TheArtOfService
Cross-Framework Mapping

NIST AI Risk Management Framework (AI RMF 1.0)vsEU AI Act

See exactly how NIST AI Risk Management Framework (AI RMF 1.0) controls map to EU AI Act. Pre-computed mappings, identified gaps, and coverage analysis.

82
Controls Mapped
0
Gaps Found
86%
Coverage

A reviewed coverage crosswalk for this pair is available. See which EU AI Act controls you already evidence.

According to the TheArtOfService Compliance Knowledge Graph:

NIST AI Risk Management Framework (AI RMF 1.0) maps to EU AI Act with 86% coverage across 62 directly mapped controls. Analysis of 72 NIST AI Risk Management Framework (AI RMF 1.0) controls identifies 10 compliance gaps, primarily concentrated in MAP - NIST AI RMF 1.0.

Source: TheArtOfService Knowledge Graph | 72 controls analysed | 686 frameworks | 310K+ cross-framework mappings

Control Mappings

Showing 20 of 82 mapped controls across 4 domains. Sign up to explore all 310K+ mappings across 686 frameworks.

GOVERN - NIST AI RMF 1.0(20 mappings)

AIRMF-GV-1.1Legal and regulatory requirements involving AI are understood, managed, and documented2 targets
→EUAI-Art.11Technical documentation
→EUAI-Art.6Classification rules for high-risk AI systems
AIRMF-GV-1.2The characteristics of trustworthy AI are integrated into organizational policies, processes, and procedures2 targets
→EUAI-Art.14Human oversight
→EUAI-Art.17Quality management system
AIRMF-GV-1.3Processes and procedures are in place to determine the needed level of risk management activities based on the organization's risk tolerance
→EUAI-Art.6Classification rules for high-risk AI systems
AIRMF-GV-1.4The risk management process and its outcomes are established through transparent policies, procedures, and other controls based on organizational risk priorities
→EUAI-Art.9Risk management system
AIRMF-GV-1.5Ongoing monitoring and periodic review of the risk management process and its outcomes are planned, organizational roles and responsibilities are clearly defined, including determining the frequency of periodic review
→EUAI-Art.72Post-market monitoring by providers and post-market monitoring plan for high-risk AI systems
AIRMF-GV-1.6Mechanisms are in place to inventory AI systems and are resourced according to organizational risk priorities
→EUAI-Art.49Registration
AIRMF-GV-1.7Processes and procedures are in place for decommissioning and phasing out of AI systems safely and in a manner that does not increase risks or decrease the organization's trustworthiness
→EUAI-Art.20Corrective actions and duty of information
AIRMF-GV-2.1Roles and responsibilities and lines of communication related to mapping, measuring, and managing AI risks are documented and are clear to individuals and teams throughout the organization2 targets
→EUAI-Art.16-22Obligations of providers of high-risk AI systems and authorised representatives (Arts 16 to 22)
→EUAI-Art.17Quality management system
AIRMF-GV-2.2The organization's personnel and partners receive AI risk management training to enable them to perform their duties and responsibilities consistent with related policies, procedures, and agreements
→EUAI-Art.4AI literacy
AIRMF-GV-2.3Executive leadership of the organization takes responsibility for decisions about risks associated with AI system development and deployment
→EUAI-Art.47EU declaration of conformity
AIRMF-GV-3.2Policies and procedures are in place to define and differentiate roles and responsibilities for human-AI configurations and oversight of AI systems
→EUAI-Art.14Human oversight
AIRMF-GV-4.1Organizational policies and practices are in place to foster a critical thinking and safety-first mindset in the design, development, deployment, and uses of AI systems to minimize negative impacts2 targets
→EUAI-Art.4AI literacy
→EUAI-Art.87Reporting of infringements and protection of reporting persons
AIRMF-GV-4.2Organizational teams document the risks and potential impacts of the AI technology they design, develop, deploy, evaluate and use, and communicate about the impacts more broadly
→EUAI-Art.27Fundamental rights impact assessment for high-risk AI systems
AIRMF-GV-4.3Organizational practices are in place to enable AI testing, identification of incidents, and information sharing
→EUAI-Art.73Reporting of serious incidents
AIRMF-GV-5.1Organizational policies and practices are in place to collect, consider, prioritize, and integrate feedback from those external to the team that developed or deployed the AI system regarding the potential individual and societal impacts related to AI risks
→EUAI-Art.72Post-market monitoring by providers and post-market monitoring plan for high-risk AI systems
AIRMF-GV-5.2Mechanisms are established to enable AI actors to regularly incorporate adjudicated feedback from relevant AI actors into system design and implementation
→EUAI-Art.20Corrective actions and duty of information

+62 more mappings

Plus AI-powered gap analysis, compliance advisory, PDF exports, and cross-mapping for all 686 frameworks.

