PSC LIVE: How AI is Building Resilience in Supply Chains

Global supply chains are operating in an era of unprecedented complexity and disruption. From geopolitical tensions to fluctuating demand patterns, supply chain leaders face mounting pressure to maintain resilience while managing costs. AI has emerged as a transformative solution, shifting supply chain operations from reactive crisis management to predictive, proactive strategies.

At Procurement and Supply Chain LIVE: The US Summit in April 2026, experts convened for the AI Innovation Debate, held in association with Zip, to explore how AI is fundamentally reshaping supply chain operations. The discussion centred on how organisations could leverage AI to navigate disruption, manage increasingly complex networks and build long-term resilience.

In today's volatile environment, supply chains are under constant threat from disruptive events. When the current period of global instability began, supply chains struggled to adapt, constantly reacting to crises without the capacity to build meaningful resilience. Now, AI integration within procurement and supply chain functions is enabling organisations to predict and mitigate disruptions before they cascade through the network.

As global demand increases and supply chain networks become more intricate, procurement and supply chain leaders have become central to driving organisational stability. However, these leaders face immense pressure to deliver results with constrained budgets. Rising inflation, tariff pressures and increased operational costs have created an environment where efficiency could mean the difference between survival and failure. AI has entered this landscape as a tool that could allow leaders to accomplish more with fewer resources. The technology handles time-consuming manual tasks at significantly reduced speed and cost, while enabling human teams to focus on strategic decision-making and customer relationships.

AI-driven disruption management

The integration of AI into supply chain operations represents a fundamental shift in how organisations approach disruption management. Rather than responding to crises as they unfold, AI-enabled systems could identify potential disruptions before they impact operations. This predictive capability is transforming supply chain resilience from a reactive process into a strategic advantage.

Supply chain complexity has grown exponentially as organisations expand their global networks and supplier bases. Managing this complexity manually is no longer feasible, particularly when disruptions can ripple across multiple tiers of suppliers within hours. AI systems could process vast amounts of data from across the supply chain network, identifying patterns and anomalies that human analysts might miss.

Machine learning algorithms can analyse historical disruption data, weather patterns, geopolitical developments and supplier performance metrics simultaneously. This comprehensive analysis enables supply chain leaders to develop contingency plans and alternative sourcing strategies before disruptions materialise. By monitoring real-time data feeds from multiple sources, AI systems provide early warning signals that allow organisations to activate backup suppliers, reroute shipments or adjust inventory levels proactively.

The experts at PSC LIVE explored how this technology is helping leaders cut costs without compromising quality, while also supporting broader business objectives across multiple functions.

Environmental considerations for AI implementation

The rapid adoption of AI as a supply chain tool has generated both enthusiasm and scepticism. While the technology could drive sustainability initiatives and support value chain optimisation, the speed of adoption has raised environmental concerns. Data centres are operating at greater capacity than ever before, consuming substantial amounts of water, energy and coal.

However, the panellists at PSC LIVE argued that this concern requires context. The resources consumed by AI systems would likely be used through manual processes, though distributed over longer timeframes.

"They're using more coal, but they're also using more wind and more solar for all of these data centres," argues Dr Alyson Freeman, Director of Data Centre Sustainability at Dell Technologies.

"Where we are in trying to make this AI transition is we need every bit of energy available. We need to be looking at how we do carbon capture as a short-term solution? How do we get to the longer-term, truly sustainable energy choices? In the long run, I believe there are definitely ways that we will move AI to be compatible with our lives, our planet and sustainability. And AI can actually be part of this solution."

For supply chain operations specifically, this environmental consideration is particularly relevant. Supply chains are significant contributors to organisational carbon footprints, and AI could play a dual role in both optimising operations and tracking sustainability metrics across complex networks.

Workforce transformation in supply chains

A central concern for AI implementation within supply chains is its impact on the workforce. The technology represents a double-edged sword, particularly when addressing labour gaps. Many supply chain functions are currently facing workforce shortages and skills gaps that threaten operational continuity.

AI is filling these gaps and ensuring supply chain operations can continue functioning effectively. However, sceptics worry this could lead to widespread workforce displacement. If AI systems can operate continuously without breaks and process information more efficiently than humans, the concern is that human workers will be pushed out of their roles.

Panellists at the debate addressed this concern directly, arguing that AI is augmenting jobs rather than replacing them entirely.

Luhua Xu, AI Product Marketing Lead at Zip, says: "I think AI will not replace our job entirely anytime soon. When we're seeing agents that we're deploying today, it helps you do your job better and in a more productive way.

"Ideally, you'll still need human oversight at the end, and that just cannot be replaced by AI today. It's helping you to transform your four hours of work to maybe two to three hours. And then you can also spend time doing the more strategic work at the end. So that's what I see in the short term. In the long term, I think that's the scepticism that comes with every new technology and every new product.

"There will always be questions around, will we lay off people with industrial revolution or with AI? It's the same question. But then hopefully as human beings in general, we get to the future that we do less manual work in general and we can spend time on more meaningful things."

The debate continued exploring how AI could work alongside supply chain professionals to enhance efficiency. Dr Jutta Pils, Global Head, Digital & Agentic Innovation & Sustainability Strategy at DuPont, argued that adaptation is crucial for supply chain professionals.

"So my only advice is AI is not taking your job," she says firmly.

"Even if you're an administrative person, it's not taking your job. AI would contribute to your job, but you have to learn it in your area. If you're administrative assistant, learn the tools to manage more people in your company, learn the tools to have more workflows in your company, make your human knowledge relevant and use AI to emphasise and grow. So it doesn't necessarily need to get rid of people, but naturally it's leadership and also your own drive."

Panellists also suggested AI could create additional roles within supply chain operations. To be most effective, AI should be applied to manual and repetitive tasks, reducing time spent on routine activities and enabling leaders to make faster, more accurate decisions. This approach allows supply chain teams to spend less time on administrative work and more time on strategic supplier relationships, risk management and customer-focused initiatives.

"How much of [the fear is] similar to the dot com bubble where what you're seeing is AI is coming in and businesses that maybe weren't adding as much value are suffering? In the industrial space, we've got a while. Vontier is critical infrastructure in almost every country we operate in," adds Rasha Hasaneen, Chief Innovation & Growth Officer at Vontier.

"There's not going to be a situation where you don't have a human in the loop when you're talking about the energy infrastructure of a country or the retail infrastructure of a country. Our customers were the ones that had to be open during COVID.

"And so in those situations, we're going to be slower to adopt AI in mission critical operations, faster to adopt AI, to reduce non-value added work. We're going to have a pretty good runway where we still have humans in the loop. We still need that expertise, that decision making, that accountability to ensure that the critical infrastructure remains intact. Maybe over time, there will be less of a need for as many people doing a specific job, but it doesn't mean that there aren't additional jobs that would be created."

Rasha's perspective highlights a crucial reality for supply chain operations: mission-critical functions will maintain human oversight while AI handles non-value-added work. This human-in-the-loop approach ensures supply chain resilience is built on both technological capability and human expertise. The debate reinforced that while concerns about AI implementation are valid, when properly deployed alongside human workers, the technology could enhance efficiency, strengthen disruption management and build the resilient supply chains necessary for navigating ongoing global instability.