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Walmart continues to make strides in cracking the code on deploying agentic AI at enterprise scale. Their secret? Treating trust as an engineering requirement, not some compliance checkbox you tick at the end.
During the “Trust in the Algorithm: How Walmart’s Agentic AI Is Redefining Consumer Confidence and Retail Leadership” session at VB Transform 2025, Walmart’s VP of Emerging Technology Desirée Gosby, explained how the retail giant operationalizes thousands of AI use cases. One of the retailer’s primary objectives is to consistently maintain and strengthen customer confidence among its 255 million weekly shoppers.
“We see this as a pretty big inflection point, very similar to the internet,” Gosby told industry analyst Susan Etlinger during Tuesday’s morning session. “It’s as profound in terms of how we’re actually going to operate, how we actually do work.”
The session delivered valuable lessons learned from Walmart’s AI deployment experiences. Implicit throughout the discussion is the retail giant’s continual search for new ways to apply distributed systems architecture principles, thereby avoiding the creation of technical debt.
Four-stakeholder framework structures AI deployment
Walmart’s AI architecture rejects horizontal platforms for targeted stakeholder solutions. Each group receives purpose-built tools that address specific operational frictions.
Customers engage Sparky for natural language shopping. Field associates get inventory and workflow optimization tools. Merchants access decision-support systems for category management. Sellers receive business integration capabilities. “And then, of course, we’ve got developers, and really, you know, giving them the superpowers and charging them up with, you know, the new agent of tools,” Gosby explained.
“We have hundreds, if not thousands, of different use cases across the company that we’re bringing to life,” Gosby revealed. The scale demands architectural discipline that most enterprises lack.
The segmentation acknowledges the fundamental need of each team in Walmart to have purpose-built tools for their specific jobs. Store associates managing inventory need different tools from merchants analyzing regional trends. Generic platforms fail because they ignore operational reality. Walmart’s specificity drives adoption through relevance, not mandate.
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