These milestones reflect not just commercial progress, but market validation of Exiger’s platform
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The US Army has licensed Exiger’s AI software in order to accelerate its defence acquisition, reduce lead times, and enhance operational readiness. It’s part of a multi-million collar contract that’s been awarded to Exiger to provide end-to-end supply chain risk illumiation.
“This is a revolutionary capability that will transform the way the U.S. Army approaches sustainment,” said Exiger CEO Brandon Daniels. “Our software will help identify at-risk NIINs that may be subject to undue constraints from a variety of factors. It will unlock the organic and additive capabilities that the government has invested in. And it will monitor for severe risk hiding in the supply chain, identifying where natural and manmade disasters, supplier operational and reputational risk, and foreign adversary sourcing could create disruptions in the weapons systems our warfighters depend on. Together, these capabilities deliver a more predictive industrial base, capable of responding to evolving mission needs at speed.”
Exiger has also joined forces with Palantir as part of this project, combining Palantir’s operating system with its own mission-built supply chain AI.
“This partnership combines Palantir’s and Exiger’s world-class technologies to integrate production decisions with battlefield demands, ensuring the US Army can deliver faster and more reliably to those on the front lines,” said Mike Gallagher, Head of Defense, Palantir.
“AI and automation across the supply chain enable deeper visibility, faster risk surfacing, active and proactive mitigation, and accelerated supply movement, giving commanders and portfolio acquisition executives a level of foresight and speed never before possible,” Daniels added.
Exiger has been awarded a huge contract to help modernise the detection of transshipment for the US government
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Exiger, the market-leading supply chain AI company, announced today that it has been awarded an exclusive, multi-million dollar contract by US Customs and Border Protection (CBP) to modernise the detection of illicit transshipment across global supply chains. Designed to evade tariffs, trade restrictions and sanctions, illicit transshipment is the practice of manipulating supply chains to disguise a product’s true country of origin. Exiger’s Trade AI will be adopted and deployed across CBP, serving as an additional tool for the US government’s transshipment detection capability.
Transshipment identification and enforcement are critical priorities for the Department of Homeland Security (DHS) and CBP. Convergent Solutions, Inc., DBA Exiger Government Solutions, will equip CBP enforcement offices and personnel across the US with access to Exiger’s AI platform and data to identify illicit transshipment at-scale and in real-time.
“Billions of dollars worth of global trade move through illegal transshipment channels that seek to bypass US restrictions,” said Exiger CEO Brandon Daniels. “A core CBP mission is to enforce US trade and forced labor laws, thereby helping ensure that American manufacturers and workers are competing on a level playing field. Exiger is proud to support this mission, bringing to bear the world’s largest proprietary supply chain database and the market’s most sophisticated AI.”
Exiger’s AI will be an additional resource available to CBP personnel to:
Detect illegal transshipment across global supply chains
Monitor and enforce tariff and trade regulations
Leverage Exiger’s proprietary AI models and trade intelligence data to enrich data in CBP systems and enhance decision making
Deploy AI-enabled validations of tariff classification, value and country of origin
Create automated bills of material for products and sub-components
Map the flow of raw materials and sub-components through global supply chains
Risk-score shipments in-real time
Collect tariff revenues earlier
Trace global supply chains to enhance import visibility and risk segmentation
Exiger’s proven AI solutions have been deployed across 60+ US Government agencies, including the Department of War, Department of State, Department of Energy, DHS, the intelligence community, and armed forces.
Exiger’s technology continues to earn top recognition. In April, Exiger was named an awardee on the Government Services Administration’s Supply Chain Risk Illumination Professional Tools and Services (SCRIPTS) Blanket Purchase Agreement, and was the highest-ranked unrestricted vendor awardee of the 10-year, $919 million contract. This year, Exiger was named a Leader in the 2025 Gartner® Magic Quadrant™ for Supplier Risk Management Solutions, a Best-of-Breed Solution and three-time Value Leader in Spend Matters’ SolutionMap, and a Leader in Omdia’s Market Radar: Firmware and Software Supply Chain Security. Exiger also won a 2025 STEVIE® Award for AI Company of the Year.
Jonathan Jackman, Regional VP at Kinaxis, dives into how AI is reshaping supply chain planning.
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Artificial intelligence (AI) is often seen as a threat to jobs, with a recent TUC poll showing half of UK adults worry that AI will take their job. When it comes to the supply chain sector, AI is shaping up to be a powerful tool that empowers planners to take on more creative, fulfilling roles.
The prospect of AI-enabled supply chain planning is an exciting one for both professionals and businesses. Scaling operations without the need to massively increase headcount is a major selling point for any enterprise, while for professionals, the prospect of removing the repetitive, mundane and manual processes that restrict and slow effective planning is surely a promising one.
Far from job elimination, AI is a major upgrade for supply chain workers in a number of different ways. We’re entering a new era of increasingly autonomous AI systems, which will elevate supply chain planning to new heights. So, how exactly will the day-to-day role of the planner evolve as we go further into the AI era?
Humans still in control
First, it’s important to dispel a myth: the supply chains of the future will not be “driverless”. Many believe that AI, and particularly agentic AI, has the potential to run supply chains on autopilot. This is far from reality: while AI can surface insights, automate tasks and even take action in a crisis, it will always need to be augmented by a human to fully interpret the nuances of the real-world.
This human oversight is a crucial failsafe. There will be many times where AI flags potential shortages and proposes the best way to respond, but it will only ever be as good as the insights it is fed and the guidance given by human. For example, what if it is missing a crucial bit of real-time information about an upcoming election which could lead to disruptive trade challenges? While the algorithms. may be great at crunching the numbers and making recommendations, only a human planner can assess the full context surrounding a decision before deciding action.
The future of supply chain planning isn’t AI instead of humans, it will be AI and humans. In the AI era, supply chain professionals will be the orchestrators, steering AI systems and validating recommendations with important human insights and context.
Each planner is likely to have fleets of AI agents beneath them, acting as demand forecasters, inventory optimisers and scenario simulators – feeding information back to the supply chain professionals to empower them to make the best decisions based on the maximum amount of data analysis, all done in real time.
Planners unleashed
With AI handling the mundane and routine supply chain tasks, planners will be unleashed to focus on the creative, strategic elements of the job that machines simply cannot do: building relationships, working with partners, building and selling strategy, and, of course, managing AI agents.
Consider negotiations with partners, for example, AI won’t be able to compete with a human. It will, though, supply planners with the data they need to enter those discussions armed with deeper insights than ever before, empowering them to work more effectively.
Planners will also play a critical role in shaping the very AI tools they use – training models, curating data, and ensuring outputs reflect reality. Over time, this human feedback loop will make the technology even more valuable.
One key evolutionary step we are starting to see is the emergence of Autonomous Concurrent Orchestration. Currently, many vendors focus on agents automating existing siloed processes, but in the future, we will see more agents that synchronise planning decisions across functions – procurement, logistics, manufacturing – in real time. Agent-to-agent communication will break down silos and speed up problem solving and decision making, easing the burden on supply chain professionals.
Augmenting, not replacing
Perhaps artificial intelligence is the wrong phrase when it comes to supply chains Instead, the industry should be discussing augmented intelligence, where machines unlock insights and real-time decision making that simply wasn’t possible when tasks relied on manual processes.
