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Japan AI Guidelines
Japan
vAI Guidelines for Business Ver1.2 (31 March 2026), with the Article 13 Guideline (19 December 2025) and the AI Promotion Act (Act No. 53 of 2025)
8 domains
87 controls
Japan's AI Guidelines for Business Ver1.2 (MIC and METI, March 2026): the non-binding, goal-based guidelines every AI developer, provider and business user in Japan is pointed to, with ten Common Guiding Principles, the Hiroshima AI Process principles, agile AI governance and role-specific matters, together with the Article 13 guideline decided under the AI Promotion Act of 2025 and the Act's one business duty. Read against the official Japanese texts.
Verified
Japan AI Guidelines is a compliance framework from Japan with 8 domains and 87 controls that map to 114 other frameworks. The largest domains are Part 2 C: Common Guiding Principles – Japan AI Guidelines (31 controls), Part 2 D: Hiroshima Process International Guiding Principles for All AI Actors – Japan AI Guidelines (13 controls), Part 3: Matters related to AI developers – Japan AI Guidelines (12 controls). Every control below carries what it requires and what an assessor expects to see.
Framework summaries on this platform are interpretations grounded in the published source, for educational and compliance planning purposes. They do not reproduce or replace the official standards. Refer to the authoritative source for the definitive text. Framework names and trademarks belong to their respective organisations.
Framework Domains (8)
AI Promotion Act (Act No. 53 of 2025) – Japan AI Guidelines
1 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::ACT-7 | Act Art. 7 Responsibilities of utilization business operators |
Article 13 Guideline: matters for R&D institutes and utilization business operators – Japan AI Guidelines
5 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::GL13-2.1 | Article 13 Guideline 2(1) Overall appropriateness through AI governance |
| japan-ai-guidelines::GL13-2.2 | Article 13 Guideline 2(2) Transparency to build trust with stakeholders |
| japan-ai-guidelines::GL13-2.3 | Article 13 Guideline 2(3) Sufficient safety |
| japan-ai-guidelines::GL13-2.4 | Article 13 Guideline 2(4) Safe environment through business continuity |
| japan-ai-guidelines::GL13-2.5 | Article 13 Guideline 2(5) Consideration for stakeholders given the importance of data |
Part 2 C: Common Guiding Principles – Japan AI Guidelines
31 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::C1.1 | 1)(1) Human dignity and autonomy of individuals |
| japan-ai-guidelines::C1.2 | 1)(2) Paying attention to manipulation by AI of decision-making and emotions |
| japan-ai-guidelines::C1.3 | 1)(3) Countermeasures against disinformation |
| japan-ai-guidelines::C1.4 | 1)(4) Ensuring diversity and inclusion |
| japan-ai-guidelines::C1.5 | 1)(5) Providing user support |
| japan-ai-guidelines::C1.6 | 1)(6) Ensuring sustainability |
| japan-ai-guidelines::C10.1 | 10)(1) Promoting open innovation and the like |
| japan-ai-guidelines::C10.2 | 10)(2) Attention to interconnectivity and interoperability |
| japan-ai-guidelines::C10.3 | 10)(3) Appropriate information provision |
| japan-ai-guidelines::C2.1 | 2)(1) Consideration for human life, body, property, mind and the environment |
| japan-ai-guidelines::C2.2 | 2)(2) Proper use (of AI) |
| japan-ai-guidelines::C2.3 | 2)(3) Proper training |
| japan-ai-guidelines::C3.1 | 3)(1) Consideration for bias in the technologies forming AI models |
| japan-ai-guidelines::C3.2 | 3)(2) Intervention of human judgment |
| japan-ai-guidelines::C4.1 | 4)(1) Protection of privacy across AI systems and services in general |
| japan-ai-guidelines::C5.1 | 5)(1) Security measures affecting AI systems and services |
| japan-ai-guidelines::C5.2 | 5)(2) Attention to the latest trends |
| japan-ai-guidelines::C6.1 | 6)(1) Ensuring verifiability |
| japan-ai-guidelines::C6.2 | 6)(2) Providing relevant stakeholders with information |
