What challenges did Fujitsu face before AI implementation?

Manually intensive process of generating tailored sales proposals for clients. Sales staff spent excessive time identifying, accessing, and consolidating dispersed data sources. New employees struggled to learn the product portfolio and locate relevant information quickly. Delayed proposal turnaround time hindered sales effectiveness.

What was the impact of the AI solution?

Boosted sales productivity by 67%. Freed up sales teams to focus on customer engagement and high-value activities. Accelerated onboarding and proposal turnaround for new staff. Provided more accurate and timely client proposals.

Source

MicrosoftLive source

Fujitsu boosts sales productivity by automating proposal generation

Use case typeAutomotive operations automationUpdated Jun 13, 2026

Fujitsu faced time-consuming and manual sales proposal creation processes, hampering staff productivity and slowing the onboarding of new salespeople. To address these challenges, Fujitsu developed an orchestrated multi-agent AI system using Microsoft Azure AI Agent Service, Azure AI Foundry, and Semantic Kernel, allowing them to automate data gathering and proposal drafting. The new system integrates with Fujitsu's existing workflows and leverages multiple specialized AI agents to dynamically retrieve, synthesize, and tailor sales proposals from dispersed enterprise data sources. As a result, Fujitsu boosted sales team productivity by 67%, enabling staff to focus on customer engagement, faster onboarding for new hires, and delivery of more accurate, data-driven, and current proposals.

Organization: Fujitsu
Industry: Tech & Comms
Location: Japan
Published: June 2025

Reported outcomes

+67%

revenueRevenue & growth

Strategic outcomes

New product / capabilityAutomated proposal drafting and data gatheringSpeed & agilityAccelerated proposal turnaroundEmployee experienceFreed sales teams for high-value workCustomer experience & trustDelivered more accurate client proposals

Catalog median for revenue & growth deployments: +34% across 150 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 2 of 2

1Automated Sales Proposal Generation with Multi-Agent AI
2AI Orchestration for Real-time Data Synthesis in Sales

Manually intensive process of generating tailored sales proposals for clients.
Sales staff spent excessive time identifying, accessing, and consolidating dispersed data sources.
New employees struggled to learn the product portfolio and locate relevant information quickly.
Delayed proposal turnaround time hindered sales effectiveness.

Developed an orchestrated multi-agent system using Azure AI Agent Service and Semantic Kernel.
Automated proposal drafting and data gathering by dynamically retrieving and synthesizing internal knowledge.
Seamlessly integrated the AI-driven approach with existing Fujitsu workflows for sales teams.

Technologies

Azure AI Agent Service Azure AI Foundry Semantic Kernel Copilot Studio

Boosted sales productivity by 67%.
Freed up sales teams to focus on customer engagement and high-value activities.
Accelerated onboarding and proposal turnaround for new staff.
Provided more accurate and timely client proposals.

Architecture

At the solution's core, Fujitsu Kozuchi Composite AI uses Semantic Kernel to orchestrate multiple specialized AI agents. Azure AI Agent Service provides foundation PaaS capabilities, allowing the orchestrator AI to coordinate agents that retrieve, synthesize, and assemble proposals from dispersed internal data. Seamless integration is achieved via Azure services into existing workflow systems.

Sources & evidence4

Live sourceStill referenced

The case's original source is still reachable.