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AI Watch: Global regulatory tracker

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Keeping track of AI regulatory developments around the world.

The global dash to regulate AI

Artificial intelligence (AI) has made enormous strides in recent years and has increasingly moved into the public consciousness.

Increases in computational power, coupled with advances in machine learning, have fueled the rapid rise of AI. This has brought enormous opportunities, as new AI applications have given rise to new ways of doing business. It has also brought potential risks, from unintended impacts on individuals (e.g., AI errors harming an individual's credit score or public reputation) to the risk of misuse of AI by malicious third parties (e.g., by manipulating AI systems to produce inaccurate or misleading output, or by using AI to create deepfakes).

Governments and regulatory bodies around the world have had to act quickly to try to ensure that their regulatory frameworks do not become obsolete. In addition, international organizations such as the G7, the UN, the Council of Europe and the OECD have responded to this technological shift by issuing their own AI frameworks. But they are all scrambling to stay abreast of technological developments, and already there are signs that emerging efforts to regulate AI will struggle to keep pace. In an effort to introduce some degree of international consensus, the UK government organized the first global AI Safety Summit in November 2023, with the aim of encouraging the safe and responsible development of AI around the world. 

Most jurisdictions have sought to strike a balance between encouraging AI innovation and investment, while at the same time attempting to create rules to protect against possible harms. However, jurisdictions around the world have taken substantially different approaches to achieving these goals, which has in turn increased the risk that businesses face from a fragmented and inconsistent AI regulatory environment. Nevertheless, certain trends are becoming clearer at this stage:

  1. "AI" means different things in different jurisdictions: One of the foundational challenges that any international business faces when designing an AI regulatory compliance strategy is figuring out what constitutes "AI." Unfortunately, the definition of AI varies from one jurisdiction to the next. For example, the draft text of the EU AI Act adopts a definition of "AI systems" that is based on (but is not identical to) the OECD's definition, and which leaves room for substantial doubt due to its uncertain wording. Canada has proposed a similar, though more concise, definition. Various US states have proposed their own definitions, which differ from one another. And many jurisdictions (e.g., the UK, Israel, China, and Japan) do not currently provide a comprehensive definition of AI. Because several of the proposed AI regulations have extraterritorial effect (meaning more than one AI regulation may apply simultaneously), international businesses may be forced to adopt a "highest common denominator" approach to identifying AI based on the strictest applicable standard.
  2. Emerging AI regulations come in different forms: The various emerging AI regulations have no consistent legal form – some are statutes, some are executive orders, some are expansions of existing regulatory frameworks, and so on. The EU AI Act is a "Regulation" (which means that most of it will apply directly in all EU Member States, without the need for national implementation in most cases). The UK has taken a different approach, declining to legislate at this early stage in the development of AI, and instead choosing to task existing UK regulators with the responsibility of interpreting and applying five AI principles in their respective spheres. In the US, there is a mix of White House Executive Orders, federal and state initiatives, and actions by existing regulatory agencies, such as the Federal Trade Commission. As a result, the types of compliance obligations that international businesses face are likely to be materially different from one jurisdiction to the next. Many other jurisdictions have yet to decide whether they will issue sector-specific or generally applicable rules and have yet to decide between creating new regulators or expanding the roles of existing regulators, making it challenging for businesses to anticipate what form their AI regulatory relationships will take in the long term.
  3. Emerging AI regulations have different conceptual approaches: The next difficulty is the lack of a consistent conceptual approach among emerging AI regulations around the world – some are legally binding while others are not, some are sector-specific while others apply across all sectors, some will be enforced by regulators while others are merely guidelines or recommendations, and so on. As noted above, the UK approach is to use existing regulators to implement five AI principles, but with no new explicit legal obligations. This has the advantage of meaning that businesses will deal with AI regulators with whom they are already familiar but has the disadvantage that different UK regulators may interpret these principles differently in their respective spheres. The EU AI Act is cross-sectoral and creates new regulatory and enforcement powers for existing bodies, including the European Commission, and also creates entirely new bodies such as the AI Board and the AI Office, while leaving EU Member States to appoint their own AI regulators tasked with enforcing the AI Act. In the US, the Federal Trade Commission, Equal Employment Opportunity Commission, Consumer Financial Protection Bureau, and Department of Justice issued a joint statement clarifying that their existing authority covers AI, while various state regulators are also likely to have competence to regulate AI. International organizations including the OECD, the UN, and the G7 have issued AI principles, but these impose no legal obligations on businesses. In principle, these initiatives encourage consistency across members of each organization, but in practice this does not seem to have worked.
  4. Flexibility is a double-edged sword: In an effort to create AI regulations that can adapt to technological advances that have not yet been anticipated, many jurisdictions have sought to include substantial flexibility in those regulations, either by using deliberately high-level wording and policies, or by allowing for future interpretation and application by courts and regulators. This has the obvious advantage of prolonging the lifespan of such regulations by allowing them to be adapted to future technologies. However, it also creates the disadvantage of uncertainty because it leaves businesses uncertain of how their compliance obligations will be interpreted in the future. This is likely to mean that it is harder for businesses to know whether their planned implementations of AI will be lawful in the medium-to-long term and may make it harder to attract long-term AI investment in those jurisdictions.
  5. The overlap between AI regulation and other areas of law is complex: A substantial number of laws that are not directly focused on AI nevertheless apply to AI by association within their respective spheres, meaning that any use of AI will often trigger compliance issues and legal challenges even where there is not (yet) any enforceable AI-specific law. These areas of overlap include: IP (e.g., IP infringement issues with respect to AI model training data, and questions about copyright and patentability of AI-assisted inventions); antitrust; data protection (which adds restrictions to processing of personal data, and in some cases imposes special compliance obligations for processing carried out by automated means, including by AI); M&A (where AI innovation is driving dealmaking in many markets); financial regulation (where financial regulatory requirements may limit the ways in which AI can lawfully be deployed); litigation; digital infrastructure; securities; global trade; foreign direct investment; mining & metals; and so on. This overlap will mean that many businesses need to understand not just AI regulations in general, but also any rules that affect the use of AI in the context of the relevant sector or business activity.