| japan-ai-guidelines::C6.3 | 6)(3) Reasonable and sincere response |
| japan-ai-guidelines::C6.4 | 6)(4) Improving explainability and interpretability for relevant stakeholders |
| japan-ai-guidelines::C7.1 | 7)(1) Improving traceability |
| japan-ai-guidelines::C7.2 | 7)(2) Explanation of the response to the Common Guiding Principles |
| japan-ai-guidelines::C7.3 | 7)(3) Designation of responsible persons |
| japan-ai-guidelines::C7.4 | 7)(4) Allocation of responsibility among the parties |
| japan-ai-guidelines::C7.5 | 7)(5) Specific actions for stakeholders |
| japan-ai-guidelines::C7.6 | 7)(6) Documentation |
| japan-ai-guidelines::C8.1 | 8)(1) Ensuring AI literacy |
| japan-ai-guidelines::C8.2 | 8)(2) Education and reskilling |
| japan-ai-guidelines::C8.3 | 8)(3) Follow-up for stakeholders |
| japan-ai-guidelines::C9 | 9) Ensuring fair competition |
Part 2 D: Hiroshima Process International Guiding Principles for All AI Actors – Japan AI Guidelines
13 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::HP.I | D-I. Risk identification, evaluation and mitigation across the lifecycle |
| japan-ai-guidelines::HP.II | D-II. Post-deployment vulnerabilities, incidents and misuse |
| japan-ai-guidelines::HP.III | D-III. Public reporting of capabilities, limitations and appropriate use |
| japan-ai-guidelines::HP.IV | D-IV. Responsible information sharing and incident reporting |
| japan-ai-guidelines::HP.IX | D-IX. Advanced AI for the world's greatest challenges |
| japan-ai-guidelines::HP.RF | HAIP Reporting Framework participation (developers of advanced AI systems) |
| japan-ai-guidelines::HP.V | D-V. AI governance and risk management policies, disclosed |
| japan-ai-guidelines::HP.VI | D-VI. Robust security controls across the lifecycle |
| japan-ai-guidelines::HP.VII | D-VII. Content authentication and provenance |
| japan-ai-guidelines::HP.VIII | D-VIII. Research and investment in risk mitigation |
| japan-ai-guidelines::HP.X | D-X. International technical standards |
| japan-ai-guidelines::HP.XI | D-XI. Data input measures and protection of personal data and intellectual property |
| japan-ai-guidelines::HP.XII | D-XII. Promote and contribute to trustworthy and responsible use of advanced AI |
Part 2 E: Building AI governance – Japan AI Guidelines
7 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::E.1 | E(1) Environment and risk analysis |
| japan-ai-guidelines::E.2 | E(2) Deciding whether to proceed and setting AI governance goals |
| japan-ai-guidelines::E.3 | E(3) Designing and operating the AI management system |
| japan-ai-guidelines::E.4 | E(4) Monitoring, evaluation and continuous improvement |
| japan-ai-guidelines::E.5 | E(5) Re-analysis after changes in the external environment |
| japan-ai-guidelines::E.LEAD | E management leadership |
| japan-ai-guidelines::E.VC | E value chain and risk chain points |
Part 3: Matters related to AI developers – Japan AI Guidelines
12 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::D-10.i | D-10) i. Contributing to creation of innovation opportunities |
| japan-ai-guidelines::D-2.i | D-2) i. Proper data training (also D-4) i.) |
| japan-ai-guidelines::D-2.ii | D-2) ii. Development considering human life, body, property, mind and the environment |
| japan-ai-guidelines::D-2.iii | D-2) iii. Development contributing to proper use |
| japan-ai-guidelines::D-3.i | D-3) i. Consideration for bias in data |
| japan-ai-guidelines::D-3.ii | D-3) ii. Consideration for bias in algorithms and other elements of AI models |
| japan-ai-guidelines::D-5.i | D-5) i. Deploying mechanisms for security measures (developer) |
| japan-ai-guidelines::D-5.ii | D-5) ii. Attention to the latest trends (developer) |
| japan-ai-guidelines::D-6.i | D-6) i. Ensuring verifiability (developer) |
| japan-ai-guidelines::D-6.ii | D-6) ii. Providing relevant stakeholders with information (developer) |
| japan-ai-guidelines::D-7.i | D-7) i. Explaining the response to the Common Guiding Principles to AI providers |
