Walmart's supply chain technology team is leveraging AI and digital twins to navigate global logistics challenges. According to Indira Uppuluri, Walmart's senior vice president of supply chain technology, the retailer uses predictive models, machine learning, and data about weather patterns and customer buying history to strengthen supply chain decision-making (Retail Dive - Technology). Walmart has access to large language models and open-source models popular among enterprises, while data science teams also build custom AI tools tailored to business objectives (Retail Dive - Technology).
The supply chain technology team uses AI agents to optimize operations across the entire network rather than examining individual nodes in isolation, helping associates understand how resources are leveraged as a whole (Retail Dive - Technology). Walmart's teams employ digital twin technology and modeling tools to simulate how the logistics network responds to facility closures, transportation delays, or sudden shifts in customer demand, enabling faster reactions to disruptions (Retail Dive - Technology). The company focuses on balancing three key factors: assortment, speed, and cost, across its supply chain operations (Retail Dive - Technology).
For commerce practitioners, Walmart's approach underscores the strategic value of agentic AI and simulation technology in managing complex, multi-node logistics networks. As geopolitical turbulence and extreme weather create supply chain volatility, the ability to model scenarios and generate actionable recommendations positions retailers to respond faster to unforeseen disruptions and optimize operations in real time.