Measuring AI adoption by active users is how organizations confuse movement for progress.
It is an attractive scoreboard because it is easy to count. Licenses assigned. Prompts submitted. Teams onboarded. Dashboards go up and leaders get a number that looks impressive without having to ask whether work improved or judgment got worse.
Generative AI does not behave like a standard software rollout.
Rebecca George shared a story that captures the risk. AI synthesis saved hours on interview analysis, then created weeks of stakeholder cleanup because biased output damaged trust. The tool made one task faster and the system slower. That is the part adoption metrics usually miss.
Change leadership has to track how work actually moves. Where did AI reduce friction. Where did it create review burden. Where did it distort a decision. Where did it make someone quieter in a room that needed their judgment. Employee Resource Groups can help pressure-test these edge cases before production politics makes them expensive.
"Human in the loop" is comfort language when nobody defines the human, the loop, or the authority. The phrase lets governance sound present without proving accountability exists.
AI adoption does not need more theater. It needs a scoreboard that rewards better decisions, not louder usage.
Speed is a weak currency when stakeholder trust is on the line.
Related episode: Rebecca George on AI, Bias, and Change Leadership.
