Abstract The rapid integration of artificial intelligence (AI) has transformed Malaysia’s financial services, making youth the primary market for AI-enabled FinTech applications. However, high technological exposure does not guarantee adequate digital financial literacy (DFL). To address this gap, this study investigates the drivers of AI-enabled FinTech adoption among Malaysian youth by extending the UTAUT2 model to include DFL as a mediating variable. Utilizing a cross-sectional quantitative design, data were collected from 259 young adults in the Klang Valley and analyzed using partial least squares structural equation modeling (PLS-SEM). The results demonstrate that performance expectancy, hedonic motivation, price value, and habit significantly predict the behavioral intention to use these applications, whereas social influence, effort expectancy, and facilitating conditions are not significant drivers. Crucially, while behavioral intention strongly influences actual usage, this relationship is partially mediated by DFL. This highlights that technological intention alone is insufficient for effective adoption without corresponding digital financial competencies. By bridging the intention–behavior gap, this research provides vital empirical insights for policymakers, educators, and developers to design targeted financial literacy initiatives and responsible AI tools.
Jahanzeb et al. (Thu,) studied this question.
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