chemistry Council
  • Stefanie Fink, Head of Global Digital Procurement, Kraft Heinz
  • Carlos Hernandez, Head of Procurement Excellence & Framework, Sanofi
  • Rosalia Snyder, Director Source-to-Pay, Microsoft

DPW New York is set to be a hub of inspiration and insight, with a broad range of figures sharing their knowledge and experiences with guests. After developing the concept of DPW in 2019, Founder Matthias Gutzmann’s event has grown into something that entices procurement professionals from all over the world. 2024 saw the DPW team putting on an intimate, invite-only New York event. This year, DPW is scaling up – and we at CPOstrategy to be there on the ground floor.

Join us at the 2025 event by buying your tickets here.

Author

Nell Walker

Published

28 August 2024

Estimated Read time

4Mins

We caught up with Shachi Rai Gupta from ORO Labs to discuss the importance of orchestration in procurement.

Simplifying procurement in smart ways is the ultimate goal for ORO Labs. Utilising the best of AI, ORO Labs aims to implement procurement orchestration across sectors, creating an experience that is simultaneously automated, augmented, and humanised.

Shachi Rai Gupta is VP Strategy at ORO Labs, with a wealth of transformation and technology experience behind her. Rai Gupta’s sharp eye on procurement has allowed her to witness the rise and fall of various trends, and understand what the sector needs as it – along with technology – evolves. 

We caught up with Rai Gupta at the DPW NYC Summit back in June, a special North American version of the event. Procurement trends, especially AI and orchestration, were very much the theme of the day, prompting lively conversations amongst some of the world’s most influential procurement leaders.

Procurement as a net positive experience generator

For Rai Gupta, the trends right now are guided by the fact that procurement has more of a  strategic and evolved role than ever, giving the function the opportunity to have a great impact on the enterprise bottom-line and the environment and community at large 

“Procurement is morphing into a function where one of its biggest responsibilities is to be a net positive experience generator,” she explains.

“Procurement really is a service function for the whole business stakeholders. We, as procurement professionals, need to see things through the lens of the business. This includes what issues the business is trying to solve, and meeting the business where it’s at for good collaboration.

“It’s also important to make this experience as easy as possible, rather than cumbersome and time intensive. That needs to be catered and customised to the individual business segments.”

Prioritising the planet

Another area Rai Gupta is seeing talked about a lot is sustainability. This topic has, for some, been sidelined a little in favour of advanced technology. But it’s just as important as it’s always been, and it’s vital to keep the discussion alive – especially in procurement.

“More and more, companies are realising the impact they’re having on the environment,” Rai Gupta explains. “It’s an increasing priority on all our agendas. The technology is still nascent in that space, in the sense that there aren’t good ways to do benchmarking or tracking. That’s going to be an interesting space to watch out for.”

The next generation

Another hot topic of the DPW NYC Summit was the talent shortage. We at CPOstrategy discuss this topic a lot with procurement professionals, and there’s no one answer for fixing the issue.

“There’s a dearth of good digital talent,” Rai Gupta states. “The skillset you need today in procurement is very different from what we’ve had before. To be able to leverage that, to really make use of the procurement teams you have and the operational model you want, it’s a different challenge. The structure of your team is more important than ever. 

“While that shortage is there, when you do have the right people in place in procurement, that’s where the department shines,” Rai Gupta adds. “That’s where procurement becomes a group of trusted advisors for the business, providing proactive opportunities. We wear a lot of hats in procurement, and we’re stepping up to a new level of evolution.”

Advanced tech for good

And, of course, AI and orchestration are terms on everyone’s lips right now – procurement included. AI is, in Rai Gupta’s words, “a solver”. Many of the blockages and challenges procurement is experiencing as it evolves can be solved, or at least aided, by AI and orchestration. “There’s so much tech out there,” Rai Gupta states. “AI is one such possibility. Every segment of procurement comes with its own risks and requires its own expertise and tool sets. 

“To manage that whole ecosystem is where that orchestration comes in. There’s a real beauty in this because it’s collaborative. It makes the whole bigger than its parts.”

Author

Andrew Woods

Published

23 July 2024

Estimated Read time

3Mins

Shelley Salomon, VP of Global Business, Amazon Business, discusses her company’s commitment to fostering gender diversity in procurement.

Procurement’s gender imbalance isn’t new.

Traditionally, the function was regarded as a male-dominated profession. But change is afoot, in more ways than one. While a digital transformation amidst technological innovation is well-publicised, another evolution is underway within the workforce.

Gender diversity has become an important component of many company strategies globally. While progress to encourage more women into procurement has already started. There still remains an imbalance, particularly among those holding leadership positions. With current statistics suggesting around one in four leadership positions are held by women, there is still room for improvement.

So, is progress happening quickly enough? Shelley Salomon, VP of Global Business at Amazon Business, discusses her organisation’s commitment to fostering gender diversity and how women can reach parity in procurement. 

