With the increasing adoption of artificial intelligence (AI) in the financial industry, customers' choices between AI and human services have become a critical issue. Grounded in Dual Factor Theory, this study investigates the influence of motivators (hedonic value, utilitarian value, and perceived competence) and inhibitors (low interaction, perceived risk and trust, and FinTech-related anxiety and knowledge gaps) on customer decisions. A questionnaire survey was conducted, yielding 129 valid responses, and data were analyzed using structural equation modeling.The findings reveal that low interaction in AI services significantly reduces customers' adoption willingness, while FinTech anxiety and lack of knowledge drive preferences for human services. Although motivators positively impact adoption intention, their effects were not statistically significant. Moreover, customer innovativeness showed a limited moderating role in certain pathways. Based on the results, banks are advised to enhance AI-human interaction, strengthen customer education on FinTech, and adopt hybrid service models tailored to specific scenarios. This study addresses the empirical gap in understanding customer preferences between AI and human services, providing practical and theoretical insights for service strategy development in banking.
