The emergence of digital technology has accelerated the growth of the financial sector in Malaysia. Artificial Intelligence (AI) technology has been integrated into investing activities to create automated investment management services known as robo-advisors. Despite the fact that numerous efforts have been attempted to publicize robo-advisors, its adoption among Malaysian retail investors remains relatively low. Hence, the aim of this paper is to extend the existing Technology Acceptance Model (TAM) to examine the main drivers of intention to adopt robo-advisors that explain the robo-advisors adoption process among Malaysian retail investors. In this study, 300 valid primary responses from Malaysian retail investors aged 18 to 77 who have used robo-advisors were collected through online questionnaire and analyzed using Partial Least Square Structural Equation Modelling (PLS-SEM) method. All the hypotheses in this study were supported. In particular, attitude was found to be the strongest predictor of behavioral intention to adopt robo-advisors followed by perceived usefulness, subjective norms, perceived behavioral control, and lastly perceived risk. As such, robo-advisory vendors and the relevant regulatory authorities should focus on these key drivers to boost robo-advisors adoption in Malaysia.