Customer Acceptance of Artificial Intelligence in Healthcare: A Systematic Literature Review and Proposition of Conceptual Framework for Future Research

Artificial Intelligence (AI) is transforming the healthcare sector worldwide. AI solutions are improving healthcare by complementing workforce requirements and enhancing the quality of care through early diagnosis, robot-assisted surgery, remote patient monitoring, electronic healthcare record keeping, etc. Customer adoption is crucial for the successful implementation of AI in healthcare. There has been an increase in academic research on customer adoption of AI in healthcare. Through a systematic literature review, this study tries to determine the state of the art of customer acceptance of AI in healthcare along with factors affecting customer adoption of AI in healthcare. The authors appliedthe Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method for article search and selection for the review. A total of 3732 articles were identified for the screening after removing duplicates, and one hundred and twenty-six articles fulfilled the inclusion and exclusion criteria. The selected articles were analyzed using the Theory, Characteristics, Contexts, and Methods (TCCM) framework. Among the articles that fulfilled the inclusion criteria in the study, the most commonly used methodology and theoretical foundation were the survey method and the Unified Theory of Acceptance and Use of Technology (UTAUT), respectively. Performance expectancy, effort expectancy, privacy concerns, etc., are some of the key factors affecting customer adoption of AI in healthcare. This review leads to a conceptual research framework of Antecedents, Service encounters, and outcomes (A-S-O) for future research on customer acceptance of AI in healthcare.