Navigating the New Reality of International AI Policy
The strategic direction of artificial intelligence (AI) policy has undergone a significant transformation since the beginning of 2025, shifting towards the ability of individual nation-states to win “the global AI race” by prioritizing national technological leadership and innovation.
As nations grapple with the implications of AI, the question arises: what does the future hold for international AI policy? Will there be a genuine appetite for addressing AI risks through testing and evaluation, or will discussions devolve into national adoption and investment priorities that stifle global collaboration?
The Upcoming AI Impact Summit
India’s upcoming AI Impact Summit in New Delhi in February 2026 offers an opportunity for national governments to advance discussions on trust and evaluations, even amidst ongoing tensions between ensuring AI safety and promoting its adoption. Governments should aim to foster a collaborative and globally coordinated approach to AI governance, focusing on minimizing risks while maximizing widespread adoption.
Paris: The AI Adoption Revolution Begins
The initial momentum for AI policies aimed at ensuring safety and addressing potential existential risks to humanity began at the first UK-hosted AI Safety Summit in Bletchley Park in 2023. Subsequent international summits in Seoul, South Korea, and San Francisco, California, further advanced these discussions. However, the AI Action Summit held in Paris in February 2025 signaled a shift, as discussions appeared to lose momentum.
At the AI Action Summit, French President Emmanuel Macron emphasized the need for “innovation and acceleration” in AI, while US Vice President JD Vance noted that “the AI future is not going to be won by hand-wringing about safety.” Yet, the United States and the United Kingdom opted not to join other nations in signing the Statement on Inclusive and Sustainable AI for People and Planet.
AI Investment and Adoption Mandates
In the United States, the Trump administration has initiated several changes, repealing previous executive actions related to AI and issuing requests for information to develop a new “AI Action Plan.” This plan emphasizes reducing regulatory burdens associated with AI development and prioritizing national security interests and economic competitiveness.
Despite ongoing debates over the federal government’s role in preempting state-level AI legislation, many state proposals on AI risk management have stalled. For example, Virginia’s proposed High-Risk Artificial Intelligence Developer and Deployer Act was vetoed, highlighting the challenges faced at the state level.
International Perspectives: The EU and G7
Across the Atlantic, the European Union (EU) continues to refine its cross-cutting EU AI Act as part of its AI Continent Action Plan. Industry leaders have expressed concerns about meeting enforcement deadlines without additional guidance. Meanwhile, the G7 Leaders’ Summit recently issued a statement focusing on the potential economic benefits of AI, emphasizing adoption over safety concerns.
Adapting to the Shift in Global AI Policy
As global AI policy discussions evolve, opportunities to advance conversations around AI trust and safety remain critical. Businesses require certainty, and fostering trust is essential for creating an ecosystem supportive of AI adoption.
Emerging technologies, such as agentic AI, which are designed to operate autonomously, necessitate ongoing discussions about what constitutes effective governance and risk management. The upcoming AI Impact Summit provides a platform to further explore these themes.
Key Areas for National Prioritization
To effectively navigate the future of AI, national governments should focus on four key areas:
- Assess Regulatory Gaps: Evaluate existing regulations to address new risks associated with evolving AI technologies.
- Advance Industry-Led Discussions: Promote transparency and collaboration around open-source and open-weight models, considering national security implications.
- Encourage AI Testing and Evaluation: Support the development of consensus-based AI testing and benchmarks to improve the reliability of AI systems.
- Drive Public-Private Collaboration: Recognize the interdependence of AI value chains and engage in international collaboration to enhance governance.
Conclusion
As the conversation around AI shifts towards adoption, it is crucial not to overlook the importance of addressing associated risks. A balanced approach that prioritizes both AI adoption and robust governance will ensure that AI technologies are implemented responsibly, paving the way for a safer and more innovative future.
