The AI Innovations Driving Supply Chain Resilience

Global supply chains have undergone significant transformation in recent years, driven by the need to respond to ongoing geopolitical volatility. Traditional methods of supply chain organisation no longer hold up in today’s ever-changing environment.

A function which once relied on spreadsheets, emails and maintained its very own operational landscape, now needs to be adaptive and much faster. 

According to GEP’s 2026 Outlook Report, 75% of respondents say that AI has exposed the limitations of legacy governance processes. 

As a result, supply chains around the world have undergone digital transformations, turning instead to AI and analytics. 

Leaders have a much deeper understanding of the need to collaborate across both the supply chain and across the company – supply chain leaders need to have strong relationships with their suppliers, but they also need strong internal communication with those in finance, sales and beyond.

Gone are the days of siloed data functions – instead, AI has driven the momentum of building operational resilience.

See the full story in the June 2026 edition of Supply Chain Digital.

Navigating turbulence

Following a period of ongoing geopolitical turbulence, organisations have had to undergo a fundamental shift in how they approach disruption management. Now, rather than responding to crises, leaders have understood the necessity of predicting disruption. AI-enabled systems have helped businesses around the world identify potential disruptions before they can impact operations. 

Through this, organisations have been able to undergo a resilience transformation, gaining a strategic advantage by preparing for the worst. 

"Supply chains need more than just faster planning, they need better intelligence and decisioning," says Dean Bain, SVP and GM, Supply Chain of Coupa.

Through predictive insights, businesses are able to utilise this information for greater innovation, risk management and inventory management.

According to IBM’s AI for Supply Chain Guidebook, 79% of surveyed executives state they anticipate generative AI will optimise inventory management through its capabilities of predicting future demand patterns. Alongside this, 62% of executives anticipate the accelerated pace of discovery through generative AI.

This technology is reshaping supply chains in numerous ways, whether through predictive analytics, machine-learning, generative AI, digital twins and agentic AI.

Developing resilience

Businesses which adopt AI or automation across their sourcing operations and supply chains are 3.7 times less likely to suffer during volatility, according to research by Keevlar. The technology provides a structural advantage for these companies, feeling less turbulence from ongoing disruption.

"The data this year is the clearest signal we've seen that procurement technology adoption isn't a nice-to-have — it's what separates organisations that absorb volatility from those that get hurt by it," says Alan Holland, Founder and CEO of Keelvar.

As volatility is constantly shifting the market, changing trade relationships or regulations, the need to make strong decisions at speed is at an all-time high. Despite this, many businesses are still unable to keep up with the pace, with 69% of leaders reporting that decision-making speed and quality causes internal obstacles, according to Keevlar. 

Many of these businesses have failed to adopt AI, resulting in the inability to maintain the necessary pace of operations as the market shifts. 

Organisations which do adopt AI across their supply chain operations have seen the benefit, in the form of cost savings, improved productivity and efficiency, faster reaction-times and greater risk management.

Unilever

Unilever’s Beauty and Wellbeing scientists have been using AI to understand consumer trends and gain key insights into decades worth of data. This has helped its R&D teams design new products within days.

Unilever Beauty & Wellbeing has a €12.8bn (US$14.6bn) portfolio, which covers Wellbeing, Skin Care and Hair Care. Across these businesses, Unilever is utilising machine learning, automation and AI in order to speed up its innovation process to meet consumer demand faster, with more accuracy. 

Using AI, Unilever can assess consumer insights 60% faster, following the analysis of engagement, search terms and brand sentiment. It automatically examines social media, retail and competitor activity, as well as search results. 

The tools offer real-time insights, which means R&D teams can act faster to design science-led products. As a result, formulation cycles have been cut from five or six rounds, to as few as one.  

“For our 4,500 researchers, AI isn’t just a time-saver. It’s changing how we discover, collaborate and innovate,” explains Jason Harcup, Chief R&D Officer of Unilever Beauty & Wellbeing.

“Structured data, AI and human creativity are redefining what’s possible in R&D, and shaping the next era of innovation at Unilever.”

PepsiCo

In collaboration with NVIDIA and Siemens, PepsiCo is redesigning how goods move from production facilities to its customers, utilising digital twin technology and AI. Utilising Siemens’ Digital Twin Composer software and NVIDIA’s Omniverse platform, PepsiCo is developing simulations of its entire supply chain operations.

This includes the reconstruction of its warehouse layouts, conveyor systems, operator movements and pallet flows, all in a virtual environment. By doing this, PepsiCo’s supply chain leaders can make more informed decisions, gaining insights into potential bottlenecks, new distribution strategies and the most efficient equipment placement. Due to the virtual world, multiple scenarios can be tested at once, without extra costs or time wasted on unsuccessful projects. This leads to faster, more confident decision-making processes, helping PepsiCo meet consumer demand better.

Through this collaboration, PepsiCo could detect up to 90% of operational issues within the simulation, without having to make changes to the warehouse floor. This minimises downtime during implementation phases significantly and reduces the risk of expensive errors. 

Ramon Laguarta, Chairman and CEO at PepsiCo, explains: "The scale and complexity of PepsiCo's business, from farm to shelf, is massive – and we are embedding AI throughout our operations to better meet the increasing demands of our consumers and customers.”

Caterpillar

Caterpillar is deploying physical AI across manufacturing, construction and mining through its collaboration with NVIDIA. Using digital twin technology, Caterpillar is optimising factory production systems and developing greater resilience throughout its supply networks. 

These technologies are allowing for greater real-time data processing and autonomous decision-making across its entire global manufacturing footprint. Through this, Caterpillar says it is navigating supply chain disruptions much more effectively. 

The company is utilising NVIDIA’s AI Factory technology to develop physically accurate digital twins of its facilities, specifically NVIDIA Omniverse libraries and OpenUSD. This allows supply chain teams to optimise production layouts without the costs and risks of making these changes on the factory floor before knowing the changes will boost efficiency, productivity and cost-savings. 

AI is also helping Caterpillar identify potential bottlenecks, therefore improving planning capabilities, with virtual testing leading to more informed decision-making. 

Joe Creed, CEO of Caterpillar, says: "As AI moves beyond data to reshape the physical world, it is unlocking new opportunities for innovation. Caterpillar is committed to solving our customers' toughest challenges by leading with advanced technology in our machines and every aspect of business."

See the full story in the June 2026 edition of Supply Chain Digital.