Verified against the official source 26 Sep 2026 · reviewed by Bhaskar Bhatt (a factual check against the official source, not a legal review or legal advice)What this label means
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Pending review
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Source-linked
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Singapore has 7 recorded AI policy instruments, none of them binding. No binding cross-sector AI law. Regulators include Infocomm Media Development Authority (IMDA), Personal Data Protection Commission (PDPC), AI Verify Foundation. Singapore governs AI through voluntary frameworks, sector guidance and existing law rather than an AI statute.
Singapore governs AI through voluntary frameworks, sector guidance and existing law rather than an AI statute. The Model AI Governance Framework (second edition, 2020) and the Model AI Governance Framework for Generative AI (2024) set out practical governance expectations; AI Verify provides a testing framework and toolkit; the Personal Data Protection Commission has issued advisory guidelines on personal data in AI systems; and the National AI Strategy 2.0 (December 2023) sets national direction. The Monetary Authority of Singapore, IMDA and other regulators add sector-specific expectations.
What is the current regulatory status?
No binding cross-sector AI law. Binding obligations come from the Personal Data Protection Act 2012, the Online Safety framework, sector regulation and consumer law. AI governance frameworks are voluntary but widely referenced.
Binding rules versus guidance
Binding: Personal Data Protection Act 2012 (PDPA), Cybersecurity Act, sector rules (for example MAS requirements for financial institutions). Guidance / voluntary: Model AI Governance Framework, Generative AI framework, AI Verify, PDPC advisory guidelines on AI, MAS FEAT principles and Veritas.
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 2020Verified (reviewed by Bhaskar Bhatt; a factual check against the official source, not a legal review)Official source
Starter Kit for Testing Agentic Systems for Safety and Reliability
A practical reference for organisations starting to test AI agents that reason, act on a user's behalf, use tools and access data. It sets out four steps (identify risks such as erroneous or unauthorised actions; design and run realistic tests without real-world harm; analyse results and operational logs; monitor and retest continuously), tests the agent's whole trajectory of reasoning and actions rather than only its output, and suggests metrics such as tool-use accuracy, handoff accuracy and human-intervention rates. It extends the agentic AI governance framework and builds on the LLM starter kit.
Pending review (a factual check against the official source, not a legal review)Official source
Accredits third-party firms that test AI systems, in benchmarking and red teaming, for 12 months at a time; the first five were AIDX Tech, Knovel Engineering, PwC Singapore, Resaro and Vulcan. Accreditation does not certify that a tester is independent or that a tested system is safe.
Pending review (a factual check against the official source, not a legal review)Official source
A governance framework for AI agents that reason and act on a user's behalf, in four areas: assessing and bounding risks upfront, making humans meaningfully accountable, technical controls across the agent lifecycle, and enabling end-user responsibility. IMDA treats it as a living document and has since added case studies and input from more than 50 organisations.
Pending review (a factual check against the official source, not a legal review)Official source
National Artificial Intelligence Strategy 2.0 (NAIS 2.0)
Singapore's second national AI strategy, launched under the banner of AI for the public good. It sets goals of excellence and empowerment and organises work across three systems, ten enablers and fifteen actions covering talent, compute, data, industry adoption, research and governance. A 2026 update set ten refreshed priorities and launched sector AI Missions under the new National AI Council.
Adopted 4 Dec 2023Verified (reviewed by Bhaskar Bhatt; a factual check against the official source, not a legal review)Official source
PDPC Advisory Guidelines on Use of Personal Data in AI Recommendation and Decision Systems
These advisory guidelines explain how the Personal Data Protection Act applies when organisations use personal data to develop, test and deploy AI systems that make recommendations, predictions or decisions. They clarify the consent obligation and relevant exceptions (business improvement and research), what to include in notifications to individuals, accountability practices such as documenting data provenance and model development, and expectations for service providers building bespoke AI systems.
Adopted 1 Mar 2024Verified (reviewed by Bhaskar Bhatt; a factual check against the official source, not a legal review)Official source
Starter Kit for Testing LLM-Based Applications for Safety and Reliability (v1.0)
Voluntary guidelines for testing applications built on large language models against five risks: hallucination and inaccuracy, bias in decision-making, undesirable content, data leakage and adversarial prompts. Baseline tests are available on Project Moonshot.
Pending review (a factual check against the official source, not a legal review)Official source
Instruments at a glance
Native-language names are shown where the record carries one; a blank means the source is in English or the name is not yet recorded.
No future deadlines are recorded for Singapore; past milestones are listed on each policy page. New dates reach the calendar feed: Singapore feed · how it works
Current priorities
National AI Strategy 2.0 implementation, AI Verify and generative-AI evaluation (Project Moonshot), safety guidelines for model developers and app deployers, and international interoperability of AI governance.
@misc{aipolicytracker2026_airegulationinsingapore,
author = {{AIPolicyTracker}},
title = {{AI regulation in Singapore}},
year = {2026},
howpublished = {\url{https://aipolicytracker.org/jurisdictions/singapore}},
url = {https://aipolicytracker.org/jurisdictions/singapore},
urldate = {2026-10-27},
note = {Data licensed CC BY 4.0. Accessed 27 October 2026}
}
Frequently asked questions
Does Singapore have an AI law?
No. Singapore uses voluntary governance frameworks, testing tools and sector guidance, with binding obligations arising from the PDPA and sector regulation.
What is AI Verify?
AI Verify is a voluntary AI governance testing framework and open-source toolkit developed by IMDA and stewarded by the AI Verify Foundation, allowing organisations to test AI systems against internationally recognised governance principles.
Who regulates AI in Singapore?
Infocomm Media Development Authority (IMDA) (AI governance frameworks and AI Verify); Personal Data Protection Commission (PDPC) (PDPA and AI advisory guidelines); AI Verify Foundation (AI Verify testing framework and toolkit).
What is the status of AI regulation in Singapore?
No binding cross-sector AI law. Binding obligations come from the Personal Data Protection Act 2012, the Online Safety framework, sector regulation and consumer law. AI governance frameworks are voluntary but widely referenced.
Is there a national AI strategy in Singapore?
Yes: National Artificial Intelligence Strategy 2.0 (2023).
What is binding and what is only guidance in Singapore?
Binding: Personal Data Protection Act 2012 (PDPA), Cybersecurity Act, sector rules (for example MAS requirements for financial institutions). Guidance / voluntary: Model AI Governance Framework, Generative AI framework, AI Verify, PDPC advisory guidelines on AI, MAS FEAT principles and Veritas.
Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.