| japan-ai-guidelines::D-7.ii | D-7) ii. Documenting development-related information |
Part 4: Matters related to AI providers – Japan AI Guidelines
11 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::P-2.i | P-2) i. Risk measures considering human life, body, property, mind and the environment |
| japan-ai-guidelines::P-2.ii | P-2) ii. Provision contributing to proper use |
| japan-ai-guidelines::P-3.i | P-3) i. Consideration for bias in the configuration and data of AI systems and services |
| japan-ai-guidelines::P-4.i | P-4) i. Deploying mechanisms and measures for protecting privacy |
| japan-ai-guidelines::P-4.ii | P-4) ii. Countermeasures against privacy infringement |
| japan-ai-guidelines::P-5.i | P-5) i. Deploying mechanisms for security measures (provider) |
| japan-ai-guidelines::P-5.ii | P-5) ii. Handling vulnerabilities |
| japan-ai-guidelines::P-6.i | P-6) i. Documenting system architecture and the like |
| japan-ai-guidelines::P-6.ii | P-6) ii. Providing relevant stakeholders with information (provider) |
| japan-ai-guidelines::P-7.i | P-7) i. Explaining the response to the Common Guiding Principles to AI business users |
| japan-ai-guidelines::P-7.ii | P-7) ii. Documenting service terms and the like |
Part 5: Matters related to AI business users – Japan AI Guidelines
7 controls
| Code | Title |
|---|---|
| japan-ai-guidelines::U-2.i | U-2) i. Proper use considering safety |
| japan-ai-guidelines::U-3.i | U-3) i. Consideration for bias in input data or prompts |
| japan-ai-guidelines::U-4.i | U-4) i. Countermeasures against inappropriate input of personal information and privacy infringement |
| japan-ai-guidelines::U-5.i | U-5) i. Implementing security measures |
| japan-ai-guidelines::U-6.i | U-6) i. Providing relevant stakeholders with information (business user) |
| japan-ai-guidelines::U-7.i | U-7) i. Explaining to relevant stakeholders |
| japan-ai-guidelines::U-7.ii | U-7) ii. Effective use of provided documents and compliance with terms |
Your Compliance Coverage
If you comply with Japan AI Guidelines, you already cover:
ISO/IEC 23894:2023
6%
6 controls mapped
Compare →Singapore Government Instruction Manual on ICT&SS Management (IM8)
6%
6 controls mapped
Compare →Singapore AI Governance Framework
5%
5 controls mapped
Compare →+ 111 more: UK Defence Standard 05-138 - Cyber Security for Defence Suppliers (5%), NIST Privacy Framework (5%)
See all 114 mapped frameworks ↓Maps to 114 other frameworks
100 total controls
ISO/IEC 23894:2023
6 source controls mapped|8 target controls covered
6%
Singapore Government Instruction Manual on ICT&SS Management (IM8)
6 source controls mapped|7 target controls covered
6%
Singapore AI Governance Framework
5 source controls mapped|4 target controls covered
5%
UK Defence Standard 05-138 - Cyber Security for Defence Suppliers
5 source controls mapped|2 target controls covered
5%
NIST Privacy Framework
5 source controls mapped|2 target controls covered
5%
ISO/IEC 27557:2022 - Organisational Privacy Risk Management
5 source controls mapped|7 target controls covered
5%
IEC 62443
5 source controls mapped|4 target controls covered
5%
South Korea ISMS-P
5 source controls mapped|5 target controls covered
5%
API 1164
5 source controls mapped|4 target controls covered
5%
ISO/IEC 27019:2024
5 source controls mapped|4 target controls covered
5%
Protective Security Policy Framework (PSPF) Release 2026
4 source controls mapped|2 target controls covered
4%
AML/CTF Act 2006 (Australia)
4 source controls mapped|2 target controls covered
4%
IEC 60601-1 - Medical Electrical Equipment Safety
4 source controls mapped|4 target controls covered
4%
EASA Part-IS - Information Security in Aviation
4 source controls mapped|5 target controls covered
4%
APRA CPS 230 Operational Risk Management
4 source controls mapped|4 target controls covered
4%
ISO/IEC 27003:2017
4 source controls mapped|2 target controls covered
4%
FBI CJIS Security Policy
