AI IN SUPPLY CHAIN

Walmart CEO Doug McMillon explains:“ There is a native AI experience coming that is multimedia, personalised and contextual.”

The AI learns, plans and predicts customer needs, making shopping“ feel more personal, intuitive and anticipatory”. The benefits are already apparent, with AI accelerating merchandising timelines by up to 18 weeks and cutting customer service resolution times by nearly half.

The investment extends to the workforce. Walmart’ s internal AI ecosystem empowers its 2.1 million employees with intelligent tools. AI-driven task management has reduced planning time for overnight stocking from 90 minutes to 30,“ freeing managers to focus on team leadership instead of logistics”.

Crucially, a real-time AI translation tool supports 44 languages, removing communication barriers across the workforce. Additionally, conversational AI, which uses generative AI to instantly convert complex policy manuals into actionable, step-by-step guides,“ reinforcing the company’ s belief that accessible AI can amplify human potential rather than replace it”.

Even in inventory management on the floor, augmented reality( AR) is being deployed. By pairing RFID-tracked products with the AR tool VizPick, associates can quickly scan racks and“ instantly visualise which items need restocking”. This convergence of AI and AR bridges the digital and physical supply chain realms, ensuring that customers“ not only find what they want but find it when they want it”.

of supply chain leaders expect continued volatility over the next five years

WEF Global Lighthouse Network, 2024

The next era of intelligence There are so many voices speaking on the future of AI, but the common ground between them all seems to be a collaborative approach. The evolution of planning points to a system in which machine intelligence is context-aware as well as inherently collaborative with human expertise.

Emily says:“ The next wave of AI in supply chain planning will be defined by contextaware intelligence – AI that not only analyses data but understands its business context and can clearly explain its decisions.”

She anticipates a“ rapid uptick in LLMs becoming embedded into planning workflows, making advanced insights conversational and accessible to non-technical users.

“ Instead of relying on point forecasts, organisations should be simulating full probability distributions to help prepare for a range of outcomes- not just the most likely one.

“ The opportunity and challenge will be integrating human expertise with machine intelligence in real-time to achieve smarter planning, stronger governance and more resilient supply chains.”

108 January 2026