Businesses in almost all sectors need to keep a close eye on these developments to ensure that they are aware of the AI regulations and forthcoming trends, in order to identify new opportunities and new potential business risks. But even at this early stage, the inconsistent approaches each jurisdiction has taken to the core questions of how to regulate AI is clear. As a result, it appears that international businesses may face substantially different AI regulatory compliance challenges in different parts of the world. To that end, this AI Tracker is designed to provide businesses with an understanding of the state of play of AI regulations in the core markets in which they operate. It provides analysis of the approach that each jurisdiction has taken to AI regulation and provides helpful commentary on the likely direction of travel.

Because global AI regulations remain in a constant state of flux, this AI Tracker will develop over time, adding updates and new jurisdictions when appropriate. Stay tuned, as we continue to provide insights to help businesses navigate these ever-evolving issues.



Voluntary AI Ethics Principles guide responsible AI development in Australia, with potential reforms under consideration.



The enactment of Brazil's proposed AI Regulation remains uncertain with compliance requirements pending review.

Sao Paulo


AIDA expected to regulate AI at the federal level in Canada but provincial legislatures have yet to be introduced.



The Interim AI Measures is China's first specific, administrative regulation on the management of generative AI services.


Council of Europe

The Council of Europe is developing a new Convention on AI to safeguard human rights, democracy, and the rule of law in the digital space covering governance, accountability and risk assessment.

European Union

European Union

The EU introduces the pioneering EU AI Act, aiming to become a global hub for human-centric, trustworthy AI.


European Union


France actively participates in international efforts and the EU AI Act negotiations, and proposes sector-specific laws.



The G7's AI regulations mandate Member States' compliance with international human rights law and relevant international frameworks.

G7 flags


Germany evaluates AI-specific legislation needs and actively engages in international initiatives.



National frameworks inform India’s approach to AI regulation, with sector-specific initiatives in finance and health sectors.



Israel promotes responsible AI innovation through policy and sector-specific guidelines to address core issues and ethical principles.



Italy plays a prominent role in EU AI Act negotiations and engages in political discussions for future laws.



Japan adopts a soft law approach to AI governance but lawmakers advance proposal for a hard law approach to generative AI foundation models.



Position paper informs Norwegian approach to AI, with sector-specific legislative amendments to regulate developments in AI.



The OECD's AI recommendations encourage Member States to uphold principles of trustworthy AI.

country flags


Singapore's AI frameworks guide AI ethical and governance principles, with existing sector-specific regulations addressing AI risks.



