<![CDATA[Despite the recognition of artificial intelligence (AI) as an innovative banking frontier, its full-scale activation is limited by an insufficient understanding of user adoption behaviors, particularly among specific demographics in emerging markets. This study explores the behavioral indicators affecting the adoption of AI among potential digital banking adopters in Indonesia classified as Gen Z. The theoretical underpinnings of the unified theory of acceptance of technology (UTAUT2) and technology acceptance model (TAM), data from 414 respondents, and the structural equation modeling (SEM) technique were used to identify the behavioral indicators of AI adoption. The empirical findings reveal that intrinsic motivations (perceived ease of use, usefulness, performance expectancy, effort expectancy, and hedonic motivation) significantly drive AI adoption among Gen Z in Indonesian digital banking. Notably, external factors such as social influence and facilitating conditions, along with demographic variables such as gender and age, were found to be insignificant, challenging the established models in this context. Conversely, the level of education and job role emerged as significant drivers. This study refines the integrated UTAUT2 and TAM framework by demonstrating how the unique characteristics of Gen Z in an emerging digital economy reshape the influence of external factors, thereby establishing crucial boundary conditions for these models. These findings offer actionable insights for banking professionals to design targeted digital marketing strategies and policies that resonate with this crucial demographic, especially in contexts similar to Indonesia's digital development stage. ]]>
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