Assess an AI Use Case

Outcome

A go / iterate / stop recommendation with evidence gaps and next actions.

Outputs

• Use-case assessment summary
• Risk and feasibility notes
• Recommended next playbook

Steps

1. Frame the business problem — State the problem in business language without naming a model.
2. Identify users and stakeholders — List who uses, decides, funds and is affected by the solution.
3. Map the current process — Explain how the work is done today and where friction appears.
4. Define the AI role — Clarify what the AI will do and what remains human-owned.
5. Assess data readiness — Identify data sources, access constraints and quality risks.
6. State the value hypothesis — Express expected value and how you will measure it.
7. Capture risks and constraints — Surface the top risks that could block a responsible go decision.
8. Make the recommendation — Choose go, iterate or stop with a clear rationale.