Multilateralism and collaboration are surrendering to unilateralism, bilateralism, and competition in international relations. In this competitive and volatile geopolitical context, AI has become one of the most popular battlefields for nations competing for economic and security leadership.
Once upon a time, AI technologies were of interest primarily to researchers, tech firms, and specialized business and government teams that used them to help detect fraud, for example. The introduction of GenAI has changed all that, catapulting AI into the consciousness of regular employees and citizens.
Although our understanding of its real impact on business and our personal lives continues to fluctuate between hype and worrying ramifications, one thing is clear: AI is driving political agendas.
Nations are implementing digital sovereignty policies and strategies that encompass AI sovereignty as a bulwark of economic competitiveness and security. Two years after the release of ChatGPT, the world is reaching a climax of these AI sovereignty political power battles.
On January 13, the U.S. Department of Commerce’s Bureau of Industry and Security, still under the Biden administration, announced export controls on advanced computing chips and certain closed AI model weights, alongside new license exceptions and updates to the Data Center Validated End User (VEU) authorization.
The same day, the U.K. Secretary of State for Science, Innovation and Technology presented the AI Opportunities Action Plan, which sets the goal for the country “to provide global leadership in fairly and effectively seizing the opportunities of AI, as the U.K. have done on AI safety.”
One week later, under the new Trump administration, the Stargate Project, a $500 billion four-year initiative to build new AI infrastructure for OpenAI in the United States, was announced. A week after that, the DeepSeek frenzy disrupted financial markets. On February 11, the President of the European Commission announced a plan that aims to mobilize €200 billion for AI. Even emerging countries, like Kazakhstan, are making their own investments.
From an economic competitiveness perspective, political leaders want to promote the growth of the national AI innovation ecosystem and ensure the resilience of their AI supply chains. From a national security perspective, they consider AI a means to protect their countries from kinetic and non-kinetic threats.
In this fast-evolving landscape, three archetypes of AI sovereignty are emerging. Countries’ positioning across the range of archetypes indicates how policy and regulation will evolve and impact technology suppliers.
The Three Archetypes of AI Sovereignty Policy
A full analysis of AI sovereignty policies — and their theoretical foundations in geopolitical strategies or data protection — is beyond the scope of this blog post. However, it is possible to compare archetypes by observing key dimensions, including:
• The strategic posture of the country defines what the nation commits to in the long term.
• The approach to AI governance determines how policymakers make decisions.
• The programs a country puts in place determine how the long-term vision translates into execution.
Taking those dimensions into account, three AI sovereignty archetypes are emerging.
Figure 1 — AI Sovereignty Policy Archetypes
- Global AI Powerhouses: There are just two global powerhouses: the U.S. and China. They aim for dominance. They have the power to unilaterally make decisions and bilaterally influence partner countries. They prioritize being at the frontier of technology innovation over responsible AI innovation. They take different approaches, however: The U.S. allows the private sector choose whether and how to develop and use AI responsibly and ethically; in China, the national government applies more direct control over private sector practices. Both have the sheer critical mass for heavy investments across the AI value chain, from talent to the raw materials that go into chips manufacturing. They have such a big internal markets, both from the supply and demand perspectives, that they can afford to dictate a “made in …” approach to public procurement.
- Aspirational AI Leaders: This cluster includes countries or regional blocs like the U.K., the EU, and Japan. It is important to note that within the EU, for example, there are nuances in terms of balance between EU multilateralism and partnerships with the U.S. or other countries. These countries aspire to leadership status but they simply do not have the critical mass on their own to dominate. They thus selectively invest in strategic areas, such as AI computing infrastructure for R&D, national security and defense, critical infrastructure protection, and public sector AI use cases. They keep their markets open for collaboration with non-domestic tech suppliers that comply with their regulations. The U.K.’s AI Opportunities Action Plan, for example, acknowledges that “Sovereign AI compute will almost certainly be the smallest component of the U.K.’s overall compute portfolio.” These countries are making a political and strategic commitment to responsible use and safe use of AI by fostering multilateral collaboration, and prioritizing investments in open source, such as the new European Commission plan. They apply a strict approach toward data protection risks. The strict approach to data protection and the ethical use of AI, which inspires policies and regulations like the EU’s GDPR and AI Act, can increase the cost of doing business for international tech suppliers. These countries are also investing in digital inclusion, for instance, by supporting the development of LLMs that cater to minorities.
- Regional Dynamos: This cluster includes countries like Saudi Arabia, India, Türkiye, and Russia that aspire to become the kernel of regional AI economies, under their political influence, while establishing a foundation to influence the global AI market. Saudi Arabia’s National Strategy for AI, for example, aims to “Position KSA as the global hub where the best of Data & AI is made reality” and, by 2030, to compete on the international scene as a leading economy utilizing and exporting data and AI. Some, like Russia, are more aligned with one of the powerhouses. But most regional dynamos take an opportunistic approach to governance and international collaboration to accelerate their economic competitiveness. They are open to non-domestic tech suppliers because they need to fill AI supply chain, AI computing infrastructure, and talent gaps. However, they have set up regulatory and financial incentives to ensure that global tech suppliers commit to making local investments, hire local talent, and collaborate with local partners.
The Silver Lining for the Tech Industry
In a complex and competitive geopolitical environment, tech suppliers that need to make AI supply chain, computing infrastructure, product and solution, talent, marketing, and sales investments should carefully align their strategic choices to maximize the ROI they can realize in different countries and regions.
- With respect to global AI powerhouses, tech suppliers should prioritize one of them in terms of AI supply chain and AI computing infrastructure. They should leverage closer alignment with that powerhouse as a door opener to strengthen their positioning in partner countries. But they should also continue to observe the evolution of AI innovations developed by opposing powerhouses. This is important to understand how their road map and ecosystem could benefit from those innovations. They should also consider selected reseller agreements to go to market with an opposing powerhouse.
- With respect to aspirational AI leaders, tech suppliers should position the breadth of their AI solution portfolio to show business and government buyers in different countries how their solutions can provide speed of innovation, agility, and scalability. Suppliers can enhance their positioning in these countries by helping local ecosystem players get value out of government AI innovation programs. They should articulate how they can provide tools and practices to help assess the risks of AI and innovate responsibly, in line with ethical principles, security standards, and regulations.
- With respect to regional dynamos, tech suppliers will have to selectively coinvest with local partners in AI computing infrastructure, open innovation hubs to collaborate with partners and customers, and train and hire local talent.
Tech suppliers that do not consider these AI sovereignty policies when making strategic decisions risk losing market share — or worse, they may face compliance actions by government regulators.