The Sovereignty Trap: National AI Strategies, Compute Nationalism, and the Fragmentation of the Global AI Supply Chain

Nations are increasingly treating artificial intelligence capabilities as matters of sovereignty - triggering a global wave of national AI strategies that combine industrial policy, compute infrastructure investment, data governance rules, and talent retention mechanisms into comprehensive programs designed to ensure that no nation is dependent on foreign AI capabilities for its economic competitiveness, national security, or democratic governance. India’s IndiaAI Mission invests in sovereign compute capacity and indigenous foundation models. The European Union’s compute sovereignty proposals aim to reduce dependence on US cloud hyperscalers. Gulf states are constructing AI cities as geopolitical positioning instruments. And US export controls on advanced semiconductors are reshaping the global compute supply chain by restricting China’s access to frontier AI hardware. This paper examines how this emergent ‘compute nationalism’ affects multinational enterprise AI strategy across three dimensions: infrastructure access and cost, talent flows, and market fragmentation. The paper introduces the Compute Sovereignty Impact Model (CSIM), which maps how sovereign AI initiatives create three enterprise-level disruption mechanisms: infrastructure bifurcation (separate compute stacks for different jurisdictions), talent pool fragmentation (national strategies competing for fixed global AI talent), and compliance multiplexing (maintaining parallel governance and deployment architectures per jurisdiction). Using evidence from India, the EU, the Gulf states, and the US-China technology decoupling, the paper demonstrates that the current trajectory leads to a fragmented global AI supply chain that increases enterprise infrastructure costs by an estimated 25–40%, reduces cross-border innovation velocity, and creates new forms of geopolitical risk. The paper proposes the Sovereign-Ready Enterprise Architecture (SREA) - a three-principle design framework for multinational AI systems that enables operation across sovereign compute environments while maintaining operational coherence. The paper concludes with implications for corporate geopolitical risk teams, government AI strategy advisors, and venture investors with cross-border AI portfolios.