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. The EU is also implementing the first comprehensive horizontal legal framework for the regulation of AI systems across EU Member States (the EU AI Act is addressed in more detail here: AI watch: Global regulatory tracker - European Union, and you can read our EU AI Act Handbook here).

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 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 EU 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.