Transforming Executive Decision-Making with Data & AI: Maximizing Business and Social Impact
Business Transformation and Enhanced Corporate Value Driven by Data & AI
Leveraging Data to Drive Decision-Making
With rapid environmental changes and increasingly complex social challenges, business management has never been more demanding. In this context, AI is evolving beyond a tool for efficiency—it is becoming a catalyst for taking corporate decision-making to the next level. Through Decision Intelligence, which integrates data and AI, Uvance empowers fast, accurate decisions and strongly supports transformation aimed at maximizing corporate value.
Balancing Business Impact and Social Impact
The remarkable evolution of AI positions it not merely as a means of operational efficiency but as a key to solving social issues while creating new value. Uvance, through Decision Intelligence that fuses data and AI, enables organizations to achieve both business impact and social impact simultaneously, accelerating the shift toward a new management model for sustainable growth.
Advanced Decision-Making Through Decision Intelligence
A Decision-Making Process Integrating Data, AI, and Human Expertise
Decision Intelligence is an approach that combines data, AI, and human insight to enable more advanced and accurate decision-making. Building on this concept, Uvance drives accelerated, AI-driven decisions and value collaboration, strongly supporting business transformation.
Enhancing Speed and Accuracy of Decisions Across the Organization
Through Decision Intelligence that fuses data and AI, Uvance dramatically improves the speed and precision of decision-making and execution across the entire organization—from the executive level to the front line. This empowers companies to maximize corporate value while achieving sustainable growth.
Autonomous Decision-Making and Collaboration Enabled by Agentic AI
Handling Massive Data Processing and Complex Scenarios
In today’s rapidly changing business environment, traditional data analysis and reporting alone cannot address complex challenges with the required speed and precision. Agentic AI enables real-time processing of vast amounts of data and complex scenario simulations, reducing decision-making cycles from days to mere hours.
Autonomous Decision-Making and Execution by AI Agents
Agentic AI shares objectives with humans and autonomously determines and executes the next actions based on collected and analyzed information, supporting optimal decision-making in collaboration with people. Uvance is building a system where multiple AI agents specialized in different business domains work together, ensuring governance, transparency, and highly reliable AI utilization.
Cross-Industry Value Creation and Trusted Data Collaboration to Realize Data Spaces
New Collaborative Value Through Trusted Data Sharing
Originating in Europe, data spaces provide a framework where diverse stakeholders securely and flexibly share trusted data, enabling mutually beneficial value creation. This trend is now expanding to Japan, fostering open ecosystems that transcend corporate and organizational boundaries and generate new collaborative opportunities.
Expanding Knowledge and Value Through AI Spaces
Building on data spaces, the concept of AI spaces accelerates the sharing of insights and value across both business and society. By combining advanced AI with seamless data integration, these ecosystems are evolving into mechanisms that drive growth and innovation collectively.
Executive Insights for the Data & AI Era
Centered on Uvance’s vision of “Human-AI Co-Creation,” we provide a structured introduction to the latest approaches—such as AI agents, Decision Intelligence, and Data & AI-native process innovation—illustrated with real-world examples. Explore industry case studies that reveal the background, frameworks, and future outlook for accelerating decision-making speed and quality, driving sustainable growth.
Beyond the limits of Data-driven management
Yamato Group's SST and Fujitsu: Collaborating for Resilient and Net Positive Logistics
Solving the "Tariff Puzzle" in an era of uncertainty with data & AI-driven supply chains
Redefining leadership decisions in the AI age
Fujitsu's Leadership in the Age of AI
Transforming Leadership: Navigating a Net Positive Future with AI
AI in action: Cross-industry collaboration and real-world impact
Working with agentic AI and its potential risks
People and AI: Fujitsu's vision for the future of business
Unlocking continuous growth: "Data & AI-native" business process transformation
A Future Strategy Powered by AI and Net Positive Thinking
AI Agents and the Transformation of the Financial Industry
Fujitsu Tackles Proprietary AI: AI + World-Leading Tech
This report summarizes a technology strategy briefing held in December 2024, focusing on cutting-edge technologies and their business applications. Key areas covered include: generative AI frameworks, multi-agent AI systems, and quantum computing. Specific use cases illustrating the practical business applications of these technologies were presented.
FAQ
What Is the Difference Between Decision Intelligence and Data-Driven Management?
Data-Driven Management (DDM) refers to using data to inform managerial decisions, such as formulating strategies and executing business initiatives.
Decision Intelligence, on the other hand, goes a step further. By leveraging data and technologies such as AI, it focuses on understanding, redesigning, and transforming the decision-making process itself—fundamentally changing how decisions are made.
What Is Decision Intelligence?
Decision Intelligence refers to the evolution of decision-making as a whole by analyzing, understanding, and redesigning decision-making processes through the use of data and technologies such as AI.
By identifying and modeling the causal relationships that influence decisions, organizations can build and execute rational, outcome-oriented decision processes that maximize business value.
What Is the Business Impact of Data & AI?
1. More Advanced and Faster Decision-Making
By combining large volumes of real-time data with predictive analytics, humans and AI can collaborate to make complex business decisions both faster and more objectively.
2. Repeatable and Scalable Management
By formalizing decision-making processes and decision models as institutional knowledge—and continuously improving them through AI learning—organizations can move away from reliance on individual judgment and establish repeatable, scalable decision cycles.
3. Increased Enterprise Value Through Outcome Optimization
Analyzing the causal factors behind decisions enables organizations to identify optimal options, leading to tangible results such as improved risk management, more efficient supply chains, and higher demand forecast accuracy across industries.
4. Organizational Learning and Sustainable Competitive Advantage
By continuously capturing decision outcomes as feedback and reusing them, organizations accelerate learning and build a resilient management foundation capable of sustained growth in rapidly changing environments.
What Are Some Examples of Data & AI in Action?
A major global electronics manufacturer integrated data distributed across more than 3,000 companies worldwide and visualized inventory and procurement data for approximately 200,000 product items.
By leveraging AI-based demand forecasting, the company now supports resilient supply chain decision-making, including during disaster scenarios.
What Is the Difference Between Data & AI and Data Science?
Data Science primarily focuses on analyzing data to generate predictions and insights.
Data & AI, by contrast, encompasses a broader approach: it combines analytics with AI, optimization, and simulation technologies to ensure that insights are actually embedded into business operations and managerial decision-making.
In short, while data science is analysis-centric, Data & AI extends beyond analysis to drive actionable decisions and operational improvements.
Consulting by Fujitsu
News
- Press Release Osaka Hospital launches project to safely utilize generative AI for healthcare workforce improvements
- Press Release Fujitsu to present latest technologies for creating social and industrial value through fusion of AI and computing at India AI Impact Summit 2026
- Press Release Fujitsu's Takane LLM successfully piloted in central government agency to streamline public comment operations
- Press Release Fujitsu launches new platform enabling autonomous operation of generative AI optimized for in-house applications in a dedicated environment
- Press Release Fujitsu recognized by World Economic Forum for project promoting sustainable hospital management leveraging AI
Related Information
Fujitsu Data Intelligence PaaS
