Purpose This study applies CASA theory to examine how algorithmic, technological, and branding factors, along with customer empowerment, shape AI-enabled experiences and influence the adoption of robo-advisor recommendations and stickiness to the robo-advisor. Design/methodology/approach This study uses the partial least squares-structural equation model (PLS-SEM) and combined importance-performance map analysis (cIPMA). Findings Research findings indicate that explainability, brand reputation and perceived anthropomorphism, task technology fit positively impact customer empowerment. Customer empowerment contributes positively to the AI-enabled experience. In turn, AI-enabled experience influences the adoption of recommendations and customers' stickiness with the robo-advisor. The cIPMA results show that, for recommendation adoption, AI-enabled experience and customer empowerment are the key factors that require prioritization, whereas, for stickiness to the robo-advisor, customer empowerment requires prioritization. Originality/value This study integrates CASA theory, signaling theory, and related constructs within the robo-advisor context, revealing how customer empowerment channels the effects of the human likeness factor, technology factor, branding factor and algorithm perception factor on the AI-enabled experience. This study also provides practical implications for enhancing users' recommendation adoption and stickiness to the robo-advisor, with particular relevance for financial inclusion initiatives.
Wang et al. (Mon,) studied this question.