United States
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Framework
Voluntary standard
NIST AI Risk Management Framework (AI RMF 1.0) and Generative AI Profile
The NIST AI Risk Management Framework is a voluntary framework for managing risks to individuals, organisations and society from AI. It organises practices into four functions: Govern, Map, Measure and Manage, and describes characteristics of trustworthy AI such as validity, safety, security, accountability, explainability, privacy and fairness. The July 2024 Generative AI Profile (NIST AI 600-1) adds risks and suggested actions specific to generative AI. Many US procurement requirements and state laws reference the framework as a recognised approach.
Adopted 26 Jan 2023
Source-linked
Official source
New York (United States)
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Act / statute
Adopted
Binding
New York Responsible AI Safety and Education (RAISE) Act (S.6953-B / A.6453-B, signed December 2025)
The RAISE Act requires large developers of frontier AI models (defined by training compute and revenue thresholds) to publish and follow a safety and security protocol, report critical safety incidents to the state within a set period, not deploy models that create unreasonable risk of critical harm, and submit to Attorney General enforcement with civil penalties; the chapter amendments create a state oversight office and align definitions with California's Transparency in Frontier AI Act.
Applies from 1 Jan 2027
Source-linked · checked 11 Sep 2026
Official source
California (United States)
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Act / statute
In force
Binding
California SB 53: Transparency in Frontier Artificial Intelligence Act
SB 53 requires "large frontier developers" (developers of the most compute-intensive models above statutory thresholds) to publish a frontier AI framework describing how they assess and mitigate catastrophic risks, publish transparency reports when deploying new frontier models, report critical safety incidents to the California Office of Emergency Services, and protect employees who report safety concerns. It also directs creation of a public computing cluster ("CalCompute").
Applies from 1 Jan 2026
Source-linked
Official source
Singapore
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Framework
Voluntary standard
Model AI Governance Framework (Second Edition) and Model AI Governance Framework for Generative AI
Singapore's Model AI Governance Framework is a voluntary, sector-agnostic guide for organisations deploying AI. The second edition (January 2020) covers four areas: internal governance structures and measures, determining the level of human involvement in AI-augmented decision-making, operations management (data, model development, monitoring), and stakeholder interaction and communication. The May 2024 Model AI Governance Framework for Generative AI extends it with nine dimensions including accountability, data, trusted development and deployment, incident reporting, testing and assurance, security, content provenance, safety and alignment research, and AI for the public good.
Adopted 21 Jan 2020
Source-linked
Official source
Hiroshima Process International Code of Conduct for Organizations Developing Advanced AI Systems (G7, 30 October 2023)
Eleven voluntary actions for organisations developing the most advanced AI systems, including foundation and generative models: risk identification and mitigation across the lifecycle, post-deployment vulnerability and incident monitoring, public transparency reports, responsible information sharing, security controls, content authentication such as watermarking, research on societal risks, priority to global challenges, technical standards, and data-input and personal-data safeguards. It sits alongside the Hiroshima Process guiding principles and, from 2025, an OECD-run voluntary reporting framework.
Adopted 30 Oct 2023
Source-linked · checked 11 Sep 2026
Official source
The Bletchley Declaration by countries attending the AI Safety Summit, 1–2 November 2023
Signed by countries including the United States, China, the EU, India, Japan and Brazil, the declaration recognises the opportunities of AI and the risks of frontier models, commits signatories to cooperate on identifying AI safety risks and building risk-based policies, and launched the summit series continued in Seoul (2024) and Paris (2025) and the network of AI safety institutes.
Adopted 1 Nov 2023
Source-linked · checked 11 Sep 2026
Official source
European Union
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Regulation
Partially applicable
Binding
Regulation (EU) 2024/1689 — Artificial Intelligence Act
The EU AI Act is a binding regulation that sets rules for developing, placing on the market and using AI systems in the European Union. It bans a small set of practices considered unacceptable, imposes detailed requirements on "high-risk" AI systems used in areas such as employment, education, credit, essential services, law enforcement and safety-critical products, requires transparency for chatbots and synthetic content, and creates separate duties for providers of general-purpose AI models. Obligations apply in phases between 2025 and 2027.
Applies from 2 Aug 2026
Source-linked
Official source
Expanded ASEAN Guide on AI Governance and Ethics – Generative AI
Endorsed in January 2025, the expanded guide addresses risks specific to generative AI (hallucination, deepfakes and misinformation, intellectual property, privacy, security, bias, embedded values) and proposes governance dimensions covering accountability, data, development and deployment, incident reporting, testing and assurance, security, content provenance, safety research and public-interest use, with policy recommendations for member states.
Adopted 17 Jan 2025
Source-linked · checked 11 Sep 2026
Official source
Australia
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Consultation
Under consultation
Proposals paper: introducing mandatory guardrails for AI in high-risk settings (Australia)
The proposals paper sought views on ten mandatory guardrails for developers and deployers of AI in high-risk settings, a principles-based definition of high-risk AI (with general-purpose AI treated as high-risk), and three regulatory options: adapting existing laws, framework legislation, or a new cross-economy AI Act. The guardrails mirror the Voluntary AI Safety Standard, covering accountability, risk management, data governance, testing, human control, transparency, contestability, supply-chain transparency, records, and conformity assessment.