Create Free Account →

Free forever, no credit card required

Coverage crosswalk

The NIST AI Risk Management Framework (AI RMF 1.0) to EU AI Act crosswalk

The table above lists candidate mappings. A crosswalk answers the narrower question you are probably here for: which EU AI Act controls your existing NIST AI Risk Management Framework (AI RMF 1.0) work already satisfies, which are real gaps, and the reasoning behind every claim so you can check it. One pair, $299, one time.

Coverage does not run both ways. NIST AI Risk Management Framework (AI RMF 1.0) into EU AI Act lands at 25.6%, while EU AI Act into NIST AI Risk Management Framework (AI RMF 1.0) lands at 66.7%, on the same two control sets. That is not a rounding difference. It is the whole reason these are two separate reports: one asks what your NIST AI Risk Management Framework (AI RMF 1.0) evidence buys you for EU AI Act, the other asks the reverse.

NIST AI Risk Management Framework (AI RMF 1.0) into EU AI Act
25.6%

11 of 43 EU AI Act controls are evidenced by work you have already done for NIST AI Risk Management Framework (AI RMF 1.0). 32 are genuine gaps.

55.6%EU AI Act - High-Risk Classification and Requirements
16.7%EU AI Act - High-Risk Operator Obligations
50%EU AI Act - Post-Market Monitoring, Market Surveillance and Rights
50%EU AI Act - General Provisions and Prohibited Practices
Machine verified. Claude Code on the Max plan, judged in context, signed off 2026-08-20. 41 candidate mappings were examined and 9 were removed by a pass whose job was to argue against them.Mappings were judged by Claude Code rather than read line by line by a practitioner. Every claim shows its reasoning so you can check it. Ask and a practitioner will review this pair.

A sample of what the report says

Evidenced: EUAI-Art.10 Data and data governance

Documented data collection and selection with representativeness and suitability is the data governance limb.

Grounded in AIRMF-MP-2.3 Scientific integrity and TEVV considerations are identified and documented, including those related to experimental design, data collection and selection, system trustworthiness, and construct validation. Confidence high, survived the refutation pass.

Gap: EUAI-Art.11 Technical documentation

Technical documentation for a high-risk AI system shall be drawn up before the system is placed on the market or put into service and kept up to date. It shall be drawn up in such a way as to demonstrate that the high-risk AI system...

Every one of the 11 evidenced controls and 32 gaps in the report carries this much reasoning, so you can check the claim rather than take it on trust.

EU AI Act into NIST AI Risk Management Framework (AI RMF 1.0)
66.7%

48 of 72 NIST AI Risk Management Framework (AI RMF 1.0) controls are evidenced by work you have already done for EU AI Act. 24 are genuine gaps.

72.7%MEASURE - NIST AI RMF 1.0
72.2%MAP - NIST AI RMF 1.0
57.9%GOVERN - NIST AI RMF 1.0
61.5%MANAGE - NIST AI RMF 1.0
Machine verified. Claude Code on the Max plan, judged in context, signed off 2026-08-20. 72 candidate mappings were examined and 10 were removed by a pass whose job was to argue against them.Mappings were judged by Claude Code rather than read line by line by a practitioner. Every claim shows its reasoning so you can check it. Ask and a practitioner will review this pair.

A sample of what the report says

Evidenced: AIRMF-GV-1.1 Legal and regulatory requirements involving AI are understood, managed, and documented

The recorded high-risk determination per system is documented understanding of which legal regime binds it.

Grounded in EUAI-Art.6 Classification rules for high-risk AI systems. Confidence high, survived the refutation pass.

Gap: AIRMF-GV-1.5 Ongoing monitoring and periodic review of the risk management process and its outcomes...

Ongoing monitoring and periodic review of the risk management process and its outcomes are planned, organizational roles and responsibilities are clearly defined, including determining the frequency of periodic review. Monitoring and...

Every one of the 48 evidenced controls and 24 gaps in the report carries this much reasoning, so you can check the claim rather than take it on trust.

NIST AI Risk Management Framework (AI RMF 1.0) to EU AI Act
$299
per framework pair, one time
  • 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 86% in the header counts how many NIST AI Risk Management Framework (AI RMF 1.0) controls carry at least one candidate mapping in the graph, before any review. The crosswalk percentage counts something stricter: how many EU AI Act 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 NIST AI Risk Management Framework (AI RMF 1.0) comparisons

NIST AI Risk Management Framework (AI RMF 1.0) vs ISO/IEC 42001:202352 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs Administrative Measures for the Security Assessment of Generative AI Services (2023) and Algorithmic Recommendation Management Provisions (2022)10 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs ASEAN Guide on AI Governance and Ethics9 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs Canada Artificial Intelligence and Data Act (AIDA)6 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs Colorado Artificial Intelligence Act (proposed SB 24-205)4 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs Australia AI Ethics Framework2 mappingsNIST AI Risk Management Framework (AI RMF 1.0) vs ISO/IEC 23894:20231 mappings

Other EU AI Act comparisons

ISO/IEC 42001:2023 vs EU AI Act42 mappingsNIST SP 800-53 Rev 5 vs EU AI Act39 mappingsSOC 2 vs EU AI Act33 mappingsISO 27001:2022 vs EU AI Act33 mappingsCloud Security Alliance Cloud Controls Matrix (CCM) v4.0.1 vs EU AI Act29 mappingsGDPR vs EU AI Act21 mappingsNIS2 Directive vs EU AI Act12 mappingsDORA vs EU AI Act11 mappings

Stop Paying Consultants to Read Spreadsheets

AI-powered compliance intelligence across 686 frameworks, at a fraction of consulting costs.

$0/forever

Free

  • ✓ 686 framework browser
  • ✓ Cross-framework mappings (310K+)
  • ✓ 824 compliance assessments
  • ✓ 3 AI queries & searches per day
Get Started Free
Recommended
$149/month

Professional

  • ✓ Unlimited AI Compliance Advisory
  • ✓ Unlimited full-text search
  • ✓ Framework self-assessment
  • ✓ PDF, Excel & CSV exports
Start 7-Day Free Trial →

Popular framework comparisons

NIST CSF vs NIST 800-53ISO 27001 vs NIST CSFCMMC vs NIST 800-53FedRAMP vs NIST 800-53NIST CSF vs SOC 2HIPAA vs NIST 800-53ISO 27001 vs SOC 2ISO 27001 vs ISO 27701

What are the key differences between NIST AI Risk Management Framework (AI RMF 1.0) and EU AI Act?

NIST AI Risk Management Framework (AI RMF 1.0) has 72 controls across its framework, while EU AI Act covers 43 controls. Direct mapping analysis identifies 62 overlapping controls (86% coverage). The frameworks diverge most significantly in MAP - NIST AI RMF 1.0, where 4 NIST AI Risk Management Framework (AI RMF 1.0) controls have no direct EU AI Act equivalent.

How many controls map between NIST AI Risk Management Framework (AI RMF 1.0) and EU AI Act?

Of 72 total NIST AI Risk Management Framework (AI RMF 1.0) controls, 62 map directly to EU AI Act controls, representing 86% coverage. The remaining 10 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 EU AI Act?

10 NIST AI Risk Management Framework (AI RMF 1.0) controls have no direct equivalent in EU AI Act. The highest concentration of gaps is in MAP - NIST AI RMF 1.0 with 4 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 EU AI Act?

The domain with the highest gap count is MAP - NIST AI RMF 1.0 (4 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

This platform provides educational compliance tools, not legal, regulatory, or professional compliance advice. Cross-framework mappings are AI-assisted interpretations and do not reproduce or replace official standards. Framework names and trademarks belong to their respective owners. Consult qualified professionals for your specific compliance requirements. See our Terms of Service.