The capabilities of artificial intelligence (AI) and machine learning are growing at an unprecedented pace. These technologies have many useful applications, from machine translation to medical image analysis. A large number of such applications are currently being developed, and an increasing number of such applications is expected in the long term. Unfortunately, weaknesses and other unpleasant aspects of AI have received insufficient attention. In this review, we consider a whole range of already known problems and possible risks associated with the use of innovative neural network technologies, paying special attention to the ways of preventing real dangers and potential threats in order to expand the range of stakeholders and profile experts involved in the discussion of current issues of medical AI cybersecurity, formation of responsible approach to the vulnerabilities of neural network platforms, increasing the reliability of equipment protection for its safe use, as well as the importance of legal and ethical aspects of regulating the use of AI. Despite certain challenges described in our review, it is clear that AI will be an important element of the healthcare future. As the population continues to age and the demand for healthcare services grows, neural networks are expected to drive healthcare very soon, especially in the areas of medical image analysis, virtual assistants, drug development, treatment recommendations and patients' data processing. We would like to emphasize that while we recognize the innovative role that digital technologies and AI can and should play in strengthening the domestic healthcare system, we should not overlook the importance of timely and accurate assessment of their beneficial or negative impact on the industry to ensure such management decisions do not unnecessarily divert our attention and resources from non-digital approaches and research. This article is a continuation of the article by Berdutin VA, Romanova TE, Romanov SV, Abaeva OP. Problematic aspects of medical artificial intelligence. Part 1. Sociology of Medicine. 2023;22(2):202–211. DOI: https://doi.org/10.17816/socm619132