In your opinion, where is procurement today in terms of women’s representation in 2024?

Shelley Salomon: “Women’s representation in procurement has seen progress these past few years, but there remains room for further improvement. Gartner’s data shows that women comprise 41% of the supply chain workforce. It’s encouraging to see greater gender diversity within the industry.

“While these statistics are encouraging, they also highlight ongoing challenges. Particularly at the leadership level. Only 25% of leadership roles are held by women. This disparity underscores the need for sustained efforts to promote gender diversity and support women’s ascension to senior positions within procurement.

“My perspective on this trend is one of cautious optimism. The progress we see is promising, reflecting a growing recognition of women’s unique contributions to procurement roles. Diverse perspectives and gender equity are vital for effective decision-making and problem-solving. Additionally, multiple credible studies show that companies with the greatest gender balance in the C-suite are likelier to achieve above average financial results. However, much work must be done to ensure these advancements translate into lasting change.”

While progress to encourage more women into the workforce seems to be underway, there is still a major disparity in the number of women leaders in procurement. What is the best way to go about rectifying this? 

Shelley Salomon: “I believe there’s a significant opportunity to welcome more women into procurement leadership roles. By establishing robust mentorship and sponsorship programmes, organisations can provide invaluable guidance, support, and networking opportunities. Thus empowering women to thrive in their careers and gain visibility within the organisation. Investing in inclusive leadership development programmes is essential. These initiatives focus on building inclusive skills and readiness for leadership roles, continuing to foster a more inclusive and dynamic workforce.

“In my opinion, implementing inclusive hiring practices that actively promote gender diversity, such as using diverse hiring panels and conducting blind recruitment processes, is essential to minimising biases. 

“Lastly, setting clear, measurable goals for increasing the number of women procurement leaders and regularly reporting on progress to hold leadership teams accountable can drive meaningful change. By taking these proactive steps, organisations can create a more equitable environment that supports the advancement of women into leadership roles within procurement.”

Read the full story here!


Author

Andrew Woods

Published

Estimated Read time

3Mins

Sagi Eliyahu, Co-Founder and CEO at Tonkean and Alejandro Fernandez, Head of Global Procurement at Semrush, discuss the power of intake orchestration and procurement’s rise to the top of the agenda in the c-suite.

In a world with almost endless possibilities, why waste time on manual or outdated processes?

Technology is an enabler in everyday and business life. It is there as a vehicle of change and a weapon of efficiency. When used correctly, AI can help people focus on higher-value and more fulfilling work – which is what an entire generation of people crave today. The problem is, technology is not leveraged as efficiently or as strategically as it could be today — especially in enterprise back-office operations, like procurement. 

This is where Tonkean comes in. Tonkean is a first-of-its-kind intake orchestration platform. Powered by AI, Tonkean helps enterprise internal service teams like procurement and legal create process experiences that transform how businesses operate. In part by changing how internal teams leverage smart technology to empower the employees they serve to do better, higher value work.

Process orchestration

Process orchestration refers to the strategy — enabled by process orchestration platforms — of coordinating automated business processes across teams and existing, integrated systems. These processes can facilitate all procurement-related activities. Importantly, they can also wrap around an organisation’s existing systems and accommodate employees’ many different working preferences and styles.

Instead of simply adding to an organisation’s existing tech stack, process orchestration allows companies to use their existing mix of people, data, and tech better together. The true promise of process orchestration is to finally put internal shared service teams like procurement in charge of the tools they deploy.

This goes a long way towards solving one of the enterprise’s most vexing operational challenges: the inefficiency of over-complexity born of too much new technology. It also allows procurement teams to truly make their technology work for them and the employees they serve. As opposed to making people work for technology. Process orchestration breaks down the silos that typically separate working environments. No longer do stakeholders have to log in to an ERP or P2P platform to submit or approve intake requests. The technology will meet them wherever they are.

All in one place

Enter Sagi Eliyahu, Co-Founder and CEO at Tonkean. He explains that over the past few years, Tonkean has focused more on procurement specifically. In part because the challenges the procurement function faces day-in and day-out represent perfect orchestration use-cases. Procurement processes touch so many different teams, tools, and departments. Poor procurement performance can often be traced back to the fact that all these moving parts otherwise aren’t able to communicate easily with each other. Tonkean was built to address exactly that problem. 

“We saw that our procurement customers were having great success with it, but the market started to heat up as well,” he reveals. “It made sense because it happened for us on the procurement and legal side. They are teams that are very central to an organisation and their process is never just siloed into their tools and department. You need that idea of orchestrating all the different moving parts for it to have high adoption, faster cycles, better quality and compliance.”

Tonkean and Semrush partnership

One of Tonkean’s biggest customers is Semrush. Semrush, in turn, understands the potential of orchestration in procurement well. As a result of Tonkean’s intake orchestration capabilities, they’ve almost halved cycle times for intake requests — from 19 days to just 10. Alejandro Fernandez, Head of Global Procurement at Semrush, works closely with Eliyahu and Tonkean and couldn’t be happier about the collaboration…

Read the full story here!

