The Effect of Al-Based Robo Advisor on Investment Decision Making Among Retail Investors

This preliminary study examines the effect of AI-based robo-advisors on investment decision making among retail investors. The study adopts a quantitative research approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4 to analyze the relationships among the proposed variables. Data were collected in March 2026 through an online survey distributed via Google Forms to retail investors who have experience using or interacting with AI-based robo-advisor services. A total of 450 valid responses were obtained and analyzed using purposive sampling. The findings indicate that the use of AI-based robo-advisors and related factors significantly influence retail investors’ investment decision-making behavior. The study further examines the role of perceived trust, perceived risk, and self-confidence in shaping investors’ willingness to rely on AI-based recommendations when making investment decisions. The findings highlight the importance of technological and behavioral factors in the adoption of AI-driven investment advisory services. This research contributes to the growing literature on artificial intelligence in financial services by providing empirical insights into how AI-based robo-advisors may influence investment decision making among retail investors and supporting the development of more responsible and user-centered digital investment advisory systems.