⚠️ This explorer is for general orientation only and is not legal advice. AI law is changing fast and several entries note pending or recently changed status. Verify against the official source before relying on it, and consult qualified counsel for your specific situation.
The global picture
The deeper the colour, the more binding AI laws are in force. Hover a country to see its stack — or click it to jump straight to the detail below.
What applies in your country?
Pick a jurisdiction to see the stack of binding laws, plus the standards and voluntary frameworks you can adopt anywhere.
European Union
The EU AI Act (risk-based, extraterritorial) + GDPR set the baseline for all 27 member states; the Council of Europe AI Convention adds a human-rights treaty layer. Member states add national implementing laws and supervisory authorities.
Binding / national rules 3
Standards & voluntary frameworks adoptable anywhere
Spain
Spain = EU AI Act + GDPR, enforced nationally by AESIA (the EU's first dedicated AI agency), plus a draft Organic Law adding strong AI-content labelling and a ban on non-consensual sexual deepfakes.
Binding / national rules 4
Standards & voluntary frameworks adoptable anywhere
Italy
Italy = EU AI Act + GDPR + the first national EU AI law (132/2025), adding criminal deepfake provisions, a human-oversight principle and sector rules (health, work, minors), supervised by AgID + ACN.
Binding / national rules 4
Standards & voluntary frameworks adoptable anywhere
France
France = EU AI Act + GDPR enforced through a distributed sector model (CNIL, DGCCRF, ARCOM, ACPR, HAS); formal national authority designation was still pending in mid-2026.
Binding / national rules 4
Standards & voluntary frameworks adoptable anywhere
Germany
Germany = EU AI Act + GDPR implemented via the draft KI-MIG, making the Bundesnetzagentur the central AI supervisor in a hybrid model with BfDI, BaFin and BSI (cabinet-adopted Feb 2026).
Binding / national rules 4
Standards & voluntary frameworks adoptable anywhere
Netherlands
Netherlands = EU AI Act + GDPR baseline; national supervision is being arranged through existing regulators (e.g., the Dutch DPA's algorithm-oversight unit). No separate national AI statute.
Binding / national rules 3
Standards & voluntary frameworks adoptable anywhere
Ireland
Ireland = EU AI Act + GDPR baseline, enforced via a distributed model of existing regulators. As host to many AI/tech firms' EU HQs, its data-protection authority is especially significant.
Binding / national rules 3
Standards & voluntary frameworks adoptable anywhere
United Kingdom
UK = no comprehensive AI Act; a pro-innovation, principles-based approach run by sector regulators (ICO, Ofcom, CMA, FCA) plus the AI Security Institute. Note the EU AI Act may still apply to UK firms selling into the EU.
Binding / national rules 2
Standards & voluntary frameworks adoptable anywhere
United States
US = no comprehensive federal AI statute — a patchwork of deregulatory federal executive orders + the voluntary NIST AI RMF, with binding obligations coming chiefly from state/city laws that stack by where you operate. As of Dec 2025 the federal government is trying to preempt state AI laws.
Binding / national rules 9
Standards & voluntary frameworks adoptable anywhere
Canada
Canada = no binding general AI law after AIDA died on prorogation (Jan 2025); governed by a voluntary GenAI code, a mandatory federal-government Directive (algorithmic impact assessments) and existing privacy law. A replacement is awaited.
Binding / national rules 2
Standards & voluntary frameworks adoptable anywhere
Brazil
Brazil = no AI law in force yet; the EU-style risk-based bill PL 2338/2023 passed the Senate (Dec 2024) but remains pending in the Chamber of Deputies. Current governance rests on the LGPD and consumer/sector law.
Standards & voluntary frameworks adoptable anywhere
China
China has the world's most developed binding AI-content regime — a layered CAC framework (algorithms → deep synthesis → generative AI → mandatory labelling) emphasising content control, security filings and transparency rather than an EU-style risk taxonomy.
Binding / national rules 3
Standards & voluntary frameworks adoptable anywhere
South Korea
South Korea = the AI Basic Act (Asia's first comprehensive horizontal AI law), effective Jan 2026 with a risk-based 'high-impact AI' approach, generative-AI transparency and a domestic-representative duty — but modest penalties and a ~1-year grace period.
Standards & voluntary frameworks adoptable anywhere
Japan
Japan = the AI Promotion Act, an innovation-first, penalty-free framework (in force mid-2025) coordinating policy via a PM-led AI Strategy Headquarters while managing risk through guidance and existing sectoral laws.
Standards & voluntary frameworks adoptable anywhere
Australia
Australia = no standalone AI Act; the Dec 2025 National AI Plan relies on existing laws, sector regulators, the Voluntary AI Safety Standard and a new AI Safety Institute, having declined immediate mandatory guardrails.
Standards & voluntary frameworks adoptable anywhere
Singapore
Singapore = a pro-innovation, voluntary, testing-and-assurance-led model (the Model AI Governance Framework for GenAI + AI Verify), with no binding AI statute but growing de facto influence through procurement and assurance pilots.
Standards & voluntary frameworks adoptable anywhere
India
India = no dedicated AI statute; the AI Governance Guidelines (Nov 2025) set a phased, institution-led, pro-innovation approach using existing laws (IT Act, DPDP Act 2023) and 'techno-legal' tools.
