The integration of AI in medicine has brought about numerous benefits, including improved diagnostics, treatment planning, and patient care. However, it also presents several legal challenges and concerns that need to be addressed: liability, transparency and explainability, licensure and credentialing. Determining liability in cases where AI systems are involved can be complex. If an AI algorithm makes a mistake in diagnosis or treatment recommendations, who is responsible—the developer, the healthcare provider, or both? Legal frameworks need to evolve to allocate liability fairly and encourage innovation while ensuring patient safety. AI algorithms often operate as «black boxes», making it difficult to understand their decision-making process. Ensuring transparency and explainability in AI systems used in medicine is crucial for accountability, trust, and regulatory compliance. AI systems that perform tasks traditionally carried out by healthcare professionals, such as diagnosing medical conditions or interpreting diagnostic images, may raise questions about licensure and credentialing. Regulators need to establish guidelines for the oversight and accreditation of AI technologies in healthcare settings. The main focus of this investigation is two different spheres of using AI in medicine: treatment and management. For example, in Russia we have special legal frameworks to use AI technologies as a support to physicians to diagnosis and to clinical managers to control effectiveness of medical services. In this article the Author on the base of comparative investigation of different legal regimes to regulate of using of AI tried to show common problems to use AI in medicine and telemedicine and to propose variants to decide it.

Mikhail Varyushin has completed his PHD at the age of 25 years from The All-Russian State University of Justice, Russia. He is the practical lawyer in medical and corporate law. He has over 40 publications.