An Empirical Study of AI Financial Advisor Adoption Through Technology Vulnerabilities in the Financial Context

Financial institutions are increasingly employing artificial intelligence (AI) solutions to optimize their financial advice and services for consumers. However, consumers have demonstrated reluctance toward adopting AI technology goods, and the intermediary psychological mechanism of adoption intention in the financial service context is unclear. Using the theoretical lens of technology affordances and constraints, this article proposes the concept of consumer technology vulnerability (CTV) as the mediating mechanism in the affordance–adoption process of AI financial advisors (AFAs). Meanwhile, consumer innovativeness and self-efficacy are investigated as individual traits that moderate perceptions and psychological impacts of AI affordances. Specifically, the study first conceptualizes AI affordances in a product innovation context by reviewing the burgeoning literature on AI to date. This is followed by a US-based survey (N = 616), which shows the positive indirect effects of information optimization, customizability, and human-likeness on AFA adoption intention through CTV. Self-efficacy and consumer innovativeness are found to enhance the positive effects of AI affordances on AFA adoption intention through CTV but diminish the impact of human-likeness on CTV. These findings highlight, for the first time, the mediating role of CTV in new technology adoption. This will help technology innovators and financial institutions to identify how consumers perceive and adopt different AI affordances, and therefore to better incorporate AI characteristics into financial product innovations.