Standards & voluntary frameworks adoptable anywhere
The framework catalog
Every law, framework and standard in the index. Filter by type or region and search by name, or open the full set in one click.
EU AI Act
European Union · European AI Office + national market-surveillance authorities
The world's first comprehensive, horizontal AI law. It classifies AI systems by risk and scales obligations accordingly — from outright bans on 'unacceptable' uses to full conformity requirements for 'high-risk' systems, lighter transparency duties for limited-risk systems, and a separate regime for general-purpose AI (GPAI) models.
What it asks & details
What it asks
- Don't deploy prohibited practices (social scoring, untargeted face scraping, manipulative or exploitative systems, most real-time biometric ID)
- High-risk systems: risk management, data governance, technical documentation, logging, human oversight, accuracy/robustness/cybersecurity, conformity assessment + CE marking, EU-database registration
- GPAI models: technical documentation, training-data summary, copyright policy; systemic-risk models add evaluation, adversarial testing and incident reporting
- Transparency (Art. 50): disclose AI interaction, label deepfakes and AI-generated content
- Fundamental-rights impact assessment for certain deployers of high-risk systems
Providers, deployers, importers and distributors placing AI on the EU market or whose output is used in the EU — including non-EU companies (extraterritorial).
Four-tier risk pyramid (unacceptable / high / limited-transparency / minimal) plus a separate two-level GPAI regime.
Up to €35M or 7% of global turnover for prohibited practices; up to €15M or 3% for most other breaches; lower caps for SMEs.
- 2024-08-01 — Entered into force
- 2025-02-02 — Prohibited practices + AI-literacy duties apply
- 2025-08-02 — GPAI model obligations, governance and penalties apply
- 2026-08-02 — Original date for high-risk (Annex III) + Art. 50 transparency (high-risk being deferred via Digital Omnibus)
- 2027-12-02 — Proposed deferred date for standalone high-risk (Digital Omnibus — not yet adopted)
GDPR
European Union · National Data Protection Authorities + European Data Protection Board
The EU's data-protection law. Where AI processes personal data, GDPR governs automated decision-making, profiling and the duty to assess and mitigate privacy risk — operating in parallel with the AI Act.
What it asks & details
What it asks
- Honour the Art. 22 right not to be subject to solely automated decisions with legal/significant effects, save narrow grounds
- Provide safeguards for permitted automated decisions: human intervention, the right to contest
- Give meaningful information about the logic and consequences of automated processing
- Run a Data Protection Impact Assessment for high-risk processing (large-scale profiling, ADM)
Any controller or processor handling personal data of people in the EU, including via AI (extraterritorial).
Risk-based accountability — heightened duties triggered when processing is likely high-risk to individuals.
Up to €20M or 4% of global turnover for the most serious infringements.
- 2018-05-25 — Became applicable
CoE AI Convention
Council of Europe (international) · Council of Europe — Conference of the Parties
The first legally binding international treaty on AI. A high-level framework requiring signatory states to ensure AI activities are consistent with human rights, democracy and the rule of law, implemented through their own national laws.
What it asks & details
What it asks
- Ensure AI respects human rights, dignity, equality, privacy and non-discrimination
- Maintain transparency, oversight and accountability across the AI lifecycle
- Conduct iterative human-rights risk and impact assessments (HUDERIA)
- Provide accessible remedies and procedural safeguards for affected people
Signatory/ratifying states (binds states, not companies directly); signed by the EU, US, UK and others.
Principles-and-outcomes based, with mandatory iterative risk/impact management.
No fines — enforced via international monitoring and each Party's domestic measures.
- 2024-09-05 — Opened for signature
- 2025-11-01 — Entered into force
Spain national AI law
Spain · AESIA — Agencia Española de Supervisión de la Inteligencia Artificial
Spain created the EU's first dedicated national AI supervisor (AESIA) and ran the EU's first AI regulatory sandbox. In 2026 it advanced an Organic Law to enforce the EU AI Act domestically, with strong AI-content labelling rules and a ban on non-consensual sexual deepfakes.
What it asks & details
What it asks
- Comply with all EU AI Act obligations, supervised domestically by AESIA
- Clearly label AI-generated or manipulated content (deepfakes)
- Prohibition on non-consensual sexual deepfakes
- Follow AESIA compliance guidance and the national sandbox regime
Providers and deployers of AI operating in Spain, mirroring the EU AI Act's scope.
Follows the EU AI Act risk model, enforced nationally by AESIA, with added content-transparency emphasis.
Mirrors EU AI Act tiers (up to €35M / 7% for prohibited practices); softened for SMEs/startups.
- 2023-08-22 — AESIA created (Royal Decree 729/2023)
- 2026-05-26 — Council of Ministers approved the draft Organic Law
Italy AI Law (132/2025)
Italy · AgID (notifying authority) + ACN (market surveillance)
The first EU member-state comprehensive national AI law. It complements (not duplicates) the EU AI Act, layering on national governance, sector rules (health, work, justice), child-protection rules and criminal provisions for harmful deepfakes.
What it asks & details
What it asks
- Keep human oversight/control over AI-based decisions
- Workplace: inform employees of AI use, its logic, purpose and oversight
- Minors under 14 may use AI only with parental consent
- New criminal offence for harmful AI-generated/altered content (1–5 years); AI as an aggravating circumstance
Providers, deployers and users of AI in Italy, layered on the directly-applicable EU AI Act.
