Measuring AI Adoption Across People & Orgs (Maturity Model)
summary
Builds and ships an open-sourced maturity model that uses Google Forms surveys, a six‑part scoring system, simple dashboards and a small stack (Superbase + Code Rabbit AI) to turn answers into person, team and org scores. Runs the survey every 3–6 months, measures ~150 people and finds most orgs stuck at adoption not impact (150 people measured). Claims token counts are misleading and identifies AI champions and concrete actions that change assignments and training (tokens != adoption) and tech used (Superbase + Code Rabbit AI + Google Forms).
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chapters (13)
- 0:00Introduction
- 1:05Token usage isn’t reliable
- 2:28How we started
- 3:53Key AI adoption insights
- 6:44People over tools
- 7:26AI maturity model
- 8:29Model components
- 10:14Organizational insights
- 11:38Actionable insights
- 13:03Survey format & scoring
- 13:48AI adoption strategies
- 14:50Adoption observations
- 16:38Summary & Q&A
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