For planners, the AI era promises exciting change: embracing new tools and evolving alongside this technology is not only good for business, but good for the careers of supply chain professionals.
SupplyChain Strategy attended July’s Exiger Executive Forum to hear from the best and the brightest in the industry.
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Supply chain resilience is one of the most pressing concerns of modern business, whether executives are aware of it or not. That was the central theme of the Exiger Executive Forum held on July 23rd 2025. Titled Supply Chain Sovereignty in a Fractured World: Winning the AI and Geopolitical Race for Resilience, the event brought together business analysts, CEOs, supply chain and procurement executives, academics, and politicians for an open discussion around supply chain sovereignty and the urgent need to secure supply chains across myriad industries and territories.
As geopolitical events, trade wars, and threats to globalised networks threaten to destabilise global and local supply chains, the case for supply chain sovereignty, which is an organisation’s ability to control its supply chain and minimise dependence on external suppliers, becomes increasingly stark. However, a myriad of stakeholders must come together to enable organisations and nations to gain independent control of supply chains, and collaboration between industry, government, and academia is essential.
Three guest speakers joined Maria Villablanca, CEO and Co-Founder of Future Insights Network, each representing voices from within politics, business, and academia: Tobias Ellwood, former UK Minister and Chair of the Defence Select Committee; Koray Köse, CEO and Chief Analyst of Köse Advisory, Senior Fellow at GlobSEC Geotech Centre, and Board Member of Slave-Free Alliance; and Karsten Machholz, Professor for Supply Chain Management and Strategic Procurement at University of Applied Sciences, Wuerzburg-Schweinfurt.
The discussion exemplified the discordancy of priorities and perspectives among senior voices from all angles regarding security, economics, policies all impacting value chains, albeit with a shared willingness to engage in secure, competitive, ethical and innovative supply chains, fuelling businesses and economies through heightened volatility in a fractured world that is recalibrating through the era of reglobalisation.
Supply chain sovereignty: Bridging political understanding, and urgency
“It is a dangerous world that we’re entering,” Ellwood warned. “If I ask you ‘Do you think the world will be safer or more dangerous in five years from now?’, I think we’d all agree in which direction it’s going. We have to then ask ourselves how we prepare for that.” To that end, Ellwood believes an increased focus on supply chain sovereignty is both an economic and military imperative.
For Ellwood, the central issue is limited understanding, both public and private, around the urgency presented by the current risk and threat environments. Through the combination of limited knowledge around supply chain complexity and an election cycle-focused impetus to enact vote-winning policies, he believes the political class lacks both the nous and urgency to prioritise supply chain sovereignty.
“After 20 years in politics, I can safely say that many politicians are simply unaware of what’s coming over the hill,” said Ellwood. “The tide took me out to the last general election, and so I went from helping to craft and nudge policy and encourage Britain to move forward to then scrutinising what we were doing, not just at home but internationally. Now that I’m outside of politics, I continue doing those same things.”
The necessity for political engagement is not lost on Köse, who through his own experiences of researching, advising and leading supply chain organisations, has been advocating for supply chain resilience as a top line driver for economies and companies, has equally encountered the depth of that disconnect.
“At an early point I realised that geopolitics is the key denominator for all value chains and all of us in this context,” he said, adding that work is overdue but starting to be underway to bridge this gap. “The London Defence Conference, as one critical congregation, is key for you all folks to be aware of. Not only because of what they do in terms of bringing the politicians into one room to debate some of the most fierce topics of the day, but it’s all about convergence. Bringing in supply chain leaders, policy makers and technology folks with a direct approach to debate.”
Villablanca noted that Ellwood’s presence was indicative of a gradually shifting tide, however. “It’s not lost on me that here we are in this panel, talking about supply chain, and we have a former politician with us,” she said. “That is very different to some of my earliest supply chain conferences where we didn’t see that, so it’s a sign of the times. Set the scene for us around why you’re here and why it’s important to discuss the geopolitical situation vis-a-vis supply chain today.”
“I spent most of my time in politics trying to strategise, trying to go four or five chess moves ahead, and I found I was on my own,” Ellwood replied. “Politicians operate for the day, for the here and now, the election cycle; the news cycle is what keeps them busy. They’re not thinking about these things and yet the world we’re now seeing in everything… everything is being weaponised because that is the change in the character of conflict.
“But today, from my perspective, I see the world splintering into two spheres of hugely competing influences. If you look at the number of countries that have signed up to China’s One Belt One Road initiative, you’ll see that many of them are either opting or hedging their bets as to where things go.
“To make matters worse, our exemplifiers of what democracy looks like aren’t in a good place. We see what’s going on in America, British politics and so on, and Europe and America are not on the same page. We aren’t promoting global law in the sense that we had a sense of determination that we had when organisations were set up in 1945. Other nations are getting together and realising that there’s an opportunity to exploit the wobbliness of our world order and do things their own way.
“That’s where the mechanisation of just about anything comes in to cause us economic harm, to sow political discord from afar. It’s very easy to do and becoming easier simply because of the openness of our society. It means, from a rudimentary perspective, anything you do can be weaponised against you.”
“It’s very easy, from afar, to then limit your supply chains and thereby limit your capabilities. There are countries that specialise in sowing economic discord from afar. They understand and learn and know supply chains better than we do, and they can work out which missing pieces will cause our assembly lines to grind to a halt.”
That lack of preparedness, he says, is an impediment to putting the nation on a footing that could support a war effort on the scale of the World Wars.
He continued: “There’s also the prospect of preparing for war, which means that we are suddenly spending more money on defence. Our ability to switch on the supply chain levers to support military capability is not there. This is why companies that have no connection with the defence world need to think about the services they provide that might have a military bearing. In five years time, you may be called upon to do exactly that.
“That is the mindset we now need to get into. Security and economy are one and the same now, and that’s what we need to learn.”
AI, foresight, and risk strategy
The conversation then shifted to the business side, where securing critical supply chains powering key technologies such as AI, defence and security, biotech, energy and quantum computing has become a more pressing concern in the wake of a range of global disruptions through the early 2020s.
Along with broad supply chain breakdown during the COVID-19 pandemic, the geopolitical environment has become more fraught. Escalating trade wars, the imposition of sweeping import tariffs in the US and heightening tensions between America and China have thrown globalised networks into question. Alongside those challenges, Environmental, Social and Governance (ESG) directives have placed an increased onus on supply chain leaders to sanitise their supply networks against modern slavery, conflict minerals, and indirectly sourcing materials from rogue nations. The case for establishing redundancies in supply, as well as heightening visibility on an end-to-end supply basis, was thus clear amongst the panel.
“Koray, you work with a lot of different companies,” began Villablanca. “Do you think there’s a mindset issue where politics and commerciality need to come together to realise the common goal and create resilient supply chains?”
“Directly, there probably is a mindset issue,” Köse replied. “I think there is a lack of clarity about the importance of geopolitics’ impact upon supply chains, and there is certainly the capability issue of understanding the context of geopolitics.” He then elaborated on the challenge by highlighting shortfalls in companies’ predictive capabilities.
“Companies operate with risk dashboards,” he continued. “Sometimes it’s just red, yellow, green, and that’s all you have. They have a few key risk indicators like financial compliance issues, quality issues, performance issues, but you never see strategic foresight. It’s retroactive, based on historical numbers. If you look at a production line it might say, ‘We didn’t have an incident for 80 days’. What if somebody were to say, ‘We won’t have an incident in the next 100 or 80 days’? You don’t see that in production; it always looks backwards because it is built on the past.