Adopts the EU AI Act risk model and adds national sector and criminal-law overlays.
Criminal penalties for AI-enabled offences (imprisonment 1–5 years) plus EU AI Act fines enforced by ACN.
- 2025-09-23 — Enacted as Law 132/2025
- 2025-10-10 — Entered into force
France AI framework
France · CNIL (data protection) + distributed sector regulators (DGCCRF, ARCOM, ACPR, HAS)
France enforces the EU AI Act through a distributed, sector-based model rather than one dedicated AI agency. CNIL has been the most visible body, issuing AI guidance under GDPR, but formal national authority designations were still pending parliamentary adoption in mid-2026.
What it asks & details
What it asks
- Comply with the directly-applicable EU AI Act
- Follow CNIL's GDPR-based AI guidance on lawful basis and automated decisions
- Observe sector regulators' rules (ARCOM, ACPR, HAS) where applicable
- Meet Art. 50 transparency duties when they apply
Providers and deployers of AI in France under the EU AI Act, with sector-specific oversight.
EU AI Act risk model, enforced through a distributed/sectoral national structure.
EU AI Act fines once the national framework is adopted; CNIL can already levy GDPR fines (up to €20M / 4%).
- 2025-02 — France hosted the AI Action Summit, Paris
- 2026 — National competent-authority designation still pending
Germany AI framework (KI-MIG)
Germany · Bundesnetzagentur (central) + BfDI, BaFin, BSI (hybrid)
Germany is implementing the EU AI Act via the draft KI-MIG, making the Bundesnetzagentur the central coordinator and market-surveillance authority in a hybrid model with sectoral regulators. Cabinet-adopted in February 2026; parliamentary passage pending.
What it asks & details
What it asks
- Comply with the directly-applicable EU AI Act across all risk tiers
- Engage with the Bundesnetzagentur as central market-surveillance/notifying authority
- Sectoral compliance: BfDI (data-protection high-risk AI), BaFin (finance), BSI (cybersecurity/KRITIS)
- Meet conformity-assessment, documentation and transparency requirements when due
Providers and deployers of AI in Germany under the EU AI Act, coordinated centrally by the Bundesnetzagentur.
EU AI Act risk model via a hybrid central-plus-sectoral supervisory structure.
EU AI Act fine ranges (up to €35M / 7% for prohibitions) once KI-MIG is adopted.
- 2026-02-11 — Federal Cabinet adopted the draft KI-MIG
- 2026 — Bundestag/Bundesrat approval pending
UK AI approach
United Kingdom · Sector regulators (ICO, Ofcom, CMA, FCA) via the DRCF + AI Security Institute
The UK has deliberately avoided a single horizontal AI law, instead asking existing regulators to apply five cross-sector principles within their remits. A growth-focused bill was signalled in 2026 but no comprehensive AI Act is enacted; the rebranded AI Security Institute handles frontier-model risk.
What it asks & details
What it asks
- Apply five principles: safety/security, transparency, fairness, accountability, contestability
- Comply with UK GDPR / Data Protection Act for AI processing and ICO AI guidance
- Follow sector-specific expectations (Ofcom, FCA, CMA)
- Engage voluntarily with the AI Security Institute on frontier-model testing
Organisations developing or deploying AI in the UK, regulated through existing sector regimes.
Context-specific and principles-based — risk managed by sector regulators, not fixed statutory tiers.
No dedicated AI fines; enforcement via sector regimes (e.g., ICO up to £17.5M or 4% under UK GDPR).
- 2023-03 — Pro-innovation White Paper (five principles)
- 2025-02-14 — AI Safety Institute renamed AI Security Institute
- 2026-05 — 'Regulating for Growth Bill' announced (not yet enacted)
US Federal AI Policy
United States (Federal) · The White House (OSTP/NEC/NSC), OMB, DOJ, Dept. of Commerce
There is no comprehensive US federal AI statute. Federal policy is set by executive orders and voluntary frameworks. The Trump administration's EO 14179 (Jan 2025) rescinded Biden's EO 14110, the AI Action Plan (Jul 2025) is in implementation, and EO 14365 (Dec 2025) pushes to preempt state AI laws.
What it asks & details
What it asks
- Repeal/modify federal rules seen as inhibiting AI innovation
- Federal agencies: appoint Chief AI Officers and publish AI use-case inventories (OMB M-25-21)
- Federal AI procurement must protect government data and avoid 'ideologically biased' models (M-25-22)
- Pursue a uniform federal framework to preempt conflicting state AI laws (EO 14365)
Directly binds federal agencies and contractors; indirectly pressures states and the AI industry.
Pro-innovation / deregulatory — minimises mandatory risk controls in favour of voluntary, market-led governance.
No statutory penalties; leverage via funding conditions, procurement terms and DOJ litigation.
- 2025-01-23 — EO 14179 rescinds Biden EO 14110
- 2025-07-23 — America's AI Action Plan released
- 2025-12-11 — EO 14365 — state-law preemption push + DOJ AI Litigation Task Force
NIST AI RMF
United States (global use) · NIST — National Institute of Standards and Technology
A voluntary, sector-agnostic framework to identify, measure and manage AI risks across the lifecycle, organised around four functions: Govern, Map, Measure, Manage. The Generative AI Profile adds 12 GenAI-specific risks and 200+ suggested actions. Widely used as a de facto baseline and a route to demonstrate compliance with binding laws.
