“Data really is the new currency; it’s IP for many companies,” says Kevin Dallas, CEO of EDB, echoing a recurring concern from customers. “The big concern is that if you’re deploying AI-infused applications with big cloud-based language models, are you losing your IP? Are you losing your competitive position?”
This question is now fueling a movement toward reclaiming both the data and AI systems that have increasingly become part of core business infrastructure. AI and data sovereignty, which refers to breaking reliance on centralized providers and establishing real control over models and data estates, is an urgent priority for many companies, says Dallas, citing internal EDB data: “70% of global executives believe they need a sovereign data and AI platform to succeed.”
The idea of AI sovereignty is becoming a global policy conversation. NVIDIA CEO Jensen Huang recently spoke about the need for such a change at the World Economic Forum annual meeting in Davos in January 2026: “I really believe that every country should be involved in building AI infrastructure, building their own AI, leveraging their fundamental natural resource – which is your language and culture – to develop their AI, continue to refine it, and build their own national intelligence. Must be made part of the ecosystem.”
This report explores how enterprises are gaining sovereignty over their models and data estates in an era of rapid AI adoption. Based on a survey of more than 2,050 senior executives by the EDB and a series of interviews with industry experts, the research confirms that the sovereignty movement is already well underway at the enterprise level.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by the editorial staff of MIT Technology Review. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes writing surveys and collecting data for the surveys. The AI tools that may have been used were limited to secondary production processes that underwent thorough human review.
