Framework readiness

From NIST AI RMF to an Evidence-Backed Assessment

GOVERN, MAP, MEASURE, and MANAGE become useful when connected to systems, decisions, records, and accountable owners.

Use the framework as a process, not a badge

The NIST AI RMF is voluntary guidance, not a NIST certification program. Its value comes from applying the functions and trustworthiness characteristics to a defined context and preserving evidence of decisions and control evaluation.

GOVERN and MAP

Establish accountable roles, inventory, classification, approval, exceptions, suppliers, incidents, change, and evidence. Then connect the AI system to its intended and foreseeable use, actors, affected groups, data provenance, architecture, third parties, human roles, dependencies, and plausible impacts.

MEASURE in context

Measures should reflect the decision, population, operating conditions, threat model, and consequence. Preserve methods, test data, results, thresholds, limitations, exceptions, independent review, and monitoring indicators.

  • Valid and reliable behavior for intended use
  • Safety, security, resilience, privacy, transparency, and harmful-impact risk as applicable
  • Performance under degraded, adversarial, unusual, and changing conditions

MANAGE into accountable action

Record the risk, evidence, likelihood and impact in context, controls, treatment, owner, timeline, dependencies, residual risk, and decision authority. Define monitoring, material-change triggers, incident response, and when a system must be restricted, reassessed, or retired.

Primary reference

Guidance should be checked for the version applicable to the decision date.

NIST AI Risk Management Framework
Explore NIST AI RMF Readiness

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