Across the lifecycle an AI system should reliably operate in accordance with its intended purpose, being reliable, accurate and reproducible as appropriate. It should not pose unreasonable safety risks and should adopt safety measures proportionate to the magnitude of potential risk. Systems should be monitored and tested so they continue to meet their purpose, identified problems should be addressed through ongoing risk management, and responsibility for ensuring robustness and safety should be clearly and appropriately assigned.
This control maps to 7 controls across 5 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 7 it maps to, and the evidence behind each claim, over MCP and REST.