Apply the updated OECD definition of AI system per the OECD Recommendation on Artificial Intelligence as amended 3 May 2024. The updated definition aligns with the EU AI Act and converging international consensus and defines an AI system as a machine-based system that for explicit or implicit objectives infers from the input it receives how to generate outputs such as predictions content recommendations or decisions that can influence physical or virtual environments. AI systems vary in their levels of autonomy and adaptiveness after deployment. The 2024 Update materially expanded scope to address foundation models + generative AI + agentic AI capabilities. Apply scope considerations covering (a) general-purpose AI models and systems including foundation models and generative AI + with consideration for downstream deployer responsibilities, (b) AI systems lifecycle covering plan and design + collect and process data + build and use model + verify and validate + deploy + operate and monitor, (c) AI actor roles per OECD taxonomy aligned with the 2024 Update including AI Developer + AI Provider + AI Deployer + AI End User + AI Subject + AI Third Party + AI Regulator + with role-specific responsibilities, (d) special considerations for frontier models with potential catastrophic risk profiles, (e) cross-framework interoperability with EU AI Act + NIST AI RMF + ISO/IEC 42001 + UK + US + Japan + Singapore + Canada AI governance frameworks.
This control maps to 40 controls across 17 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 40 it maps to, and the evidence behind each claim, over MCP and REST.