What Factors Streamline Adoption of AI-Powered Language Translation tools?

The objective of the study is to investigate the characteristics that influence professionals' propensity to employ AI-powered language translation tools (AILTT) in their professional activities. The research involved collecting survey data from 450 participants through a stratified sample method among Gen-Z professionals, resulting in 371 valid responses after cleansing the data. The research introduced a conceptual framework guided by the adapted AI Device Use Acceptance Model (AIDUA), with hypotheses evaluated by structural equation modeling (SEM) utilizing Smart-PLS. Data was collected through an online survey, and analysis was performed using Smart-PLS to evaluate relationships between variables. The findings indicate that performance expectancy, effort expectancy and emotion significantly influence users' intentions to adopt AI-powered language translation tools, but social influence and perceived social usefulness did not significantly affect users’ adoption intentions in this context. This study is pioneering in the studying the adoption variables for disrupting digital technology like AILTT by incorporate TTF with the AIDUA model. The results of this research have significant significance for developers, educators, and organizations engaged in the deployment of AI-driven language translation technologies.