Global AI health care market, worth $ 29.01 billion in 2024, It is expected to reach 504.17 billion to 2032. In Europe itself, The market is expected to increase From USD 7.92 billion in 2024 to USD 143.02 billion to 2033, with an amazing 38% annual growth rate.
The growing adoption emphasizes the significant potential of artificial intelligence in many areas of healthcare: it can enhance accuracy and early detection of diseases, support personalized treatment plans, improve administrative tasks, such as invoicing and planning, and improve hospital resource management through predictive analysis. In clinical practice, AI is already influenced In such areas as early sepsis detection and improved breast cancer screening.
As Antoine Tesnière, a medical professor and managing director of Parisanté Campus, noted, in an interview with Himss TV: “AI is a real revolution for healthcare. AI tools allow us to understand that we will have super precise, super-production, superpreventive, super-personal approaches in the near future.”
AI develops beyond only helping clinicians in making decisions. “The level of performance is approaching today’s man, but will exceed the human performance level, bringing new horizons to the overall health care efficiency,” said Tesnière.
Critical challenges with AI
Despite the growing enthusiasm, grave fears remain. “The error can affect the making clinical decisions and the patient’s care during the implementation of algorithmic tools,” said Dr. Jessica Morley, the post-coating researcher at the Yale Digital Ethics Center, in an interview with Himss TV. It indicates current restrictions on systems, such as arrhythmia detecting devices, which usually do not work so well for people with darker skin and melanoma algorithms that fail in various populations.
Morley also identifies a deeper system problem, which he calls “reverse data quality law”: “where you have the greatest need, you often have the lowest availability of high quality data.” This basic challenge means that the creation of fair AI systems requires solving both technical restrictions and management obstacles.
Despite these obstacles, Morley remains optimist that the right approaches can overcome current challenges. He believes that innovations, such as secure data environments, offer a real path ahead: “You can still protect the data of individual patients and continue to use health benefits at the population level at the group level. You can have a cake and eat them too”-he is held.
Balancing innovation and protection
To meet AI’s challenges, the European Union has established two breakthrough regulatory frames to ensure that AI development balance in the field of healthcare innovations in the field of ethics, transparency and respect for fundamental rights.
. I give an act It aims to improve access to data generated by connected medical devices, helping to create more diverse and representative data sets, while reducing the risk of algorithmic bias. Meanwhile I have an act Specifies clear requirements for high -risk AI systems in healthcare, introducing security, such as compulsory impact assessments, human supervision, explaining AI models and data verification.
These frames are aimed at supporting the environment in which AI healthcare can provide precise and personalized care, while maintaining trust, honesty and responsibility.