What it asks & details
What it asks
- Govern — set AI culture, policies, roles and accountability (cross-cutting)
- Map — establish context and identify AI risks and impacts
- Measure — assess trustworthiness (validity, safety, bias, security, transparency)
- Manage — prioritise, treat and monitor risks across the lifecycle
Any organisation that designs, develops, deploys or uses AI — adoption is voluntary.
Voluntary, context-based lifecycle risk management (Govern/Map/Measure/Manage).
None — voluntary framework.
- 2023-01-26 — AI RMF 1.0 published
- 2024-07-26 — Generative AI Profile (AI 600-1) released
Colorado AI Act
Colorado, US · Colorado Attorney General (exclusive enforcement)
The first US comprehensive 'high-risk AI' law (2024) never took effect: before its delayed start it was repealed and replaced by SB 26-189 (signed May 2026), a narrower automated-decision-making (ADMT) disclosure/rights framework effective Jan 1, 2027. The original risk-management, impact-assessment and reasonable-care duties were dropped.
What it asks & details
What it asks
- Developers provide documentation about covered ADMT to deployers
- Deployers give consumers notice when covered ADMT materially influences a consequential decision
- Consumer rights (notice/explanation) around covered ADMT
- Scope limited to seven domains: education, employment, housing, finance, insurance, healthcare, government services
Developers and deployers of covered ADMT used in consequential decisions affecting Colorado consumers.
Narrowed from EU-style 'high-risk' management to a targeted notice/transparency-and-rights model.
Enforced by the Colorado AG as a deceptive trade practice; no private right of action.
- 2024-05-17 — SB 24-205 signed (original Act)
- 2026-05-14 — SB 26-189 repeals & replaces the Act
- 2027-01-01 — Replacement ADMT law takes effect
California AI Laws
California, US · California Attorney General + Dept. of Technology
California regulates AI through targeted laws rather than one statute: AB 2013 (training-data transparency), SB 942 (AI content labelling + detection tools), and SB 53 (first US frontier-AI safety law). The broader SB 1047 was vetoed in 2024; SB 53 is its lighter successor.
What it asks & details
What it asks
- AB 2013: publicly post a summary of datasets used to train generative AI
- SB 942: large providers must label AI-generated content and offer a free detection tool
- SB 53: large frontier developers publish a safety framework and transparency reports
- SB 53: report critical safety incidents and protect whistleblowers
GenAI developers and large 'covered providers' serving Californians; frontier developers above compute/revenue thresholds (SB 53).
Targeted/transparency-first: input transparency, output disclosure, and frontier-risk safety reporting.
Civil penalties enforced by the California AG (SB 53 up to ~$1M per violation for frontier-safety breaches).
- 2024-09-28 — AB 2013 signed
- 2025-09-29 — SB 53 (frontier AI) signed
- 2026-01-01 — AB 2013, SB 942 and SB 53 take effect
TRAIGA
Texas, US · Texas Attorney General (exclusive enforcement)
Texas is the third state with a comprehensive AI law, but the enacted version is narrow — it mainly governs state-agency AI use and bans a short list of harmful uses, with a first-in-nation AI regulatory sandbox.
What it asks & details
What it asks
- Government agencies follow AI governance/disclosure rules
- Prohibits AI for government social scoring
- Prohibits AI intentionally designed to incite self-harm, violence or crime
- 60-day cure period before penalties; 36-month AI regulatory sandbox
Texas state agencies (broad duties) and any business engaging in the specifically prohibited uses.
Intent-based prohibitions on defined harmful uses plus government-use governance.
AG-enforced civil penalties (roughly $10k–$200k per violation; $2k–$40k/day continuing); no private right of action.
- 2025-06-22 — HB 149 signed
- 2026-01-01 — Takes effect
Utah AI Policy Act
Utah, US · Utah Division of Consumer Protection + Office of AI Policy
Utah was the first state with a broadly applicable generative-AI consumer-disclosure law. 2025 amendments narrowed it so proactive disclosure is generally required only in 'high-risk' interactions (health, finance, biometric, regulated-occupation advice), with a safe harbour if the AI clearly discloses it is non-human.
What it asks & details
What it asks
- Disclose generative-AI use to consumers on request
- Proactively disclose in high-risk interactions (health, finance, regulated occupations)
- Safe harbour if the AI itself clearly discloses it is non-human
- Existing consumer-protection law still applies to AI-produced statements
Persons/businesses using generative AI in consumer transactions and regulated occupations in Utah.
Disclosure-based, tiered to 'high-risk' interactions — light-touch.
Administrative fines (up to ~$2,500 per violation) plus AG enforcement.
- 2024-05-01 — SB 149 takes effect
- 2025-05-07 — 2025 amendments take effect
Illinois HB 3773 + BIPA
Illinois, US · Illinois Dept. of Human Rights; private right of action (BIPA)
Illinois pairs the nation's strictest biometric-privacy law (BIPA) with a new AI-in-employment anti-discrimination rule. HB 3773 (effective Jan 1, 2026) bars employers from using AI that has a discriminatory effect on protected classes and from using ZIP code as a proxy, and requires notice when AI is used in employment decisions.
