AI investment is rising, but measurable business outcomes from AI adoption remain elusive. According to IDC, only 11% of organizations report success in more than 75% of their AI projects – and on average, just 45% of AI initiatives deliver measurable outcomes.* But when AI initiatives succeed, the returns can be substantial. Nearly 55% of organizations estimate a 3–4x return on investment from their GenAI projects.**
Episode 1 of the Fujitsu impact series focuses on why so many AI initiatives stall, and what differentiates organizations that successfully move from pilots to enterprise-scale impact.
(1) IDC’s Technology Investment and Innovation Monitor: Tech Buyer and IT Spending Outlook
and AI/Agent Adoption Survey, September 2025
(2) IDC’s Market Perspective: Generative AI ROI, Global Survey, June 2025
Listen to John Walsh (VP & Chief Technology Officer, Fujitsu Services Europe), Aditya Raj (AI Subject Matter Expert & Go To Market Strategist, Fujitsu) and guest speaker, Dr. Chris Marshall (VP, IDC Asia Pacific) who identify AI adoption as a business transformation challenge, rather than a technology roll-out problem. Learn from their real-world experiences with customers and independent analyst perspectives.
Access the recording below for the full episode to learn how to confidently scale AI, manage emerging risks and safeguard customer trust.
Designed for C-suite leaders and transformation owners who need clear, actionable guidance on scaling AI from pilot phase to enterprise value.
"A significant portion of an AI project's investment should be dedicated to adoption and good quality business change, truly injecting AI into your work processes as opposed to using it simply as a very smart search tool."
John Walsh, VP & Chief Technology Officer, Fujitsu Services Europe
Unlock even deeper insights into the strategies, structures and real‑world practices that help organisations turn AI ambition into measurable impact. Dive into our extended white paper for a fuller exploration of the trends shaping enterprise‑ready AI, and get a fast, at‑a‑glance view of the key takeaways in our companion infographic.
Business clarity drives AI success more than tool selection Clear objectives, use cases, and value metrics matter more than choosing the “right” AI platform.
C-suite sponsorship is critical for enterprise AI adoption Executive ownership accelerates decision-making, funding, and organization-wide AI adoption.
Data readiness and AI governance are prerequisites for trustworthy AI High-quality data, security, and governance frameworks enable responsible and compliant AI at scale.
Workflow redesign and organizational visibility unlock scalable AI value Redesigning processes and improving cross-functional visibility determine whether AI scales beyond pilots.
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 SME and GTM Strategist at Fujitsu Europe
MODERATOR
Global Thought Leadership Evangelist
Unlock the full potential of AI-driven transformation with our exclusive white paper, AI Adoption - A Practical Playbook for CxOs.
This resource distills insights from the Fujitsu impact series, a six-part event to help enterprises with their AI strategies. The white paper provides a step-by-step framework for successful AI implementation, emphasizing responsible, secure deployment practices that ensure sustainable business value – not technology hype.
Learn how leading organizations:
• Start with clear business problems, not tool wish lists
• Build enterprise-grade governance, security, and explainability into every stage of AI adoption.
• Establish governance and accountability for AI projects
• Invest in data readiness and operational dashboards to measure impact
With expert guidance from Fujitsu’s technology leaders, this paper addresses central critical topics. Whether you’re a CxO, a marketing strategist, or a decision-maker seeking competitive advantage, this white paper offers actionable insights to accelerate growth and innovation, and scale AI for measurable business value.
Looking for a fast, digestible way to understand AI-driven transformation? This infographic delivers the essentials at a glance. Based on insights from the Fujitsu impact series and our comprehensive white paper, this infographic breaks down the key steps for successful AI implementation for enterprises.
Key capabilities for delivering enterprise AI at scale
Focus on business outcomes: Discover how successful AI strategies start with clearly defined business outcomes, ensuring AI investments deliver measurable value rather than experimental proof points.
Ensure AI governance and trust frameworks: Understand how to establish AI governance models that ensure accountability, data sovereignty, security, and regulatory compliance across enterprise AI initiatives.
Establish data readiness for enterprise AI: Explore the data strategies required to make AI effective, including data quality, integration, and lifecycle management that enable reliable and responsible AI at scale.
Safeguard scalable AI frameworks for long-term impact: Learn how to design and orchestrate scalable AI frameworks that move from pilot to production, enabling repeatable outcomes and long-term business impact.
Build Smarter, Faster, Resilient Manufacturing with Data & AI.
Manufacturers face rising economic and geopolitical pressure, making it harder to align strategic goals with daily operations. The IDC InfoBrief ‘Data & AI: The Essentials for Building Robust Manufacturing Operations’ reveals how leading manufacturers use data and AI to boost efficiency, resilience, and productivity.
Discover the top priorities shaping the next two years, how AI improves KPIs across plant operations, supply chain, and R&D, and where companies are investing to scale impact. Learn how a persona-driven data and AI strategy helps organizations modernize faster and achieve measurable performance gains.
AI adoption is the shift from isolated AI pilots to AI that is embedded in enterprise workflows and delivers measurable business outcomes. This page positions AI adoption as a business transformation challenge, not a “technology roll-out” exercise.
Measurable outcomes remain elusive for many organizations, and points to a common pattern: initiatives stall when teams focus on tools rather than clear business outcomes. The related blog reinforces this by emphasizing business clarity and success criteria as a key differentiator.
It means designing AI initiatives around business KPIs, backing them with governance and data foundations, and operationalizing them so leaders have visibility into performance and impact. The blog specifically calls out dashboards to connect strategy to execution and to decide when to scale, refine, or stop initiatives.
This blog post describes a persistent myth: that the “best” technology guarantees success; instead, stalled initiatives often fail because they aren’t anchored in a clearly articulated business problem and measurable success criteria.
C‑suite sponsorship is an important accelerator for enterprise adoption. Sustained executive sponsorship and coordinated decision-making help organizations move beyond department-level experiments and scale AI successfully.
Data readiness and governance foundations are prerequisites for trustworthy AI and scalability. Successful initiatives rest on trusted data foundations - data that is accurate, governed, and accessible - so AI becomes more predictable, explainable, and scalable.
For Manufacturing and Supply Chain organizations, AI adoption plays a decisive role because operational complexity, siloed data, and volatile conditions make it difficult to achieve speed, resilience, and efficiency at scale. AI initiatives in manufacturing depend on strong data foundations, clear ownership, and operational visibility so AI can be embedded into production, supply chain, and operations workflows to deliver measurable performance improvements rather than isolated pilot results.
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.
