For years, data sovereignty was treated as a compliance requirement, focused mainly on keeping data within specific geographic borders. Today, that definition is no longer sufficient. True data sovereignty now encompasses control, visibility, and accountability over data wherever it resides, moves, or is processed.

In an era shaped by AI adoption and increasingly fragmented cloud environments, sovereignty has become a core driver of enterprise resilience and operational autonomy rather than a regulatory checkbox. In this episode of The Security Strategist, Tim Pfaelzer, Senior Vice President and General Manager, EMEA at Veeam, explains how the meaning of data sovereignty has fundamentally changed.

From Compliance Concept to Strategic Priority

A decade ago, data lived in well-defined corporate environments managed by internal IT teams. Today, it is distributed across public cloud platforms, SaaS ecosystems, edge devices, and third-party suppliers. This distribution has expanded the attack surface while making ownership and control significantly harder to define.

As a result, organisations are being forced to rethink sovereignty not as a legal constraint, but as a foundation for resilience, security, and trust.

Why Data Sovereignty Requires Cultural Change

One of the key arguments Pfaelzer makes is that data sovereignty cannot be solved through technology alone. It requires organisational alignment and executive ownership.

Data is now created and consumed across every business function, which means governance must extend beyond IT. Leadership teams must treat data as a critical business asset, with clear accountability structures across its lifecycle.

This shift is reinforced by regulatory pressure. Frameworks such as GDPR, the EU Data Act, and emerging AI governance rules now require organisations to demonstrate not only where data is stored, but how it is accessed, processed, and protected.

The Five Dimensions of Modern Data Control

Pfaelzer outlines five core dimensions that define effective data sovereignty today:

Visibility: Knowing where all data exists, including backups and third-party copies
Ownership: Clear accountability for data across its lifecycle
Access governance: Controlled and regularly reviewed permissions
Portability: The ability to move data without vendor lock-in
Compliance readiness: Continuous compliance rather than audit-only validation

Together, these determine how much real control an organisation has over its data estate.

Data Sovereignty as the Foundation of Resilience

Modern resilience is no longer defined by backup alone. It is defined by recovery speed, completeness, and operational continuity. A prolonged outage or ransomware incident can cause significant damage, but the difference between minutes and days of downtime often comes down to recovery architecture and how rigorously it has been tested under real-world conditions. In this context, sovereignty and resilience are directly linked. Without control over data, there is no predictable recovery.

AI Has Raised the Stakes

Artificial intelligence has introduced a new layer of data risk that many organisations are still underestimating. As AI systems increasingly automate decision-making and customer interactions, the quality and integrity of training and operational data become critical. If that data is corrupted, incomplete, or outdated, the impact can spread silently across business processes before detection.

Unlike infrastructure failures, AI-driven data issues are not always immediately visible. This makes governance even more important. Pfaelzer argues that AI systems should operate under the same strict data controls as human users, including lineage tracking, access controls, and continuous validation of data integrity.

Why Data Sovereignty Now Defines Enterprise Autonomy

Ultimately, data sovereignty has changed into a measure of enterprise independence. Organisations that understand, govern, and control their data are better positioned to manage risk, comply with regulation, and adopt new technologies such as AI safely. Those who do not risk becoming dependent on opaque systems where visibility and control are limited. In 2026 and beyond, sovereignty is no longer just about where data lives. It is about who controls it, how it is used, and how quickly an organisation can recover when things go wrong.

Takeaways

Data sovereignty beyond geographic boundaries
Risks of data fragmentation across cloud and edge environments
Strategies for rapid data recovery and resilience
Ensuring data integrity and trust in AI systems
Control and ownership of data in a distributed landscape

Chapters

00:00 Introduction to Data Sovereignty and Resilience

02:49 The Evolution of Data Management

06:03 Control, Risk Exposure, and Accountability in Data

08:57 Data Sovereignty Beyond Geography

12:04 Ensuring Data Integrity in AI Systems

15:05 Human Error and Data Management

18:02 Case Study: University of Manchester's Data Strategy

21:01 Non-Negotiables for Building a Resilient Data Strategy