Walmart and Target Take Divergent Paths in AI Shopping
Walmart and Target are pursuing fundamentally different strategies to capture sales through AI shopping tools, revealing competing visions for how retailers will operate in an AI-driven market.
Walmart is building its own AI systems in-house. Target is betting on partnerships with OpenAI's ChatGPT and Google's Gemini. Both approaches aim to get their products in front of consumers using AI answer engines to research and buy items, but the execution differs sharply.
The stakes are clear: retailers that don't appear in AI search results risk losing visibility to shoppers. The question for executives is whether to control the technology directly or integrate with existing platforms.
Walmart's In-House Build
Walmart is developing four "super agents"-AI systems designed for specific functions. Sparky is the consumer-facing shopping assistant embedded in Walmart's mobile app. Marty helps suppliers manage operations and advertising. Two others assist store associates and developers.
CEO John Furner framed the strategy as simplifying operations and reducing friction for shoppers. Walmart is embedding Sparky directly into ChatGPT and Google's Gemini, allowing customers to add multiple products to shopping baskets within those platforms.
This approach leverages Walmart's scale. The retailer processes enormous transaction volumes in grocery and fulfillment, generating training data for AI optimization. Kashif Zafar, CEO of retail adtech firm Xnurta, said Walmart's position is strong because it's "tying it to their scale in grocery and last-mile fulfillment."
Walmart's ecommerce investments over recent years have already gained market share from Amazon. The AI strategy extends that momentum.
Target's Partnership Model
Target signed a deal with OpenAI in November to make products shoppable through ChatGPT. The retailer and OpenAI's design teams built a ChatGPT-specific app in one month. Target's ad arm, Roundel, can also sell ads within ChatGPT's advertising program.
Target is separately working with Google to integrate products into Google Search's AI Mode and Gemini. The retailer developed Target Trend Brain internally-a tool that helps designers synthesize trend data to create products faster.
Target's new CEO Michael Fiddelke is investing $2 billion incrementally in 2026 on guest experiences, including AI and brand marketing, as part of a broader turnaround effort.
Prat Vemana, Target's chief information and product officer, emphasized speed. "You have to be at that pace and speed-otherwise it's hard to innovate with them," he said of working with OpenAI.
Where Consumers Actually Buy
Early data shows consumers are still primarily using AI tools for discovery and recommendations, not transactions. Vemana said Target's learnings indicate "people are still more in the upper funnel, in the inspiration space."
Shoppers ask AI assistants for product suggestions for trips or movie nights. They're not yet buying groceries through these interfaces. This matters for both retailers-it means AI tools are currently funneling traffic rather than closing sales directly.
ChatGPT recently shifted its commerce strategy away from instant checkout to directing users to retailers' apps. This benefits Target's ChatGPT-specific app, which connects to customer accounts and shows personalized recommendations based on shopping history.
The Data Advantage Question
Zafar noted that Target has "strong first-party data and great engagement in discovery categories like beauty and apparel," but its strategy has historically relied on partners. Walmart's approach of building tools in-house gives it direct control over how customer data informs product recommendations and ad optimization.
The real competition isn't just about having AI-it's about converting shopper data into automated optimization faster than rivals. Zafar said the question for advertisers is "who can turn shopper data into automated optimization the fastest."
Ecommerce analyst Juozas Kaziukėnas singled out Walmart as the only established retailer making meaningful progress in AI commerce. "Given Walmart's history of lagging in ecommerce for years to only eventually wake up to try to catch up in a market lost to Amazon, they are approaching AI differently," he said.
For executives evaluating their own AI strategy, these two approaches offer a clear choice: build proprietary systems that integrate with existing platforms, or partner deeply with established AI providers and optimize for speed and integration.
AI Strategy for Executives and AI Learning Path for Retail Managers provide frameworks for understanding how these retail strategies apply across industries.
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