“A big problem in a lot of the military complex, and in politics, is thinking that the next war will be like the last one. They cannot necessarily understand that asymmetric, hybrid and proxy warfare is really where things are going, and the same goes for technology. Supply chains are often built on yesterday’s technology.”
To then end, he believes supply chain leaders should be more forthright in leveraging their profound influence upon business operations: “In supply chain, we see the conversation about having a ‘seat at the table’ for decades now and I always say, ‘Just bring your own freaking table’, and invite everybody to it. Everything, every cent in an organisation, goes through you. Own that leverage and don’t run after them, invite them to come to you. Your table is where value is generated, secured and innovation and competitiveness are established. You hold the fate of the future.”
As to politics’ place within meeting this challenge, Villablanca asked Ellwood whether the political sphere could be doing more to shape the corporate agenda.
“Yes, and that last point you said is the most critical; recognising that there is a massive risk, that this is a very different world that we’re now facing, and I expect the point that’s really being made is the absence of politicians,” he said. “The politicians themselves need to be told what we need because their expertise in understanding this arena is poor.
“China now owns the periodic table. If you are into silicon wafers, where’s your serum going to come from? If you’re into magnets, where’s your Europium going to come from? You need to know this sort of detail, and it’s not just you yourself. It’s your suppliers and the suppliers of your suppliers, too.”
While supply chain transparency has undoubtedly increased in recent years, he stressed that considerable work remains to realise total visibility.
“At a recent procurement event I was astonished at how many household names were unaware of what their second and third-tier partners were doing during the procurement cycle,” Ellwood continued. “They didn’t understand the vulnerabilities, down to the SMEs, of what’s going on. If the assembly line stops then that’s quite serious, but what’s going to happen because of that stress?
“There are people who don’t understand it over here, not recognising that our competitors are deliberately looking at our supply chains and working out where that vulnerability lies. It is so that Ford stops making trucks, so that pharmaceuticals stop making medicines. Ministers are ignorant about this and we need to become better at it. This is the frontline of the next war that we’ll fight, and that war is coming.”
“I would add that some can’t fathom the complexity of certain supply chains and the vulnerability and risk associated with multiple tiers within them,” Villablanca posited. “There’s probably a translation issue with regards to business and politics around supply chain.”
To this, Ellwood stressed that international government groups hold the keys to unlocking a broader understanding within members’ respective political spheres.
“The G7, the Five Eyes Alliance, this is where these conversations need to go,” said Ellwood. “To recognise this must be a priority within the western world, we now need to have an alternative source to make sure that we can build our aircraft, we can build our factories, we can build our products. It isn’t so much the rare earth minerals themselves, but it’s the processing. Setting up a processing factory for rare earth minerals takes almost a decade.”
Here, a guest interjected with a point that hearkened back to Ellwood’s own admission that politicians have an innate directive to focus on local, vote-winning issues: “Politicians recognise there are no votes in this. The average MP will say their inbox is full of ‘fix the NHS’, ‘get the roads fixed’.”
Resolving political challenges such as those, Ellwood replied, is predicated upon strengthening economies to open fiscal headroom for public investment.
“If our economy is affected by problems with our supply chains, there’ll be no money in the treasury,” he explained. “Not for health, transport, potholes, policing, defence. It’s imperative that if you want to fill the coffers, then we need to protect ourselves. You can only do that with supply chain resilience. As a politician, you’ve got to take the people with you if you want to make the case.”
Villablanca then repositioned the conversation with regards to pressing issues around sustainability.
“There’s a lot of risk associated with our supply chains that goes beyond geopolitics,” she said. “We also have climate issues, economic issues. How do we maintain sovereignty in our supply chains while still trying to pursue goals around sustainability?”
“Supply chain transparency is something that I advocated for when I was a young consultant in the early 2000s when my hair was not so grey,” said Machholz, highlighting the gradual shift in supply chain priorities around identifying the finer details across those networks. “It isn’t a new topic and in the EU we now have the Critical Raw Materials Act.
Machholz drew the conversation towards sustainability in the context of integrity and continuity. “I’m German, and what we have is engineering power. We are good at car and machine manufacturing, but we have no natural resources. We have a little bit of coal, but all other things need to be imported. There have to be some sources to get those things.
“There’s Trump and tariffs going up and down, and we have some other geopolitical tensions affecting supply. You might say, ‘Where do I source this particular thing from? We don’t really have a second source of supply, because both of these sources are located in the same geographical spot.’ Maybe both of them are coming out of China.”
For Machholz, lessons to be gleaned around forecasting with technology’s latest predictive capabilities were presented en masse by the pandemic. “If we look at COVID, almost all supply chains were disrupted and you were running out of materials,” he continued. “You needed to be much more risk alert, and this is the problem we have already touched on: not looking in the back mirror, but using your data and turning insights into foresights to see what could happen, and then being agile and adapting.
“Sustainability could be one thing, having several sources, having alternatives, but of course, especially if we’re talking about critical raw materials, critical parts or maybe patent-protected or monopolistic suppliers, we are in an ambitious situation, put it that way, to find some alternatives.”
Machholz stressed: “This is something that each supply chain manager, CPO, and CFO, needs to understand to set boards’ scenarios. I’m pretty sure with the help of artificial intelligence we can elaborate much more on our data and predict different scenarios so we can be more prepared rather than just reactive.”
Shifting from cost-cutting to resilience
Of course, supply chain executives are under siege from an enormous breadth of challenges, whether it’s geopolitics, technological evolution as both a benefit and a threat, and shifts in consumer behaviours precipitated by those same factors. Rising to meet those challenges on all fronts, especially in a business landscape that often adheres to cost optimisation and efficiency over investing in resilience, can give rise to decision paralysis or financially-stymied strategies.
Turning to Köse, Villablanca asked: “There’s a mountain of black swan events lurking around us, ready to attack at any minute. What are the things that a supply chain leader should be focusing on today to try to build resilience?”
“To be honest, I don’t think they’re looking at building resilience,” said Köse. “What they’re doing right now is cost optimisation, looking at inflation and making sure that the profit margins are going to be protected through the bottom line, not considering top line revenue maximisation.
“I think agility and economics always need to come back to top line, which basically means in the context of normal business 101 you are producing something, that there is a want and a need and a willingness to pay, and not necessarily hyper-focusing on the cost line or saying, ‘I’m not going to produce a bunch of bullshit that nobody’s going to pay for, just because I got to claim savings to my CFO’.”
“I’m going to challenge you there,” Villablanca interjected. “I think, theoretically, that’s great, but everybody in this room is running a business. We have our own boards, people above us, board directors and so on saying, at the end of the day, you are remunerated and we are all remunerated for our quotas. How do you deal with the day-to-day management of your business as well as building that kind of resilience, agility and visibility?”
To this, Köse stressed that the difference can be made by reframing how businesses examine and counteract risk. “We’re thinking about turning the tide by really embedding foresight in risk indicators. Those risk indicators need to incorporate geotechnical, geostrategic issues with foresight,” he continued before highlighting what he implied to be a tendency for organisations to bury their heads in the sand when faced with developing geopolitical challenges.
