Navigating the new reality of international AI policy

The rapid evolution of Artificial Intelligence continues to reshape global dynamics, prompting a scramble among nations to establish regulatory frameworks. While early 2025 hinted at increased international cooperation, the current landscape reveals a significant pivot towards national priorities, with countries prioritizing domestic innovation and leadership in what many are calling “the global AI race.”

This shift presents a complex new reality for international AI policy. The initial enthusiasm for harmonized global standards, exemplified by efforts from bodies like the UN, Council of Europe, and the EU, appears to have yielded to a more fragmented approach. The European Union’s complete AI Act, now in various stages of implementation and facing industry concerns over deadlines, stands as a notable attempt at a unified regional framework. However, even its leadership is seen more through a normative lens than a technological one.

Across the globe, the focus is increasingly on national AI strategies. China, for instance, has embarked on a colossal $100 billion investment to secure its position as an AI superpower, with an industrial policy approach spanning hardware to software. India is also actively developing its regulatory framework, aiming for an ethical and inclusive approach, particularly in the realm of international trade. Meanwhile, the United States, while home to major AI innovators, is pursuing a more decentralized regulatory model, relying on state-level initiatives and a less direct government investment compared to China.

This divergence raises critical questions about the future of international AI governance. While some argue that a focus on national technological leadership is essential for competitiveness, others express concern that it could lead to regulatory gaps, hinder cross-border collaboration, and exacerbate existing inequalities between nations. The imperative to balance innovation with safety and ethical considerations remains paramount.

Despite the fragmentation, there’s a growing recognition of common underlying principles. Concepts like transparency, accountability, fairness, data privacy, and human oversight are emerging as cornerstones in various national and regional AI policies, as seen in frameworks like the OECD AI Principles and NIST’s AI Risk Management Framework.

The challenge now lies in finding mechanisms for interoperability and shared understanding amidst differing national priorities. While a single global AI policy may be a distant dream, continued dialogue, shared best practices, and collaborative efforts on specific risk areas like bias mitigation and cybersecurity will be crucial to navigating this new, complex reality of international AI policy. The world is watching to see if the race for AI dominance can ultimately pave the way for a more responsible and equitable technological future.