The Michelin Effect: Why 200 AI Projects Succeed While Others Fail
Researched and written with AI, editorially reviewed. Sources are linked at the end. How we work with AI
AI adoption and AI transformation are not the same. Success requires three things: value-first thinking (not tool-first), visible leadership commitment, and workflow redesign rather than tool deployment. Michelin's 200 scaled projects generating 50M euros annually demonstrate that discipline in ROI validation, post-deployment reviews, and systematic scaling creates sustainable returns—while 88% of leaders at top performers actively model AI use daily.
The Doubling That Changed Nothing
Enterprise-wide AI adoption has doubled in 2026: from 12% in 2025 to 24% in 2026. Among digital pioneers, the rate reaches 38%, while laggards manage only 9%. The numbers sound impressive—until you look deeper.
Multiple high-profile 2025 reports reveal a hard truth: the vast majority of AI pilots stagnate or fail, and most organizations see minimal measurable return on investment. BCG surveyed 300 CMOs worldwide: 96% reported that AI is fundamentally transforming their function, yet only about one-third have actually implemented the systems required to make that happen.
This gap exposes a fundamental misunderstanding: does not automatically equal . Many organizations confuse tool implementation with value creation.