Author

Andrew Woods

Published

18 June 2024

Estimated Read time

5Mins

Our cover story this month…  Marriott International Inc: A more sustainable supply chain  With science-based targets approved, Marriott is accelerating…

Our cover story this month… 

Marriott International Inc: A more sustainable supply chain 

With science-based targets approved, Marriott is accelerating work to help make its supply chain more sustainable. We speak to Stéphane Masson, Senior Vice President, Procurement, Marriott International, Inc. – for our exclusive cover story this month – to find out how… 

“Like many global companies, Marriott recognises that serving our world helps the communities where we operate and is also good business,” Masson tells us. “This Earth Day, we announced the approval of our near-and-long-term science-based emissions reduction targets by the Science-Based Targets initiative (SBTi), with a goal to reach net-zero greenhouse gas (GHG) emissions by no later than 2050. Approval of these targets is bringing heightened focus on our work to embed sustainability in our operations.  

Specifically, the company has committed to reduce absolute scope 1 and 2 GHG emissions 46.2% by 2030 from a 2019 base year. Marriott also commits to reduce absolute scope 3 GHG emissions from fuel and energy-related activities, waste generated in operations, employee commuting, and franchises 27.5% within the same timeframe.  

Importantly for our team and the suppliers we work with across the globe, Marriott’s targets include 22% of our suppliers by emissions—covering purchased goods and services, capital goods, and upstream transportation and distribution—which will have science-based targets by 2028. 

In the longer term, Marriott also aims to reduce absolute scope 1 and 2 GHG emissions 90% by 2050 from a 2019 base year and reduce absolute scope 3 GHG emissions 90% within the same timeframe.  

Our Global Procurement organisation plays an important role in setting up Marriott as we work to achieve the targets within this timeline. And it will require an evolution in how we engage Marriott associates, our suppliers, and other members of the industry.” 

Read the full story here! 

Grupo Modelo: Procurement and sustainability in action! 

We speak to Soqui Calderon, Regional Director of Sustainability for Grupo Modelo and the Middle Americas Zone, to see how the beverage giant is tackling sustainability from a procurement perspective… 

Grupo Modelo is a giant. A leader in the production, distribution and sale of beer in Mexico, Grupo Modelo is part of the Middle America Region (of the AB InBev Group) and boasts 17 national brands, among which are Corona Extra, the most valuable brand in Latin America, as well as Modelo Especial, Victoria, Pacífico and Negra Modelo. The company also exports eight brands and has a presence in more than 180 countries while operating 11 brewing plants in Mexico. 

Through more than nine decades, Grupo Modelo has invested and grown within – and with – Mexico, generating more than 30,000 direct jobs in its breweries and vertical operations, located throughout the country. 

Grupo Modelo, like many forward-thinking companies, is currently focused on a drive towards establishing a truly sustainable business. This endeavour is best exemplified in the Middle Americas Zone (MAZ), where sustainability efforts have been led by for the past five years by Soqui Calderon Aranibar, Regional Sustainability and ESG Director. Ambitious targets have been established for the region, but some remarkable achievements have already been made. As Calderon says: “For our team, sustainability is not just part of our business, it IS our business.” 

Read the full story here! 

SDI International: Delivering tail spend excellence 

SDI International’s Brendan Curran and Joaquín Morales discuss empowering procurement innovation, the importance of effective tail spend management, and how its Master Vendor programme transforms the function 

In a world of greater complexity and risk, technology adoption and digitalisation, and an ever-evolving compliance and regulatory environment, procurement teams still grapple with a perennial challenge: cost reduction. Which is why tail spend management – often overlooked and unmanaged while procurement focuses its attention on strategic, high-spend categories – is so important. Indeed, for many organisations, taking effective control of costly, one-off buys and high-volume, low-value purchases involving numerous suppliers can deliver as much as 5% to 10% of cost savings, according to Boston Consulting Group. 

But tail spend, by its nature, is complicated. It requires significant focus to effectively manage high volumes of data, often has a perceived lack of strategic importance within both procurement and the wider organisation, lacks visibility, involves vast numbers of transactions, many product categories, and a largely anonymous supplier base, and can bring potential compliance risks because of poor onboarding processes or inconsistent terms and conditions.  

Tackling the problem can be daunting for procurement teams. But, according to SDI International, it doesn’t have to be. The organisation, one of the world’s largest diversity and woman-owned procurement outsourcing and technology providers, delivers industry-leading holistic tail management solutions based on a successful formula: simplify, digitalise, innovate. Its Master Vendor programme provides procurement teams looking to tackle their tail with a one-stop solution for tail spend that leverages the latest and most efficient technologies to handle supplier onboarding and on-time payment, and manage the entire tail supply chain, stakeholder servicing, and escalations. The result is a procurement department better able to drive cost saving, efficiencies, and more strategic outcomes.  

Read the full story here!