Keep the AI management system working by (a) documenting and running a process that proactively finds deficiencies, including non-compliance in AI systems or in their development or deployment, with root causes, corrective actions and revisions to the management system recorded; (b) planning changes to the management system; (c) identifying and documenting internal and external factors, such as infrastructure or deployment context, that may affect the ability to meet its responsibilities; and (d) providing enough resources, such as human effort and compute, to deploy AI systems safely and responsibly across their lifecycle.
This control maps to 1 controls across 1 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.
The graph holds this control, the 1 it maps to, and the evidence behind each claim, over MCP and REST.