How the Organizations Generating Real AI Value Think Differently from Everyone Else
We spent a year in executive conversations with CEOs, CTOs, CFOs, and heads of AI. We entered expecting to diagnose a cost visibility problem. We left with a different conclusion.
Most organizations already know what AI costs them. What they have not built is a systematic way to understand which AI behaviors produce results and how to move those behaviors across the workforce. This report documents what we found.
88% adopted AI in some capacity Stanford HAI, 2026 | 74% struggle to achieve meaningful value BCG, 2024 | 6% generate substantial AI value tied to outcomes McKinsey, 2024 |
The 19-page report covers:
- Five findings from fifty-plus executive conversations
- Why the gap between your best and worst AI users dwarfs any model gap
- What the 6% actually built that the 94% did not
- The four-layer framework for building compounding AI capability
- Specific implications for CEO, CTO, CFO, and Head of AI
Who this is for: Engineering leaders, heads of AI, CTOs, and CFOs at organizations with serious AI deployments.