Walmart's AI stack: LLMs, digital twins, and 2M-employee certification push

Walmart is scaling its supply chain intelligence with advanced AI and digital twin technologies, a strategic push detailed by Indira Uppuluri, the company's senior vice president of supply chain technology. Speaking to CIO Dive and published in July 2026, Uppuluri emphasized that the retail giant's supply chain division had leaned on predictive analytics well before the wider corporate rollout of AI to 2 million employees, but the current era brings an order-of-magnitude improvement in data granularity and model capability. The team now ingests real-time weather signals, detailed customer purchase histories, and a host of operational telemetry from its vast network of nodes—receiving, processing, storage, and shipment points—to generate stronger signals for routing, inventory placement, and fulfillment. This data backbone powers both large language models (LLMs) from partners like OpenAI and Google, as well as in-house custom models built by Walmart's data science and optimization units. Digital twins, a concept that creates a virtual replica of physical supply chain assets, are being deployed to simulate scenarios and de-risk operations amid growing complexity such as geopolitical conflicts, extreme weather events, and the demand for same-day delivery. The announcement directly follows Walmart's Sam's Club introducing one-hour delivery in April 2026, highlighting the operational pressure to accelerate without breaking the supply chain. Walmart is also investing in workforce upskilling through its Squiggly platform, offering AI certifications in partnership with OpenAI and Google, enabling employees to build their own tools. This move underscores a dual strategy: top-down technological infrastructure and bottom-up innovation from associates who interact with processes daily. From a market perspective, Walmart's AI adoption signals a defensible moat in logistics-driven retail, where rivals like Amazon and Target are also investing heavily. The ability to predict and simulate disruptions before they happen—whether a typhoon in the Pacific or a trade rerouting—can translate into billions in cost avoidance and inventory efficiency. The company's sheer scale, with over 4,700 U.S. stores and hundreds of distribution centers, magnifies the impact: a 1% improvement in on-time delivery or inventory turnover directly boosts margins. Looking ahead, Walmart's integration of AI across the supply chain positions it to better compete on speed and cost, while also providing a blueprint for industrial AI adoption. The use of digital twins may soon expand beyond logistics to store layouts and energy management, creating a closed-loop digital enterprise. However, challenges remain, including model explainability for critical decisions, data governance across global operations, and the risk of over-relying on simulations that may not capture black-swan events. Uppuluri's message is clear: AI is not just a bolt-on but a fundamental re-architecting of how Walmart moves products around the world.