AI transformation
Making AI adoption an organizational practice.
A shared framework for understanding how engineering teams use AI—and where to go next.
Context
AI adoption is as much an organizational challenge as a technical one.
The challenge
Individual tool use does not show whether AI is embedded in a team’s development process.
The approach
- Assess technical maturity alongside the practices that sustain adoption.
- Use self-assessment, supporting evidence, and deliberation to make the result understandable.
A framework for the next decision
The useful output is not a ranking alone. It is a clearer conversation about the next change a team can make. The published account describes two assessment axes and 14 criteria, connecting engineering practice with organizational support.
What this work brings together
Evaluation design, stakeholder alignment, evidence review, and a repeatable operating process.
What changed
The Engineering AI Banzuke established a shared view of adoption across 44 development organizations.
What the evidence tells us
This is the scope of an assessment, not a measured productivity gain. Longer-term outcomes need separate evidence.