“I published an article before Russia invaded Ukraine, about Russia getting ready to invade Ukraine, that went through loads of red tape and debate internally that calling Russia an aggressor was cancelled out from the research note,” said Köse. “They said, ‘You can’t say that’ while it was pretty obvious that Russia were clearly the aggressors.
“The supply chain-focused function needs to spread out and have these geopolitical indicators, geotech-related risk indicators, and not just the last financial report from your supplier A to Z or tier one or tier two.
“We must then tie it back to the value and revenue you’re generating. Get away from this hyper focus and obsession with savings. In that context, make your analytics smarter with a bold analysis of things that you feel uncomfortable about. Think about ‘what now?’ and think about politics. I know we eradicated politics out of business as much as we eradicated many other beliefs from the conversation, but it has to come back.”
With this in mind, he proposed that cost optimisation is to an organisation’s detriment where resilience is concerned, not to its security. “Your indicators for success are not just on the cost line item or bottom line. Your priority must be on the top line. If I sell more, I can grow. With cost optimisation you can shrink yourself to death. That’s what some countries have done with political reviews where you shrink this, you shrink that, let’s shrink here, let’s shrink there. Potholes, collapsing bridges and rail systems, come because of the shrinkage of your investment budget for public infrastructure, for example. What I have found in the last decade of the sustainability high is that it actually impeded resilience, while the narrative said it was supposed to increase resilience.”
To this, Machholz highlighted the data behind Köse’s comments that resilience offers heightened growth potential than cost-cutting measures.
“There were some studies from McKinsey which showed that companies who are investing in risk management are 4.7 times more profitable than those who don’t,” Machholz shared, stressing that businesses engaged in this mindset are missing growth opportunities.
“People just fall back and say, ‘Okay, now the risk is over, COVID is over, whatever event is over,” he continued. “‘We can just go back to business as usual’. Resilience is just extra cost, extra inventory, maybe a second supply chain that needs attention, money, and people to take care of it, and they just simply don’t do it. This is, I think, one of the big threats that we are all facing.”
Exiger Executive Forum: A closer look
The Exiger Executive Forum (EEF) in London is a global think tank that brings together elite independent voices from strategy, policy, technology and business to equip leaders with the frameworks and foresight needed to navigate the multipolar era. The EEF is exclusively curated for industry experts, analysts, policy makers, and senior procurement and supply chain decision-makers through Exiger, a market-leading supply chain AI company. The next Exiger Executive Forum ‘War-time Economics: How Europe’s €800BN Defence Spend Will Reshape Supply Chains’ will take place in London on Thursday, September 18th, 2025.
Ellwood concurred that this lack of foresight and willingness to invest in protective supply chain measures leaves businesses undefended against interruptions both foreseen and not. “We need to prepare ourselves for unexpected events to happen as the norm,” he said. “What would happen to any business if it didn’t have power for 72 hours? How would you look after your personnel? How do you make sure you salvage the business so that, after 72 hours, you can get back up and running. These aren’t questions that we naturally posed at the moment because again, we tend to park these things.
“The mentality may be, ‘The world certainly feels like it’s getting dangerous, but my life actually looks okay.’ That isn’t the right attitude. If you go to Sweden or Finland, who are much closer to the war with Russia, they are preparing in a way that we are not for a major event or incident. It may well be that when something happens and it’s the moment where governments wake up, but you shouldn’t be waiting for that moment.”
Villablanca then highlighted the recent, universal example of poor supply chain resilience bringing business, both domestic and international, to a grinding halt. “Did we learn nothing from COVID?” she asked. “Did we not take the opportunity to stress test our supply chains and look for the vulnerabilities within multiple layers?”
In response, Ellwood invited guests to consider whether the muscle developed in response to COVID’s interruptions had been allowed to atrophy. “I think that’s a question for everybody; how much of that was retained?” he asked before blending the conversation of supply chain agility with the potential for organisations to support national security should their respective nations go to war.
“During COVID, supply opportunities came about,” he said. “Everyone here today represents diverse businesses. What services do you provide that you could tweak or add value to where something else has fallen short?
“That’s where life really becomes interesting because that’s what happened in the First and Second World Wars. We called on organisations that previously had no interest in helping out with the war effort to add support and value to the wider machine and protect ourselves from a resilience perspective.”
Challenges faced by supply chains, he explained, have analogues to business that clearly marry the political and business spheres: “When we say ‘war effort’ today, it isn’t just Army, Air Force, Navy, air, land and sea. It’s now cyber, it’s space, it’s coastguard, it’s AI. This greater warfare is where a lot of the real pain will happen. As happened in COVID, it’s going to be the clever people in the industry that step forward to say, ‘I’ve already thought about this’. They’re in the patent-esque mode, they’ve done the work to say, with a few tweaks here and there, give us some extra money, and I can alter what I’m producing to provide a solution.”
The roles of government and industry
While there are clear precedents for, and incoming needs to, prioritise supply chain resilience in both the political and business spheres, the conversation made it clear that a unified front stands to offer the most impact.
The challenge, particularly in a political environment preoccupied with economic stabilisation, increased productivity, and soothed international relations, is identifying a shared north star or galvanising body to lead the shared project.
Striking at the heart of the conversation, one guest posited: “If we want to align supply chain and geopolitics moving forward with a mutually-reinforcing relationship and shared goals, joint risk assessment, a focus on resilience over efficiency, and heightened cross-disciplinary talent and data, what are the forward steps?
“What can we within industry do in partnership with governments to move this forward?”
Representing the political voice, Ellwood replied: “There are certainly supply chain improvements that you can do on a national, sovereign basis. But from where I sit, there is a wide political threat that we face and are losing right now. One of them is to do with the energy supply, and another is the threat of AI. The quantum race will be won or lost in the next five years’ time, and that will be game-changing. It simply means that if the winner can harness the power of computing on that scale, everything’s over.”
Ellwood then invoked the technological advancements made in modern wartime, stressing that political figures must wield the mindset of those times to accelerate progress.
“I would like to see some two or three Manhattan Project equivalents, if you like, to ask, ‘How do we harness modular nuclear power?’,” he said. “That’s a very easy way to keep our lights on locally. Then, how do you harness AI? Let’s make sure it is this side of the world that wins that.
“Again, there isn’t that coordination, that sense of urgency, because it’s too far down the road,” he concluded, then highlighting that opposing forces on the world stage already have the unified capabilities that many Western nations lack. “State, industry, and academia in China, for example, are all morphed into one and that gives them huge benefits in the race for these key arenas.”
Köse elaborated on this point by highlighting Turkey’s effective coalescence of business and government.
“If you think about the private-public national defence sector in Turkey, it came from being totally dependent on the US armoury to a leading innovator of drone wars,” Köse explained. “When you think about asymmetric warfare, innovative, impactful and economic weaponry, from drones to secure soldier transportation and all of that, think about what Turkey is producing right now in technology compared to others. The headway Turkey experienced in the last decade in the defence sector is unprecedented.
“That private-public sector coalition and symbiosis has covered such a need for them in a decade that many are surprised. I think that is something that Europe has to relearn, because Europe thinks a lot about public sector dominance in an area where the private sector should actually take charge. In the US, it’s the opposite. They say, ‘keep the public sector out’. The solution lies in collaboration and bringing each sectors strength to the table while leaving out their weaknesses and flaws.
