Geopolitics and Generative AI — A New BattlegroundGeopolitics and Generative AI — A New Battleground

The way countries choose to regulate, adopt and leverage generative AI will shape their economic futures and their roles on the world stage: Gartner

Tsuneo Fujiwara, Distinguished VP analyst, Gartner

January 29, 2025

4 Min Read
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Generative AI has swiftly become a driving force, reshaping industries and economies worldwide. But its rapid adoption isn’t just about innovation; it’s also transforming the geopolitical landscape, fuelling a digital arms race among global superpowers. The way countries choose to regulate, adopt and leverage generative AI will shape not only their economic futures but also their roles on the world stage.

A Technological Power Shift

Imagine a world where AI not only augments human capabilities but also actively redefines global power dynamics. This isn’t a futuristic scenario—it’s today’s reality. The race to harness generative AI’s potential is intensifying, with nations and regions like the U.S., EU and China adopting markedly different approaches.

The U.S. has leaned into its innovation-first ethos, championing a relatively hands-off regulatory approach that allows startups and tech giants alike to thrive. Initiatives like the Biden administration’s AI Executive Order seek to establish safeguards while keeping the tech ecosystem flexible. On the other hand, the EU has opted for a structured framework, introducing the AI Act to prioritize ethical governance and consumer protections. Meanwhile, China’s focus on digital sovereignty has led to strict oversight, emphasizing content control and aligning AI technologies with state goals.

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These differing approaches are more than policy choices — they reflect competing ideologies in a fragmented digital ecosystem.

The Fragmentation of the Digital World

This divergence has sparked what some call the rise of the “Four Internets”—distinct digital spheres dominated by the U.S., EU, China and Russia. Each operates under its own set of rules, creating challenges for businesses and governments alike. Cross-border compliance, trade restrictions and cultural differences add layers of complexity for organizations looking to adopt generative AI at scale.

For example, the U.S. has implemented export controls on AI technologies, particularly chips used in advanced AI models, to limit China’s capabilities. Similarly, China mandates algorithm registries and strict data localization, while the EU’s risk-based framework scrutinizes AI applications for their societal impacts. These regulations are shaping not just the adoption of AI but the geopolitical alliances and tensions around it.

Opportunities and Risks for Businesses

For multinational companies, the geopolitics of generative AI is both a hurdle and an opportunity. Navigating this fractured landscape demands adaptability, foresight and strategic investment.

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  • Regulatory Complexity: Diverging regulations create compliance hurdles. Enterprises must adapt their AI deployments to meet jurisdiction-specific requirements, such as China's algorithm registry or the EU’s risk-based regulatory framework.

  • Trade and Supply Chain Risks: Sanctions and export controls, like U.S. restrictions on AI chips to China, disrupt supply chains and push nations toward self-sufficiency in critical technologies.

  • Ethical and Cultural Considerations: The ethical implications of AI, including bias and privacy concerns, vary widely across regions, requiring organizations to tailor their AI governance frameworks.

Recommendations for Organisations

  • Develop a Geopolitical AI Strategy: Businesses must conduct thorough geopolitical risk assessments to identify vulnerabilities in their AI deployments. Planning for technological decoupling, such as adopting composable architectures and edge operations, ensures continuity across fragmented markets.

  • Prioritise Regulatory Compliance: Establish robust monitoring systems to track regulatory changes. Validate AI outputs to align with jurisdictional standards, particularly around bias, ethics and privacy.

  • Invest in Localisation: Tailor generative AI models and applications to fit local requirements. Leveraging open-source and fit-for-purpose models can offer greater control over training data and ensure compliance with national laws.

  • Collaborate for Sustainability: Engage with policymakers and industry leaders to advocate for harmonized global standards that balance innovation with ethical governance. Public-private partnerships can play a crucial role in shaping the future of AI regulation.

As generative AI becomes more embedded in society, its role in shaping geopolitics will only grow. Nations are grappling with how to manage generative AI’s risks while maximizing its benefits and businesses must do the same. Collaborating with policymakers to advocate for harmonized standards, investing in localized models and preparing for a fragmented digital future will be key strategies for staying ahead.

The race to harness the power of generative AI is well underway. The stakes? Nothing less than the future of global power, economic growth and technological leadership. How nations and companies navigate this moment will define not just who leads in AI but who shapes the digital world of tomorrow.

About the Author

Tsuneo Fujiwara

Distinguished VP analyst, Gartner, Gartner

Tsuneo Fujiwara is a distinguished vice president, analyst and Gartner fellow. With 35 years of IT experience, his research focuses on digital business strategy and transformation, digital innovation including AI-driven, data-driven and business model innovation, with a focus on geopolitics, organizational culture change and emerging technology trends. 

Mr. Fujiwara has held various IT leadership positions in the financial services industry, successfully leading large-scale application development and digital business transformation projects on a global scale, including planning and delivery of IT cost optimization, paperless insurance applications, mobile claims apps, commission systems, ERP (SAP and Oracle), CRM (Salesforce) and regulatory compliance projects.

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