Artificial Intelligence in Healthcare
Artificial Intelligence (AI) has become a tangible reality in healthcare, with the potential to revolutionize the sector by making it more efficient, accessible, and sustainable. AI facilitates the efficient allocation of resources through predictive modeling, reduces costs and administrative burdens through automation, and improves diagnostics through accuracy and early detection. Practical applications include early detection of sepsis in intensive care and breast cancer detection through mammography, often surpassing the capabilities of specialists. In the pharmaceutical sector, AI accelerates drug discovery, optimizes dosing, facilitates clinical trials, and enhances quality control, reducing time and costs. Additionally, predictive analytics supports public health by anticipating disease outbreaks. Through the AICare@EU initiative, the European Commission aims to remove barriers to the implementation of AI in clinical practice, promoting equitable and effective adoption. The overarching goal remains to harness this transformative technology to provide equitable and high-quality healthcare for all.
26 October 2026 · dr. ing. Gabriel Saftescu · 5 min
Key points
- AICare@EU (implementation of AI in healthcare)
Transforming the Future of Medicine
Just a few years ago, discussions revolved around the potential of artificial intelligence (AI). Today, it has become a tangible reality. In addressing the complexity of global health challenges, AI emerges not only as a tool but also as a transformative force reshaping healthcare delivery. Advancements in AI technology present unprecedented opportunities to revolutionize healthcare, making it more effective, accessible, and economically sustainable. By promoting the integration of AI through appropriate policies, we can enhance equity, improve care, and ensure that new technologies, treatments, and medications benefit society as a whole. AI can facilitate the efficient allocation of medical resources. Predictive modeling can forecast patient admissions and optimize the use of hospital beds, staff, and equipment. This ensures that resources are available where and when they are needed most, avoiding waste and improving the quality of care. Additionally, AI has the potential to address some of the most pressing challenges in healthcare, such as rising costs, inefficiency, and the demand for high-quality care. AI can reduce costs and streamline administrative tasks, such as patient scheduling, billing, and managing electronic health records by automating and optimizing operations. This allows healthcare professionals to focus more on patient care. In terms of diagnostics, AI adds precision and enables early detection, often leading to less invasive and more cost-effective treatment options. AI-based personalized treatment plans can complement traditional approaches, providing more targeted and effective healthcare, improving patient outcomes while also helping to reduce the financial burden on health systems. Practical applications of AI in clinical practice: early detection of sepsis: AI systems implemented in intensive care units can anticipate potential sepsis, a life-threatening condition, several hours before the onset of clinical symptoms, allowing for timely intervention. breast cancer detection, based on AI: AI systems used in mammography screening can identify early signs of breast cancer with high accuracy, often surpassing the capabilities of radiologists. AI is transforming the pharmaceutical sector throughout the entire drug lifecycle, from drug discovery and development to pharmacokinetics, evaluation, manufacturing, marketing, approval, and pharmacovigilance. In terms of new drug discovery, AI accelerates the process by identifying targets and optimizing the drug creation procedure. Throughout the drug development process, AI enhances formulations and facilitates their customization. In pharmacokinetics, AI-based predictions contribute to determining optimal dosing, while in clinical studies, AI facilitates patient stratification, digital twins, and trial simulations. Drug manufacturing benefits from AI through automation and improved quality control. Moreover, AI simplifies drug authorization procedures and pharmacovigilance, enabling digital transmission and analyzing real-world data to detect safety signals early. These advancements significantly reduce time and costs by streamlining research, optimizing processes, and minimizing clinical trial failure rates, thereby accelerating the delivery of safe and effective medications. The reform of EU pharmaceutical legislation plays an important role, as it: *provides
Challenges Related to the Integration of AI in Healthcare
The integration of AI in healthcare presents a series of challenges. To achieve digital transformation, particularly in advancing AI technologies, several essential components are necessary. Additionally, to realize its full potential, it is crucial to build trust in AI and its acceptance in healthcare delivery, as well as to address the challenges related to its implementation in clinical practice. These include access to high-quality medical data, measures to promote innovation in AI, and ensuring that AI systems used in medicine are safe and reliable. Moreover, for the adoption of AI, it is essential to ensure sustainable funding, especially in public hospitals, as well as its integration into clinical workflows—not just as an additional tool but as part of a more efficient and redefined care process. Equally important is the establishment of a solid framework that allows victims to effectively seek compensation from manufacturers in cases of harm caused by defective products, including AI systems.