What it asks & details
What it asks
- BIPA: obtain informed consent before collecting biometric identifiers; publish a retention policy
- HB 3773: don't use AI with a discriminatory effect on protected classes in employment
- HB 3773: don't use ZIP code as a proxy for a protected class
- HB 3773: notify employees/applicants when AI is used in covered decisions
Entities handling Illinois biometric data (BIPA); employers using AI in employment decisions (HB 3773).
Rights-based consent regime (BIPA) plus an effects-based anti-discrimination/notice rule (HB 3773).
BIPA: $1,000 (negligent) / $5,000 (intentional) statutory damages per person; HB 3773 via Human Rights Act remedies.
- 2024-08-09 — HB 3773 signed
- 2026-01-01 — HB 3773 AI-in-employment provisions take effect
NYC Local Law 144
New York City, US · NYC Department of Consumer and Worker Protection (DCWP)
The first US law mandating independent bias audits of AI hiring tools. Employers and agencies using an automated employment decision tool in NYC must obtain an annual independent bias audit, publish the results, and notify candidates. A Dec 2025 state audit found enforcement weak, signalling tighter scrutiny.
What it asks & details
What it asks
- Obtain an annual independent bias audit of each AEDT
- Publicly publish a summary of audit results (impact ratios by sex, race/ethnicity)
- Notify candidates/employees at least 10 business days before AEDT use
- Disclose the qualifications/characteristics the AEDT assesses
Employers and employment agencies using AEDTs to screen NYC candidates/employees.
Mandatory bias-audit and transparency obligation focused on disparate impact in hiring.
Civil penalties up to $500 (first) and $500–$1,500 (subsequent); each day a separate violation.
- 2023-07-05 — Enforcement begins
- 2025-12-02 — State Comptroller audit finds enforcement 'ineffective'
Canada AI (AIDA)
Canada · ISED (policy) + Treasury Board (federal Directive)
Canada's flagship AI bill (AIDA, in Bill C-27) died when Parliament was prorogued in January 2025 and the government has said it will be replaced, not revived. With no successor enacted, Canada relies on a voluntary generative-AI code and a binding-on-government Directive applying algorithmic impact assessments.
What it asks & details
What it asks
- Voluntary Code: accountability, safety, fairness, transparency, human oversight for advanced GenAI
- Voluntary Code: impact/risk assessments, bias testing, incident reporting
- Directive (federal gov): complete an Algorithmic Impact Assessment before deploying ADM systems
- Directive: ensure transparency, explanation rights, human-in-the-loop and monitoring
Voluntary Code — signatory AI developers; Directive — Canadian federal institutions. No general binding private-sector duty.
Soft-law / risk-based via impact assessments; no enforceable national statutory regime after AIDA's demise.
None for the Code; the Directive is enforced administratively within government. A replacement framework is awaited.
- 2023-09 — Voluntary Code of Conduct on advanced generative AI launched
- 2025-01-06 — Prorogation kills Bill C-27 / AIDA
Brazil AI Bill (PL 2338)
Brazil · National Congress; ANPD anticipated as lead authority
Brazil's comprehensive, EU-inspired AI bill establishes a risk-based framework that bans 'excessive-risk' systems and imposes governance, impact-assessment and transparency duties on high-risk systems. The Senate approved it in December 2024; it remains under review in the Chamber of Deputies as of mid-2026.
What it asks & details
What it asks
- Classify AI by risk (minimal → high → excessive) and ban excessive-risk uses
- Require algorithmic impact assessments for high-risk AI
- Governance, documentation and human-oversight duties for high-risk systems
- Guarantee individual rights (information, explanation, contestation, non-discrimination)
Developers, suppliers and operators of AI offered or used in Brazil (scope to be finalised).
Risk-based, modelled on the EU AI Act — tiered duties with outright prohibition of excessive-risk systems.
Proposed administrative fines (reported up to ~R$50M per infraction) — not yet in force.
- 2024-12-10 — Federal Senate approves the bill
- 2025-03-17 — Sent to Chamber of Deputies (still under review)
China GenAI Measures
China · Cyberspace Administration of China (CAC) + six agencies
China's first dedicated rules for public-facing generative AI. They impose content, data and transparency duties on providers offering generative AI to the Chinese public, including alignment with 'core socialist values' and security assessments / algorithm filings.
What it asks & details
What it asks
- Ensure generated content is lawful and reflects core socialist values
- Use legitimate data sources; respect IP and personal-information rules in training
- Label/identify AI-generated content
- Conduct security assessments and file algorithms with the CAC where required
Providers offering generative AI services to the public within mainland China.
Obligation-and-security-led oversight tied to service provision (not an EU-style risk taxonomy).
Warnings, rectification orders, service suspension and fines under the measures and underlying laws.
- 2023-08-15 — Effective
China AI Labelling Measures
China · Cyberspace Administration of China (CAC) + MIIT, MPS, NRTA
A comprehensive labelling regime requiring both visible ('explicit') and metadata/watermark ('implicit') labels on AI-generated text, images, audio, video and virtual scenes — widely described as the world's most comprehensive AI transparency-labelling framework.
