Walmart Provides Agentic AI Update, Says Customers Need To ‘Effectively Train Their Agents’

Retail giant Walmart has been pursuing a significant expansion into the generative AI (GenAI) space, particularly its own proprietary agentic AI model. From providing customers with a customized shopping companion to streamlining operations in order to allow human associates to do other tasks, the possibilities appear rife with opportunity.

According to a May 29 blog post penned by Walmart U.S. CTO Hari Vasudev, Walmart is slated to drill down on its broader AI strategy to produce specific tools that are tailored to retail-specific tasks. Machine-led shopping, in particular, is one facet that the blue-and-yellow brand would like to further refine into a more complete sales and service channel for its customers.

On the production side, Walmart gestured toward improvements to its merchant tools, which can automate an array of time-intensive tasks for those sellers who participate in its marketplace platform — and to a tune-up of its Trend-to-Product fashion product pipeline, a tool that Vasudev said could trim the total production time from design to sale by as much as 18 weeks.

Walmart CTO: Customers Will ‘Need To Effectively Train’ AI Agents as Tech Gains Further Foothold in Retail

On the customer-facing side, Vasudev noted that Walmart’s Customer Support Assistant had improved significantly since its initial launch, and that further adjustments were in the works to transform it into a frictionless shopping companion — particularly for users with even a modest understanding of casual prompt engineering.

“Customers need to effectively train their agents. This involves providing specific query parameters — think budgetary limits, brand preferences, sizes, colors and even preferred store locations. Crucially, providing feedback to the agent over time will allow it to learn and adapt to individual needs. Consistent use will be key to the agent truly understanding its user,” the CTO stated.

It’s not all on the customer, however, at least some of the onus of the customer’s journey from sparking desire to spend and fulfillment rests on Walmart itself building the appropriate links between the agentic AI and human agents working in the background to ensure consumers’ desires are truly being met swiftly and appropriately.

“Retailers and providers need to build the bridges for personal shopping agents to effectively communicate shopper needs to internal agents. This will allow us to validate whether we can meet the needs of the customer’s personal agent and help facilitate the purchase,” Vasudev continued.

Vasudev went on to say that Walmart was already seeing a high degree of engagement from its customers regarding agentic AI, and that, in particular, shopping for essentials or everyday items was actually becoming more popular through this channel.

Walmart CTO Says ‘Co-Pilot’ Model, Blending Agentic AI and Human Employees, Is Best

Near the end of the blog post, the CTO suggested that Walmart was zeroed in on a “co-pilot” model wherein agentic AI and experienced Walmart employees worked in tandem to address the strengths and shortcomings of both sides of the sales and logistics equation.

Finally, Vasudev underscored the notion that while certain tasks will be suitable for AI tools in the immediate or near future, there will always be operational necessities better handled by human expertise. Figuring out where exactly that fine line may rest was the goal of this nascent tech rollout, with invaluable research and data points being littered along the way.

“For retailers, the potential for agentic AI is immense. Imagine complex personal shoppers that understand nuanced preferences, dynamic store environments that adapt in real-time based on customer needs, and self-optimizing logistics networks that ensure products are always in the right place at the right time,” Vasudev said.

“This is why we’re so invested in building the right foundation today, to not only meet but anticipate the needs of tomorrow,” he concluded.