While of course not advocating for adopting the political model, he agreed with Ellwood that nations like China have an innate advantage in this race. “When you think about the way that the autocratic countries are going about it, it’s the public sector dominating the private sector environment,” he said. “That’s why they’re so hyperfocused on things and they can scale but not necessarily innovate in this sector.
“I love the government when it’s in the right place to actually do something positive and impactful. But when I’m exposed to it, I usually get anxiety issues due to the lack of pragmatism, innovation and agility. But hopefully there’s this convergence of politics, business and academia driving intelligence into critical sectors and industry, and we’re trying to drive it through this think tank here.”
The unified case for supply chain sovereignty
Exiger’s Supply Chain Sovereignty in a Fractured World event was an enlightening review of the supply chain landscape and the myriad challenges and stakeholders it encompasses.
While the panellists’ conversation in many ways highlighted the disconnect between government, business, and academia, the resonating message was one of shared pressures and goals. Where governments have pulled back on the reins of public spending, many organisations have in kind adopted a cost-optimisation mindset that may protect the bottom line but opens the door to heightened vulnerability.
Where governments must consider challenges around energy sovereignty and insulating populations against the breakdown of globalised networks – as was demonstrated upon Russia’s invasion of Ukraine in 2022 – supply chain executives must create redundancies to cover lapses and minimise potential disruptions to production and wider organisational integrity.
The guests’ final comment, that states which can marry both the public and private spheres towards shared interests, neatly encapsulates the urgency with which those worlds must reunite. While much work remains to enmesh those spheres, it is clear that the conversation is progressing at pace.
Simon Bowes, CVP Manufacturing Industry Strategy EMEA at Blue Yonder, on how to navigate challenging situations in supply chain.
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Organisations worldwide continue to face severe supply chain disruptions, creating immense operational challenges. Compounding these difficulties is a bleak economic outlook that shows few signs of improving, keeping consumer confidence stubbornly low.
Meanwhile, experts are claiming that President Trump may stand firm on his plans for sweeping global tariffs. This is despite a US trade court ruling that the President had exceeded his authority in imposing the duties and ordered an immediate block on them – only for a federal appeals court to temporarily reinstate the most sweeping of the President’s tariffs. This means tariffs remain an ongoing problem and, the UK market will likely face further disruption.
When you factor in increased costs, labour shortages, escalating geopolitical tensions, cybersecurity attacks, and weather-related disasters (like the $27 billion in damages seen in the US alone), it’s evident that constant instability has become the new normal for supply chains.
Senior executives agree, with 84% stating in a recent survey, that they have encountered disruptions within their supply chain over the past year. Therefore, organisations must be prepared for the unexpected, understand the potential consequences, and have a plan in place to mitigate such risks.
How can organisations create a strategy for the unpredictable? The answer is by building a comprehensive plan that integrates the capabilities, processes, and technologies needed to operate efficiently, no matter what happens.
End-to-end supply chain planning
The first step is to create an overarching strategy that encompasses the entire supply chain. Having visibility across all areas will support synchronised planning and communication across disparate functions.
When organisations bring together teams and processes, they can start to overcome the traditionally fragmented approach to supply chain management. Uncoordinated procedures inevitably create an inefficient and weaker supply chain, which makes it particularly vulnerable to disruptions.
Whereas, resilience is strengthened by collaboration between functions, if backed with integrated data systems and communication methods to enable sharing of real-time information. Keeping all parties in the loop, with relevant data and meaningful insights, encourages better and faster responses to problems, as well as increases awareness of potential forthcoming issues.
Ideally, what’s needed is an end-to-end connected platform where all departments, offices and sites are working from the same consistent, up-to-date data. And, are not required to change systems to find or cross-check relevant information and iron out anomalies.
Smart decision making with AI and automation
Next, it’s vital to incorporate intelligent automation to improve and speed up decision making. Companies are already using data tools to forecast supply and demand planning, but they now can incorporate AI’s ‘always-on’ capabilities to dynamically evaluate and adapt to changes in supply and demand.
AI-powered solutions can assess how work is progressing by automating data gathering for analysis and optimisation. Automation can handle routine issues, leaving supply chain professionals free to focus on more strategic tasks. Furthermore, AI can facilitate transparent, trackable decision-making to accommodate predicted supply chain disruptions or react to unexpected ones. This level of auditing provides vital insights that will help refine future decisions and actions for the next time similar circumstances materialise, improving outcomes in the long-term.
Additionally, organisations can leverage AI to predict the likelihood of disruptive events happening. Knowing how often they occur and how they have unfolded in the past can inform decision-making and planning. Whether that’s examining competitor behaviour or economic trends, AI tools can process millions of pieces of real-world data to model likely what-if and worst-case scenarios that could impact the supply chain. While these instances may seldom occur, proactive scenario pre-planning provides the foundation for an effective response in the event of real-world disruptions or disasters.
Organisations should identify the specific issues which present the highest risk to their business and ensure appropriate mitigation measures are ready to be activated immediately they are needed.
Investment in flexible, agile solutions
Restrictive working practices coupled with outdated technology can make it harder to react effectively when disruptions occur. Building long-term supply chain resilience means finding a best-in-class solution and partner with deep domain expertise to guide deployment of appropriate modern technologies.
When considering options, businesses should keep in mind fundamental requirements for flexible, agile technologies. These include checking how a software or platform supports data integration and cross-organisational collaboration, whether it can simulate market conditions in near real-time, if the technology architecture is compatible with AI, and how easily does it scale.
It’s critical to have a technology platform that’s designed for scalability and extensibility to manage changing workloads and requirements. Therefore, organisations should look for products with a cloud-native architecture for scalability and resilience, a microservices-based approach for flexibility, and solutions that are easy to configure and maintain without specialised IT expertise.
Building a resilient supply chain
In today’s volatile business landscape, organisations must embed resilience into their end-to-end supply chains, supported by the right technical infrastructure. Investing in modern technologies and platforms offers additional advantages. Advanced solutions that adapt easily to changing conditions, automate manual processes, and harness the power of AI can also provide a competitive edge. For instance, AI’s ability to crunch and analyse vast amounts of data can reveal hidden opportunities stemming from unexpected events—opportunities that might have been overlooked previously.
By making smart technology decisions, organisations can build more resilient supply chains, enabling them not only to survive in current unstable conditions but also to optimise performance and operate more profitably.
By Mohammad Mesgarpour, Head of Data Sciences at Microlise, discusses why we need to think beyond data when it comes to logistics.
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Data is everywhere — often invisible, but constantly at work behind the scenes. As we move through our day, it quietly powers much of what we experience. A simple card payment in a shop sets off a chain reaction: your bank processes the transaction, the store updates its stock levels, capturing vehicle location and driving behaviour location data by telematics box, and the company’s central system records the sale.
It’s data that informs the display board on a train platform, letting you know your train is just two minutes away. From our morning routines to our evening commutes, data is woven into how we live in 2025.
And the scale of it is immense.
Today, it’s estimated that there are around 181 zettabytes of data globally. That’s equivalent to one trillion gigabytes or one billion terabytes. In just a few years, this figure is expected to soar to 394 zettabytes — a rapid expansion that highlights just how central data has become to everyday life.
