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Walmart

Walmart launches generative AI search on Azure OpenAI Service, contributing to 22% global ecommerce growth in Q1 FY2025

Walmart built a generative AI-powered search engine using Azure OpenAI Service and proprietary retail models, enabling shoppers to submit natural-language, occasion-based queries and receive curated product bundles. The company reported 22% global ecommerce growth in the quarter when the capability went live.

Global ecommerce growth (Q1 FY2025)22%
eCommerce share of net sales (FY2025)18%
4 min read

Background

Walmart's digital customers performed multiple disconnected searches to accomplish single shopping goals — a fragmented experience reflecting the limitations of keyword search. The company sought to move to intent-aware, conversational search that understood the occasion behind a query, enabling a more seamless digital shopping experience. With ecommerce growing as a share of Walmart's business, improving digital discovery had direct revenue implications.

What Was Implemented

  • Built a generative AI-powered search function across iOS, Android, and Walmart.com
  • Combined Walmart's proprietary retail-specific models with foundation models via Microsoft Azure OpenAI Service
  • Designed to interpret contextual, goal-based natural-language queries and return curated, personalized product bundles
  • Announced at CES, January 2024, by Walmart CEO Doug McMillon and Microsoft CEO Satya Nadella
  • Simultaneously deployed "My Assistant," a generative AI productivity tool for ~50,000 non-store associates, on the same Azure OpenAI infrastructure

Results

Walmart reported 22% global ecommerce growth in Q1 FY2025 (SEC Form 8-K, May 16, 2024). Over two fiscal years, ecommerce grew more than 20% annually, reaching 18% of net sales . The company credited investment in AI and experience-enhancing technologies among growth drivers, though the earnings release does not isolate the contribution of the AI search feature independently.

Lessons

  • Goal-based, occasion-driven search requires combining general-purpose large language models with proprietary retail and product data — neither alone delivers the specificity needed
  • Internal associate productivity tools can run on the same AI infrastructure as consumer-facing features, improving return on AI investment
  • A company-level ecommerce growth figure and a specific AI feature can be reported together without the company quantifying a causal relationship — these claims should be kept analytically separate

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