Robo-advisors represent a significant technological advancement in the financial sector, including within Indonesia’s growing digital investment landscape. Despite their increasing integration into local platforms, skepticism regarding usability and security continues to hinder widespread adoption. This study aims to examine the indirect influence of Perceived Ease of Use (PEOU) on users’ intention to use robo-advisors through the mediating roles of Perceived Usefulness (PU) and Attitude (ATT). Additionally, it investigates the indirect relationship between Perceived Privacy (PP) and Usage Intention (UI) through Perceived Risk (PR). Data was collected through an online survey of 119 Indonesian participants, evaluating their intention to use robo-advisors in OJK-approved, digital investment applications. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to examine indirect and chain-mediated effects. The findings reveal how PEOU and PP shape users’ intention through PU, ATT, and PR, offering valuable insights for digital investment platforms to enhance user engagement strategies, with strong explanatory power, as the model accounts for 50.1% of the variance in UI. By encouraging the adoption of robo-advisors, this study contributes to improving financial inclusion and literacy among Indonesians, enabling broader access to affordable, data-driven investment management. Strengthening user adoption of these technologies can support the growth of Indonesia’s digital financial ecosystem and promote more informed, efficient financial decision-making. Notably, this study validates an extended Technology Acceptance Model (TAM) framework that better captures user behavior in Indonesia’s dynamic financial technology landscape.