This study investigates how organizational factors shape employees’ perceptions of AI usefulness and their intention to adopt AI. Six factors commonly discussed in technology adoption research competitive advantage, decision-making support, work efficiency, cost burden, technological uncertainty, and internal resistance were examined using survey data from 197 employees. The data were analyzed through exploratory factor analysis, correlation analysis, and mediation testing with PROCESS Macro (Model 4). The results show that the three facilitative factors were associated with higher perceived usefulness, whereas cost burden, uncertainty, and internal resistance reduced perceived usefulness. Perceived usefulness was a significant predictor of AI adoption intention and mediated most relationships between the examined factors and adoption intention. These findings demonstrate that adoption decisions depend not only on organizational conditions but also on employees’ evaluations of AI’s value, indicating the importance of addressing both enabling and inhibiting influences when implementing AI within organizations.
Do et al. (Sat,) studied this question.