Measure the Human Work Behind an AI Workflow

An AI workflow can finish tasks and still create more work for the people supporting it. A useful pilot should track not only whether the task succeeds, but also how much human review, correction, and recovery it takes.

Try a human-effort check on one bounded workflow:

• Note when a person must review, correct, or restart a task.
• Record who handles those cases and what the safe next step is.
• Revisit whether the workflow is reducing support effort without shifting risk or upkeep onto someone else.

This makes the real cost of delivery easier to see—and gives the team a fair reason to keep, repair, or retire the automation. Who owns that review once the pilot ends?