This study proposes a research model to explain the intention to use robo-advisors for investment by extending the elaboration likelihood model (ELM). In this model, three factors—argument strength, source reliability, and previous exposure—are hypothesized to positively influence usage intention through the mediating effects of disposition and anticipated results. Additionally, the positive impact of these factors on disposition and anticipated results is proposed to be moderated by learning-oriented motivation. Finally, the study discusses the implications and limitations based on these propositions.