One of the most significant aspects of Artificial Intelligence in finance is a robo-advisor, a virtual financial advisor that delivers algorithm-driven financial services to investors on digital platforms, assisting them with their portfolio selection with no human intervention.
Despite the gradual increase in the use of robo-advisors, their poor penetration remains a matter of concern. Extant research testifies to the various benefits of using robo-advisors. While robo-advisors are capturing a large portion of the financial market, little is known about the factors that impact investor adoption and use. This research examines the factors that influence the adoption of robo-advisors in the Indian context. Data was gathered from 445 investors with prior experience in stock market investing using a non-probability-based snowball sampling method. We analysed our results using partial least square- structural equation modelling (PLS-SEM). We find trust, anxiety, performance expectancy, and preference for human advisors as significant determinants of behavioural intention. These factors are tested under the moderating effects of age, gender, and investment knowledge.
Our study considers the user-centric perspective and leverages the responses of investors, the ultimate users of this service, to gain insights into the factors that drive the adoption of robo-advisory services. Such insights would be of great use to service providers in increasing their customer base. Existing and potential investors may be familiarised with the AI-based services via brochures, manuals, and testimonials explaining the advantages, usage, and scope of these services.
