Contingency processes are in place to handle failures or incidents in third-party data or AI systems deemed to be high-risk. For third-party components assessed as high risk there is a worked contingency, a fallback, a redundancy or a defined manual path, and it has been tested.
NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-GV-6.2 is one control. If you already hold one of the frameworks below, a reviewed crosswalk already says how much of NIST AI Risk Management Framework (AI RMF 1.0) your existing evidence covers. Hold EU AI Act and 48 of 72 NIST AI Risk Management Framework (AI RMF 1.0) controls already carry evidence.
Each report names every control your existing framework evidences, every one it does not, the reasoning behind each claim, and the claims that were argued against and rejected. 10 were rejected on the EU AI Act pair alone.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.