Autonomous Decision-Making and Collaboration Enabled by Agentic AI

The Evolution of AI Adoption and the Cutting Edge of Enterprise Decision-Making

AI has moved beyond the adoption phase and is evolving into a core driver of enterprise transformation. Working alongside people, Agentic AI supports processes from decision-making through execution, dynamically reshaping business operations. Fujitsu Uvance provides a practical path for adopting and advancing Agentic AI, helping customers strengthen their competitive advantage.

This graphic illustrates the changing role of humans in work. From 2025 to 2030, the share of work performed solely by humans is expected to decline, shifting toward a model in which humans, technology, and human-technology collaboration each account for around 30% of work. As a result, the role of humans will evolve from executing tasks to leading value creation in collaboration with AI and robots. In addition, more than 70% of business leaders expect technology to help reduce disparities in employment, healthcare, and education, as well as accelerate solutions to social challenges.

From Fujitsu Technology and Service Vision 2026

What is Agentic AI

As generative AI becomes part of everyday business, the real evolution of AI is just beginning. Next-generation Agentic AI autonomously makes decisions and takes action to achieve goals—handling everything from data collection and analysis to decision-making and execution. Moreover, multiple AI agents can collaborate to tackle complex challenges with greater flexibility. Fujitsu connects specialized AI agents across different business domains, enabling massive data processing and intricate scenarios to be executed in a fraction of the time. With Governance(※) and transparency at its core, we position AI as a trusted partner in decision-making—driving competitiveness and accelerating business transformation.
Fujitsu’s AI agent has been named “Watomo.” The name Watomo is derived from the concepts of connection, friendship, and togetherness, reflecting an AI that works collaboratively with people—thinking, learning, and taking action side by side to move things forward. As an AI agent that embodies the principles of agentic AI in real-world operations and decision-making, Watomo will continue to evolve over time.
※A responsible AI governance framework that enables organizations to understand AI risks and deploy AI safely and securely in society by establishing appropriate rules, organizational structures, processes, and technologies.

Generative AI is only the prologue to AI’s evolution. The next leap is toward Agentic AI—systems that act autonomously to achieve goals. In this new era, multiple agents will collaborate, enabling humans and AI to co-create, solve complex challenges, and unlock entirely new sources of value.

The Three Pillars of AI Agents”Watomo”

In today’s increasingly complex and uncertain business and social environments, the evolution of AI is becoming a driving force for new value creation. Fujitsu emphasizes a human-centric perspective—placing people at the heart of everything—and advocates for an era where humans and AI collaborate and co-create to generate unprecedented ideas and innovations.
Agentic AI supports human decision-making, enhances operational efficiency, and fosters creativity, contributing to the sustainable growth of businesses and society as a whole. Furthermore, through cross-industry ecosystems, we aim to expand value creation driven by human-AI collaboration across society, ultimately improving environmental sustainability, economic prosperity, and overall well-being.

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1. Enhancing Flexibility and Productivity with Domain-Specific Agents

An Illustration of Industry-Specific AI Agents Leveraging Enterprise Data to Improve Operational Efficiency and Productivity

For AI agents to truly replace enterprise tasks, they must understand business processes as well as—if not better than—humans.
Fujitsu has spent decades co-creating applications with customers, building deep expertise in industries and operations alongside strong development capabilities. On the technology front, we’ve developed foundational elements that enable AI agents to thrive—such as Takane, our Japanese-optimized LLM, and the Enterprise Generative AI Framework, which ensures accurate interpretation of corporate data through structured data and contextual understanding.
This position as a technology company deeply rooted in real-world operations is the core strength of Uvance.

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2. Solving Complex Challenges Through Multi-Agent and Multi-Vendor Collaboration

An Illustration of Multi-Agent AI Collaborating with External Systems and Third-Party Agents to Support Workflow Automation, Optimization, and Decision-Making

Specialized AI agents will collaborate seamlessly across domains, working together with external systems and third-party agents to achieve end-to-end automation and optimization of business processes.
These multi-AI agents(※) operate as a dynamic network, selecting the most suitable agent based on objectives and context—handling everything from information extraction to decision-making and execution.
Unlike centralized management, this approach leverages the unique strengths of each system and agent, enabling flexible integration. By connecting diverse AI technologies and vendors, we can respond to complex business challenges quickly and accurately.
※A multi-AI agent system in which multiple AI agents collaborate according to their respective roles and areas of expertise. By dividing tasks such as information gathering, analysis, decision-making, and execution, the system helps solve complex challenges that are difficult for a single AI agent to address.