4 source controls mapped|2 target controls covered
4%
UAE Virtual Asset Regulatory Authority (VARA) Regulations
4 source controls mapped|3 target controls covered
4%
Annex 11 to EU GMP - Computerised Systems
4 source controls mapped|1 target controls covered
4%
ICAO Annex 17 - Aviation Security (AVSEC)
4 source controls mapped|2 target controls covered
4%
German Supply Chain Due Diligence Act (LkSG)
4 source controls mapped|2 target controls covered
4%
Vermont Data Privacy and Online Surveillance Act
3 source controls mapped|2 target controls covered
3%
Privacy Act 1988 (Australia)
3 source controls mapped|5 target controls covered
3%
Ecuador Ley Orgánica de Protección de Datos Personales (LOPDP)
3 source controls mapped|4 target controls covered
3%
Law No. 172-13 on the Protection of Personal Data
3 source controls mapped|2 target controls covered
3%
Switzerland New Federal Act on Data Protection (nFADP/nDSG, 2023)
3 source controls mapped|15 target controls covered
3%
Bahrain PDPL
3 source controls mapped|7 target controls covered
3%
Federal Decree-Law No. 45 of 2021 on the Protection of Personal Data (UAE PDPL)
3 source controls mapped|5 target controls covered
3%
OCC Heightened Standards (12 CFR Part 30, Appendix D)
3 source controls mapped|2 target controls covered
3%
APRA CPS 234
3 source controls mapped|4 target controls covered
3%
FFIEC IT Examination Handbook
3 source controls mapped|6 target controls covered
3%
BS 65000:2014 - Guidance on Organizational Resilience
3 source controls mapped|3 target controls covered
3%
FFIEC Cybersecurity Assessment Tool (CAT)
3 source controls mapped|3 target controls covered
3%
Aged Care Quality Standards 2019 (repealed edition)
3 source controls mapped|1 target controls covered
3%
IEC 62304:2015 Medical Device Software Lifecycle Processes
3 source controls mapped|3 target controls covered
3%
ISO 20400:2017 - Sustainable Procurement
3 source controls mapped|1 target controls covered
3%
ISO 22320:2018
3 source controls mapped|1 target controls covered
3%
AS9100D - Aerospace Quality Management System
3 source controls mapped|1 target controls covered
3%
IAIS Insurance Core Principles (ICPs)
3 source controls mapped|2 target controls covered
3%
ICH Q10 - Pharmaceutical Quality System
3 source controls mapped|1 target controls covered
3%
ISO 15189:2022 - Medical Laboratories Requirements for Quality and Competence
3 source controls mapped|1 target controls covered
3%
ISO 28001:2007 Supply Chain Security Management
3 source controls mapped|1 target controls covered
3%
ISO 22000:2018
2 source controls mapped|2 target controls covered
2%
Regulation on the European Health Data Space (EHDS)
2 source controls mapped|2 target controls covered
2%
US Gramm-Leach-Bliley Act (GLBA) - Higher Education Safeguards Rule
2 source controls mapped|3 target controls covered
2%
ASIS SPC.1-2009 - Organizational Resilience Standard
2 source controls mapped|4 target controls covered
2%
ISO/IEC 25012:2008 - Data Quality Model
2 source controls mapped|4 target controls covered
2%
ISO/IEC 27031:2011
2 source controls mapped|3 target controls covered
2%
ASD Strategies to Mitigate Cyber Security Incidents
2 source controls mapped|2 target controls covered
2%
ITU-T X.805 - Security Architecture for End-to-End Communications
2 source controls mapped|2 target controls covered
2%
Vietnam Law on Cybersecurity (No. 116/2025/QH15)
2 source controls mapped|2 target controls covered
2%
South Korea PIPA
2 source controls mapped|2 target controls covered
2%
AWWA Cybersecurity Guidance for the Water Sector (American Water Works Association)
2 source controls mapped|2 target controls covered
2%
BSI IT-Grundschutz
2 source controls mapped|3 target controls covered
2%
ISO 27799:2025
2 source controls mapped|4 target controls covered
2%
US Consumer Product Safety Act (CPSC) Manufacturer and Importer Duties
2 source controls mapped|2 target controls covered
2%
Barbados Data Protection Act 2019
2 source controls mapped|6 target controls covered
