Establishing AI and data sovereignty in the age of autonomous systems

Initially, businesses readily embraced generative AI, trading immediate capabilities for future control. They fed proprietary data into third-party AI models for powerful results, despite lacking ownership over the systems or control over their governance. The security of their data was contingent on the provider's policy updates.

However, with generative AI now integral to daily operations and sophisticated agentic AI systems emerging, companies are reevaluating these terms. Concerns about losing intellectual property and competitive advantage due to reliance on cloud-based large language models are prevalent.

This has spurred a movement towards reclaiming data and AI systems, which are now core business infrastructure. AI and data sovereignty, defined as breaking dependence on centralized providers and establishing genuine control over models and data, is a pressing priority. EDB data indicates that 70% of global executives believe a sovereign data and AI platform is essential for success.

The concept of AI sovereignty is also gaining traction in global policy discussions. NVIDIA CEO Jensen Huang emphasized the need for every country to build its own AI infrastructure, leveraging its unique language and culture to refine national intelligence.

This report, based on an EDB survey of over 2,050 executives and expert interviews, confirms that the enterprise-level sovereignty movement is already well underway.