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Sovereign AI

Sovereign AI is the principle that an organisation, or a country, should retain control over the AI it relies on: its data, its models and the infrastructure they run on. Rather than depending entirely on a single external provider, sovereign AI keeps the important decisions, and the sensitive data, in your own hands.

The idea is closely tied to data sovereignty: the notion that data is subject to the laws and governance of the place where it is collected and stored, and that you should be able to say where it lives and who can see it.

Why it matters​

Handing every query and document to an opaque third‑party service raises real concerns:

  • Privacy and confidentiality: sensitive data may leave your control or jurisdiction.
  • Compliance: regulations may require that certain data stays within specific borders.
  • Independence: relying on one provider creates lock‑in and exposure to their pricing, policy and availability.
  • Transparency: you may need to know, and prove, how an answer was produced.

What it looks like in practice​

Sovereign AI is usually pursued through a combination of choices: the ability to run open models you control, to keep data within chosen boundaries, to swap providers rather than be locked to one, and to audit how the system behaves.

Sovereign AI in Rational AI​

These principles are built into the platform. You decide which models to use through the AI Model Registry, including open models, and reach external providers only through explicit connectors. Your Knowledge stays your own, and Governance gives you a transparent record of how models are used. The result is generative AI you can adopt without giving up control of your data or your choices.

Additional resources​

  • Connectors: control exactly which external providers the platform talks to.
  • Knowledge: keep your organisation's data under your own management.
  • Governance: maintain a transparent, auditable record of AI usage.