AI Governance Guidelines: Regulator Guidance and Interpretations
Non-binding guidance from regulators and agencies that shapes how AI rules are applied in practice.
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What applies to me? →Bletchley Declaration on AI Safety
At the inaugural AI Safety Summit, 28 governments signed this political declaration. They recognized risks from frontier (most advanced) AI and committed to international cooperation on safety, evaluation, and information sharing.
China AI Standardization White Paper
Chinese standards authorities issued this non-binding policy document to map AI standards work. It identifies priorities and outlines planned national and international standardization efforts.
EU General-Purpose AI Model Training Data Public Summary Template
The European Commission published a template for general-purpose AI providers’ public training-data summaries. It supports disclosure obligations under the EU AI Act. Providers are expected to follow its structure when preparing those summaries.
FATF AI Anti-Money Laundering Guidance
Guidance from the Financial Action Task Force (FATF) addresses AI and machine learning in anti-money laundering, counter-terrorism financing, and proliferation financing compliance. It sets expectations for transaction monitoring, customer due diligence, and suspicious activity detection.
FDA AI/ML Software as Medical Device Guidance
FDA’s action plan and guidance address AI and machine learning (AI/ML) Software as a Medical Device. They introduce a total product lifecycle approach and predetermined change control plans. Self-updating clinical algorithms also face transparency and monitoring requirements.
Sound Practices for Responsible Adoption of Artificial Intelligence (Consultation Report)
The Financial Stability Board proposes 12 practices for responsible AI adoption throughout its lifecycle. They cover banks, insurers, and other regulated financial entities developing or deploying AI. Institutions should map them to governance, model risk, third-party oversight, and lifecycle controls.
Five Eyes Guidance on the Careful Adoption of Agentic AI Services
This joint Five Eyes advisory addresses enterprises and public bodies deploying autonomous AI agents. It covers agents taking independent actions, accessing systems, or interacting with other agents. The guidance calls for low-risk tasks, minimum necessary access, and integration into existing security governance.
G7 Hiroshima AI Code of Conduct
The G7 Hiroshima AI Process issued this voluntary international code of conduct. It sets eleven principles and corresponding actions for advanced AI developers and operators, particularly frontier (most capable) and general-purpose models. The code uses voluntary commitments to guide responsible development.
MDDI Response on Extending AI Governance to Agentic AI Systems
Singapore’s Ministry of Digital Development and Information clarified its January 2026 agentic AI framework in a parliamentary response. Enterprises should designate oversight roles, maintain human accountability, and scale controls to how independently systems act. The response treats AI agents as systems that act on their own and require specific governance.
India AI Governance Framework
An advisory from India's IT ministry (MeitY) sets responsible AI principles and interim expectations for platforms deploying AI in India. It focuses on harm prevention, traceability, and government approval before deploying undertested models.
Japan AI Guidelines for Business
Guidelines from METI, Japan's trade ministry, help Japanese businesses govern AI throughout its lifecycle. They address risk management, transparency, accountability, and intellectual property, drawing on the Hiroshima AI Process and international frameworks.
Principles to Promote Fairness, Ethics, Accountability and Transparency (FEAT) in the Use of Artificial Intelligence and Data Analytics in Singapore's Financial Sector
MAS FEAT is a voluntary framework for Singapore financial institutions using AI and data analytics. Its four principles are Fairness, Ethics, Accountability, and Transparency.
New Zealand Responsible AI Guidance for Business
New Zealand’s government issued voluntary guidance on responsible commercial AI use. It covers governance structures, risk management, and accountability. The guidance sets expectations for businesses developing and deploying AI in New Zealand.
NIST ITL AI Program: Guidance and Templates for Public-Facing AI Documentation (Initial Public Draft)
NIST’s initial public draft provides guidance and templates for publicly disclosed AI system documentation. It supports developers, deployers, and procurers needing governance records, transparency, or audit evidence. Public comments close September 16, 2026.
NIST Guidelines on Protecting Online Identity and Access Tokens from Misuse
The US National Institute of Standards and Technology (NIST) has finalized guidance establishing security requirements for protecting online identity credentials and access tokens from unauthorized use or misuse. The guidance applies to organizations that use tokens to control access to AI models, automated AI agents, and privileged administrative systems. Covered entities are expected to implement controls that prevent token theft, reuse of stolen tokens, and attackers gaining higher access rights across their digital identity infrastructure.
OCC Updated Model Risk Management Guidance (2026)
The Office of the Comptroller of the Currency (OCC) has issued updated model risk management guidance establishing revised expectations for how national banks and federal savings associations develop, validate, monitor, and govern models. The guidance applies to all institutions supervised by the OCC that use models in material business decisions, with particular relevance where AI or machine learning is embedded in credit underwriting, pricing, fraud detection, or compliance monitoring workflows. Institutions are expected to maintain rigorous validation programs, clear governance structures, and documented controls proportionate to the risk a given model presents.
OMB Memorandum M-26-04: Increasing Public Trust in AI Through Unbiased AI Principles
Office of Management and Budget (OMB) Memorandum M-26-04 sets unbiased AI principles for federal systems interacting with or affecting the public. It covers executive agencies procuring, developing, or operating AI. Agencies must address algorithmic bias (unfair AI outcomes) and maintain transparency and accountability in AI-supported decisions.
SEC AI Governance Guidance
SEC rules, guidance, and proposals address investment advisers, broker-dealers, and public companies using AI. Topics include predictive-analytics conflicts, securities disclosures, and examination priorities for algorithmic systems.
The 2026 Singapore Consensus on Global AI Safety Research Priorities
The 2026 Singapore Consensus sets out a structured agenda for global AI safety research, covering testing methods, alignment techniques (keeping AI acting as intended), and governance mechanisms. It is produced by an international coalition of academic researchers and addresses organizations building or deploying advanced AI systems. Enterprises can use it as a reference framework for structuring safety testing programs and model oversight documentation before deployment.
UK AI Growth Lab Regulatory Sandbox - Consultation on Two Models
The UK Department for Science, Innovation and Technology (DSIT) opened consultation on the proposed UK AI Growth Lab in October 2025. The sandbox would let firms test AI under relaxed or modified rules. Options include central government administration across sectors or individual sandboxes managed by lead regulators. The aim is reduced compliance barriers with continued oversight.
AI Risk Management Toolkit
The UK Government published this toolkit to help organizations understand, assess, and manage risk throughout the full lifecycle of AI projects. It applies to teams involved in designing, procuring, or delivering AI products and services, including public and private sector buyers. The toolkit provides structured guidance for embedding risk management into project approval checks, procurement checklists, and delivery-stage governance.
UNESCO Recommendation on the Ethics of Artificial Intelligence: 2026 Implementation Tools Update
UNESCO has released a new set of implementation tools extending its 2021 Recommendation on the Ethics of Artificial Intelligence (AI), announced at the Global Forum on the Ethics of AI held in Riyadh, Saudi Arabia. The tools are designed to help governments, enterprises, and AI deployers put the Recommendation's ethical principles into operational practice. Organizations using or developing AI systems are the primary audience, with particular emphasis on ethics review processes, responsible AI documentation, and oversight controls for AI model deployment.
Verifiable Semiconductor Manufacturing: Governance and Verification Systems for AI Supply Chain Oversight
Oxford Martin’s AI Governance Initiative examines semiconductor governance and verification in AI supply chains. The guidance addresses large-scale hardware design, production, procurement, and deployment. It outlines assurances for chip origin, integrity, and manufacturing standards.