Overview
Digital sovereignty applied to artificial intelligence
Digital sovereignty means keeping control of your data, your tools and your technology choices, without depending on a foreign provider or extraterritorial legislation. Applied to AI, it rests on three pillars: where the data lives, which regulation applies, and who controls the model.
Pillars
The three pillars of sovereign AI
1. Data location
EU hosting alone does not determine the applicable jurisdiction. Assess contracting entities, subprocessors, support access and key control across the full processing chain.
2. Regulatory compliance
Two texts govern the use of AI in Europe: the GDPR (protection of personal data) and the AI Act (regulation of AI systems). A sovereign AI is designed to comply with both by construction, not as an afterthought.
3. Control over the model
The model (LLM) is open weight or open source, executed on your infrastructure. No black box, no telemetry, and no dependency on a vendor who could change its pricing or its terms.
Comparison
Sovereign vs public AI: what really changes
| Criterion | Sovereign AI | Public AI (US) |
|---|---|---|
| Data location | European Union | Vendor servers (often US) |
| CLOUD Act | Not applicable | Possible exposure |
| Control over the model | Full (open weight) | None (black box) |
| Reversibility | Complete | Limited |
| GDPR / AI Act documentation | Provided | Depends on the vendor |
Contact
Take back control of your AI
We deploy sovereign AI infrastructure for public bodies and organisations, with the compliance documentation ready for your DPO.
To validate
Responsibilities to validate
Documentation supports the controller and DPO for the actual processing. A public-interest task requires a legal basis in law and processing necessary for that task; it is not universal. A GDPR DPIA and an AI Act fundamental-rights impact assessment are distinct. Human oversight alone does not rule out high-risk classification.