Cross-Framework Mapping

Japan AI GuidelinesvsNIST AI Risk Management Framework (AI RMF 1.0)

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

23
Controls Mapped
20
Gaps Found
23%
Coverage

According to the TheArtOfService Compliance Knowledge Graph:

Japan AI Guidelines maps to NIST AI Risk Management Framework (AI RMF 1.0) with 23% coverage across 10 directly mapped controls. Analysis of 43 Japan AI Guidelines controls identifies 33 compliance gaps — primarily concentrated in Principle.

Source: TheArtOfService Knowledge Graph | 43 controls analysed | 716 frameworks | 430K+ cross-framework mappings

Control Mappings

Showing 20 of 23 mapped controls across 4 domains. Sign up to explore all 430K+ mappings across 716 frameworks.

Japan AI Guidelines: AI Risk Management(9 mappings)

JP-AI-01AI risk identification and assessment3 targets
AIRMF-MAP-02AI Risk Identification
AIRMF-MAP-03AI Impact Assessment
NIST-AI600-MAP-2Stakeholder Impact Assessment
JP-AI-03Bias detection and mitigation2 targets
AIRMF-GOV-01AI Risk Management Policies
AIRMF-MAN-01AI Risk Treatment
JP-AI-04AI model validation and testing2 targets
AIRMF-GOV-01AI Risk Management Policies
AIRMF-MAN-01AI Risk Treatment
JP-AI-05Ongoing AI risk monitoring2 targets
AIRMF-GOV-01AI Risk Management Policies
AIRMF-MAN-01AI Risk Treatment

Japan AI Guidelines: AI Transparency & Explainability(9 mappings)

JP-AI-06AI system documentation requirements3 targets
AIRMF-GOV-01AI Risk Management Policies
AIRMF-GOV-02AI Risk Culture
AIRMF-MEA-03AI Transparency and Explainability
JP-AI-07Algorithmic transparency measures3 targets
AIRMF-GOV-01AI Risk Management Policies
AIRMF-GOV-02AI Risk Culture
AIRMF-MEA-03AI Transparency and Explainability
JP-AI-10Record-keeping for AI decisions3 targets
AIRMF-GOV-01AI Risk Management Policies
AIRMF-GOV-02AI Risk Culture
AIRMF-MEA-03AI Transparency and Explainability

Japan AI Guidelines: AI Data Governance(2 mappings)

JP-AI-14Privacy protection in AI training data2 targets
NIST-AI600-GOV-1Legal and Regulatory Compliance
NIST-AI600-MAP-1GAI Risk Identification

+3 more mappings

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

Japan AI Guidelines has 43 controls across its framework, while NIST AI Risk Management Framework (AI RMF 1.0) covers 52 controls. Direct mapping analysis identifies 10 overlapping controls (23% coverage). The frameworks diverge most significantly in Principle, where 10 Japan AI Guidelines controls have no direct NIST AI Risk Management Framework (AI RMF 1.0) equivalent.

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

Of 43 total Japan AI Guidelines controls, 10 map directly to NIST AI Risk Management Framework (AI RMF 1.0) controls — representing 23% coverage. The remaining 33 controls represent compliance gaps requiring additional documentation or compensating controls to satisfy both frameworks simultaneously.

What are the compliance gaps when mapping Japan AI Guidelines to NIST AI Risk Management Framework (AI RMF 1.0)?

33 Japan AI Guidelines controls have no direct equivalent in NIST AI Risk Management Framework (AI RMF 1.0). The highest concentration of gaps is in Principle with 10 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 Japan AI Guidelines and NIST AI Risk Management Framework (AI RMF 1.0)?

The domain with the highest gap count is Principle (10 gaps). Export the full domain-by-domain gap breakdown via the Professional tier to generate a prioritised remediation roadmap.

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.