Since its entry into force on August 1, 2024, AI Act has set an unprecedented framework for artificial intelligence in Europe.
However, just a few weeks from the application of its key provisions, particularly on AI models for general use (GPAI) of large, mostly American digital companies in Europe such as Amazon, Apple and even Google have requested a legal break, remains vague and complex.
This episode reveals a paradox: Europe is advancing on the regulation of AI, but struggles to pose rules clearly clear to protect its technological and digital sovereignty. Beyond innovation, the real issue is clear: staying in control of its technology in an ecosystem marked by regulatory instability and strategic dependencies.
For companies as well as for states, it is therefore no longer just a question of taking advantage of AI – but of keeping hands on data confidentiality, their security as well as regulatory compliance. How can they continue to capitalize on the potential transformer of AI while keeping the sovereign mastery of their data?
Data sovereignty, a sine qua non condition of a confidence
Artificial intelligence rests entirely on data. But as companies exploit them more and more – to train, refine or deploy their models – they come up against complex issues, whether compliance with regulations, flow safety, or even control of infrastructure. So many challenges that the sovereign approach makes it possible to deal in a concrete way, by restoring organizations control over their technological environment.
First of all, AI mobilizes massive volumes of sensitive data – personal, financial, sometimes even governmental. In this context, compliance with regulations becomes an imperative: GDPR in Europe, CCPA in the United States, not to mention the many sectoral executives that apply. This is where sovereign AI takes on its full meaning. It allows companies to meet these requirements, while providing them with precious flexibility: by relying on several sovereign suppliers, they can adapt the accommodation and processing of data to the rules specific to each country or sector. A way of combining innovation, conformity … and mastery.
Data security and legal control are another point of vigilance. When an AI is hosted in a hyperscaler, the data can be subject to foreign laws, such as the US Cloud Act, exposing companies to interference that they do not master. Conversely, a sovereign AI provides local processing of data, under national jurisdiction, with private environments which dismiss any risk of unwanted pooling.
This need for control is accompanied by an imperative of technological independence: at a time when owner models and critical dependencies are increasing, more and more organizations adopt hybrid and modular architectures. A way to strengthen the resilience of their infrastructure while keeping their hands on their strategic choices.
An innovation lever … and economic sovereignty
Opting for a sovereign AI is the choice of independence as much as that of efficiency. At a time when data becomes an asset as strategic as energy or critical infrastructure, states and businesses seek to regain control of what they produce, host and exploit. The objective is clear: to build sustainable digital autonomy, capable of supporting innovation while protecting national and economic interests.
It is also the logic underlying recent public policies, whether it is to support investment in trusted clouds, strengthen data portability or supervise the use of AI via AI Act. Organizations capable of innovating while guaranteeing strict compliance with these new requirements benefit from a decisive competitive advantage. Betting data sovereignty is limiting risks, protecting its strategic assets and keeping the course towards controlled technological development.
Concrete profits in the most critical sectors
It is not a theory: the benefits of the sovereign cloud – and the sovereign AI that is based there – are already visible in several key sectors. In health, sovereign AI makes it possible to use patient data for research or diagnosis without compromising their confidentiality. This opens the way to more secure approaches to personalized medicine, while respecting HIPAA and GDPR standards.
In the public sector, sovereignty protects sensitive or strategic data from unauthorized access. The state can thus rely on AI for critical decisions, while retaining a locally governed technological ecosystem.
Financial institutions also find their account: fraud detection, risk management, regulatory compliance, etc. Sovereign AI ensures that banking data remain under national control, without sacrificing performance.
Finally, the legal sector benefits from a framework where confidential documents or legal databases resulting in AI models are protected. This avoids any leakage of sensitive information and guarantees total compliance with the laws on sovereignty and confidentiality.
Artificial intelligence already transforms our ways of producing, deciding and interacting. But tomorrow, it is the choices in terms of data sovereignty that will make the difference between an innovation suffered and a controlled innovation. The companies that integrate this dimension today build a lasting advantage – in compliance, in resilience, in competitiveness. For others, the risk is not only to slow down, but to lose control. It is therefore no longer a question of debating the need for sovereign AI, but of accelerating its implementation.
