How Enterprises Are Reclaiming Control Over AI and Data Sovereignty

When generative AI first entered the business world, companies made a tacit trade-off: immediate capability in exchange for future control. They fed proprietary data into third-party AI models to get powerful results, but their data passed through systems they didn‘t own and under governance they didn’t set. The protections they relied on were only as durable as the provider’s next policy update.

The Shift from Capability to Control

Now, with generative AI deeply embedded in everyday operations and sophisticated agentic AI systems advancing rapidly, companies are rethinking that bargain. “Data is really a new currency; it’s the IP for many companies,” says Kevin Dallas, CEO of EDB. “The big concern 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?”

How Enterprises Are Reclaiming Control Over AI and Data Sovereignty — Source: www.technologyreview.com

This concern is driving a movement to reclaim both data and AI systems that have become core business infrastructure. AI and data sovereignty—breaking dependence on centralized providers and establishing genuine control over models and data—is now an urgent priority for many organizations.

The Risks of Losing Intellectual Property

Feeding proprietary data into third-party models exposes companies to several risks:

Data leakage: Sensitive information may be used to train future versions of the model, potentially benefiting competitors.
Vendor lock-in: Switching costs become prohibitive, and providers can change terms, pricing, or policies unilaterally.
Regulatory non-compliance: Data residency requirements in regions like Europe, Asia, and the Middle East often conflict with cloud-based AI services.

As Kevin Dallas notes, “70% of global executives believe they need a sovereign data and AI platform to be successful,” citing internal EDB data from a survey of over 2,050 senior executives.

The Global Push for AI Sovereignty

The concept of AI sovereignty is gaining traction at the policy level. NVIDIA CEO Jensen Huang recently spoke at the World Economic Forum’s annual meeting in Davos: “I really believe that every country should get involved to build AI infrastructure, build your own AI, take advantage of your fundamental natural resource—which is your language and culture—develop your AI, continue to refine it, and have your national intelligence be part of your ecosystem.”

This sentiment resonates beyond governments. Enterprises in industries such as finance, healthcare, and defense are recognizing that their proprietary data and models represent strategic assets that cannot be entrusted entirely to external providers.

Survey Confirms Urgency

EDB’s survey of global executives underscores the urgency. The research, conducted in collaboration with MIT Technology Review, confirms that the sovereignty movement at the enterprise level is already well underway. Key findings include:

70% of executives believe a sovereign data and AI platform is essential for success.
60% have already started building or planning such platforms.
Data security and IP protection are the top drivers, cited by 80% of respondents.

The report also highlights that sovereignty is not just about technology—it involves governance, compliance, and organizational change.

Building a Sovereign AI Platform

To achieve AI and data sovereignty, enterprises need to consider several steps:

1. Assess Data Residency Requirements

Understand where data must physically reside to comply with regulations and internal policies. This may involve deploying on-premises infrastructure or using localized cloud regions.

2. Choose Open or Controllable Models

Opt for AI models that can be run on your own infrastructure, such as open-source large language models or those with flexible licensing. This avoids dependency on a single provider’s API.

3. Implement Strong Governance

Establish clear policies for data access, model training, and decision-making. Use role-based access controls and audit trails to maintain accountability.

4. Invest in Data Infrastructure

Build or adopt a data platform that supports sovereignty—such as a PostgreSQL-based database with AI capabilities—that gives you control over storage, processing, and integration.

Learn more about the global push for AI sovereignty.

Conclusion

The era of “capability now, control later” is ending. As AI becomes central to business strategy, enterprises are moving to reclaim sovereignty over their data and models. With 70% of executives seeing this as critical, the shift is no longer optional—it is a competitive imperative. By taking proactive steps to build sovereign AI platforms, companies can protect their intellectual property, comply with regulations, and maintain strategic autonomy in an increasingly AI-driven world.

This report draws on a survey of over 2,050 global senior executives conducted by EDB and supported by MIT Technology Review Insights. The research confirms that sovereignty is already a priority for many organizations.

Tags: