Regulatory activity in the EU and UK over the past month has focused on AI in health care, health data access, and digital innovation frameworks. Recent regulatory developments in the EU and UK point to a decisive shift from high level policy ambition to the practical mechanics of enabling AI driven health care, with particular emphasis on health data governance, regulatory pilots, and institutional readiness.

At the EU level, attention is increasingly focused on building durable frameworks to support innovation while maintaining regulatory confidence. The European Medicines Agency is preparing to pilot enhanced regulatory support for breakthrough medical devices and in vitro diagnostics (IVD), an initiative expected to shape future reforms of the EU medical device and IVD regimes. In parallel, the European Commission has taken further steps to operationalize the European Health Data Space (EHDS) through new implementing rules on the governance of the European Health Data Space Board, signaling a move from legislation to execution. The European Data Protection Board (EDPB) has also issued draft guidelines on the application of the General Data Protection Regulation (GDPR) to scientific research, offering long awaited clarification on lawful bases, consent models, and secondary use of data, issues that are central to data intensive research and AI development and likely to influence practice across Member States once finalized.

In the UK, scrutiny has centered on whether existing data and regulatory structures are capable of supporting personalized medicine and AI at scale. Evidence to the House of Lords Science and Technology Committee highlighted the UK’s rich but underexploited health data assets and the persistence of access barriers since the pandemic, with witnesses pointing to fragmented governance and delays in data access as ongoing constraints. At the same time, the expansion of the Medicines and Healthcare products Regulatory Agency’s (MHRA) AI Airlock program, continued work by the National AI Commission, and targeted support for AI driven drug discovery reflect a more iterative, test and learn approach to AI regulation, focused on post market oversight rather than wholesale reform.