This quantitative study investigates key factors influencing Malaysian medical professionals’ adoption of Smart Clinical Decision Tools (AI-CDT). Using the UTAUT2 framework, data from 154 practitioners across public and private healthcare settings were analyzed with PLS-SEM. Results show that performance expectancy, social influence, and hedonic motivation positively affect adoption intent, while effort expectancy and facilitating conditions do not. The model explains 65.1% of the variance. The findings highlight the need for contextual adaptation of UTAUT2 and stress the importance of demonstrating benefits, peer influence, and user experience to promote adoption. The study contributes to understanding AI integration in healthcare within a developing country.