EU Legislation Governing the Use of AI in Healthcare
Regulation on AI On 1 August 2024, the EU Regulation on artificial intelligence (AI) came into force. It aims to promote the responsible development and implementation of artificial intelligence in the EU. High-risk AI systems, such as AI-based software for medical purposes, must comply with a series of requirements, including risk mitigation systems, high-quality datasets, clear information for users, and human oversight. Additionally, the Commission is set to finalize a code of good practices for general-purpose AI (GPAI) providers by April 2025. This code, mandated by the AI Regulation, will address critical areas such as transparency, copyright-related norms, and risk management. Provisions regarding GPAI will apply 12 months after the entry into force of the AI Regulation. A European Office for Artificial Intelligence has been established, serving as the center of expertise in the field of AI in the EU. The European Office for Artificial Intelligence plays a crucial role in implementing the AI Regulation – particularly for general-purpose AI – promoting the development and use of reliable AI and international cooperation. The AI Office will oversee the application of the AI Regulation concerning general-purpose AI models. The AI Regulation aims to provide developers and implementers of AI with clear requirements and obligations for certain AI applications, while also striving to minimize administrative and financial burdens, especially for small and medium-sized enterprises (SMEs). The AI Regulation is part of a broader package of policy measures designed to support the development of reliable AI, including the AI Innovation Package and the Coordinated Plan on AI. Together, these measures ensure the safety and fundamental rights of citizens and businesses regarding AI. They also enhance the adoption of AI, as well as investments and innovation in AI at the EU level. The AI Regulation came into force on 1 August 2024 and will be fully applicable after 2 years, with some exceptions: prohibitions will come into effect after six months, governance rules and obligations for general-purpose AI models will become applicable after 12 months, and rules for AI systems – incorporated into regulated products – will apply after 36 months. To facilitate the transition to the new regulatory framework, the Commission has launched the AI Pact. This voluntary initiative aims to support future implementation and invites AI developers in Europe and beyond to comply in advance with the main obligations set out by the AI Regulation. Regulation on the European Health Data Space The development and implementation of AI in medicine requires access to various high-quality medical data to ensure accuracy, robustness, and fairness among different populations. The European Health Data Space plays a crucial role in this regard, enabling the secondary use of electronic health data for research and innovation.
By allowing the training, testing, and evaluation of algorithms - including those used in medical devices, in vitro diagnostic tools, clinical decision support systems based on AI, and digital health applications - the European health data space will contribute to the promotion of cutting-edge AI solutions while ensuring compliance with ethical standards and data protection. This structured access to health data will stimulate innovation and enhance patient safety and equity in AI-based healthcare.
The European Health Data Space will be a key pillar of a strong European Health Union and is the first common data space at the EU level in a specific domain resulting from the European Data Strategy. The European Health Data Space will come into effect in 2025. The European Health Data Space: allows individuals to take control of their health data and will facilitate data exchange for the provision of healthcare across the EU (primary use of data) promotes a genuine single market for electronic health record systems ensures a coherent, trustworthy, and efficient system for the reuse of health data for research, innovation, policy-making, and regulatory activities (secondary use of data). Thus, within the European Health Data Space, the EU will be able to fully leverage the potential offered by the safe and secure exchange, use, and reuse of health data, benefiting patients, researchers, innovators, and regulatory authorities. Trust is a fundamental determining factor for the success of the European Health Data Space. The European Health Data Space will provide a trusted framework for secure access to a wide range of health data and for their secure processing. It is also based on: General Data Protection Regulation (GDPR) Data Governance Regulation Data Act Cybersecurity Directive. As horizontal frameworks, these provide rules that also apply to the health sector. However, the European Health Data Space will introduce specific sectoral rules, considering the sensitivity of health data.
