Reclaiming Control: The Urgent Drive for AI and Data Sovereignty in the Enterprise

When generative AI first transitioned from research labs into practical business applications, enterprises often made a quiet compromise: prioritizing immediate capabilities over long-term control. This arrangement typically involved feeding proprietary data into third-party AI models, yielding powerful results but at the cost of relinquishing direct ownership and governance. The integrity and protection of this sensitive data became inherently tied to the policies and updates of external providers, creating a precarious dependency. Today, with generative AI deeply embedded in daily business operations and sophisticated agentic AI systems rapidly advancing, companies are critically re-evaluating the terms of this initial bargain. The growing anxiety centers on the potential loss of intellectual property and competitive advantage. As Kevin Dallas, CEO of EDB, aptly states, "Data is really a new currency; it’s the IP for many companies." This sentiment echoes a widespread concern among executives regarding the deployment of AI-infused applications with cloud-based large language models and the associated risks of losing vital corporate assets. This pressing concern is now fueling a significant movement towards reclaiming both the data and the AI systems that have become integral to core business infrastructure. AI and data sovereignty, defined as breaking free from reliance on centralized providers and establishing genuine, independent control over models and data estates, has emerged as an urgent strategic priority for many organizations. Internal EDB data underscores this urgency, revealing that a striking 70% of global executives believe a sovereign data and AI platform is essential for their future success. The concept of AI sovereignty is also rapidly evolving into a global policy conversation. A notable example is NVIDIA CEO Jensen Huang's address at the World Economic Forum in Davos in January 2026, where he emphasized the critical need for every nation to build its own AI infrastructure. Huang advocated for countries to leverage their fundamental natural resources—their language and culture—to develop and refine their own AI, thereby integrating national intelligence into their unique ecosystems. This strategic shift is not merely theoretical; it is actively being pursued by enterprises worldwide. A comprehensive report, based on a survey conducted by EDB involving over 2,050 senior executives and a series of interviews with industry experts, confirms that the sovereignty movement at the enterprise level is already well underway. Companies are proactively seeking ways to establish greater autonomy over their AI models and data estates, recognizing that true innovation and security in the age of autonomous systems demand genuine control.