Bank Employees' Attitudes Toward Artificial Intelligence: An Empirical Investigation Of Human-Ai Integration Through An Extended Utaut-2 Model

The rapid proliferation of artificial intelligence (AI) in the banking sector necessitates a deeper understanding of the integration between biological and artificial brains. This study aims to investigate the factors influencing bank employees' acceptance and self-reported use behavior of AI technologies. The research employs a quantitative approach, utilizing data collected via convenience sampling from 290 bank employees operating in Ankara, Turkey. The proposed theoretical model was tested using a dual-stage analysis: descriptive statistics and validity and reliability tests were conducted via SPSS, while the hypotheses and structural relationships were validated through Structural Equation Modeling (SEM) using AMOS software. The results of the SEM analysis indicate that Social Influence, Hedonic Motivation, and Price Value are significant positive predictors of bank employees' Behavioral Intention to use AI. Furthermore, the findings demonstrate that Behavioral Intention serves as a critical and significant determinant in explaining the self-reported Use Behavior of these technologies within the organizational setting. Despite the global trend toward AI integration, there is a notable gap in the literature regarding the empirical measurement of AI adoption among bank employees in the Turkish context. This study fills this gap by providing localized empirical evidence and contributes to the broader "AI-Human Integration" discourse by highlighting the specific drivers of technology acceptance in a high-stakes service environment like banking.