PRESS RELEASE
Fujitsu developed an AI Agent to collaborate with store managers for AEON Food Style’s strategic store operations
Fujitsu Limited
Kawasaki, Japan, July 13, 2026
Fujitsu Limited today announced that it will begin a field trial of an AI agent developed jointly with AEON Food Style Co., Ltd. (AEON Food Style), to autonomously support store operations under its Uvance for Retail initiative, which aims for sustainable growth in the retail industry through Data & AI. The trial will take place at a physical store in July 2026. This AI agent is designed to support store strategy formulation and sales floor layout planning, and the trial will verify its effectiveness in accelerating decision-making, standardizing operations, and improving efficiency in store management. Moving forward, Fujitsu will leverage the results of this field trial to further enhance store operations and management for AEON Food Style.
Background
The retail industry faces challenges such as chronic labor shortages, and store manager responsibilities, in particular, are diverse and heavily reliant on individual experience and skills, leading to issues of task expertise residing with specific individuals.
AEON Food Style was established on March 1, 2026, through the integration of MaxValu Kanto, Daiei's Kanto operations, and AEON Market. Amid a declining population and diversifying consumer needs, AEON Food Style decided to promote the utilization of AI agents in collaboration with Fujitsu to support store managers in making swift decisions and executing strategic store operations, thereby realizing consistent, higher-quality service across all stores.
Overview
In developing this AI agent, Fujitsu's Forward Deployed Engineers (FDEs) and designers identified common tasks across the integrated companies' store operations and clarified the ideal store manager profile for AEON Food Style. Based on this, they formulated an optimal operational process (business model) for store management. Within approximately 10 days, four AI agent prototypes were developed to assist store managers in tasks where they felt a strong need for support, such as store strategy formulation, shelf layout planning, feasibility studies for initiatives, and trade area analysis. This field trial will focus on two of these AI agents.
Trial Period: Expected to be several days in July 2026
Targeted operations and verification content
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Store strategy formulation
The AI agent supports the execution of analysis based on the 3C's framework and the formulation of medium- to long-term store strategies. This trial will verify its effectiveness by measuring the reduction in the time store managers spend on strategy formulation and the adoption rate of AI agent-generated plans. Additionally, it will verify the agent's effectiveness in training new store managers following personnel changes and standardizing practical operations.
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Shelf allocation and layout planning
The AI agent generates detailed shelf plans and layout images based on headquarters' display instructions, product information, and store characteristics. This trial will verify the efficiency improvements in tasks from shelf plan creation to instructing sales floor personnel, as well as the effectiveness of smooth communication through sharing layout images.
Future Plans
Moving forward, based on the results of this field trial, Fujitsu will collaborate with AEON Food Style to improve the accuracy and expand the application scope of the AI agent. Fujitsu will also consider further trials of AI agents aimed at increasing sales.
Fujitsu aims to develop multi-AI agents for the retail industry, where multiple AI agents, including the store manager support AI agent, collaborate to autonomously execute tasks. Through Uvance for Retail, Fujitsu will drive innovation in the experiences of consumers and workers, thereby enhancing the retail industry's competitiveness and promoting sustainable growth.
Press Contacts
Fujitsu Limited
Public, Investor and Analyst Relations Division
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Date: 13 July, 2026
City: Kawasaki, Japan
Company: Fujitsu Limited