We may not always see it, but at every digital touchpoint, data is shaping the world around us.
Data in logistics
The logistics industry has long recognised the value of data and has been quick to adopt technologies that help improve performance and efficiency. As new tools and systems have emerged, the sector has consistently found ways to use them to its advantage.
It started with the basics. Early telemetry services, such as GPS tracking, gave operators a clear view of their vehicles’ location on a map – a simple yet powerful tool. From there, the industry moved into deeper insights, analysing fuel consumption patterns and driving behaviours to improve overall fuel efficiency and road safety.
Since then, the capabilities have expanded significantly.
Today, vehicles can generate ten times more data than they did just ten years ago. Thanks to advances in both hardware and software, operators now have access to a wealth of information that can transform decision-making and drive smarter logistics operations.
But this volume of data doesn’t come without challenges. More data doesn’t always mean better outcomes or deeper insights. Businesses are beginning to recognise that without the right systems; high-quality and relevant data; and effective analysis, they can become overwhelmed rather than empowered.
The real opportunity lies not just in capturing data, but in turning it into meaningful, manageable and actionable insight. It can drive operational efficiency, informed decision-making and measurable business outcome.
The appliance of data science
It’s easy to assume that simply collecting data is enough to transform logistics and haulage operations. But in reality, raw data alone won’t deliver results. To drive real value, that data needs to be refined, analysed in context of strategic business objectives. This is where the real analytical challenge begins.
There’s a well-known saying in data science: garbage in, garbage out. And it’s more relevant than ever in an era where artificial intelligence tools – like ChatGPT – are increasingly part of the conversation where the quality of data directly determines the accuracy and effectiveness of the AI model’s output.
Anyone with deep subject matter expertise will quickly spot the flaws when these models are asked about highly specific topics. They may generate convincing answers based on flawed or outdated sources, and while experts can see through the inaccuracies, others may accept them at face value. When that misinformation is reused and reinforced, the cycle continues, leading to skewed conclusions and poor decisions.
The bottom line? Better data leads to better outcomes.
This principle becomes even more important in real-world applications, such as complying with the government’s updated requirement to inspect trailer braking systems at least four times a year instead of once. With accurate, well-managed data, operators can confidently predict when inspections should take place, helping to reduce downtime, avoid unnecessary checks and keep fleets moving efficiently.
Turn around, go back
Geofencing is another area where accurate data is critical to the success of logistics operations. When systems misreport how long a delivery takes after entering a geofence (delivery site), the ripple effects can disrupt far more than just one delivery.
Inaccuracies here can throw off turnaround times, leading to incorrect arrival and departure times, delayed subsequent jobs, inaccurate performance metrics and ultimately frustrated customers. What begins as a small data issue can quickly escalate, leading to missed expectations, strained relationships and inefficiencies across the board. Moreover, if this inaccurate turnaround time is fed into a machine learning model to improve future logistics planning, it can lead to a systematic degradation in the model’s reliability and usefulness, and consequently, in the effectiveness of the plan itself.
High-quality data helps avoid these pitfalls entirely. When the source information is precise, the systems built around it work as intended. And importantly, solving data issues upstream before they feed into larger workflows is far simpler than trying to fix the consequences later on.
In logistics, precision isn’t a luxury. It’s essential.
Open source informs much more
Modern technology plays a key role in identifying the behaviours that impact operational efficiency. Actions like harsh braking, rapid acceleration or excessive cornering speed all contribute to increased fuel consumption. And today’s systems don’t just monitor them, they help correct them. Moreover, onboard sensors and telematics devices track and monitor vehicle health in real time, flagging issues before they become costly problems. Whether it’s the driver, the transport manager or fleet manager, having this information early enables proactive maintenance rather than reactive fixes.
The story doesn’t stop at the vehicle.
Open-source and crowd-sourced data brings another layer of intelligence, offering a broader context that goes beyond what’s happening inside the cab. By combining internal data with external sources, hauliers can gain insight into accident-prone areas, localised weather patterns or planned road closures; all of which influence route planning and delivery performance.
This level of enrichment adds real value. Rather than simply receiving updates every mile or minute, operators benefit from a fuller picture of the journey, making location data smarter, not just more frequent.
Reporting for duty
Accurate data – whether it’s tracking punctuality, fuel consumption or driver performance – underpins a wide range of operational reports. These insights can be tailored to suit each customer’s needs, helping them streamline operations, drive efficiencies and stay competitive in a fast-moving industry.
As we move toward an expected 394 zettabytes of global data by 2028, the value of this information lies not just in volume, but in context and quality. Future data won’t simply indicate what happened, it will increasingly help explain why it happened, too.
Take driver behaviour as an example. Instead of just recording that a driver braked harshly, new systems will identify the circumstances behind the action. This shift means drivers will be recognised for making safe, responsive decisions rather than penalised by isolated statistics.
It’s a powerful step forward. But unlocking the full potential of this data-driven future depends on how well the information is used. Data must be processed, applied and interpreted thoughtfully.
When done right, it not only enhances internal operations, but it also delivers measurable value to customers as well.
Charles Crossland, Managing Director at Goodman UK, discusses the unique challenges the food supply chain is facing.
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The food supply chain operates under unique pressures. With short product life cycles and a complex journey from source to shelf, it must navigate strict regulatory demands, price volatility, and increasing consumer expectations – all while maintaining speed, freshness, and traceability.
In recent years, global disruptions have exposed vulnerabilities. From reduced access to imported goods to increased transport costs, the sector has had to rapidly adapt. In response, many businesses are turning to technology and data-driven strategies to build resilience and agility into their supply chain operations.
Building resilience in a volatile market
Stock shortages are no longer unusual, and customers are increasingly aware of the fragility of food supply systems. There’s now greater scrutiny on how food moves through the supply chain and growing pressure on businesses to deliver consistency and transparency.
Businesses are adopting new technologies such as artificial intelligence (AI), predictive analytics, and automation to improve supply chain visibility and performance. AI-powered forecasting tools, for example, can help businesses respond faster to demand fluctuations, minimising waste and reducing risk.
At the same time, many have moved away from “just-in-time” approaches for non-perishable goods and are reassessing their sourcing strategies. Dual sourcing, diversified supplier bases, and increased inventory holding are helping to minimise risk and prevent single points of failure.
Smart logistics and strategic warehousing
The transport and distribution stages of the supply chain are also evolving. Soaring fuel prices, labour shortages, and carbon targets are forcing businesses to review delivery routes and optimise their warehouse networks. Proximity to customers is now more important than ever.
By investing in strategically located distribution hubs — close to major infrastructure and consumer populations — businesses can reduce lead times, optimise last-mile logistics, and cut transport-related emissions.
All logistics operations, from warehousing to transport, are increasingly equipped with smart systems for real-time tracking, allowing for greater control over stock movement and condition. For temperature-sensitive goods in particular, the use of tracking sensors helps monitor freshness, reduce spoilage, and maintain product quality throughout transit.
Extending freshness through technology
Warehousing is undergoing a quiet revolution. Robotics and automated systems are now performing tasks such as picking, sorting, and packing with improved accuracy and speed. This is especially valuable in the food sector, where shelf life and freshness are key.
