Walmart Applying Agentic AI to Optimize In-Store, Marketing Operations
Walmart is accelerating its artificial intelligence strategy to prepare for a future in which personal shopping agents – powered by generative AI – may assist consumers throughout the path to purchase.
A large part of this effort involves optimizing in-store tools for associates and rethinking marketing to accommodate both human and machine-led shopping using agentic AI.
The retailer is already applying agentic AI — AI systems capable of independent decision-making — within store environments to automate repetitive associate tasks and streamline operations. These agents help free up store staff to focus on more complex, customer-facing responsibilities, enhancing the in-store experience.
“AI has long been highly pervasive throughout our business, and the path to agentic AI has been paved — many of our Gen AI-powered copilot tools are well on their way to becoming assistive agents to fully autonomous agents,” Hari Vasudev, chief technology officer, Walmart U.S., wrote in a corporate blog post.
Marketing Use Cases
Simultaneously, Walmart is developing new advertising pathways to ensure product visibility in a world where digital agents, not people, may be the ones making purchasing decisions. This includes agent-specific SEO and advertising strategies designed to communicate directly with AI systems that shop on behalf of consumers — strategies that will complement, not replace, Walmart’s traditional marketing tactics.
“Agents may be less likely to be attracted to images or visuals designed to elicit an emotional response,” Vasudev wrote. “So, while Walmart’s core value proposition — Every Day Low Prices — and the spirit in which we market to customers won’t change, we need to develop new pathways for agent discovery.
In addition, Walmart is applying agentic AI in merchandising use cases. Merchant tools such as “Trend-to-Product” help shorten the traditional production timeline for Walmart fashion by as much as 18 weeks.
Personalized, AI-Driven Shopping Experiences
Walmart is building its own retail-specific large language models (LLMs) and AI infrastructure to support task-specific agents across the business. These include tools for item comparison, personalized recommendations, shopping journey completion and more, all trained on proprietary Walmart data.
Within the shopper journey, Walmart's Gen AI-powered shopping assistant already utilizes “multi-agent orchestration” and evolving voice and camera capabilities to support consumers from product discovery to purchase, per Vasudev.
These tools are precursors to more advanced personal shopping agents, which will require customers to “train” them with preferences around price, brand, color, size and store locations. Retailers like Walmart, in turn, must build infrastructure that communicates with these agents and helps validate and fulfill their requests.
This article first appeared on the site of sister publication P2PI.
