What does AI sovereignty mean in practice, and why are governments increasingly focused on it?

AI sovereignty refers to a nation's ability to maintain control over AI technologies, infrastructure, and data to ensure independence from foreign dependencies, particularly in critical areas like public services, military applications, and economic competitiveness [1][3][4][11]. In practice, this involves developing domestic AI capabilities, such as sovereign AI-based public services that are viable and affordable without relying on concentrated foreign infrastructure, and leveraging decentralized systems for "infrastructural sovereignty" where AI agents can persist and act with non-overrideable control [2][4]. Governments may pursue nationalization of AI development to mitigate risks from tech oligarchs, enforce sector-specific regulations for comparative advantages, and align infrastructure with regional needs, like Europe's digital sovereignty through partnerships [5][6][8]. Governments are increasingly focused on AI sovereignty due to escalating geopolitical tensions, such as the US-China AI race viewed as an existential strategic battle requiring domestic critical infrastructure and export controls [10]. Concerns over structural concentration in AI expertise, potential unavailability of foreign technologies (e.g., US military AI not shared with allies like South Korea), and the shift from safety to sovereignty as a priority for economic growth further drive this emphasis, alongside national security risks from privatized AI profits and over-investment bubbles [3][6][11].