Authors - Kalinka Kaloyanova, Elitza Kaloyanova Abstract - Despite the increasing use of artificial intelligence (AI) in healthcare, clinician adoption of AI tools is still obstructed by algorithmic aversion, which reflects scepticism about the results of AI use. This article examines how hospitals can enhance AI adoption by strengthening AI competencies in physicians and mitigating mistrust through a systematic, data-driven approach. A review of behavioral studies reveals barriers to AI adoption across technical, cognitive, organizational, and ethical domains. A framework is proposed that focuses on integrating individual clinician competencies with structured strategies implemented by hospitals that support workflow and create conditions for continuous learning. The implementation of data-centric strategies, explainable AI tools, competency programs, simulation training, and interprofessional collaboration is recommended to increase trust in AI in medicine, support its ethical use, which ultimately leads to safer healthcare delivery.
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