Trust in AI

What does it take to lead with confidence in an AI‑driven world?

AI is accelerating ambition – and reshaping how organizations operate. The pressure for leaders to act is real, but not at the expense of control, confidence or trust. Because falling behind is a risk – but getting it wrong carries greater consequences.

As systems begin to think, act and decide, trust becomes critical. The more AI can do, the more human judgement matters.

We believe trust isn’t given – it’s earned. That’s why we design AI with trust built in. AI that’s explainable in its decisions, sustainable in its impact, connected across real-world operations, secure and ethical at its core, and governed with care for data.

Shaped by decades of delivering technology where trust must be proven, our approach is enterprise-grade, grounded in real use, and continuously evolving. We focus on delivering outcomes – reliably, responsibly, and at scale.

AI that leaders can depend on – built with trust at every step.

Child and robot hand touching fingers. AI and human interaction.

A new perspective on trust in AI

AI is evolving—from a convenient tool into a trusted presence that supports work and business-critical decision-making. For that reason, AI today must be more than simply capable. It must be something people can rely on with confidence: safe to use, dependable, and worthy of trust. Yet the factors that determine AI trustworthiness are broad and complex, making the full picture difficult to grasp.

Trust in AI is a framework developed to organize this complexity, making it easier to understand and apply in real business contexts.

Read “Trust in AI”: a new perspective for embedding trust into AI

Uvance Wayfinders - Consulting that guides complex change to real outcomes

Uvance Wayfinders combines AI-native consulting, deep industry expertise, and Fujitsu's technology capabilities to help organizations turn strategy into measurable business outcomes.

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The world is already asking: Can AI truly be trusted?

77 %

77% of executives say AI should only be adopted if it is fully trustworthy.

13 %

However, only 13% report that they have strong security and robust data governance to support their AI operations.

Source: FT Longitude, Global Survey

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Closing the AI trust gap: What leaders are seeing about trust in AI

Trust in AI is key to unlocking better business outcomes. See how trust in AI drives performance and how to build it across data, governance, and skills.

Full report available here

How is trust built into AI? — The five pillars of Trust in AI

As AI moves closer to the core of business, trust must be designed from the outset—not added later.
These five pillars are not optional.
Together, they form the foundation required to make AI a true driver of transformation.
Applies this experience to design and implement AI and digital environments that can be used with confidence in real business operations.

Hierarchical diagram illustrating the five key elements of Trust in AI: Explainable, Secure & Ethical, Sovereign, Sustainable, and Connected. Beneath these elements are Fujitsu’s AI governance initiatives, including the Fujitsu Group AI Commitment and the Fujitsu Group External Advisory Committee on AI Ethics. The diagram also maps key technologies within the Fujitsu Kozuchi AI platform, such as Causal AI, Knowledge Graph Enhanced RAG, Multi AI Agent Technology, AI Security Technology, AI Ethics & Fairness Technology, Data & AI Space Collaboration Technology, Takane, 1-Bit Quantization Technology, and AI Computing Broker. At the foundation layer, supporting infrastructure technologies include the FUJITSU-MONAKA series, Quantum Computing, Quantum-HPC Hybrid Computing Technology, AI-RAN, APN (All Photonics Network), and AI Network OS.

How trust in AI is built — the technologies and business value behind each element

To learn more about each element, along with the related initiatives and technologies, please explore the sections below.

Explainability

When the reasoning behind AI decisions cannot be explained, organizations cannot confidently accept or take responsibility for them. Explainability is therefore fundamental to trustworthy AI.

Secure and Ethical

As AI adoption expands, readiness for security vulnerabilities and ethical risks becomes essential. Security and ethical integrity are key prerequisites for earning trust and enabling sustainable growth.

Sovereign

Data and AI sovereignty are essential. If AI is exposed to external influence, organizations cannot maintain control or accountability. Sovereignty is essential to retaining both.

Sustainability

As AI evolves, rising energy consumption and costs can no longer be ignored. Long-term AI adoption depends on sustainability by design.

Connectivity

When AI is confined to isolated domains, its full potential remains unrealized. True transformation comes from connectedness – integrating data and AI across organizational boundaries.

Trust in AI: A lesson from history

History’s turning points remind us that progress only matters when people can trust it.

Through powerful stories and Fujitsu’s real-world technologies, this series explores how trusted AI leads to better decisions and stronger business outcomes. Each article draws on the five essential pillars of Trust in AI, showing how confidence can be designed into every step. Because when trust is built in from the start, AI can help create a more sustainable future.

The Copernican lesson for Trust in AI

Explainable

Inside an observatory dome with a telescope pointed at the night sky.

From Renaissance dreams to sustainable AI

Sustainable

Bird's-eye view of the Duomo (Florence Cathedral) in Florence, Italy.

The Silk road for Trusted AI

Connected

A caravan of camels carrying people across a desert at sunset.

Is your AI becoming the Titanic?

Secure and Ethical

View from a ship's bow of the open sea and sunset on the horizon.

The new trade routes of AI sovereignty

Sovereign

Silhouette of a sailboat on the water reflecting the sunset, against a sunset sky and sea.

FAQ

Q1: What is Trust in AI?

A framework based on decades of AI research and engineering expertise, that outlines the conditions required to ensure trust in AI.

Q2: Why redefine “Trust in AI”?

As the global landscape evolves, evaluating AI purely on performance is no longer sufficient—trust has emerged as a critical dimension. Against this backdrop, we identified five key elements necessary to embed trust into AI and consolidated them into our “Trust in AI” framework.

Q3: What is Uvance Wayfinders?

Uvance Wayfinders is Fujitsu’s consulting brand, built on its heritage of engineering excellence and real-world delivery. Wayfinders connects strategy, architecture, technology, and execution to deliver end-to-end change, from planning through to adoption and measurable outcomes, turning technology into value that works in real business.

Q4: What is the difference between general AI Trust/AI Governance and Trust in AI?

As AI rapidly evolves and becomes central to business management and operations, its trustworthiness becomes increasingly critical. AI Trust encompasses multiple layers, from foundational AI ethics principles and policies/regulations designed to secure them within society, to technological architectures for their implementation. However, the broadness of these perspectives can make it challenging to grasp the overall picture, especially from the standpoint of business implementation. Against this backdrop, Trust in AI focuses on elements that can be readily achieved and enhanced through technology to embed trust in AI, organizing them into an easy-to-understand framework.