Most AI projects fail for organizational reasons, not technical ones: nobody owns the workflow, nobody measured the "before," and nobody planned for what happens when the AI is wrong. Earned Autonomy fixes all three.
Stage 1 — Red: human decides
The AI researches and drafts; a person makes every decision. Use this for any new workflow and for anything touching money, legal exposure, or an upset customer.
Exit criteria: you have a labeled test set of real examples, and you know the AI's accuracy on it.
Stage 2 — Yellow: human approves
The AI acts, but a person reviews before anything reaches a customer. Every output carries a confidence score; low-confidence items go to a separate queue.
Track: accuracy, share of outputs approved without edits, and escalation rate.
Stage 3 — Green: AI runs, people audit
Promote one task type at a time — for example, "hours and directions" emails — once it holds its pass rate for an agreed period. Keep sampling a fixed percentage every month.
The rules that make it work
- Every workflow has a named owner.
- Baseline first. Measure time, cost, and error rate before building.
- Promotion is a decision, not a drift. It's written down, with the data that justified it.
- Demotion is allowed. If accuracy drops, the task goes back to Yellow.