What’s holding organizations back from deploying AI in high-stakes, regulated environments?
They can’t consistently explain, audit, or defend automated decisions at the level required for mission-critical use - so trust becomes the limiting factor.
This page shows you how to overcome these challenges with a proven, practical, and trustworthy approach to enterprise AI.
(1) According to IDC’s February 2025 Future Enterprise Resiliency and Spending Survey (n=885, global).
AI adoption is accelerating across industries, yet organizations face mounting pressure to ensure systems are compliant, defendable, and ethically aligned with clear AI risk management and governance.
Regulatory expectations are rising, reputational risks are growing, and leaders must be confident that AI supports - not undermines - critical business operations.
This episode of the Fujitsu impact series reveals how to build AI systems that are robust, explainable, and trustworthy by design from day one.
Join John Walsh (VP & CTO, Fujitsu Europe), Aditya Raj (AI SME & GTM Strategist, Fujitsu), and IDC guest speaker Dr. Chris Marshall as they share:
Access the recording below for the full episode to learn how to design AI systems that are robust, explainable, and trustworthy
Designed for C-suite leaders, AI strategists, and enterprise architects who need clear, actionable guidance on building and operationalizing trustworthy AI from day one.
“Trust isn’t an add-on—it’s designed in, from strategy through execution, so organizations can deploy AI responsibly and with confidence in critical environments.”
John Walsh, VP & Chief Technology Officer, Fujitsu Services Europe
Dive into our extended white paper for a comprehensive exploration of the principles and practices for building trustworthy AI, and get a fast, at-a-glance view of the key takeaways in our companion infographic.
Why trust - not tech - decides whether AI scales
What “trustworthy AI” means in the enterprise world
How to bake trust into every step of the AI lifecycle
How Kozuchi AI + AKOS Hub put trustworthy AI into action
VP at IDC Asia / Pacific AI Lead, Data, Analytics & Sustainability Research
VP & CTO for Fujitsu Europe, 30+ years in Enterprise IT and AI Governance
AI Subject Matter Expert and Go-To-Market Strategist, Fujitsu
MODERATOR
Global Thought Leadership Evangelist
AI is reshaping how organizations make high impact decisions - but without trust, even the most advanced systems fail to scale. As enterprises integrate AI into mission critical workflows, the ability to explain, audit, and defend AI powered decisions becomes essential for regulatory confidence, operational reliability, and stakeholder buy-in.
Hands-On Insights for AI Leaders:
If your goal is to scale AI safely, accelerate value, and reduce risk, the insights in this paper show exactly how to get there.
AI is scaling fast, but trust remains the biggest blocker. Our new infographic shows why 41% of organizations still hesitate to adopt AI due to transparency gaps, hallucinations, and false positives - and what leaders must do to fix it.
The infographic highlights:
If you want a clear, visual snapshot of what it takes to build trustworthy AI from day one, this infographic delivers it.
Leading manufacturer of polymer-based solutions, REHAU joined forces with Fujitsu to implement AI-powered quality inspection solution that transforms how quality is monitored in high-speed production. With more than 200,000 product variants, traditional checks couldn’t keep up. The new AI system enables fully automated, continuous visual inspection, detects even the smallest defects in real time, and reduces complaints, rejects, and waste. The result: higher product quality, lower costs, and more sustainable manufacturing.
Trustworthy AI describes systems that are accurate, explainable, auditable, and governed so leaders can defend AI‑assisted decisions in high‑stakes environments.
According to IDC, 41% of organizations cite transparency gaps, hallucinations, and false positives as primary blockers to adoption. Trust, not technology, limits scale.
Regulatory confidence, operational reliability, and stakeholder buy‑in, with measurable practices that turn trust from a concept into daily operations.
Explainability, provenance tracking, continuous assurance, bias detection, knowledge graph–grounded RAG, and multimodal intelligence.
Fujitsu Kozuchi AI and the AKOS Hub toolset (that leverages cutting-edge Fujitsu AI Trust technologies) help embed explainability, governance, and reliability into real‑world workflows across the lifecycle.
Continuously track model performance, data drift, and bias, with human accountability and auditable controls.
Reliable, secure outputs and transparent, explainable processes that regulators and stakeholders can defend.
Trustworthy AI in manufacturing means accuracy, transparency, auditability, and strong governance. In manufacturing, these principles carry greater weight because they underpin high‑stakes decisions affecting product quality, operational safety, and production efficiency.
With Fujitsu AI, you can confidently deploy and leverage AI across your business, ensuring better decisions and stronger operations without compromising data sovereignty, security, or control.
Designed for enterprise use, our AI leverages industry expertise and partner technologies to deliver full explainability, robust governance, and strong security. This enables safe and reliable AI deployment in critical,regulated environments. Trust our practical, secure, and transparent AI toaccelerate innovation with confidence in every decision.
