Name in original language
Stratégie intelligence artificielle et données de santé 2025‑2028
Initiative overview
The strategy addresses structural challenges in the French health data ecosystem, particularly fragmentation, limited interoperability, and complex access procedures. It seeks to unlock the potential of existing datasets by improving their organisation, quality, and reuse, while ensuring compatibility across systems and supporting large-scale data-driven innovation.
A major focus is the preparation for the European Health Data Space framework, which introduces new obligations for data sharing and reuse across the EU. The strategy outlines concrete steps to align national systems with these rules, including defining national bodies responsible for data access, setting up standardised procedures, and creating coordinated infrastructures to enable secure and efficient data exchange at both national and European levels.
The initiative also defines a comprehensive governance model to oversee the use of health data and AI. This includes strengthening institutional coordination, creating mechanisms for stakeholder participation, and establishing oversight structures to monitor compliance, security, and ethical standards. Particular emphasis is placed on protecting individuals’ rights, improving transparency around data use, and ensuring accountability in the management of sensitive health information.
In addition, the strategy introduces operational measures to accelerate innovation, such as the development of open tools, shared resources, and experimental environments to test new data uses and AI applications. It supports the emergence of new use cases while encouraging collaboration between public and private actors, including in research, healthcare delivery, and industrial development.
Finally, the strategy incorporates mechanisms for long-term sustainability, including financial planning for data infrastructures and the introduction of economic models governing data access and reuse. It also establishes monitoring tools, indicators, and evaluation processes to assess the effectiveness, impact, and equity of data and AI use in healthcare over time.
