Menlo Park, Calif. – – September 12, 2026 -- A new report from the Ethical AI Governance Group (EAIGG) and Draup argues that national AI advantage depends on strategic interdependence rather than complete technological self-sufficiency, challenging a core assumption driving global AI policy.
Report introduces scorecard ranking five national AI ecosystems
The AI Sovereignty Paradox: Why AI Advantage Depends on Interdependence unveils the Global AI Adoption Scorecard, a framework assessing national AI readiness across talent, infrastructure, data ecosystems, innovation, capital formation, and policy. The inaugural study benchmarks five ecosystems—the United States, Israel, France, India, and Japan—to determine how AI capability converts into economic and strategic advantage.
Researchers reject full national control as the definition of AI sovereignty
Emmanuel Benhamou, EAIGG Managing Director and lead author, said long-term AI advantage is shaped less by models and chips and more by a nation's ability to deploy AI at scale, build talent pipelines, and establish trusted institutions. The report instead frames sovereignty as strategic control and optionality—ensuring countries retain enough choice across models, infrastructure, data, and partnerships that no single vendor or geopolitical disruption can dictate their AI trajectory.
Report identifies a widening gap between AI capability and enterprise deployment
EAIGG Executive Director Anik Bose said competitive advantage increasingly stems from connectivity rather than isolation, with nations building cross-border partnerships better positioned than those pursuing full independence. The study flags an AI deployment gap—the disconnect between available AI capability and large-scale operational adoption—as a defining challenge for governments and enterprises, requiring institutional capacity and workforce readiness beyond mere technology access.
Cross-border collaboration named as a sovereignty-strengthening strategy
Key findings state that countries can reinforce AI sovereignty through architectural optionality and strategic specialization rather than attempting to control every layer of the AI stack. Cross-border partnerships, the report notes, expand access to talent, capital, infrastructure, and markets without creating dependence on a single ecosystem.
Draup CEO points to hybrid technologist-domain talent as the critical bottleneck
Draup CEO Vijay Swaminathan said the talent layer combining technologists with domain expertise—needed to make AI models functional for enterprises—will be the most crucial factor accelerating enterprise AI adoption. The report targets policymakers, economic development agencies, institutional investors, enterprise leaders, and technology strategists assessing global AI competitiveness.