Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors

Abstract

The purpose of this review is integrating and contextualizing relevant literature on the factors influencing the adoption of AI in the healthcare industry into a comprehensive framework. Health systems are considered fundamental to creating societal value. However, global health systems are challenged by the increasing number of patients due to population aging and the growing prevalence of chronic diseases and cancer. Meanwhile, the United Nations calls for equal access to healthcare, tackling costs, and addressing resource constraints to foster the sustainable development of societies. In this context, artificial intelligence (AI) is gaining attention as it constitutes a promising technology to address these burgeoning challenges. Despite opportunities, the literature specifically on the adoption of AI in the healthcare industry is fragmented across various research fields, lacking a comprehensive overview. It lacks theoretically grounded research integrating, for example, the factors that influence the adoption of AI in healthcare institutions.Derived from a multi-disciplinary systematic literature review, building on 130 studies, we propose the Adoption of AI in the Healthcare Industry Model. This model encompasses five dimensions influencing the adoption of AI in the healthcare industry and contextualizes them. We propose that macro-economic, regulatory, and technological readiness serve as external antecedents whereas organizational and individual readiness constitute internal antecedents influencing adoption of AI in healthcare institutions.Our review has implications for research on technology acceptance related to AI in healthcare. Further, we provide hands-on guidance for AI providers, health institutions, and official bodies such as governments to foster the adoption of AI to leverage value.