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Your AI pilots are working. Your AI strategy isn't.
Executive summary
Most enterprises are running AI. Few are scaling it.
The Gartner Growth Agenda Survey reveals a widening “confidence-to-execution gap.” Enterprises report high AI usage — interpreted as pilots, but confidence in AI’s ability to deliver strategic outcomes at scale remains low due to structural blockers.
This complimentary Gartner® report maps the four structural blockers standing between AI pilots and enterprise-wide value, and gives leaders a way to treat AI as a portfolio-wide capability, not a collection of disconnected experiments.
Key takeaways
Why confidence in AI lags adoption, and the four structural blockers driving the gap: unclear strategy, unproven ROI, skills, and platform maturity.
Organizational readiness lags: 26% of executives in our survey point to “organizational readiness” and a “lack of clear AI strategy” as critical roadblocks to moving beyond isolated experiments Scale is blocked by people, skills and data, not model access: “Skills or talent gaps” represent the single largest internal barrier to scaling AI, identified by 37% of organizations.
Confidence is stuck behind ROI proof: Despite high usage, 30% of enterprise growth leaders cite a “lack of tangible results or proven ROI” (e.g., sales conversion rates, depth of wallet increases, customer retention, revenue uplift, etc.) as the primary reason for low confidence in AI success.
Gartner, Closing the AI Execution Gap: It's Not the Model, It's the Machine, David Furlonger, Andy Rowsell-Jones, April 19, 2026.
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