Countries with clearer, more flexible copyright rules that don't restrict AI training are pulling ahead in artificial intelligence development, according to a major new analysis from Oxford Economics. The finding suggests that legal policy, not just computing power or talent, is becoming a decisive factor in the global AI competition. As governments across Asia-Pacific and beyond race to capture AI's economic potential, copyright frameworks are emerging as an overlooked but critical piece of the puzzle.

The stakes are enormous. AI could add up to $6 trillion to global GDP over the next decade, but where those gains materialize depends heavily on policy choices made today. The Oxford Economics report examined how copyright rules shape the AI ecosystem across seven Asia-Pacific countries, finding that legal certainty around AI training data creates measurable advantages in research, development, and investment attraction.

Why Does Copyright Policy Matter for AI Development?

At first glance, copyright law might seem like a dry legal matter with little relevance to cutting-edge AI. But copyright rules directly determine what data companies can use to train AI models. When copyright frameworks are restrictive or unclear, companies face legal uncertainty about whether they can use published works, news articles, books, and other copyrighted material to teach AI systems. This uncertainty discourages investment and slows innovation.

Conversely, countries with clear, flexible copyright rules that explicitly allow AI training create a more attractive environment for AI companies and researchers. These jurisdictions tend to perform more strongly across key dimensions of the AI value chain, particularly in frontier AI research and development. Legal clarity helps attract the investment, talent, and supporting infrastructure that frontier AI companies need to build next-generation models.

The report emphasizes that copyright policy is just one piece of a larger puzzle. Infrastructure quality, access to talent, investment capital, and broader ecosystem conditions all matter significantly. However, countries that combine legal certainty with strong ecosystem fundamentals appear best positioned to capture the economic benefits of AI.

How Can Organizations Manage AI Governance Today?

While copyright policy shapes the macro environment, individual organizations face immediate governance challenges as AI adoption accelerates. Many companies are discovering that employees are already using generative AI tools without formal approval or oversight. This creates practical risks around data security, confidentiality, and accuracy that require urgent attention.

• Identify Current AI Use: Map both formally approved AI systems and informal employee use of tools like ChatGPT or other generative AI platforms across the organization to understand where confidential information might be entering AI systems.
• Assess Legal and Regulatory Obligations: Recognize that existing laws around data protection, intellectual property, cybersecurity, and sector-specific regulation continue to apply to AI use, even where comprehensive AI legislation does not yet exist.
• Establish Clear Governance Policies: Develop an AI governance framework appropriate to your organization's size and risk profile, including rules about approved tools, handling of confidential data, processes for approving new applications, and requirements for human review of AI outputs.
• Protect Confidential Information: Implement safeguards to prevent employees from entering trade secrets, client data, or personal information into publicly available AI platforms without understanding how that information will be stored and processed.
• Review Third-Party Contracts: Assess agreements with AI providers, paying particular attention to data ownership, confidentiality, intellectual property rights, cybersecurity standards, data retention periods, and cross-border data transfer rules.

The challenge is particularly acute in regulated sectors like financial services, where AI is increasingly used for fraud detection, anti-money laundering monitoring, and customer onboarding. In these contexts, appropriate human review and verification of AI-generated outputs remain essential, especially where AI recommendations influence significant legal, regulatory, or commercial decisions.

What Happens When AI Governance Lags Behind Adoption?

Organizations that allow AI adoption to move faster than governance face real risks. Employees may unknowingly expose confidential information, process personal data inappropriately, or rely on inaccurate AI-generated content for important decisions. Generative AI systems can produce information that appears confident and authoritative while being inaccurate, incomplete, or misleading.

Data protection is one area requiring particular attention. Where an AI system processes personal data, organizations remain responsible for complying with applicable data protection laws. In Bahrain, for example, organizations must ensure that personal data processed through AI systems complies with the Personal Data Protection Law, including requirements around lawful processing, security measures, and cross-border data transfer rules.

The broader lesson is that AI should be considered within an organization's existing legal and compliance framework rather than treated solely as a technology issue. Legal, compliance, information security, IT, and business teams all have a role to play in determining how AI can be used safely and responsibly.

As AI adoption continues to accelerate globally, the gap between countries with clear copyright frameworks and those with legal uncertainty may widen. Similarly, organizations that establish governance structures now will be better positioned to adapt as regulatory landscapes develop, while those that delay governance decisions risk accumulating technical debt and compliance exposure. The priority for both policymakers and business leaders is not to anticipate every future development, but to establish clear rules and frameworks that can evolve as the technology matures.