Before accepting an AI vendor claim
Can the AI vendor prove it?
Turn AI vendor claims into common demonstrations, evidence requests, acceptance conditions, monitoring duties, and exit questions.
Time
About 5 minutes
You leave with
AI vendor evidence agenda
Privacy
No account. No submission.
Use operational facts, not confidential records.
Do not enter confidential procurement, student, personnel, resident, vendor, security, or incident information. Answers are saved only in this browser and are not sent to JS Technology Solutions.
Source record
Primary sources behind this pressure test
Last verified August 26, 2026
- Artificial Intelligence Risk Management Framework
National Institute of Standards and Technology. AI RMF 1.0 with current NIST resource updates. Supports: Voluntary risk management across Govern, Map, Measure, and Manage, including trustworthiness considerations throughout the AI life cycle.
- Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile
National Institute of Standards and Technology. July 26, 2024. Supports: Generative AI risks and suggested actions involving content provenance, information integrity, privacy, security, evaluation, and human oversight.
- M-25-22, Driving Efficient Acquisition of Artificial Intelligence in Government
Office of Management and Budget. April 3, 2025. Supports: Cross-functional acquisition teams, competition, testing, performance monitoring, pricing transparency, data rights, portability, privacy, and protection against vendor lock-in.
- Artificial Intelligence Acquisitions: Agencies Should Collect and Apply Lessons Learned to Improve Future Procurements
U.S. Government Accountability Office. April 13, 2026. Supports: Current acquisition challenges, contract considerations, performance oversight, and systematic collection of lessons learned.
These sources provide useful disciplines and risk frames. They do not make every cited rule applicable to every state, local, or K-12 organization.