MN-4.2 Measurable activities for continual improvements are integrated into AI system updates and include regular…
Measurable activities for continual improvements are integrated into AI system updates and include regular engagement with interested parties, including relevant AI actors. Improvement activities are measurable and attached to the update cycle, and interested parties are engaged as part of that cycle rather than consulted separately.
Source: NIST AI RMF 1.0, MN-4.2. The statement above is our statement of the clause, read from the published text and cited so you can check it against the official text, not the instrument verbatim. Open NIST AI RMF 1.0 in the compliance library.
These are the artefacts auditors commonly ask for on this requirement, our guidance rather than text from the standard. Your assessor decides what is sufficient in your context, and asks for samples across the period when a report covers one.
system holds itEvidence a system already holds
none for this control
periodic reviewEvidence produced at each review
- Records of engagement with interested parties within the update cycle · Document repository
- Root cause analyses for degradation, drift, near misses and failures · Document repository
- Evidence an improvement activity changed a subsequent release · Source control / CI pipeline
governing documentDocuments that govern the control
- The improvement activities integrated into the system update process, with their measures · Document repository
First move
Common gaps auditors find
- Improvement recorded as a backlog with no measure of effect
- Engagement conducted annually and disconnected from releases
- Root cause analysis performed for outages only, not for behavioural degradation
Do this for your whole sheet
Paste the rows you run your controls from and get this mapping for every control at once, with the periodic-review ones flagged and a first move per row. No account for the first run.
Build my evidence sheetMN-4.1 Post-deployment AI system monitoring plans are implemented, including mechanisms for capturing and evaluating… · MN-4.3 Incidents and errors are communicated to relevant AI actors including affected communities, and processes for…