What it asks & details
What it asks
- Add explicit (user-visible) labels to AI-generated/synthesised content
- Embed implicit labels (metadata + watermarks) identifying the provider
- App stores/platforms must verify and convey labelling status
- Prohibit removing, tampering with or forging required labels
Internet information service providers and content platforms generating/disseminating AI content in China.
Transparency/provenance-by-default across all AI-generated content.
Rectification orders, fines and suspension under the labelling and generative-AI/deep-synthesis rules.
- 2025-09-01 — Effective (with mandatory standard GB 45438-2025)
China Deep Synthesis / Algorithm rules
China · Cyberspace Administration of China (CAC) + MIIT, MPS, SAMR
Two earlier pillars of China's AI rulebook: the Deep Synthesis Provisions (deepfakes/synthetic media labelling and consent) and the Algorithm Recommendation Provisions (transparency, opt-out, anti-manipulation, and an algorithm registry).
What it asks & details
What it asks
- Label deep-synthesis (deepfake) content; obtain consent for biometric editing
- Disclose recommendation algorithms and offer an opt-out from personalisation
- Prohibit price discrimination and addictive/manipulative algorithmic design
- File significant algorithms in the CAC registry
Providers of deep-synthesis and recommendation services (and their users) operating in China.
Targeted conduct regulation of synthetic media and recommender systems, with a registry overlay.
Warnings, rectification orders, fines and service suspension.
- 2022-03-01 — Algorithm Recommendation Provisions effective
- 2023-01-10 — Deep Synthesis Provisions effective
Korea AI Basic Act
South Korea · Ministry of Science and ICT (MSIT) + National AI Committee
Asia's first comprehensive horizontal AI law, combining industry promotion with risk-based trust obligations. It introduces categories for 'high-impact AI' and generative AI, with transparency, safety and human-oversight duties and a domestic-representative requirement for large foreign providers. Effective Jan 2026 with a ~1-year enforcement grace period.
What it asks & details
What it asks
- Notify users in advance when they interact with generative or high-impact AI
- Label/disclose AI-generated outputs (esp. realistic deepfakes)
- Risk management, safety and human-oversight measures for high-impact AI
- Large foreign providers must designate a domestic representative in Korea
AI developers, providers and deployers affecting Korean users — including foreign companies (extraterritorial).
Risk-based, centred on 'high-impact AI' in sensitive domains plus generative-AI transparency.
Administrative fines up to KRW 30M (~USD 20k) for specified violations — modest vs. the EU AI Act.
- 2025-01-21 — Promulgated
- 2026-01-22 — Effective
- 2027-01 — End of ~1-year penalty grace period (approx.)
Japan AI Promotion Act
Japan · Cabinet Office — AI Strategy Headquarters (PM-chaired)
Japan's first AI-specific statute, deliberately non-punitive. It sets national objectives and coordination structures, relying on guidance, cooperation and existing sectoral laws rather than fines — a soft-law-plus framework to spur AI adoption.
What it asks & details
What it asks
- Establish the AI Strategy Headquarters and an AI Basic Plan
- Promote R&D, infrastructure and AI utilisation across government and industry
- Encourage responsible/ethical AI through guidance rather than mandates
- Provide for state fact-finding and guidance (no fines)
Primarily the national government, research institutions and businesses, as a coordination framework.
Innovation-first soft law: no risk tiers and no penalties; risks managed via guidance and existing laws.
None — enforcement relies on guidance, cooperation and existing sectoral laws.
- 2025-06-04 — Most provisions effective
- 2025-09-01 — AI Strategy HQ / Basic Plan provisions effective
Australia AI Safety Standard
Australia · Dept. of Industry, Science and Resources / National AI Centre
A voluntary standard of 10 'guardrails' of good-practice AI governance. The Dec 2025 National AI Plan confirmed Australia will rely on existing laws, sector regulators, voluntary guidance and a new AI Safety Institute — declining a standalone AI Act and immediate mandatory guardrails.
What it asks & details
What it asks
- Establish accountability and governance for AI
- Conduct risk management, data governance and security
- Test, monitor and maintain human oversight of AI systems
- Provide user transparency, contestability and record-keeping
Organisations across the economy that develop or deploy AI (voluntary adoption).
Voluntary, risk-management-based good practice; mandatory guardrails were proposed but shelved.
N/A — voluntary (existing laws and sector regulators still apply).
- 2024-09-05 — Voluntary AI Safety Standard released
- 2025-12-02 — National AI Plan declines mandatory guardrails / no AI Act
Singapore Model AI Framework
Singapore · IMDA + AI Verify Foundation
A pro-innovation, voluntary governance framework. The 2024 generative-AI edition sets nine dimensions (accountability, data, trusted development, incident reporting, testing/assurance, security, content provenance, safety, AI for public good); AI Verify provides a testing/governance toolkit. No binding AI statute.
What it asks & details
What it asks
- Establish accountability across the AI development chain
- Ensure data quality and address training-data/IP concerns
- Test, evaluate and provide assurance (AI Verify)
- Enable content provenance (watermarking/labelling) and incident reporting
Organisations developing/deploying AI — voluntary, but a de facto benchmark in procurement.
Voluntary, risk-proportionate, testing-and-assurance-led.
N/A — voluntary (PDPA still applies to data aspects).
- 2024-05-30 — Model Framework for Generative AI launched
- 2025-02 — Global AI Assurance Pilot
India AI Governance Guidelines
India · Ministry of Electronics and IT (MeitY); IndiaAI Mission
India's first comprehensive AI governance framework — deliberately pro-innovation and non-legislative, relying on existing laws (IT Act, DPDP Act 2023), new institutions and 'techno-legal' tools. Structured around six pillars and seven 'AI Sutras'.
What it asks & details
What it asks
- Apply existing laws (IT Act, DPDP Act) to AI rather than a new AI law (for now)
- Adopt a risk-based, phased approach with voluntary commitments
- Build institutions: AI Governance Group, expert committee, AI Safety Institute
- Use techno-legal tools (transparency, deepfake/content provenance, grievance redress)
AI developers, deployers and platforms in India (guidance; binding effect via underlying laws).
Risk-based and phased, pro-innovation with graduated/voluntary measures.
N/A for the guidelines — enforcement flows from existing statutes (IT Act, DPDP Act).
- 2025-11-05 — India AI Governance Guidelines released
OECD AI Principles
OECD (international) · Organisation for Economic Co-operation and Development (OECD)
The first intergovernmental AI standard: five values-based principles plus five policy recommendations, adopted by 47 adherents. The 2024 update added emphasis on generative/general-purpose AI, information integrity, safety, privacy/IP and sustainability.
What it asks & details
What it asks
- Pursue inclusive growth, sustainable development and well-being
- Respect human rights, democratic values, fairness and privacy
- Ensure transparency and explainability
- Ensure robustness, security and safety; hold AI actors accountable
Governments and AI actors in adhering countries — guidance, not law.
Values-based, risk-aware lifecycle guidance (non-tiered).
N/A — voluntary.
- 2019-05-22 — Adopted
- 2024-05-03 — Updated
G7 Hiroshima Code
G7 (international) · G7; monitoring hosted by the OECD (HAIP Reporting Framework)
A voluntary code of conduct for organisations developing advanced (frontier) AI, promoting transparency, risk management and accountability. The 2025 OECD-hosted reporting framework lets companies disclose comparable information on their AI risk-management practices.
What it asks & details
What it asks
- Identify, assess and mitigate risks across the AI lifecycle
- Be transparent and publicly report capabilities and limitations
- Share information and report incidents
- Invest in security (incl. model weights) and content authentication/provenance
Organisations developing the most advanced AI systems (frontier/foundation models) — voluntary.
Voluntary lifecycle risk management for advanced AI.
N/A — voluntary.
- 2023-10-30 — Code of Conduct issued
- 2025-02-07 — OECD HAIP Reporting Framework launched
UNESCO AI Ethics
UNESCO (international) · UNESCO
The first global standard-setting instrument on AI ethics, grounded in human rights and dignity, adopted by all 193 member states. It sets values and principles plus 11 policy-action areas, implemented via tools like the Readiness Assessment Methodology and Ethical Impact Assessment.
What it asks & details
What it asks
- Protect human rights, dignity and human oversight of AI
- Ensure transparency, explainability, fairness and non-discrimination
- Strengthen data governance and privacy protection
- Conduct Ethical Impact Assessments and build national readiness
UNESCO member states (and, through them, AI actors) — guidance for national policy.
Human-rights-based ethics framework with proportionality and impact-assessment tools.
N/A — voluntary.
- 2021-11-23 — Adopted by 193 member states
ISO/IEC 42001
International (ISO/IEC) · ISO/IEC JTC 1/SC 42
The world's first certifiable AI management-system standard. It specifies requirements to establish, implement, maintain and improve a governance system for responsible AI across the lifecycle. Like ISO 27001, it is auditable and organisations can be formally certified by an accredited body — increasingly used as the practical route to demonstrate EU AI Act compliance.
What it asks & details
What it asks
- Establish an AI policy, objectives and assigned accountability (Clauses 4–10)
- Run AI risk assessment and AI system impact-assessment processes
- Apply Annex A controls (data management, transparency, human oversight, lifecycle)
- Monitor, internally audit, review and continually improve
Any organisation that develops, provides or uses AI products or services, regardless of size or sector.
Risk-based, lifecycle-oriented Plan-Do-Check-Act management system.
N/A — voluntary standard (non-conformance means loss/denial of certification).
- 2023-12-18 — Published (first edition)
- 2024 — First accredited certifications issued
ISO/IEC 23894
International (ISO/IEC) · ISO/IEC JTC 1/SC 42
Guidance (not itself certifiable) on managing AI-specific risk across the lifecycle. It adapts the generic risk-management standard ISO 31000 to AI, adding AI-specific risk sources and process steps, and is commonly used to operationalise the risk-management requirements inside ISO 42001.
What it asks & details
What it asks
- Apply ISO 31000 principles and process to AI contexts
- Identify AI-specific risk sources (bias, opacity, data quality, autonomy)
- Assess and treat risks across the AI lifecycle
- Document risk management as an ongoing, iterative activity
Organisations that develop, produce, deploy or use AI systems, services or products.
ISO 31000-aligned, lifecycle-based AI risk management.
N/A — voluntary guidance standard.
