Small Business AI Pros buyer guide
Guide 6: Set acceptance criteria for an AI project
Decide how the business will recognize a useful, bounded result before a demonstration becomes a deployment.
Test the real workflow
Choose representative cases that are approved for testing, including ordinary work, difficult edge cases, incomplete inputs, and situations that should stop or escalate. Define the expected human review and the official destination for an accepted result.
Avoid a single accuracy percentage without a clear test set and consequence model. A useful output may still be unacceptable if it creates too much review, hides uncertainty, exposes information, or fails at an important edge.
Name the acceptance owner
The person who can judge the workflow should approve the result. Technical completion, business acceptance, security approval, and legal approval may be separate decisions. Write which decisions are required for the intended release.
Record failures and changes rather than tuning only toward a polished demonstration. The evidence should help the business decide to accept, revise, narrow, or stop.
Keep rollback practical
Document how to disable access, stop an automation, remove a connection, restore the former process, and preserve required records. Test the stop path before the project becomes business-critical.
Acceptance is not permanent. Set a review trigger for material changes in the workflow, data, product, model, users, or business risk.