🔴Illinois HB 3773IN EFFECTUp to ~$70K/violation|🔴Texas TRAIGA (HB 149)IN EFFECTAG-enforced|🔴Utah AI Policy ActIN EFFECT$2,500/violation|⚠️Colorado AI Act (SB 205)Jan 1, 2027AG-enforced|⚠️California SB 942Aug 2, 2026$5K/day|⚠️EU AI Act Art. 50Aug 2, 2026€35M or 7% revenue|⚠️New York RAISE ActJan 1, 2027AG civil penalties|
European Union · EU AI ActNo enacted AI-specific law - the AI Governance Bill remains pre-drafting; existing digital law binds

Malaysia AI Compliance Requirements

Mandatory and recommended controls under EU AI Act + national rules, including the role of the local data-protection authority.

Deadline: No AI-specific compliance deadline. The AI Governance Bill remains a pre-drafting proposal and imposes no obligation; the existing data-protection, cyber-security, online-safety and communications laws continue to apply.Penalty: No AI-specific penalty exists. NO SINGLE CURRENT PDPA FIGURE IS PRINTED HERE, AND THAT IS DELIBERATE: both official consolidations this project can read are pre-amendment. The Attorney General's Chambers' own updated reprint of Act 709 is stated 'As At 01-07-2023', and the Personal Data Protection Department's consolidated PDF is the 2022 version - in which section 5(2) makes contravention of the seven Personal Data Protection Principles an offence carrying a fine not exceeding RM 300,000 or imprisonment not exceeding two years, or both. The Personal Data Protection (Amendment) Act 2024 (Act A1727) is recorded in the register's own Amendment series and revised those penalties; no consolidated official text reflecting it is machine-readable from either portal today, so the amended figure is not asserted here. Check the gazetted amendment directly before relying on an amount.

How AI law works in Malaysia

Malaysia has not enacted an AI statute. That finding now rests on bounded source measurements rather than a rough register estimate: 1,699 rows across the Attorney General's Chambers' complete updated, amendment, repealed and revised principal-law title exports were screened, and Parliament's official full-text bill search was traversed for 13 English and Malay AI terms from 2015 through 22 September 2026. It produced 78 candidate bill documents; 72 PDFs were read, six broken PDF links were resolved from Parliament's own indexed snippets, and the only exact in-window hit was an unrelated biometric border-control provision. The separate proposed Artificial Intelligence (AI) Governance Bill is real but remains at PRE-DRAFTING consultation stage: the official consultation ran from 10 July to 1 August 2026, no bill code or tabled text exists, and it creates no obligation. Malaysia's AI-specific policy shelf contains six non-binding instruments kept separate from law: AI-Rmap 2021-2025, AIGE, the JPDP Automated Decision-Making and Profiling Guideline, the voluntary AI Code of Ethics, the Boardroom Primer, and AI Nation 2030. What binds an AI deployer is still the existing digital stack: the Personal Data Protection Act 2010, Cyber Security Act 2024, Online Safety Act 2025, Communications and Multimedia Act 1998 and Computer Crimes Act 1997.

Applicable laws

  • 📜 Proposed Artificial Intelligence (AI) Governance Bill (pre-drafting consultation closed 1 August 2026 - not tabled)
  • 📜 Act 709 - Personal Data Protection Act 2010 (amended by Act A1727, the Personal Data Protection (Amendment) Act 2024)
  • 📜 Act 866 - Online Safety Act 2025
  • 📜 Act 854 - Cyber Security Act 2024
  • 📜 Act 588 - Communications and Multimedia Act 1998
  • 📜 Malaysia National Artificial Intelligence Roadmap 2021-2025 (AI-Rmap - policy)
  • 📜 National Guidelines on AI Governance & Ethics (AIGE, 2024 - voluntary)
  • 📜 National AI Action Plan 2026-2030 (AI Nation 2030 - policy)

EU AI Act requirements begin with system risk assessment. Your organization must evaluate every AI system against the EU AI Act's risk framework: prohibited systems (facial recognition in law enforcement, social credit scoring, subliminal manipulation), high-risk systems (hiring, benefits determination, law enforcement, biometric ID), limited-risk systems (chatbots), and minimal-risk systems (game AI, spam filters). The legal requirement is to classify your system correctly. Misclassification — for example, claiming that a hiring AI is minimal-risk when it is high-risk — is itself a compliance violation. High-risk classification triggers the heaviest compliance burden: conformity assessment, bias and fairness testing, documented risk mitigation, human oversight, transparency, and record-keeping. If you are uncertain whether a system is high-risk, the safe assumption is to treat it as high-risk and apply the full compliance framework.

Pre-deployment conformity assessment is the core requirement for high-risk systems. Before deploying a high-risk AI system (or immediately, if it is already deployed), you must complete a documented assessment covering: data quality — are the training and decision-making data representative of the population affected by the system, and do they contain known biases?; model performance — does the model perform equally well across demographic groups, or is accuracy lower for protected groups?; system explainability — can you explain to an affected individual why the system made a particular decision?; human oversight design — what process allows an individual to escalate the AI decision to human review?; and risk mitigation — what controls have you implemented to reduce the risk of discriminatory outcomes? This assessment must be documented in writing, reviewed by qualified personnel, and updated at least annually.

