Ask what the solution will actually do.
A useful proposal identifies the business output, available sources, system operations and decisions people retain. Ask how an implementation uses current tools and what changes staff must adopt. Request evidence that concerns a comparable task rather than a generic AI demonstration.
Agree evaluation before the pilot.
Discuss representative inputs, difficult cases and the definition of completion. Ask how output quality, review effort, response time and operating cost will be assessed. Clarify the route for unavailable sources or failed operations.
| Question | Useful evidence |
|---|---|
| What is delivered? | A scoped output and defined system connections |
| How is it evaluated? | Representative acceptance criteria and pilot findings |
| Who owns operation? | Named roles, instructions and maintenance scope |
| What has been built before? | Relevant project scope with attributable results |
Understand ownership after delivery.
Name the business owner and establish operating instructions, source maintenance and the feedback route. Clarify handover, code and data responsibilities, support scope and ongoing changes in the engagement terms. These details make the implementation usable after the demonstration.
A practical next step
Ask a potential partner to show a scoped output, relevant delivered work, agreed evaluation and a usable handover. Those four commitments give your team a concrete basis for comparing proposals.
Explore the related work