Technologies being deployed include:
Grading visibility systems which assess produce quality and reduce manual handling
Advanced freshness testing which pinpoints stages of ripeness with precision
Specialised climate control systems, including zoned heating and cooling, to maintain product quality
By reducing errors, extending shelf life, and improving product flow, these innovations contribute directly to reduced food waste.
Sustainability as a supply chain driver
Sustainability is no longer a nice to have — it’s becoming central to how supply chains are designed and operated. The environmental impact of food production and distribution is under growing scrutiny from regulators, retailers, and consumers alike.
Businesses are now expected to track and report on carbon outputs across their operations. Efficient route planning, electrified fleets, and eco-friendly packaging are just some of the areas seeing rapid investment.
Data is critical here too. By using detailed analytics, organisations can identify hotspots for energy use or waste and adjust operations accordingly. Many are now measuring not only emissions but also transport efficiency in a bid to reduce their environmental footprint.
Looking ahead: A tech-enabled, resilient future
Incorporating smart technologies into warehouse workflows and logistics strategies is already delivering benefits — from productivity gains to improved safety and fewer errors. But this is just the beginning.
As food supply chains grow more connected and responsive, businesses will need to continually adapt. The future will be shaped by those able to combine agility with long-term planning — embracing innovation, forming deeper supplier relationships, and keeping sustainability at the core.
Without trust, AI cannot deliver on its full potential, leaving manufacturers hesitant to go beyond pilot projects, says Darren Falconer.
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It’s no secret that trust is the foundation for successful AI adoption. By addressing scepticism, prioritising data quality, and ensuring algorithms are explainable and auditable, AI can become a powerful force-multiplier in manufacturing operations.
Manufacturers are increasingly looking to AI to boost efficiency, streamline operations and automate routine tasks. 75% are planning to step up their AI spending in 2025. However, much of this attention is focused on Generative AI – something that we believe is poorly suited to factory settings.
Part of this misalignment stems from a lack of understanding of AI’s practical applications in industry. With only 7% of manufacturing leaders feeling “very knowledgeable” about AI applications, scepticism and trust issues loom large.
Feedback from vendors and end-users consistently points to trust as a leading barrier to adoption. Without trust, AI cannot deliver on its full potential. This leaves many manufacturers hesitant to go beyond pilot projects, XpertRule’s Technical Director, Darren Falconer explores this further.
Overcoming the AI ‘fear factor’
The portrayal of AI in the media has long been dominated by dystopian headlines and Hollywood blockbusters, with fears of mass unemployment and doomsday narratives. For manufacturers, this continuous, subliminal bombardment creates a trust deficit before any AI project even begins.
Business leaders are having to overcome not only technical hurdles but also the deep-seated scepticism that AI solutions are uncontrollable or inherently risky. To counter this, companies must approach AI with transparency and explainability at every stage, showing that AI is a tool to amplify human capability not replace it.
For a simple comparison, think about cruise control in a car. [within cars today,] Traditional cruise control maintains a set speed but that’s all. Compare that to adaptive cruise control, which considers real-time conditions, adapts to your driving preferences and responds intelligently. Similarly, AI in manufacturing must adapt to the unique needs and complexities of each operation.
For those implementing these systems, understanding the ‘mechanics’ – how algorithms interact with data inputs and external influences – is a vital part of building trust. Explainable AI bridges the gap between automation and operator oversight, providing a clear view of how the system reacts and adapts. This clarity increases confidence among users, fostering trust in AI’s outputs.
But of course, building trust also requires a mindset shift – from a data-centric focus to a decision-centric approach.
Trust starts with decisions, not data
A common misstep in AI adoption is starting with the data instead of focusing on the desired outcomes. Many manufacturers think, We have all this data – what can we do with it? However, this approach often leads to complex systems that lack focus, transparency, fail to deliver meaningful outcomes and reinforce doubt over AI’s value.
A decision-centric approach begins by asking, What do we want to achieve, and what decisions need to be made to deliver those outcomes? Only then should businesses ask, What data supports those decisions and what are the models linking these decisions to this data?
From there, manufacturers must focus on ensuring data quality – calibrating sensors, cleaning data streams, validating inputs and standardising formats. Remember, the vast majority of AI success lies in data preparation and only a small percentage in the modelling itself.
Imagine a manufacturer aiming to improve quality control. They might gather extensive data from every step of the production process to find possible defects, leading to an overwhelming volume of disjointed data with no clear path to action.
Using a decision-centric approach, they would:
Define the goal: Improve product quality and aim to reduce defects by 10% over the next quarter.
Identify key decisions: What factors directly impact product quality? What parameters should trigger quality checks? How can inspection processes be optimised to catch defects earlier? What actions should be taken when deviations are detected?
Use AI to model the outcomes: Build AI models that analyse historical production data , to discover explainable patterns relating outcomes to metrics like machine settings, material consistency or environmental conditions. The system can then use these models in real time to flag anomalies that indicate potential defects and recommend adjustments to maintain product quality.
This clarity in purpose makes AI implementations transparent, explainable and, ultimately, more trustworthy. It also provides a clear framework for measuring success, helping to build greater confidence from engineers, users and management alike.
Decision intelligence – the missing link
A key factor in building trust is recognising that AI doesn’t replace human insights and experience – quite the opposite. Human operators and engineers bring a level of expertise, contextual knowledge and intuition that machines cannot replicate. Having a ‘human in the loop’ is therefore critical to an AI system’s effectiveness.
Decision Intelligence connects Explainable AI principles with operational trustworthiness by embedding human oversight at its core. For example, experienced technicians possess knowledge built up over years of practice. While they can’t be everywhere at once, their expertise can be integrated into AI systems to automate routine decisions while reserving complex or ambiguous scenarios for human intervention.
This balance between human and machine intelligence ensures AI systems remain transparent, reliable and dynamic. It also enables manufacturers to scale the knowledge of their experts, reducing variability across shifts and locations while maintaining trust and accountability.
From pilots to trusted partner
For AI adoption to move from pilot projects to the heart of manufacturing operations, trust must come first. A decision-centric approach offers a practical pathway to achieve this, ensuring AI systems are transparent, aligned with business goals and designed to augment human expertise.
When manufacturers trust their AI systems, they can harness the technology’s full potential, creating new opportunities for efficiency, resilience and competitive advantage. Decision Intelligence becomes the connector between Explainable AI and operational trust, moving AI from being perceived as a risk to becoming a trusted partner.
Sylvain Rottier, General Manager at Tennant Company, explores how supply chain professionals are shoring up against labour shortages.
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Europe is facing an ongoing workforce crisis that demands major solutions, meaning business leaders can’t really afford to wait. The numbers are disconcerting: labour shortages across the European Union have grown from 1.7% in 2014 to 2.6% in the first quarter of 2024—a 53% increase that shows no signs of slowing.
Indeed, Europe’s demographic crisis seems to be accelerating, with projections indicating the continent will lose 95 million working-age people by 2050 compared to 2015 levels. For supply chain executives, this threatens operational continuity and competitive positioning.
The impact may vary dramatically across sectors, but few industries will feel the pressure more acutely than essential services like cleaning and facilities management. Annual turnover rates in janitorial services have reached 200-400%, creating a revolving door that diminishes institutional knowledge and operational effectiveness.
The impact beyond empty positions
Twenty-five percent of EU businesses now report production problems directly attributable to labour shortages, transforming what was once a staffing inconvenience into an operational constraint.
