Fujitsu develops self-evolving multi-AI agent technology that learns and adapts to business operations

• 26 May 2026
• TM Team
• 0 Comments

Fujitsu Limited announced the development of a self-evolving multi-AI agent technology that enables multiple AI agents to perform tasks as a team, continuously and safely learning from daily execution results, human feedback, policy revisions, and specification changes.

In corporate operations, legal revisions, system changes, specification updates, and on-site rule modifications occur continuously. In business operations involving vast amounts of documents and design specifications, determining which information to reference, which judgment criteria to prioritize, and the extent of impact to confirm when responding to business needs has traditionally relied on the experience and tacit knowledge of skilled professionals. In addition, from a system perspective, continuous adjustments by experts were necessary to reflect changes in prompts, search methods, evaluation criteria, and operational rules.

While conventional AI agents demonstrate high processing capabilities for given instructions, they have found it difficult to independently analyse reasons for failure and safely incorporate them into subsequent operations. Consequently, adapting AI agents to the latest business environments required experts to continuously adjust prompts, search methods, evaluation criteria, and operational rules.

To address this challenge, Fujitsu has developed a technology that allows AI agents to safely learn by autonomously verifying their operational experience.

This technology is a multi-AI agent technology that continuously and safely evolves by adapting to changes in business environments and incorporating business execution results, human feedback, institutional revisions, and specification changes. Its most significant feature is that while performing tasks, AI agents identify reasons for success and failure, extract actionable knowledge and operational insights, and do not simply store generated improvement proposals. This allows AI agents to take over tasks such as prompt adjustments and evaluation criteria updates, which were previously performed continuously by experts. Furthermore, by deploying AI within the customer's environment, it continuously adapts to individual rules and judgment criteria that arise during business operations, realizing a business foundation that evolves with people and the environment.