TheArtOfService
Cross-Framework Mapping

NIST AI Risk Management Framework (AI RMF 1.0)vsAdministrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)

See exactly how NIST AI Risk Management Framework (AI RMF 1.0) controls map to Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022). Pre-computed mappings, identified gaps, and coverage analysis.

25
Controls Mapped
27
Gaps Found
21%
Coverage

According to the TheArtOfService Compliance Knowledge Graph:

NIST AI Risk Management Framework (AI RMF 1.0) maps to Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) with 21% coverage across 11 directly mapped controls. Analysis of 52 NIST AI Risk Management Framework (AI RMF 1.0) controls identifies 41 compliance gaps — primarily concentrated in AI RMF Functions.

Source: TheArtOfService Knowledge Graph | 52 controls analysed | 718 frameworks | 332K+ cross-framework mappings

Control Mappings

Showing 20 of 25 mapped controls across 5 domains. Sign up to explore all 332K+ mappings across 718 frameworks.

Govern(9 mappings)

AIRMF-GV-1.1Legal and regulatory requirements involving AI are understood, managed, and documented3 targets
→CN-ALG-A7Algorithm Security Management System
→CN-ETH-REVScience and Technology Ethics Review
→CN-GAI-A9Provider Responsibility for Outputs
AIRMF-GV-1.2Trustworthy AI characteristics are integrated into organisational policies, processes, and procedures2 targets
→CN-ALG-A16Algorithm Transparency Disclosure to Users
→CN-GAI-A19Regulatory Inspection Cooperation
AIRMF-GV-4.1Organisational culture and incentives prioritise AI risk management4 targets
→CN-ALG-A24Algorithm Filing
→CN-ALG-A27Algorithm Security Assessment
→CN-DS-A19Deep Synthesis Filing
→CN-GAI-A17Security Assessment and Algorithm Filing

AI RMF Functions(1 mappings)

AIRMF-MEA-03AI Transparency and Explainability
→CN-ALG-A28Audit Cooperation and Log Retention

Manage(3 mappings)

AIRMF-MN-1.1AI risks are prioritised and resources are allocated to manage them
→CN-ALG-A7Algorithm Security Management System
AIRMF-MN-2.1Mechanisms for tracking identified risks over time are in place
→CN-ALG-A8Periodic Algorithm Review (Anti-Addiction)
AIRMF-MN-4.1AI risk management documentation and processes are improved continuously
→CN-GAI-A14Illegal Content Disposal and Reporting

Map(5 mappings)

AIRMF-MP-1.1Context of AI system use is established and understood2 targets
→CN-DS-A20Security Assessment Before New Functions
→CN-GAI-A4Content Compliance and Prohibited Content
AIRMF-MP-2.1Categorisation of AI systems is performed3 targets
→CN-DS-A14Training Data Security and Biometric Consent
→CN-GAI-A7Training Data Lawfulness
→CN-GAI-A8Data Annotation Rules

Measure(2 mappings)

AIRMF-MS-1.1Appropriate methods and metrics for measuring AI risk are identified and applied2 targets
→CN-ALG-A27Algorithm Security Assessment
→CN-DS-A15Security Assessment of Editing Functions

+5 more mappings

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Related Comparisons

Other NIST AI Risk Management Framework (AI RMF 1.0) comparisons

NIST AI Risk Management Framework (AI RMF 1.0) vs Canada Artificial Intelligence and Data Act (AIDA)20 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs ASEAN Guide on AI Governance and Ethics16 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs ISO/IEC 23894:202314 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs Federal Decree-Law No. 45 of 2021 on the Protection of Personal Data (UAE PDPL)13 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs OECD AI Principles12 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs NIST Privacy Framework12 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs Azure Security Benchmark12 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs FTC GLBA Safeguards Rule (16 CFR Part 314)11 mappings

Other Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) comparisons

OECD Recommendation on Artificial Intelligence (2024 Update) vs Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)11 mappingsGDPR vs Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)3 mappingsISO 27701:2019 vs Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)1 mappingsNIST SP 800-53 Rev 5 vs Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)1 mappings

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What are the key differences between NIST AI Risk Management Framework (AI RMF 1.0) and Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)?

NIST AI Risk Management Framework (AI RMF 1.0) has 52 controls across its framework, while Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) covers 48 controls. Direct mapping analysis identifies 11 overlapping controls (21% coverage). The frameworks diverge most significantly in AI RMF Functions, where 30 NIST AI Risk Management Framework (AI RMF 1.0) controls have no direct Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) equivalent.

How many controls map between NIST AI Risk Management Framework (AI RMF 1.0) and Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)?

Of 52 total NIST AI Risk Management Framework (AI RMF 1.0) controls, 11 map directly to Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022) controls — representing 21% coverage. The remaining 41 controls represent compliance gaps requiring additional documentation or compensating controls to satisfy both frameworks simultaneously.

What are the compliance gaps when mapping NIST AI Risk Management Framework (AI RMF 1.0) to Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)?

41 NIST AI Risk Management Framework (AI RMF 1.0) controls have no direct equivalent in Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022). The highest concentration of gaps is in AI RMF Functions with 30 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 NIST AI Risk Management Framework (AI RMF 1.0) and Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)?

The domain with the highest gap count is AI RMF Functions (30 gaps). Export the full domain-by-domain gap breakdown via the Professional tier to generate a prioritised remediation roadmap.

Related Resources

How to Map Controls Across Frameworks|Multi-Framework Compliance Guide|Compliance Glossary

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