Walmart U.S. Chief Technology Officer Hari Vasudev unveiled the retailer’s agentic AI strategy and implementation plans, preparing for an era where robot shoppers will buy products and services from robot sellers, accessing websites optimized for them with the goal of delivering fast, hyper-personalized experiences to human shoppers. First, Walmart identifies core agentic AI capabilities that would work best for the retailer, are cohesive and can scale globally, per the post. Next, it uses a “surgical” approach to agentic AI. That means its agents will be experts at specific tasks, unlike the more generic solutions from other providers. Finally, Walmart agents’ work outputs will be stitched together to solve complex workflows. As an example, Walmart taps its retail-expert large language model to build agents within its generative AI shopping assistant, which appears as a smiley face chatbot. These agents can do specific tasks such as deep personalization, item comparison and shopping journey completion, among others. The model is trained on the retailer’s data and can be combined with other models to contextually address the customer’s needs Walmart’s existing generative AI-powered tools are on their way to becoming fully autonomous agents. Walmart is also exploring using AI agents across the company, from doing in-store tasks to merchandising planning at the home office and beyond. Shoppers are already using Walmart’s shopping assistant to find products, and the next step is to let an agent do the research, make decisions and place the order. This autonomous task would be ideal for repeat purchases of everyday necessities. Walmart is aware of the risk of hallucinations, or AI models making things up. So, it is adding a layer of governance, checks and balances, as well as evaluating which parts of agentic AI need human oversight and approval