One of the primary challenges in the development and deployment of artificial intelligence (AI) is the level of acceptance and alignment by organizations and users. Without a comprehensive understanding of the key acceptance factors, implementing AI in sensitive sectors like healthcare may face serious obstacles. This study aims to identify and prioritize the key factors influencing AI adoption in hospital performance management systems.

The research is applied in nature and initially involved extracting relevant models and influencing factors from the literature and expert opinions. The Best-Worst Method (BWM), a multi-criteria decision-making technique, was then used for prioritization. A total of 15 hospital managers participated in the study.

The findings revealed 12 key factors affecting AI acceptance, including: managerial commitment and support, strategic alignment with organizational goals, data governance and accessibility, organizational agility and innovation capacity, ethical and legal considerations, minimal viable ecosystems, financial and economic capacity, organizational culture and readiness for change, technological infrastructure and security, AI compatibility with organizational conditions, AI-related knowledge and skills, and environmental pressures and market demand. Among these, managerial commitment and strategic alignment were identified as the most influential factors, while environmental pressures and market demand were ranked as the least significant.