NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-MN-4.1: Post-deployment AI system monitoring plans are implemented, including mechanisms for capturing and evaluating input from users and other relevant AI actors, appeal and override, decommissioning, incident response, recovery, and change management
Post-deployment AI system monitoring plans are implemented, including mechanisms for capturing and evaluating input from users and other relevant AI actors, appeal and override, decommissioning, incident response, recovery, and change management. A single implemented plan covers the post-deployment lifecycle end to end, and each named element, including appeal and override, is actually operating.
Maintained by Gerard Blokdyk·Verified against the published standard ·Control text last updated
What else in your programme already covers this
This control maps to 5 controls across 4 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
You are reading one control. How much of NIST AI Risk Management Framework (AI RMF 1.0) have you already done?
NIST AI Risk Management Framework (AI RMF 1.0) AIRMF-MN-4.1 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.