European Commission Insights: Study on the Deployment of Artificial Intelligence in Healthcare – 2025
- Sharan Murugan
- 16 hours ago
- 2 min read
On 8 August 2025,  the European Commission released an in-depth study on the "Deployment of artificial intelligence (AI) in healthcare". The report provides a comprehensive view of how AI is transforming patient care, diagnostics, hospital workflows, and health system sustainability — while highlighting the challenges that must be addressed to ensure safe, effective, and ethical adoption.
The study was commissioned to:
Assess the current state of AI adoption in healthcare across EU Member States.
Identify barriers to AI deployment and propose solutions.
Evaluate ethical, legal, and regulatory implications of AI in medical contexts.
Provide policy recommendations to the European Commission for fostering responsible AI use.
Key Findings – AI in Healthcare Today
The study highlights that AI is already widely integrated in certain areas, while adoption remains slow in others due to cost, interoperability, and regulatory hurdles.
High-use cases:
Medical imaging – automated tumour detection, radiology triage systems.
Clinical decision support systems (CDSS) – AI-assisted diagnosis and treatment recommendations.
Operational optimisation – hospital resource allocation, patient flow prediction.
Emerging use cases:
Digital twins for personalised treatment simulation.
AI in genomics for rare disease detection.
Predictive analytics for early disease outbreak alerts.
AI in healthcare in the EU is shaped by:
Artificial Intelligence Act (AIA): Risk-based approach, strict requirements for high-risk medical AI.
Medical Device Regulation (MDR) & In Vitro Diagnostics Regulation (IVDR): Safety and clinical evidence requirements for medical devices and diagnostics using AI.
Product Liability Directive (PLD): Ensures manufacturers are liable for harm from defective AI tools.
Health Technology Assessment Regulation (HTAR): Joint EU clinical evaluations for high-risk health technologies.
European Health Data Space (EHDS): Cross-border data standards, interoperability, data access.
Respondents noted benefits of harmonized frameworks, but also highlighted regulatory complexity and raised the need for specific guidance and compliance support at the hospital level.
Current State of AI Deployment in Healthcare in the EU
Research, development, and patenting in AI medical devices are rapidly expanding.
Clinical deployment lags behind development:
Surveys among radiologists: 48% in Europe, 35% in the US use AI clinically; rates are lower in the general health workforce.
Adoption is concentrated in urban/metropolitan regions and advanced centers; rural/underserved areas lag behind.
Radiology leads in AI adoption, driven by large available datasets and imaging needs; most deployed AI in radiology is low/medium risk (Class IIa).
Cloud-based deployment is prevalent, enabling scaling but raising data security concerns.
The real-world deployment demands more than technical solutions: alignment on data standards, supportive regulations, ongoing education, and inclusive organizational strategies are vital for wide and equitable benefit. For the full report, including all case studies, stakeholder insights, methodology, and implementation checklists, refer to the official publication: