NIST AI RMF and agent authority

Use task and action decisions as evidence for mapped risks; assign risk acceptance to human governance

01 / Source and scope

Who acts, and what changes?

Principal and authority origin

Organization operating AI systems. Voluntary NIST AI RMF governance process.

Consequential action

Map, measure and manage risks from agent actions.

02 / Action-time control

Make the requested effect testable.

The RMF is guidance, not a product certification or blanket authorization rule. Use task and action decisions as evidence for mapped risks; assign risk acceptance to human governance.

OriginVoluntary NIST AI RMF governance process
RequestMap, measure and manage risks from agent actions
DecisionEvaluate and enforce before effect

03 / Evidence and responsibility

Permission, execution, and outcome are separate.

Risk register, control design, test results, exceptions and monitored outcomes.

ProofGrid can contribute action-level control evidence. The organization still performs the RMF governance, impact assessment and monitoring.

Primary source

Check the governing material.

Architecture discussion

Map one consequential action from origin to observed outcome.

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