Spain creates Europe's first AI supervisory agency and actively participates in EU AI Act negotiations.



Switzerland's National AI Strategy sets out guidelines for the use of AI, and aims to finalize an AI regulatory proposal in 2025.



Draft laws and guidelines are under consideration in Taiwan, with sector-specific initiatives already in place.

Taiwan city

United Kingdom

The UK prioritizes a flexible framework over comprehensive regulation and emphasizes sector-specific laws.

London hero image

United Nations

The UN's new draft resolution on AI encourages Member States to implement national regulatory and governance approaches for a global consensus on safe, secure and trustworthy AI systems.

United Nations

United States

The US relies on existing federal laws and guidelines to regulate AI but aims to introduce AI legislation and a federal regulation authority.

New York city photo


Tim Hickman
Erin Hanson
New York
Dr. Sylvia Lorenz

AI Watch: Global regulatory tracker - Singapore

Singapore's AI frameworks guide AI ethical and governance principles, with existing sector-specific regulations addressing AI risks.

7 min read

Laws/Regulations directly regulating AI (the “AI Regulations”)

Currently, there are no specific laws, statutory rules, or regulations in Singapore that directly regulate AI. 

To strike a balance between allowing innovation in AI to develop, and safeguarding public interest in AI ethics and governance, the Singapore government has developed various frameworks and tools to guide AI deployment and promote the responsible use of AI, including:

  • The Model AI Governance Framework1 (2019, updated in 2020) (2020 Framework), which provides detailed guidance to private sector organizations to address key ethical and governance issues when deploying AI solutions
  • AI Verify2, an AI governance testing framework and toolkit designed to help organizations validate the performance of their AI systems against AI ethics principles through standardized tests. AI Verify was developed by the Infocomm Media Development Authority of Singapore (IMDA) in consultation with private sector organizations. IMDA has also set up the AI Verify Foundation (AIVF), a not-for-profit foundation to crowd in expertise from private sector organizations and the global open-source community to develop AI testing frameworks, standards and best practices
  • The National Artificial Intelligence Strategy 2.03 (first launched in 2019, updated in 2023) (NAIS 2.0), which outlines Singapore’s ambition and commitment to building a trusted and responsible AI ecosystem, driving innovation and growth through AI, and empowering its people and businesses to understand and engage with AI

In light of recent advances in generative AI, the AIVF and IMDA have also developed a draft Model AI Governance Framework for Generative AI4 (2024 Framework), which seeks to expand on the 2020 Framework by addressing new issues that have emerged from Generative AI and providing guidance on suggested practices for safety evaluation of Generative AI models. The 2024 Framework is currently undergoing public consultation and will be finalized within 2024.

Status of the AI Regulations

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. 

Other laws affecting AI

There are various laws that do not directly seek to regulate AI but may affect the development or use of AI in Singapore. A non-exhaustive list of key examples includes:

  • The Road Traffic Act 1961, which was amended in 2017 to allow for the testing and use of autonomous motor vehicles5
  • The Health Products Act 2007, which requires medical devices that incorporate AI technology to be registered before they are used6

In addition, various Singapore regulatory agencies have adopted soft-law approaches by issuing guidelines on the responsible use of AI. A non-exhaustive list of key examples includes:

  • The Personal Data Protection Commission of Singapore issued the Advisory Guidelines on Use of Personal Data in AI Recommendation and Decision Systems7 in 2024 to provide organizations with certainty on when they can use personal data to develop and deploy systems that embed machine-learning models
  • The Monetary Authority of Singapore issued the Principles to Promote Fairness, Ethics, Accountability and Transparency (FEAT) in the Use of Artificial Intelligence and Data Analytics in Singapore’s Financial Sector8 in 2018 (updated in 2019) to provide a set of foundational principles for firms to consider when using AI in decision-making in the provision of financial products and services
  • The Ministry of Health, Health Sciences Authority and Integrated Health Information Systems jointly issued the Artificial Intelligence in Healthcare Guidelines9 in 2021 to improve the understanding, codify good practice and support the safe growth of AI in healthcare

Definition of “AI” 

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. Accordingly, no clear definition of AI is currently recognized in Singapore’s national legislation. 

