Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)vsNIST AI Risk Management Framework (AI RMF 1.0)
See exactly how Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls map to NIST AI Risk Management Framework (AI RMF 1.0). Pre-computed mappings, identified gaps, and coverage analysis.
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According to the TheArtOfService Compliance Knowledge Graph:
Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) maps to NIST AI Risk Management Framework (AI RMF 1.0) with 35% coverage across 17 directly mapped controls. Analysis of 48 Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls identifies 31 compliance gaps, primarily concentrated in Algorithm Recommendation.
Source: TheArtOfService Knowledge Graph | 48 controls analysed | 704 frameworks | 306K+ cross-framework mappings
Control Mappings
Showing 20 of 24 mapped controls across 4 domains. Sign up to explore all 306K+ mappings across 704 frameworks.
Algorithm Recommendation(8 mappings)
Deep Synthesis(5 mappings)
Ethics(1 mappings)
Generative AI Measures(6 mappings)
+4 more mappings
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A Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) to NIST AI Risk Management Framework (AI RMF 1.0) crosswalk, built to order
The table above lists candidate mappings. A crosswalk answers the narrower question you are probably here for: which NIST AI Risk Management Framework (AI RMF 1.0) controls your existing Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) work already satisfies, which are real gaps, and the reasoning behind every claim so you can check it. One pair, $299, one time.
This direction has not been through crosswalk review and sign off, so no coverage figure is published for it. Reporting an unreviewed number would be worse than reporting none. It can be built to order at the same price as a pair that is already on the shelf.
If the two frameworks turn out to have too little in common for a crosswalk to help you, we say so and refund it rather than send a number worth nothing.
This direction has not been through crosswalk review and sign off, so no coverage figure is published for it. Reporting an unreviewed number would be worse than reporting none. It can be built to order at the same price as a pair that is already on the shelf.
If the two frameworks turn out to have too little in common for a crosswalk to help you, we say so and refund it rather than send a number worth nothing.
- Every evidenced control, with the reasoning behind it
- Every gap, with what it requires
- Its level of review stated plainly, not a bare number
Why this page shows two different percentages. The 35% in the header counts how many Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls carry at least one candidate mapping in the graph, before any review. The crosswalk percentage counts something stricter: how many NIST AI Risk Management Framework (AI RMF 1.0) controls are actually evidenced, after a pass that argued against each mapping and kept only what survived. They answer different questions and they are not meant to agree.
A crosswalk narrows the work. It does not replace an audit, and your assessor may take a different view on individual controls. Mappings between frameworks are judgements, not text printed in either standard, which is why every claim in the report shows its reasoning. Questions go to support@theartofservice.com.
Related Comparisons
Other Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) comparisons
Other NIST AI Risk Management Framework (AI RMF 1.0) comparisons
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What are the key differences between Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) and NIST AI Risk Management Framework (AI RMF 1.0)?
Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) has 48 controls across its framework, while NIST AI Risk Management Framework (AI RMF 1.0) covers 72 controls. Direct mapping analysis identifies 17 overlapping controls (35% coverage). The frameworks diverge most significantly in Algorithm Recommendation, where 14 Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls have no direct NIST AI Risk Management Framework (AI RMF 1.0) equivalent.
How many controls map between Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) and NIST AI Risk Management Framework (AI RMF 1.0)?
Of 48 total Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls, 17 map directly to NIST AI Risk Management Framework (AI RMF 1.0) controls, representing 35% coverage. The remaining 31 controls represent compliance gaps requiring additional documentation or compensating controls to satisfy both frameworks simultaneously.
What are the compliance gaps when mapping Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) to NIST AI Risk Management Framework (AI RMF 1.0)?
31 Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls have no direct equivalent in NIST AI Risk Management Framework (AI RMF 1.0). The highest concentration of gaps is in Algorithm Recommendation with 14 unmapped controls. These gaps represent areas where additional controls, policies, or documentation must be created to achieve compliance with both frameworks.
Which control domains have the most gaps between Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) and NIST AI Risk Management Framework (AI RMF 1.0)?
The domain with the highest gap count is Algorithm Recommendation (14 gaps). Export the full domain-by-domain gap breakdown via the Professional tier to generate a prioritised remediation roadmap.
Related Resources
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