Fig. 01 · Answer
How do you choose AI use cases?
Leadership teams turning AI ideas into a ranked backlog.
The short answer
Choose AI use cases by scoring business value, feasibility, risk, adoption effort, data readiness, review needs, and measurement clarity. The best use cases are not the most novel; they are the workflows where AI can improve a visible operating outcome safely.
What informs this answer
Selected results from related operator-led engagements, by industry and scale:
- AI Transformation Blueprint service published
- AI Opportunity Score shipped
- AI Project Use-Case Scoring Model published
What to ask next
What scoring dimensions matter most?
Value, feasibility, risk, adoption effort, data readiness, review design, and measurement clarity matter more than tool novelty.
Who should choose the use cases?
A business owner, function leader, IT or data owner, and the users affected by the workflow should all be represented.
What should be deferred?
Defer use cases with sensitive decisions, poor source material, no owner, unclear value, or weak human review.
Answered by Justin Leader · Human Renaissance · Updated 2026-04-30 · Research methodology