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3. Creating a Trusted Environment with Robust Reliability and Governance

An Illustration of Enhancing AI Agent Governance and Reliability to Control Security Risks and Hallucinations

As AI agents increasingly integrate with diverse systems and take on advanced decision-making roles, mitigating risks such as factually incorrect outputs (hallucinations) and information leaks becomes more critical than ever.Fujitsu has decades of expertise in AI ethics, security, and privacy, and is globally recognized for its industry-leading accuracy in hallucination suppression. Building on this knowledge, we will deliver technologies that monitor and control inter-agent communication and behavior—providing a level of trust and governance that competitors cannot match.

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New Use Case Demos Powered by AI

Autonomous Inventory Management with Fujitsu's AI Agent

Inventory management is becoming increasingly challenging in today’s complex supply chains. In this video, we showcase how seven Fujitsu AI agents work together to handle stockout alerts, illustrating the entire process from proposal to adoption, evaluation, and continuous improvement. By integrating data and leveraging AI, the solution automates and streamlines inventory operations, delivering dramatic gains in productivity.

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Dynamic Supply Chain Management optimizes inventory using Fujitsu AutoML's demand forecasting

Traditionally, inventory management in manufacturing has relied heavily on experience, but rising labor costs and a shortage of skilled workers are pushing this approach to its limits. By leveraging AI and data, companies can now automate demand forecasting and inventory calculations, dramatically improving supply chain efficiency. This transformation not only boosts competitiveness but also drives sustainable business growth.

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FAQ

What Is Agentic AI?

Agentic AI refers to AI systems that autonomously make decisions and take actions to achieve defined goals.
They can handle the entire cycle—from information gathering and analysis to decision-making and execution—on a continuous basis.
By enabling multiple AI agents to collaborate, Agentic AI can respond flexibly and rapidly to complex challenges.
Fujitsu promotes the use of AI as a trusted partner for enterprise decision-making by combining domain-specific AI agents while ensuring governance, transparency, and control.

How Do AI Agents Improve Operational Efficiency?

Multiple task-specialized AI agents work together to autonomously handle data collection, analysis, decision-making, and execution.
This enables continuous and rapid support for advanced management decisions.
As a result, tasks that were traditionally manual—such as proposal creation, report generation, operational judgment, and coordination—can be automated or significantly streamlined.
This reduces lead times and workloads while allowing people to focus on final decision-making and value creation, ultimately improving productivity and decision quality across the organization.

What Is the Difference Between Agentic AI and AI Agents?

Agentic AI is a system in which AI understands goals and makes decisions and takes actions autonomously. An AI agent is an individual AI that performs a specific task or role within that system. The two are not separate concepts; Agentic AI is realized through the collaboration of multiple AI agents.

What Is a Multi-Agent System?

A multi-agent system is an approach in which multiple AI agents with different roles and areas of expertise collaborate, dividing tasks according to a shared objective to carry out business processes. Each agent observes the situation, develops plans, makes decisions, takes action, and continuously improves through an iterative feedback loop.
For complex challenges that are difficult for a single agent to address, specialized AI agents can work together with an orchestrator AI agent that coordinates their activities and a verifier AI agent that validates the accuracy and appropriateness of their outputs. This enables more flexible and sophisticated responses.
Through multi-agent and multi-vendor AI environments, Fujitsu supports autonomous decision-making and execution across a wide range of enterprise operations.

In What Situations Can the AI Agent ”Watomo” Be Used?

Watomo is the name of Fujitsu’s AI agent. Fujitsu positions Watomo as an AI agent that brings the concept of Agentic AI into real-world business operations and decision-making.
Fujitsu’s Watomo AI agent can be used in situations where people and AI collaborate to advance business processes and decisions. Beyond information retrieval and content generation, Watomo supports tasks involving information gathering, analysis, decision support, and execution. It is particularly effective as a business-specific AI agent for complex challenges involving multiple processes and stakeholders, helping people make more informed decisions.

How Is Governance Ensured for Agentic AI?

Yes, Agentic AI can be used in Japanese-language business environments.
Fujitsu provides a foundation for understanding Japanese-language context and utilizing enterprise data through technologies such as Takane, a large language model optimized for Japanese, and the Enterprise Generative AI Framework, which enables AI to accurately interpret corporate data. This allows AI agents to more effectively gather and analyze information, support decision-making, and assist with execution in business processes involving Japanese-language internal documents, operational rules, customer interactions, reports, proposals, and frontline data.

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Autonomous Decision-Making and Collaboration Enabled by Agentic AI

The Evolution of AI Adoption and the Cutting Edge of Enterprise Decision-Making

What is Agentic AI

The Three Pillars of AI Agents”Watomo”

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1. Enhancing Flexibility and Productivity with Domain-Specific Agents

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2. Solving Complex Challenges Through Multi-Agent and Multi-Vendor Collaboration

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3. Creating a Trusted Environment with Robust Reliability and Governance

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