The global Artificial Intelligence (AI) race is accelerating, with new rival frameworks making AI increasingly a tool of geopolitical power. Technology and risk leaders now face the challenge of navigating diverging regulatory and ideological landscapes, particularly among the U.S., China and Europe. The U.S. and China are now clearly on adversarial footing, with each seeking to “dominate” the future of AI and quantum computing. For multinationals operating across multiple continents, now is a critical time to understand the geopolitics involved, as foundational decisions made today will have long-reaching implications over the next few years.
Ironically, the increasingly ideological approaches taken by the U.S. and China may be propelling Europe, despite lagging in AI development, into a potential leading spot as enterprises determine how to govern AI ecosystems and maintain autonomy and competitiveness across global markets.
I spend a lot of time in Asia and the global south (I’m actually writing this in New Zealand), and while the competing stakes for the influence of the global south are high, many countries and enterprises don’t want to pick sides if they can avoid it.
However, these smaller countries are challenged to muster the resources to build their own stacks from the ground up, so it’s going to be a very interesting couple of years as this tug of war accelerates. One thing is clear: the “big brothers” – U.S. and China – want everyone to pick a side, and pick it soon.
While some alliances are clear and obvious already, this is going to be a harder choice with longer-reaching implications than many realize.
Geopolitical Stakes in AI Regulation
Both the U.S. and China are embedding their own ideological and strategic priorities into AI governance, transforming technology standards into extensions of foreign policy and economic leverage. For global enterprises, this escalating rivalry poses risks of vendor lock-in, political entanglement and diminished operational autonomy.
As Washington and Beijing promote their competing AI “stacks,” multinational companies are increasingly pushed to take sides or face trade-offs between market access, technological flexibility and regulatory compliance. Choosing the “wrong” stack could impair market access, complicate global operations, and limit future competitiveness.
The U.S. Approach: Deregulation and Ideological Filters
The U.S. centers its AI agenda around innovation, light regulation, and exporting a full “American AI stack” to allies. America’s recently published AI Action Plan emphasizes “ideological neutrality” in AI development. This means excluding datasets tied to DEI or climate change and promoting “objective,” truth-seeking models.
This approach positions U.S. technology as “unbiased” but impairs usefulness for markets that prioritize climate action or diversity—most notably Europe. The American export strategy can create lock-in, especially if future policy shifts or global integration become necessary.
The China Approach: Self-Reliance and Strategic Control
U.S. export controls have prompted China’s drive for a domestic, “controllable” AI ecosystem. Through its Global AI Governance Initiative (GAIGI), Beijing champions a ‘more inclusive’ set of standards to help China influence and win over the Global South. China also leverages open-source models to enhance global influence while allowing partner countries greater customization.
At home, China’s “safety-driven, people-centered” regulation is not only pushing AI literacy but also driving AI-led surveillance and stringent content controls, including adherence to “socialist principles.” This introduces significant legal and ethical risks for multinationals, especially in terms of privacy, data protection, and potential complicity in state-driven rights violations.
Europe’s Third Way: The Pragmatic Path of the EU AI Act
As one of the world’s most experienced regulators, the EU and the EU AI Act offer the world’s first comprehensive horizontal framework for AI, grounded in rights, safety, transparency, and accountability. Its risk-based approach bans the most dangerous uses (e.g., social scoring) while tightly regulating high-risk applications spanning biometrics, law enforcement, and critical infrastructure.
With its extraterritorial scope mirroring the “Brussels Effect” seen in GDPR, the Act’s rules apply to any AI system used in or impacting the EU market. The result is that compliance with EU standards is becoming a strong baseline for global AI deployment. Non-compliance poses severe penalties: up to €35 million or 7% of global turnover. While some warn the Act could dampen innovation, especially for startups, several countries are already adopting similar frameworks, recognizing the value of balancing innovation and risk.
Implications & Strategic Guidance for Technology Leaders
- Don’t “Fall Into” Geopolitical Lock-In: If you choose either the US or Chinese stack, do it on purpose, or consider if your enterprise would be better served via “AI agnosticism,” to minimize conflict-of-law risks as regulations tighten and diverge.
- Strengthen Internal Governance: If you aren’t already, now is the time to establish robust, proactive AI governance. The decisions we make today are going to stick with us.
- Integrate Geopolitical Intelligence: Security leadership should now extend beyond technical protection to encompass geopolitical risk, integrating intelligence into strategy to anticipate regulatory shifts and supply chain considerations.
Strategic Insight
What is important is making decisions on purpose, rather than “falling into” a standard based on what your technology teams are playing with in the lab. The AI race condition isn’t slowing down anytime soon, so before you choose a car to hop in, make sure it’s going where you need to go.
In other words, the key to winning your race is making sure you maintain the autonomy to steer your own destiny, and things aren’t getting any easier for multinationals in an era of exponential advancement and geopolitical change.
