Reclaiming Control: The Urgent Case for AI and Data Sovereignty

When generative artificial intelligence (AI) transitioned from research labs to real-world business applications, companies made a significant trade-off: they gained powerful capabilities but at the cost of losing control over their data. Feeding proprietary information into third-party AI models promised impressive results, yet this data passed through systems owned and governed by others. The protections these companies relied on were only as strong as the provider’s next policy update.

Now, with generative AI deeply embedded in everyday business operations and new agentic AI systems advancing rapidly, organizations are reevaluating this bargain. "Data is really a new currency; it’s the IP for many companies," says Kevin Dallas, CEO of EDB, reflecting a common concern among customers. "The big worry is, if you’re deploying an AI-infused application with a cloud-based large language model, are you losing your IP? Are you losing your competitive position?"

The Sovereignty Movement Gains Momentum

This question has sparked a growing movement toward reclaiming both data and AI systems that have become integral to core business infrastructure. AI and data sovereignty-breaking dependence on centralized providers and establishing genuine control over models and data estates-is now an urgent priority for many companies. According to Dallas, citing internal EDB data, 70% of global executives believe they need a sovereign data and AI platform to succeed.

The concept of AI sovereignty is not just a corporate concern; it has become part of the global policy conversation. NVIDIA CEO Jensen Huang emphasized this shift at the World Economic Forum’s annual meeting in Davos in January 2026. "Every country should get involved to build AI infrastructure, develop your own AI, and take advantage of your fundamental natural resources-your language and culture," he stated. "This will allow you to refine your AI continuously and integrate it into your national ecosystem."

EDB's report, based on a survey of over 2,050 senior executives and interviews with industry experts, delves into how enterprises are pursuing sovereignty in an era of rapid AI adoption. The research confirms that the sovereignty movement is gaining traction at the enterprise level. Companies are increasingly seeking to build their own AI models and data platforms to maintain control over their intellectual property and competitive edge.

One key strategy is to develop on-premises or private cloud solutions, which allow companies to keep their data within their own infrastructure. This approach not only enhances security but also ensures that the data remains under the company’s direct governance. Open-source AI models are gaining popularity as they offer transparency and flexibility without the constraints of proprietary systems.

What Comes Next

The movement toward AI and data sovereignty is driven by a combination of business necessity and ethical considerations. Companies recognize the importance of protecting their intellectual property and maintaining competitive advantages in an increasingly data-driven world. At the same time, there are growing concerns about privacy, data misuse, and the potential for AI to amplify existing inequalities.

As more organizations embrace sovereign approaches, policymakers will need to address the regulatory landscape. Ensuring that companies can build and maintain their own AI infrastructure while adhering to ethical standards will be crucial. This includes developing frameworks for data governance, transparency, and accountability.

The journey toward AI and data sovereignty is just beginning, but it is a critical step in ensuring that the benefits of AI are distributed fairly and responsibly. By reclaiming control over their data and AI systems, companies can not only protect their interests but also contribute to a more equitable and sustainable future.