Even though the acceptance of AI-based technologies among healthcare professionals is significant, little is known about the factors that influence their acceptance. This study aims to examine the theories and models used to study the adoption of AIR in healthcare and to identify the significant factors that affect the adoption of AIR in healthcare across countries. A systematic literature review with the PRISMA framework was conducted. The results reveal an increase in the number of studies concentrating on AIR adoption in healthcare sector in recent years. In addition, this study revealed that the UTAUT model is the most frequently used one. The AIR adoption among countries is primarily due to three main factors: perceived usefulness, perceived ease of use, and behavioural intention. Thirteen factors in developed countries and seventeen factors in developing countries have been identified due to their impact on AIR adoption. The findings of this study constitute a valuable contribution to the current body of knowledge by enhancing the understanding of AIR adoption in healthcare. Moreover, the results offer assistance to policymakers when making decisions and developing strategies related to the adoption of AIR in healthcare.