2%
GDPR
2 source controls mapped|8 target controls covered
2%
ISO/IEC 29134:2023
2 source controls mapped|3 target controls covered
2%
ISO 14001:2015
1 source controls mapped|1 target controls covered
1%
ISO 45001:2018
1 source controls mapped|1 target controls covered
1%
OWASP DevSecOps Maturity Model (DSOMM)
1 source controls mapped|1 target controls covered
1%
NIST Special Publication 800-34 Revision 1, Contingency Planning Guide for Federal Information Systems
1 source controls mapped|1 target controls covered
1%
FedRAMP High
1 source controls mapped|1 target controls covered
1%
FedRAMP Moderate
1 source controls mapped|1 target controls covered
1%
South Korea Cloud Security Assurance Program (CSAP)
1 source controls mapped|1 target controls covered
1%
NATO AQAP 2110 - Quality Assurance Requirements for Design, Development, and Production
1 source controls mapped|1 target controls covered
1%
ISO/IEC 20000-1:2018
1 source controls mapped|1 target controls covered
1%
IEC 62351 - Power Systems Communication Security
1 source controls mapped|2 target controls covered
1%
US EPA Safe Drinking Water Act (SDWA) - Cybersecurity Requirements
1 source controls mapped|1 target controls covered
1%
ISO/IEC 27007:2020
1 source controls mapped|1 target controls covered
1%
COBIT 2019
1 source controls mapped|1 target controls covered
1%
ITIL 4
1 source controls mapped|1 target controls covered
1%
PCAOB AS 2201 - Audit of Internal Control Over Financial Reporting (ICFR)
1 source controls mapped|2 target controls covered
1%
Nevada Gaming Control Board Cybersecurity Requirements
1 source controls mapped|3 target controls covered
1%
ISO/IEC 29147:2018
1 source controls mapped|1 target controls covered
1%
SQF Code Edition 9 - Safe Quality Food
1 source controls mapped|2 target controls covered
1%
ISO 26262:2018 - Functional Safety for Road Vehicles
1 source controls mapped|1 target controls covered
1%
French Sapin II Law (Law No. 2016-1691)
1 source controls mapped|2 target controls covered
1%
IAEA Nuclear Security Series - Computer Security at Nuclear Facilities (NSS-17-T Rev 1)
1 source controls mapped|1 target controls covered
1%
ISO 22313:2020 - Guidance on Business Continuity Management Systems
1 source controls mapped|1 target controls covered
1%
OWASP ASVS
1 source controls mapped|1 target controls covered
1%
MITRE D3FEND
1 source controls mapped|1 target controls covered
1%
ISO/IEC 27043:2015
1 source controls mapped|1 target controls covered
1%
ISO/SAE 21434
1 source controls mapped|1 target controls covered
1%
ISO 14064 - Greenhouse Gas Accounting and Verification (Parts 1-3)
1 source controls mapped|1 target controls covered
1%
ISO/IEC 27010:2015
1 source controls mapped|1 target controls covered
1%
21 CFR Part 211 - Current Good Manufacturing Practice
1 source controls mapped|3 target controls covered
1%
FDA Quality Management System Regulation (QMSR)
1 source controls mapped|1 target controls covered
1%
USMCA Chapter 19 - Digital Trade (United States-Mexico-Canada Agreement)
1 source controls mapped|2 target controls covered
1%
TEFCA - Trusted Exchange Framework and Common Agreement
1 source controls mapped|1 target controls covered
1%
Rhode Island Data Transparency and Privacy Protection Act (RIDTPPA)
1 source controls mapped|1 target controls covered
1%
Russia Federal Law on Personal Data (152-FZ)
1 source controls mapped|2 target controls covered
1%
Pakistan Personal Data Protection Bill 2023
1 source controls mapped|3 target controls covered
1%
Law on Personal Data Protection (Official Gazette No. 42/2020)
1 source controls mapped|1 target controls covered
1%
Jordan Personal Data Protection Law (Law No. 24 of 2023)
1 source controls mapped|2 target controls covered
1%
Australian Privacy Principles (APPs)
1 source controls mapped|3 target controls covered
1%
Estonia Personal Data Protection Act (Isikuandmete kaitse seadus, 2019)
1 source controls mapped|1 target controls covered
1%
Austria Data Protection Act (Datenschutzgesetz, DSG, amended 2018)
1 source controls mapped|6 target controls covered
1%
Albania Law No. 124/2024 on Personal Data Protection
1 source controls mapped|3 target controls covered
1%
APPI
1 source controls mapped|3 target controls covered
1%
ISO/IEC 29100:2024
1 source controls mapped|3 target controls covered
1%
COSO Internal Control - Integrated Framework (2013)
1 source controls mapped|1 target controls covered
1%
Connecticut Data Privacy Act (CTDPA)
1 source controls mapped|1 target controls covered
1%
Armenia Law on Protection of Personal Data (2015)
1 source controls mapped|3 target controls covered
1%
ISO/IEC 27400:2022
1 source controls mapped|4 target controls covered
1%
Azure Security Benchmark
1 source controls mapped|1 target controls covered
1%
Azerbaijan Law on Personal Data (2010)
1 source controls mapped|4 target controls covered
1%
Florida Digital Bill of Rights (FDBR)
1 source controls mapped|2 target controls covered
1%
FTC GLBA Safeguards Rule (16 CFR Part 314)
1 source controls mapped|2 target controls covered
1%
ISO 26000:2010
1 source controls mapped|1 target controls covered
1%
ISO/IEC 27011:2024
1 source controls mapped|3 target controls covered
1%
CISA Cross-Sector Cybersecurity Performance Goals (CPG) 2.0
1 source controls mapped|1 target controls covered
1%
DAMA-DMBOK2 - Data Management Body of Knowledge (2nd Edition)
1 source controls mapped|2 target controls covered
1%
Coverage is not the same as your position
This page shows what Japan AI Guidelines overlaps with in general. Where your organisation actually stands, against the standard you are going for and the certifications you already hold, is a different question. Same graph and the same recorded refutations, scoped to you rather than to a pair.
The Compliance Position Diagnostic, $5,000 fixed, ten business daysWhat is Japan AI Guidelines and who does it apply to?
Japan AI Guidelines is a compliance framework from Japan with 8 domains and 87 controls. Japan's AI Guidelines for Business Ver1.2 (MIC and METI, March 2026): the non-binding, goal-based guidelines every AI developer, provider and business user in Japan is pointed to, with ten Common Guiding Principles, the Hiroshima AI Process principles, agile AI governance and role-specific matters, together with the Article 13 guideline decided under the AI Promotion Act of 2025 and the Act's one business duty. Read against the official Japanese texts. It is used by organisations to establish and maintain compliance with industry standards and regulatory requirements.
What does Japan AI Guidelines actually require?
Japan AI Guidelines has 87 controls organised across 8 domains. The largest domains are Part 2 C: Common Guiding Principles – Japan AI Guidelines (31 controls), Part 2 D: Hiroshima Process International Guiding Principles for All AI Actors – Japan AI Guidelines (13 controls), Part 3: Matters related to AI developers – Japan AI Guidelines (12 controls). Each control defines specific requirements that organisations must implement to achieve compliance.
If I already comply with another framework, how much of Japan AI Guidelines do I already cover?
Japan AI Guidelines maps to 114 other compliance frameworks. The top mapping partners are ISO/IEC 23894:2023 (6% coverage), Singapore Government Instruction Manual on ICT&SS Management (IM8) (6% coverage), Singapore AI Governance Framework (5% coverage). Use our comparison tool to explore control-level mappings between frameworks.
How do I implement Japan AI Guidelines?
Start your Japan AI Guidelines compliance journey by running a self-assessment on our platform to identify your current compliance posture. Our AI advisory can answer specific questions about Japan AI Guidelines requirements, and cross-framework mapping helps you leverage existing controls from other frameworks you may already comply with. Create a free account to access all 87 controls and track your progress.
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