{"id":3698,"date":"2024-11-18T12:00:30","date_gmt":"2024-11-18T20:00:30","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/semantic-kernel\/?p=3698"},"modified":"2025-02-10T10:21:22","modified_gmt":"2025-02-10T18:21:22","slug":"customer-case-study-fujitsu-kozuchi-ai-agent-powered-by-semantic-kernel","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/agent-framework\/customer-case-study-fujitsu-kozuchi-ai-agent-powered-by-semantic-kernel\/","title":{"rendered":"Customer Case Study: Fujitsu Kozuchi AI Agent Powered by Semantic Kernel"},"content":{"rendered":"

Customer Case Study: Fujitsu Kozuchi AI Agent Powered by Semantic Kernel<\/span><\/h3>\n

Japanese multinational Fujitsu, a pioneer of information and communications technology, has been transforming industries since 1935. With a workforce of 124,000 dedicated professionals across 50 countries, Fujitsu\u2019s mission is to \u201cmake the world more sustainable by building trust in society through innovation.\u201d<\/span><\/p>\n

After introducing their groundbreaking Composite AI earlier this year, Fujitsu is back with another innovative business solution. The Fujitsu Kozuchi AI Agent is an autonomous system that functions as a full team member, making proactive suggestions and analyses.\u00a0<\/span><\/p>\n

Launched in late October for use in business profitability discussions and negotiations, a broader line of agents will eventually expand to cover production management and legal affairs, among other functions.\u00a0<\/span><\/p>\n

From Interactive to Proactive<\/b><\/h3>\n

Early generative AI was based on a call-and-response model that required human users to input instructions and only generated responses based on previously learned data. These models were useful tools that increased productivity but lacked the ability to discover issues on their own or propose novel solutions.<\/span><\/p>\n

The Fujitsu Kozuchi AI Agent uses proprietary processing logic to break down abstract issues from conversations and generate discrete tasks. It proactively enters and participates in a discussion, creates a plan to complete tasks, and selects multiple AI models to implement.\u00a0<\/span><\/p>\n

It acts just as a regular team member would, making proactive suggestions and generating new, creative ideas.\u00a0<\/span><\/p>\n

\"Image<\/a><\/p>\n

Practical example<\/strong><\/span><\/h3>\n

Let\u2019s say two team members are discussing the current sales figures for an important region, and there\u2019s a disagreement over performance. The meeting transcription reads like this:<\/p>\n

Team member 1: <\/em><\/strong>Recently, I\u2019ve been hearing that deals in Asia are not going well.<\/em><\/p>\n

Team member 2: <\/em><\/strong>No, I think Asia is fine. I\u2019ve heard we lost a few small deals, but I don\u2019t think it\u2019s affecting the big picture.<\/em><\/p>\n

Team member 1: <\/em><\/strong>I know Dan, the head of Asia, has said as much, but apparently, the numbers show otherwise.\u00a0<\/em><\/p>\n

With the AI agent present, additional data could be suggested to clear up the confusion. The system would select several AI models and direct them to perform sales analysis in the Asia region. Depending on the result, it would present a clear answer, easily digestible visuals, and reasons for the discrepancy.<\/p>\n

This is done completely autonomously, without either team member inputting instructions or interacting with the AI. The meeting can continue with better insight, and decisions can be made more effectively.<\/p>\n

Fujitsu Kozuchi AI Agent<\/a><\/strong><\/span><\/p>\n