The global IA health care market, estimated at 29.01 billion USD in 2024, should reach 504.17 billion USD by 2032. In Europe only, The market should grow From USD 7.92 billion in 2024 to 143.02 billion USD by 2033, with an incredible annual growth rate of 38%.
The growing adoption underlines the significant potential of AI in many areas of health care: it can improve the precision and early detection of diseases, support personalized treatment plans, rationalize administrative tasks such as invoicing and planning, and improve the management of hospital resources thanks to predictive analyzes. In clinical practice, AI already shows an impact In areas such as early detection of septicemia and improving breast cancer screening.
Like Antoine Tesnière, professor of medicine at and managing director of Parisanti Campus, noted in an interview with Himss TV: “AI is a real revolution for health care. AI tools allow us to understand that we will have super precise, super productive, super-preventive and super-personalized approaches in a very close future.”
The AI ​​is advancing beyond the simple help of clinicians to make decisions. “The level of performance is approaching that human from today, but it will go beyond the level of human performance, bringing new horizons for the overall performance of health care,” said Tesnière.
Critical challenges with ai
Despite growing enthusiasm, important concerns remain. “The bias may have an impact on clinical decision -making and patient care when we deploy algorithmic tools,” said Dr. Jessica Morley, a postdoctoral researcher at Yale Digital Ethics Center, in a Himss television interview. It highlights the current limits in systems such as arrhythmia detection devices which generally do not work on people with people with darker skin and melanoma algorithms that fail through various populations.
Morley also identifies a deeper systemic problem that she calls the “law of inverse data”: “where you have the greatest need, you often have the lowest high -quality data availability.” This fundamental challenge means that the creation of fair AI systems requires treating both technical limitations and governance obstacles.
Despite these obstacles, Morley remains optimistic that the right approaches can overcome current challenges. She thinks that innovations such as secure data environments offer a viable path: “It is quite possible to protect data from individual patients and take advantage of the health health benefits. You can have your cake and eat it too,” she said.
Balance innovation and protection
To meet the challenges of AI, the European Union has established two historic regulatory frameworks to ensure that the development of health care AI balances innovation with ethics, transparency and respect for fundamental rights.
THE EU data law aims to improve access to data generated by connected medical devices, helping to create more diverse and more representative data sets while reducing the risk of algorithmic biases. In the meantime, the EU ACT AI Defines clear requirements for high -risk AI systems in health care, by introducing guarantees such as compulsory impact assessments, human surveillance, explainable AI models and data verification.
Together, these executives seek to support an environment where the AI ​​of health care can provide precise and personalized care while maintaining confidence, fairness and responsibility.
Antoine Tesnière, Director General of Parisanti Campus, and Dr Jessica Morley, Postdoctoral researcher at Yale Digital Ethics Center, will speak to Himss Europe 2025Taking place in Paris from June 10 to 12.
