AI has increasingly become one of the key strategic areas global governments are focused on – with each aiming to secure the talent, data, and infrastructure to build and control advanced systems at home. This push — which NVIDIA’s Jensen Huang has popularized as sovereign AI — reflects a broader return of state power to global markets.
On a recent webinar, the Jefferies Washington Strategy Team spoke with Professor Ahmed Banafa of San Jose State University, who highlighted five key themes shaping this competition.1
- Defining Sovereign AI
Sovereign AI is a nation’s ability to develop, deploy, and govern AI on its own terms. It’s about achieving autonomy across the full AI stack — data, infrastructure, and algorithms — so countries maintain strategic control. Unlike nationalization, which means direct government ownership, sovereign AI often includes private companies working in step with national goals. The U.S. shows this model in action through public-private partnerships and export controls, like the recent NVIDIA deal requiring 15% of revenue from China-bound chip sales to go to the federal government.
- Major Powers in the Lead
The race for AI sovereignty is intensifying among major powers. China has narrowed its AI gap with the U.S. to roughly a year, leveraging civil-military fusion and partnerships with firms like Alibaba and Huawei to target global leadership by 2030. The EU is pushing GAIA-X, an effort to build a secure, interoperable cloud that avoids reliance on U.S. giants like Amazon and Microsoft. But fragmented regulations and slower innovation remain hurdles for Europe’s competitiveness.2
- Middle Powers on the Rise
Countries like Saudi Arabia and the UAE are emerging as important players in the sovereign AI landscape. Saudi Arabia’s HUMAIN initiative launched ALLAM, an Arabic-language generative AI model, alongside plans to train one million citizens in AI. The UAE is investing heavily in data centers and domestic infrastructure. These moves reflect a broader shift: regional AI ecosystems forming outside the U.S.–China axis, with ambitions to cut dependence on foreign tech by the early 2030s.
- Opportunities and Risks
Sovereign AI can boost security, protect privacy, spur local economies, and create high-skilled jobs. It also supports autonomy in critical sectors like healthcare, finance, and defense. But the trade-offs are real: high infrastructure costs, siloed ecosystems, risks of bias from localized datasets, and limited talent diversity. These factors could slow innovation and lead to duplicative efforts across borders.
- Global Norms vs. Fragmentation
Efforts at global AI standards — through the UN, for example — may help set rules around privacy, ethics, and explainability (how an AI arrives at its outputs). These norms may help mitigate risks of unchecked AI proliferation and foster transparency across borders. However, with geopolitical competition and divergent regulatory philosophies, fragmentation is likely to persist.
The Implications for Investors
The push for sovereign AI favors domestic hardware makers, cloud infrastructure providers, and compliance specialists. NVIDIA, AMD, and firms advising on regulation stand to benefit. At the same time, investors need to account for volatility tied to export controls, shifting alliances, and uneven regulation. Key moves to watch include government funding levels, commitments to domestic buildouts, and the emergence of new regional AI hubs.
Looking Ahead
Sovereign AI is both an engine of innovation and a source of geopolitical friction. For investors and policy-makers, the challenge is to anticipate how governments will wield their power — and to position ahead of a future where AI leadership is defined less by global tech platforms and more by national borders.
Find more insights from the Jefferies Washington Strategy Team at Jefferies Insights.
