Artificial intelligence (AI) is reshaping the financial services landscape, yet little is known about which consumers are most interested in adopting AI financial advice. This study examines the factors associated with consumer interest in AI financial advice and explains heterogeneous adoption pathways. Using nationally representative data from the 2024 National Financial Capability Study, the research combines logistic regression with k-means clustering within a Financial Capability and Digital-Psychological Readiness framework. Regression results reveal that interested consumers tend to have higher objective financial knowledge, stronger financial planning habits, greater risk tolerance, and more developed digital financial habits. In contrast, higher subjective knowledge is negatively associated with interest after controlling for other factors. The cluster analysis, organized around the constructs of financial capability and readiness, identifies four distinct consumer segments with divergent motivations for adoption, clarifying counterintuitive regression findings. The results provide actionable insights for practitioners seeking to design tailored targeted AI solutions and for policymakers concerned with digital inclusion and consumer protection.

Accepted Oral Presentation