The Impact of the Generative AI Implementation Environment on Employees’ Intention to Adopt, Mediated by Psychological Variables

This study aims to empirically investigate the structural pathways through which organizational factors associated with the adoption environment of generative artificial intelligence (AI) influence employees' intentions to adopt AI through psychological mechanisms.Based on the Technology-Organization-Environment (TOE) framework, a macro-level technology adoption model, the adoption environment was categorized into technological, organizational, and environmental factors.AI self-efficacy and AI anxiety were established as mediating variables representing opposing psychological mechanisms, while intention to adopt was specified as the dependent variable.To empirically test the proposed research model, a survey was conducted among 327 Korean employees who were currently using generative AI in their work.The hypotheses were tested using structural equation modeling (SEM) and bootstrapping analysis.The results indicate that both technological and organizational factors significantly enhanced AI self-efficacy while simultaneously reducing AI anxiety.Environmental factors had a significant positive effect on AI self-efficacy but did not have a significant effect on reducing AI anxiety.Furthermore, AI self-efficacy was found to have a positive effect on intention to adopt, whereas AI anxiety was identified as a key mediating factor that negatively affects intention to adopt.This study contributes to the literature by identifying an integrated mechanism through which macro-level environmental stimuli are translated into behavioral intentions through individuals' internal psychological evaluations.From a practical perspective, the findings suggest that organizations should move beyond simply following external trends in generative AI adoption.Instead, they should focus on enhancing employees' self-efficacy through technological maturity and internal organizational training, while simultaneously addressing employees' concerns and fears regarding potential technological replacement.