Directive on Product Liability The new Directive on Product Liability updates and adapts EU rules regarding liability for new technologies, ensuring better protection for victims and greater legal certainty for economic operators. The Directive on Product Liability guarantees that victims can seek compensation from manufacturers when they suffer damages caused by such products. This directive is based on two fundamental principles: the manufacturer must compensate for the damage caused by a defective product the victim must prove the existence of the defect and the damage and establish that the damage was caused by this defect in the product. Software, such as operating systems, firmware, computer programs, applications, or AI systems, is increasingly prevalent in the market and plays an ever more important role in product safety. Under the new Directive on Product Liability, software is a product to which strict liability applies, regardless of how it is provided or used. Software developers or manufacturers, including providers of AI systems as defined by Regulation (EU) 2024/1689 of the European Parliament and of the Council (AI Regulation), should be considered manufacturers and treated as such. To assess the defective nature of a product, all circumstances are taken into account, including the effect on the product of any ability to continue learning or acquiring new features after being placed on the market or put into operation. Furthermore, a product is presumed to be defective when the claimant demonstrates that it does not meet the mandatory safety requirements set out in Union law or national law to protect against the risk of harm suffered by the injured party.
AICare@EU (the implementation of AI in healthcare)
Despite significant progress in the research and development of AI/machine learning-based medical devices, their presence in the market remains relatively limited, and the integration of AI into clinical practice is progressing slowly. The AI Regulation, the European Health Data Space, and the Product Liability Directive aim to promote the research, development, and implementation of AI in healthcare. However, various challenges must be addressed to ensure the effective and efficient implementation of AI tools and to expand their equitable and fair adoption in clinical practice. In this regard, DG Health and Food Safety promotes several interconnected initiatives under AICare@EU. This initiative builds on the foundations provided by the aforementioned legislative frameworks and focuses on addressing the main obstacles to the implementation of AI in healthcare, particularly in clinical practice. AICare@EU encompasses a series of coordinated efforts, including: - a study on the implementation of AI in healthcare – this initiative by DG Health and Food Safety aims to investigate the challenges and enabling factors of AI implementation in clinical practice. The identified challenges are classified into four key areas: technological and data-related challenges, legal and regulatory barriers, organizational and commercial obstacles, and social and cultural factors. - a call for proposals "EU for Health" (2024 work program) regarding the promotion of AI adoption in health: this call for proposals, which closed in January 2025, aims to accelerate the safe and effective implementation of AI systems in clinical settings, contributing to the broader integration of AI in healthcare. - the SHAIPED project – AI and entities responsible for access to medical data (funded through the "Digital Europe" program): starting in March 2025, this project tests the development, validation, and implementation of AI models and tools using the HealthData@EU infrastructure of the European Health Data Space. - exploring key priorities in AI in line with the new political guidelines of the Commission for the period 2024-2029: - AI application strategy: a strategy to stimulate new industrial uses of AI and improve the delivery of public services, such as healthcare. The biotechnology initiative includes the development of legislation on biotechnology that explores ways to accelerate the development and implementation of AI and digital solutions in the biotechnology sector, securely and responsibly leveraging health data within the European Health Data Space. - cardiovascular disease prevention: emphasis is placed on prevention, diagnosis, treatment, and rehabilitation. - international collaborations on AI in healthcare: - DG Health and Food Safety collaborates with WHO Europe to support the development and adoption of AI solutions to improve health outcomes in the WHO European region. - DG Health and Food Safety works closely with OECD to promote the expansion of AI in healthcare, focusing on practical application and policy alignment. - The European Commission (DG Health and Food Safety) collaborates with G7 and G20 partners on various workflows related to AI in healthcare.