The financial implications are potentially severe. Companies experiencing 200% annual turnovers —unfortunately common in labour-intensive sectors—spend six-figure sums annually just on replacement hiring. This figure encompasses recruitment costs, training expenses, and the hidden price of reduced productivity during onboarding periods. However, these costs represent a small part of the problem.
Quality degradation becomes inevitable when organisations rely heavily on inexperienced workers. Higher error rates, missed cleaning protocols, equipment damage, and inconsistent service delivery damage customer satisfaction and brand reputation. In supply chain environments where precision and reliability are paramount, these quality issues can trigger costly disruptions throughout the entire network.
Perhaps most concerning is the competitive disadvantage that emerges when labour shortages force companies to reject new business opportunities. Constrained order books and inflated production costs create a vicious cycle where struggling organisations become less attractive employers, further exacerbating their staffing challenges.
From automation to intelligence
Traditional automation offered limited relief because it required extensive programming for specific tasks and was often an awkward-at-best fit for changing conditions. Today’s AI-enabled robotic systems represent a huge leap forward, delivering true operational intelligence that can learn and adapt, and also optimise performance in real-time.
Modern robotic platforms (such as BrainOS, which power Tennant AMR Machines) leverage machine learning algorithms to improve their performance based on environmental feedback and operational data. Unlike their predecessors, these systems can navigate complex, dynamic environments while avoiding obstacles, adjusting cleaning patterns based on usage data, and even predicting maintenance needs before equipment failures occur.
Integration capabilities have also come a long way. Contemporary AI-powered robots connect with existing warehouse management systems, inventory tracking platforms, and facility management software. This connectivity enables centralised monitoring, performance optimisation, and data-driven decision-making that extends far beyond the robots’ immediate task purpose.
The technology’s greatest advantage lies in its ability to maintain consistent performance standards. While human workers may struggle with fatigue, illness, or high turnover, AI-enabled robots deliver consistent results that enable accurate capacity planning and service level guarantees.
Implementation strategy
Successful AI-robotics deployment requires a shift in thinking from replacement to augmentation. The most effective implementations complement human capabilities rather than eliminate human roles entirely. This approach not only addresses practical concerns about workforce displacement but also maximises return on investment by leveraging the unique strengths of both human intelligence and artificial intelligence.
Smart organisations begin with pilot programmes that target specific, well-defined tasks within controlled environments. This approach allows teams to understand integration challenges, optimise workflows, and build internal expertise before scaling to full deployment. Critical success factors include ensuring compatibility with existing systems, establishing clear performance metrics, and maintaining open communication with affected workers throughout the transition.
The skills landscape is evolving rapidly, creating new job categories in real time. Rather than eliminating careers, thoughtful implementation transforms traditional roles into technology-empowered positions that offer greater career advancement potential and higher compensation. For sectors like cleaning services, which have long struggled with “dead-end job” perceptions, this transformation can meet turnover rates with higher-calibre talent.
Training programmes should prepare workers for collaborative environments where human judgment combines with robotic precision. These hybrid roles often prove more engaging and rewarding than traditional positions, creating career pathways that retain institutional knowledge while embracing technological advancement.
Building tomorrow’s competitive advantage
The demographic trends driving current labour shortages will intensify over the coming decades. Organisations that delay AI-robotics adoption risk falling behind competitors who embrace these technologies early and develop operational expertise while the market is still developing.
However, successful transformation requires more than technology acquisition. Companies must strike a balance between technological capabilities and the human touches that drive innovation, customer relationships, and adaptive problem-solving. The goal isn’t to create fully automated facilities but to build resilient, flexible operations that can weather demographic headwinds.
Leadership teams must think beyond immediate cost savings to consider long-term strategic positioning. AI-enabled robotics offers the foundation for sustained growth in an environment where traditional staffing models look increasingly untenable. Early adopters will develop competitive advantages that compound over time, while late movers may find themselves perpetually disadvantaged in both talent acquisition and operational efficiency.
The question isn’t whether AI-enabled robots will reshape supply chain operations—that transformation is already underway. The critical decision facing business leaders is whether they’ll proactively shape this evolution or reactively respond to competitive pressures once their options become more limited and expensive.
Europe’s demographic winter demands timely action. For forward-thinking supply chain executives, AI-enabled robotics represents not just a solution to current staffing challenges, but a strategic foundation for long-term competitive success in a potentially shaky marketplace.
Mark Wilkinson, Senior Vice President for OpenText’s Global Business Network, discusses AI-driven success in supply chains.
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AI in industry
AI might be transforming industries, but its ability to drive accurate workflows relies on a foundation of reliable data. For those working with supply chains, this data can generate assessments of global circumstances and highlight upcoming disruption to operations before it’s felt by the consumer.
In the past year, extreme weather, trade disputes, and geopolitics have tested the limits of business preparedness. For example, in October 2024, it was estimated that the storms that hit Valencia caused damage to its farming industry worth almost £1bn. That includes the produce lost and the rendering of underlying infrastructure as unusable. As the impact of the climate crisis drives an increase in natural disasters, supply chains must prepare for widespread disruption.
Looking to 2026 and beyond, this trend is unlikely to change for the better. To best future-proof business processes, AI will be fundamental. But where should organisations start?
Which data is good enough?
High-quality, accurate data is important for driving AI success in supply chains and providing users with accurate predictions. This enthusiasm is reflected in the expectation that the big data market will be worth over £300 billion by 2028. Despite this significant investment, most organisations, surveyed across industries, still face data-quality issues.
At present, only 12% of data and analytics professionals believe that their company’s data is ready for AI adoption despite 76% recognising data-driven decision-making as a priority. To drive success in supply chains, this lack of readiness needs to change.
Data preparation
Though action must be taken to remedy these concerns, companies shouldn’t view the quality of their own data as a blocker to innovation. Instead, they can ‘test’ the data before using it to drive insights.
As a first step, it’s essential to identify the format and quality of existing data assets. With complete knowledge of all the information available, corporations can integrate AI tools that work with their data, instead of trying to fit it into incompatible solutions.
Next, team leaders must be certain that their employees are trained on noticing hallucinations and changing processes to ensure accurate AI forecasting. Creation of the right procedures will feed into a successful long-term data governance strategy, ensuring full value is extracted by AI tools.
For ongoing insights, directly reflecting global circumstances, data must be continually fed into AI systems. By setting up the extraction of data from a reliable platform, companies can ensure that the insights they receive directly correspond with the most pressing logistical concerns.
Incompatible sources
Strategic partnerships can bring essential expertise for agile transformation, helping companies to scale at speed and improve their assessment of risks. For instance, by integrating data from a partner organisation, visibility across the global logistics landscape will be increased. Concerns arise, however, when data is formatted differently at each company. To mitigate the chance of hallucinations, data-trained workers should be proactively advised to scan insights for duplicates, misspellings, and inaccurate information.
Visibility
For operational success amid an ever-changing global landscape, the importance of preparing and ‘cleaning’, data should not be understated. To ensure accurate insights are produced by AI tools, integrated solutions should be compatible with current data-formatting, proactively mitigating the chance of hallucinations. To derive full value, the same ‘cleaning’ procedure should be used for partner data. By taking the right steps at the beginning of the adoption journey, business leaders can drive effective insights, consistently being updated, to support future growth.