The first useful AI workflow is usually narrow. It handles a recognizable task, shows its evidence and gives a person a clear point to review or intervene.
Start with a bounded decision
Good first use cases have a recognizable input, a useful output and a person who already owns the decision. Classification, extraction and drafting often fit better than open-ended autonomy.
Design the exception path
Confidence thresholds, source context and human approval are product features. They make uncertain output visible and give the workflow somewhere safe to go when automation should stop.
Measure usefulness, not novelty
Create a representative test set and review accuracy, time saved, corrections and failure modes before expanding the workflow.
Working principle
Define the handoff to a person before automating the routine path.