Walmart revolutionizes retail merchandising with generative AI assistant
Walmart implemented a generative AI assistant, named 'Wally,' using Azure AI and Azure OpenAI Service to improve merchant decision-making on product assortment, pricing, and inventory replenishment. The assistant integrates with Walmart's internal systems, enabling merchants to ask natural language questions and receive contextual, data-driven insights in real time. This eliminates the need for manual dashboard analysis and reduces reliance on analysts, speeding up operations. Wally reasons across various data inputs to provide consistent and agile decision support tailored to retail workflows. The deployment focuses on augmenting employee capabilities, leading to a more responsive and efficient merchandising process. The project addresses operational inefficiencies, inconsistency in decisions, and the time merchants spent gathering and analyzing data. It is part of Walmart’s broader strategy of infusing AI and automation into retail operations to boost responsiveness and profitability.
- Organization
- Walmart
- Industry
- Retail
- Location
- United States
- Published
- May 2025
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Walmart
- Provider
- Microsoft
- Maturity
- Production
- Linked source
- vktr.com
The project addresses operational inefficiencies, inconsistency in decisions, and the time merchants spent gathering and analyzing data
Primary read
Use case focus
Showing 3 of 3
- 1Generative AI assistant for retail merchandising
- 2Automated decision support for product assortment and pricing
- 3Natural language analytics for inventory optimization
- Implemented a generative AI assistant ('Wally') using Azure AI and Azure OpenAI Service.
- Integrated Wally into internal data sources and merchant systems for seamless access to real-time insights.
- Enabled natural language queries so merchants can quickly obtain actionable, contextual information.
- Automated reasoning across multiple data streams to provide decision support and optimize inventory and pricing.
- Reduced reliance on specialized analysts, freeing up resources.
- Enabled more agile operations, leading to better inventory management and enhanced responsiveness to market dynamics.
Sources & evidence1
- Customer explicitly identified
- Deployment status explicitly supported
- Technical implementation details available
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