Integration of Artificial Intelligence into Medical Practice at the Medical Centers of the “University Medical Center” Corporate Fund: Perception of Medical Staff

Abstract

This study discusses the preparation of implementing the use of artificial intelligence (AI) into clinical practice in the University Medical Center (UMC), and what motivates the willingness to adopt it and what circumstances influence trust of using AI-assisted decision-making. The research is based on a mixed-method design where a cross-sectional survey of the staff is conducted with intensive qualitative interviews to collect both quantifiable predictors of readiness and practical issues that arise in the actual clinical processes. This quantitative analysis suggests that the willingness to use AI is most closely related to perceived usefulness, digital confidence, and organizational readiness, which means that positive attitudes are prone to turn into adoption intent at the moment when the staff members feel competent and trained and equipped to do this. The qualitative results add a deeper shade to this image because they demonstrate that superficial optimism may be combined with opposition under the conditions of uncertainty about operational rules, in particular, accountability, verification processes, and workflow integration. In both strands, there is increased trust when AI generated outputs are clinically explicable, patient data security is plausible and comprehensible, and accountability to AI-aided decision making is well-controlled. The research concludes that effective AI implementation in the UMC is not determined by the degree of enthusiasm about technology but rather the establishment of governance systems that are safe, transparent, and role-specific capacity building and accountability. The findings highlight a more controlled implementation policy, enhanced data governance, and preparedness of the organization instead of quick deployment.