As AI use expands globally, questions are emerging about where training data originates, who owns it, and how organizations keep sensitive information secure. This is the domain of sovereign AI: the protection of data, its uses, and its results, which is becoming increasingly important as AI moves from proof-of-concept to production deployments spanning entire countries and continents.

Beyond where data is stored, sovereign AI is really a question of who controls an organization's or region's AI capabilities. In practice, this requires control over the entire infrastructure stack, both software and hardware, along with policies governing who can view data, manage infrastructure, and install software.

Because data protection laws and practices vary widely across geographies – even within Europe – the governance of data flows and processing pipelines must be understood and followed.

While sovereign AI is often discussed on a country-by-country basis, the same rules and procedures apply to enterprises. For them, questions of data location, ownership, and transmission are even more complex.

Location is only part of the story

Much attention has focused on where a data center is physically located, but a closer look at what a data center actually comprises is needed when assessing sovereign infrastructure.