Bias and fairness testing is a specific requirement for high-risk systems. The EU AI Act does not prescribe a particular testing methodology, but requires that your organization conduct documented testing and be able to demonstrate that you have evaluated the system for discriminatory impact across protected characteristics (race, color, religion, national origin, sex, gender identity, sexual orientation, disability, age, etc.). Testing must include: hold-out test data not used in training, representative of the affected population; evaluation of decision-rate parity across groups (does the AI approve loans at the same rate for all genders, races, and age groups?); and performance parity testing (does the AI make accurate predictions equally well across all groups?). Document test results, identify any disparate impact, and implement mitigation (rebalance training data, adjust decision thresholds, redesign features, or limit the system's scope).

Transparency and human-rights mechanisms are mandatory for all systems, with intensity scaling to risk level. For limited-risk systems (chatbots), you must disclose that the individual is interacting with AI. For high-risk systems, transparency is much deeper: you must inform affected individuals before the AI system makes a decision about them, explain what data the system is using, describe how the system works (at a non-technical level accessible to the individual), and provide the individual with a clear, accessible process to request human review and appeal the AI decision. In employment and benefits contexts, individuals must be able to request re-evaluation by a human reviewer, and that human review must be genuine — a human who has authority to override the AI decision and the information needed to make an independent judgment.

Ongoing monitoring, record-keeping, and individual-rights response are permanent obligations. You must monitor every high-risk AI system's performance and decisions on an ongoing basis (not just at deployment). Maintain audit logs of every high-risk decision for at least three years, capturing inputs, decision outputs, confidence scores, human-review flags, and any human override. When an individual requests an explanation of an AI decision, you must respond within 30 days with accessible, non-technical information about how the system works and why it made that particular decision. When an individual requests appeal or human review, you must provide it. Failure to respond to individual rights requests is a documented compliance violation and a source of private civil liability.

Malaysia compliance requirements, ranked

Mandatory under EU AI Act + GDPR

Risk classification per national framework + GDPR-equivalent DPIA
Public AI-use disclosure to end-users in their language
Human review path for adverse automated decisions (GDPR Art. 22)
Cooperation with Malaysia's supervisory authority + serious-incident reporting
Records sufficient to reconstruct each automated decision (3+ years)

Strongly recommended

Annual third-party bias / fairness audit
AI vendor due-diligence questionnaire (training data provenance, sub-processors, retention)
Cross-functional AI governance committee
Public-facing complaint mechanism

Country context

Applicable framework: Proposed Artificial Intelligence (AI) Governance Bill (pre-drafting consultation closed 1 August 2026 - not tabled)
Applicable framework: Act 709 - Personal Data Protection Act 2010 (amended by Act A1727, the Personal Data Protection (Amendment) Act 2024)
Applicable framework: Act 866 - Online Safety Act 2025
Applicable framework: Act 854 - Cyber Security Act 2024
Applicable framework: Act 588 - Communications and Multimedia Act 1998
Applicable framework: Malaysia National Artificial Intelligence Roadmap 2021-2025 (AI-Rmap - policy)
Applicable framework: National Guidelines on AI Governance & Ethics (AIGE, 2024 - voluntary)
Applicable framework: National AI Action Plan 2026-2030 (AI Nation 2030 - policy)
Regulator: see official sources block below for Malaysia's primary AI / data-protection authority.
Status: No enacted AI-specific law - the AI Governance Bill remains pre-drafting; existing digital law binds. Headline penalty exposure: No AI-specific penalty exists. NO SINGLE CURRENT PDPA FIGURE IS PRINTED HERE, AND THAT IS DELIBERATE: both official consolidations this project can read are pre-amendment. The Attorney General's Chambers' own updated reprint of Act 709 is stated 'As At 01-07-2023', and the Personal Data Protection Department's consolidated PDF is the 2022 version - in which section 5(2) makes contravention of the seven Personal Data Protection Principles an offence carrying a fine not exceeding RM 300,000 or imprisonment not exceeding two years, or both. The Personal Data Protection (Amendment) Act 2024 (Act A1727) is recorded in the register's own Amendment series and revised those penalties; no consolidated official text reflecting it is machine-readable from either portal today, so the amended figure is not asserted here. Check the gazetted amendment directly before relying on an amount..

More Malaysia resources

✅ AI Compliance Checklist💰 AI Law Fines & Penalties📖 AI Compliance Guide⏰ AI Law Deadlines← All Malaysia resources

Other countries

Germany (EU)France (EU)Netherlands (EU)Spain (EU)Italy (EU)Sweden (EU)
Editorial standards

Anchored to the primary government source (statute, bill text, or agency rule) and verified directly against it · Last verified Sep 22, 2026. See our methodology.

Primary sources · Malaysia
  • ↗lom.agc.gov.myhttps://lom.agc.gov.my/principal.php?type=updated
  • ↗lom.agc.gov.myhttps://lom.agc.gov.my/principal.php?type=amendment
  • ↗lom.agc.gov.myhttps://lom.agc.gov.my/subsidiary.php?type=pua
  • ↗parlimen.gov.myhttps://www.parlimen.gov.my/portal/carian.html?lang=en&uweb=web
  • ↗upc.mpc.gov.myhttps://upc.mpc.gov.my/view-consultation/264
  • ↗digital.gov.myhttps://www.digital.gov.my/en-GB/siaran/Kementerian-Digital-Mulakan-Libat-Uru…
  • ↗ai.gov.myhttps://ai.gov.my/governance/
  • ↗mosti.gov.myhttps://www.mosti.gov.my/wp-content/uploads/2022/08/AIR-Map-Playbook-Overall-…
  • ↗mosti.gov.myhttps://www.mosti.gov.my/wp-content/uploads/2024/09/NATIONAL-GUIDELINES-OF-AI…
  • ↗pdp.gov.myhttps://www.pdp.gov.my/ppdpv1/akta/akta-pdp-2010-my/