A Sovereign AI means an artificial intelligence system developed and controlled by a national entity or organisation, with the aim of safeguarding its strategic autonomy, security and interests.
It is part of a logic of technological sovereigntyThis is where a country or region seeks to master the key technologies, data and infrastructures associated with AI, without depending on foreign players or external platforms.
Key features
- Data control :
- The data used to train and operate the AI is stored and managed locally, in accordance with national laws (e.g. in the United States): RGPD in Europe).
- Protection against exploitation by foreign players or multinational companies.
- Technological autonomy :
- Development of local infrastructures (supercomputers, sovereign cloud) and national skills (training, research).
- Reduced dependence on foreign tools or services (e.g. proprietary AI models such as ChatGPT).
- Governance ethical and regulatory :
- National legal frameworks to regulate AI (e.g. AI law in Europe).
- Alignment with the country's cultural, ethical and societal values.
- National security :
- Protection against cyber attacksThe use of foreign AIs to manipulate or spy on us.
- Use of AI in critical sectors (defence, health, energy).
Concrete examples
- L'European Union promotes a " Trusted AI "This will be achieved through strict regulations and investment in projects such as Gaia-X (sovereign cloud).
- La China is developing AI aligned with its geopolitical priorities and governance model.
- La France is investing in supercomputers (Jean Zay) and initiatives such as the France IA programme.
Issues and challenges
- High costs : Developing sovereign AI requires major investment in R&D and infrastructure.
- Balancing sovereignty and cooperation : Working internationally without losing control.
- Competitiveness Risk of falling behind the technological giants (United States, China).
- Ethical dilemmas How can we reconcile innovation, security and individual freedoms?
In short, sovereign AI embodies a political will to avoid external technological domination, while ensuring that AI serves national priorities and the common good.
| Category | Sovereign AI | Traditional AI |
|---|---|---|
| Purpose and objectives | Designed to guarantee technological independence, safety and security, the resilience of a geographical or organisational entity, by controlling its development, deployment and local regulation. | Designed to perform specific tasks (such as image recognition, prediction or spam filtering) using pre-programmed algorithms and defined rules. |
| Control and governance | Total control is based on a single entity (country, organisation): training and operating data, infrastructure (servers, networks), algorithms and training processes. | Often managed by external players (private companies, third-party suppliers) and designed for isolated tasks, with no requirement for sovereignty. |
| Data management | Prioritises the protection and location of sensitive databy preventing them from being outsourced outside the controlled area. | Uses structured data, often limited to the context of the assigned task, without the need for geographical control. |
| Infrastructure and deployment | Requires local hosting and a proprietary infrastructure (servers, national clouds) to avoid external dependencies. | Can be deployed on any infrastructure (public cloud, third-party servers), with no specific localisation requirements. |
| Adaptability and evolution | Can incorporate advanced technologies (such asGenerative AI), but under the strict control of its developer to avoid bias or safety risks. | Rigid and specialised: its performance depends on predefined data and rules, with no capacity for autonomous adaptation. |
| Concrete examples | A national facial recognition system controlled by a government, using local data and infrastructure. | E-commerce product recommendation software based on pre-programmed algorithms. |
