Why 93% of enterprises use AI but most aren't seeing the ROI they were promised
Exclusive insights from direct conversations with 35 CIOs and CTOs reveal the disconnect between AI hype and implementation reality.
What we found
The expectation gap is real. While 93% of organizations now use AI in some form, only 21.4% report success rates above 80%. High-profile implementations — including Microsoft Copilot, automated bid tools, and headcount reduction initiatives — are delivering disappointing returns. As Ian Cohen, who has led technology at Lloyds, the Financial Times, and Addison Lee, puts it:
There is so much hype, and it is our job to temper that enthusiasm with a healthy dose of reality.
Technology isn't the problem. The barriers to AI value realization are organizational, not technical. Poor data quality, disconnected data systems, and inadequate change management top the list of blockers. Organizations are repeating the pattern that has plagued past technology implementations: seeing only 10-20% of potential benefits because they fail to drive proper adoption and education.
The pace problem is breaking trust. A CIO of a global internet platform shared that proof of concepts that failed nine months ago now work perfectly, making it difficult to maintain credibility with business stakeholders. "Technology has never moved this quickly," they noted. Boards consuming vendor marketing expect transformation; CIOs are managing the nuanced reality on the ground.
People still beat platforms. When forced to choose between hiring 10 data scientists or buying an enterprise AI platform, 64.3% of technology leaders chose the people. As one CIO explained:
We need bright people finding bright ways to use bright technology — not technology operating in isolation.
Why this research is different
Unlike survey-based research where you don't know if respondents have actual budget authority, this report captures authentic experiences from facilitated debates with named CIOs and CTOs who are implementing AI at scale. These are direct conversations with technology leaders responsible for billions in technology spend.
CIOs and CTOs who contributed to this research include:
- Ian Cohen - Former CIO at Lloyds, Financial Times, Addison Lee, Acacium Group
- Nick Capell - CIO, Gately (Law Firm)
- Julie Pierce - CIO, Food Standards Agency
- Eoin O'Connell - Interim CIO, Andwis
- Prasad Desai - GE Healthcare
- Sid Muthevi - NEBOSH
- Sharon Peters - CIO, Boldyn Networks
- James Maunder - CIO, Unite
- Paul Airey - Chief Digital and Information Officer, Anthony Nolan
Plus 26 additional CIOs and CTOs from leading global organizations
What you'll learn
- Why data quality and change management — not technology — are the primary barriers to AI value
- Which high-profile AI use cases are failing to deliver ROI
- The seven critical elements organizations need to be truly AI-ready
- How to manage board expectations when AI capabilities are advancing faster than stakeholder understanding
- Why cloud hosting dominates (71.4%) and what's driving the decision
- What it means when organizations are gambling 50% or more of their AI budgets on unproven technologies