- 2023-02 — Published (first edition)
ISO/IEC 42005
International (ISO/IEC) · ISO/IEC JTC 1/SC 42
Guidance for conducting AI system impact assessments — how an AI system and its foreseeable uses may affect individuals, groups and society. A companion to ISO 42001, designed to feed the impact-assessment process its management system requires.
What it asks & details
What it asks
- Define when and how to perform AI impact assessments
- Assess impacts on individuals, groups and society
- Document assessment scope, process and results
- Repeat assessments across the lifecycle
Organisations developing or deploying AI that want a structured impact-assessment method.
Impact-focused — evaluate societal/individual harms throughout the lifecycle.
N/A — voluntary guidance standard.
- 2025 — Published (first edition)
ISO/IEC 27001
International (ISO/IEC) · ISO/IEC JTC 1/SC 27
The flagship certifiable information-security management standard and the security baseline that ISO 42001 builds on — a practical prerequisite for trustworthy AI (data confidentiality, integrity, availability). The 2022 revision restructured Annex A into 4 themes and 93 controls.
What it asks & details
What it asks
- Establish an ISMS with leadership commitment and scope (Clauses 4–10)
- Conduct information-security risk assessment and treatment
- Apply Annex A controls (93 controls) and maintain a Statement of Applicability
- Undergo certification audit by an accredited body
Any organisation wanting to protect information assets; broadly applicable across sectors.
Risk-based ISMS — identify, treat and monitor information-security risks.
N/A — voluntary standard.
- 2022-10-25 — ISO/IEC 27001:2022 published
- 2025-10-31 — End of transition from the 2013 edition
FDA AI Medical Devices
United States (Healthcare) · US FDA — Center for Devices and Radiological Health
The FDA regulates AI/ML-enabled medical devices through its existing device pathways plus AI-specific tools. The headline mechanism is the Predetermined Change Control Plan (PCCP, finalised Dec 2024), letting manufacturers pre-authorise specified future model changes, reinforced by Good Machine Learning Practice and a total-product-lifecycle approach.
What it asks & details
What it asks
- Clear/authorise AI devices via 510(k), De Novo or PMA
- Submit a PCCP describing planned modifications and their impact
- Apply the 10 GMLP guiding principles (data quality, validation, human factors)
- Maintain post-market monitoring and real-world performance oversight
Manufacturers of AI/ML-enabled medical devices marketed in the US.
Risk-based premarket review plus a lifecycle model allowing controlled, pre-specified change.
FDA enforcement (warning letters, recalls, seizure, injunctions, civil penalties) for unauthorised marketing.
- 2024-12-03 — Final PCCP guidance published
- 2025-01 — Draft AI lifecycle-management guidance
US Model Risk Management
United States (Finance) · Federal Reserve, OCC and FDIC (interagency)
Model risk management is the US supervisory backbone for risks from quantitative models, and its broad 'model' definition has long covered AI/ML and credit models. The original SR 11-7 (2011) was rescinded on April 17, 2026 and replaced by modernised, principles-based interagency guidance (OCC Bulletin 2026-13), with an AI-specific request for information signalled.
What it asks & details
What it asks
- Sound model development, implementation and use
- Independent model validation, ongoing monitoring and benchmarking
- Effective model governance, policies, roles and an inventory
- Risk-tiered controls proportionate to model materiality
Banks and supervised financial institutions using quantitative models (incl. AI/ML) in decisions.
Principles-based, risk-tiered model risk management across the model lifecycle.
Guidance, not a rule — deficiencies can lead to supervisory findings and safety-and-soundness enforcement.
- 2011-04-04 — SR 11-7 issued
- 2026-04-17 — SR 11-7 rescinded; revised interagency guidance issued
No frameworks match those filters.
Standards vs legislation — how they differ
Legislation sets the legal obligation and the penalties; standards and voluntary frameworks supply the auditable method to meet them. ISO/IEC 42001 and the NIST AI RMF are increasingly the practical route to demonstrate EU AI Act compliance and serve as recognised safe-harbour frameworks in US state laws.
| Framework | Type | Legally binding | Certifiable | Risk model | Geographic scope | Penalties |
|---|---|---|---|---|---|---|
| EU AI Act | Law (regulation) | Yes | No (conformity assessment) | 4-tier risk pyramid + GPAI | EU + extraterritorial | Up to €35M / 7% turnover |
| Colorado AI Act | State law | Yes (from 2027) | No | Narrowed ADMT disclosure | Colorado | AG enforcement, no private action |
| Korea AI Basic Act | Law | Yes | No | High-impact AI + GenAI | South Korea + extraterritorial | Up to ~KRW 30M |
| NIST AI RMF | Voluntary framework | No | No | Govern/Map/Measure/Manage | Global (US-origin) | None |
| ISO/IEC 42001 | Standard | No | Yes (accredited) | Lifecycle AIMS (PDCA) | Global | None (loss of certification) |
| ISO/IEC 23894 | Standard (guidance) | No | No | ISO 31000-aligned AI risk | Global | None |
| OECD AI Principles | Intergovt. recommendation | No | No | Values-based principles | 47 adherents | None |
How this is built. Each entry is curated from official primary sources (EUR-Lex, national regulators, ISO/IEC, NIST, FDA and others) and re-checked monthly, with a per-entry "last change" date so you can see what moved. It is general orientation, not legal advice — always confirm against the official source and qualified counsel.