However, the 2020 Framework defines AI as “a set of technologies that seek to simulate human traits such as knowledge, reasoning, problem solving, perception, learning and planning, and, depending on the AI model, produce an output or decision (such as a prediction, recommendation and/or classification).”10

The 2024 Framework defines Generative AI as “AI models capable of generating text, images or other media. They learn the patterns and structure of their input training data and generate new data with similar characteristics. Advances in transformer-based deep neural networks enable Generative AI to accept natural language prompts as input, including large language models”.11

Territorial scope 

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. Accordingly, there is no specific territorial scope at this stage.

Sectoral scope 

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. Accordingly, there is no specific sectoral scope at this stage. Nevertheless, there are certain sector-specific laws and guidelines that have been implemented in Singapore to regulate the use of AI, examples of which have been listed in section 3 above.

Compliance roles 

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. Accordingly, there are currently no specific or unique obligations imposed on developers, users, operators and/or deployers of AI systems.  

Core issues that the AI Regulations seek to address

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. Nevertheless, the 2024 Framework proposes nine dimensions to be looked at in totality to foster a trusted ecosystem12:

  1. Accountability – allocation of responsibility to players along the AI development chain
  2. Data – ensuring quality of data fed to AI models through the use of trusted data sources
  3. Trusted development and deployment – encouraging transparency and disclosure to enhance broader awareness and safety
  4. Incident reporting – establishing incident-management structures and processes for timely notification and remediation
  5. Testing and assurance – adopting third-party testing against common AI testing standards to demonstrate trust to end-users
  6. Security – addressing risks of new threat vectors being injected through AI models
  7. Content provenance – developing technologies to enhance transparency about where and how content is generated
  8. Safety and alignment research & development – accelerating investment in research & development to improve model alignment with human intention and values
  9. AI for public good – harnessing AI to benefit the public by democratizing access, improving public sector adoption, upskilling workers and developing AI systems sustainably

The NAIS 2.0 also sets out Singapore’s long-term visions and goals with regard to AI, which includes working towards three systems through a series of “enablers”: “Activity Drivers (Enablers: Industry, Government, Research)”, “People & Communities (Enablers: Talent, Capabilities, Placemaking)”, and “Infrastructure & Environment (Enablers: Compute, Data, Trusted Environment, Leader in Thought and Action).”13

Risk categorization

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. The relevant frameworks and guidelines also do not set out an AI-related risk categorization. However, the 2024 Framework mentions that reporting of incidents should be proportionate and calibrated for practicality, and cites the EU AI Act as a potential reference point, which adopts risk categorization with regard to incident reporting.14

Key compliance requirements 

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. However, there are certain compliance requirements for the use of AI in certain sectors, such as health and transport, as explained in section 3 above.


Singapore does not currently have a specific designated regulator for AI, as the use of AI is currently governed by existing sectoral laws. However, the IMDA oversees the responsible adoption of AI across both public and private sectors, primarily through the aforementioned frameworks and guidelines. In addition, the Smart Nation and Digital Government Office, along with the Ministry of Communication and Information, issued the NAIS 2.0 and are responsible for implementing the national strategy for AI.

Enforcement powers and penalties 

As noted above, there are currently no specific laws or regulations in Singapore that directly regulate AI. As such, enforcement and penalties relating to the creation, dissemination and/or use of AI are governed by related violations in non-AI legislation.

1 The Model AI Governance Framework is available here.
Details of AI Verify are available here.
The National Artificial Intelligence Strategy 2.0 is available here.
The draft Model AI Governance Framework for Generative AI is available here.
The Road Traffic Act is available here, see Articles 6C and 6E
The Health Products Act is available here.
The Advisory Guidelines on Use of Personal Data in AI Recommendation and Decision Systems are available here
The Principles to Promote Fairness, Ethics, Accountability and Transparency (FEAT) in the Use of Artificial Intelligence and Data Analytics in Singapore’s Financial Sector are available here.
The Artificial Intelligence in Healthcare Guidelines are available here.
Please see the Model AI Governance Framework available here, page 18.
Please see the draft Model AI Governance Framework for Generative AI available here, page 3.
Please see the draft Model AI Governance Framework for Generative AI available here.
Please see the National Artificial Intelligence Strategy 2.0 available here, page 14.
Please see the draft Model AI Governance Framework for Generative AI available here, page 14.

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This article is prepared for the general information of interested persons. It is not, and does not attempt to be, comprehensive in nature. Due to the general nature of its content, it should not be regarded as legal advice.

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