Aim: The primary aim of this study was to investigate and compare the opinions of professional groups responsible for the development of medical AI and ML models regarding the use of those models for their own treatment. Materials and Methods: This survey was conducted through a blend of private interviewing and anonymous online polling, utilizing platforms such as Telegram, LinkedIn, and Viber. The target audience comprised specific international groups, primarily Russian, German, and English-speaking, of healthcare and IT practitioners. These participants ranged in their levels of expertise and experience, from beginners to veterans. The survey centered on a singular, pivotal question: “Do you agree with AI making decisions about your treatment including diagnostics, surgeries, and medications?” Respondents had the option to choose from three responses: “Yes”, “Yes, if supervised by a doctor”, and “No”. Results: A total of 427 unique and verified individuals participated in this survey, comprising 226 IT and 201 healthcare practitioners. The survey results revealed a statistically significant (p-value < 0.0001) difference between the two groups. Over 50% of healthcare workers definitively answered “No” to the application of AI and ML algorithms in their own treatment. In contrast, IT practitioners demonstrated a higher level of trust in the healthcare system's integration with technology, with 70% expressing willingness to be treated by AI under the supervision of a doctor. Only 10% of respondents agree to the application of AI in their own treatment without human supervision. Conclusion: This study reveals a marked contrast in the level of trust between healthcare and IT practitioners regarding the application of AI and ML in their own treatment. Only 50% of healthcare workers express trust in AI, compared to 80% of IT practitioners. Notably, complete trust in AI-driven treatment without human supervision is exceedingly low in both groups, at less than 10%. In clinical settings, patients should be informed about AI applications in their diagnostic and treatment processes.