Introduction
A practical checklist to help government organizations assess AI vendors, manage risk, and make more informed procurement decisions. The goal is not governance for its own sake. The goal is to make better decisions, strengthen accountability, and help AI deliver real value in the environments where it will actually be used.
1. What problem is the AI solving?
Start with a clear use case, intended outcomes, and mission fit. A well-defined problem helps keep procurement focused on value.
2. What evidence supports performance claims?
Ask for meaningful evidence, testing, evaluations, and limitations. Understand what was measured and under what conditions.
3. How is data handled?
Understand collection, storage, access, reuse, retention, and whether customer data is used to improve or train models.
4. What oversight and controls exist?
Review monitoring, human intervention, incident handling, change management, and the ability to challenge or override outputs.
5. How will changes, monitoring, and exit be managed?
Plan for updates, reassessment, data return, transition support, portability, and vendor dependency before signing.