Generative AI (GenAI) is increasingly reshaping service work and creating new demands for employees’ cognitive and psychological adaptation to human–AI interaction and collaboration. Although prior research has examined the organizational consequences of GenAI, limited attention has been paid to how employees’ acceptance of GenAI is associated with service performance through cognitive adaptation and how this association varies across employees. Drawing on sociotechnical systems theory, this study examined whether knowledge elaboration serves as a cognitive adaptation mechanism linking GenAI acceptance to employee service performance, and whether future orientation strengthens this process.
This study employed a two-wave, multi-source survey design. Data were collected from 890 supervisor–employee dyads in the service sector. Employees reported their GenAI acceptance, future orientation, and demographic information at Time 1, while employees reported knowledge elaboration and supervisors evaluated service performance at Time 2. The hypothesized mediation and moderated mediation models were tested using regression analysis and bootstrapping procedures.
GenAI acceptance was positively associated with knowledge elaboration, which in turn was positively related to employee service performance. The estimated indirect association between GenAI acceptance and service performance through knowledge elaboration was significant, while the direct association remained significant. In addition, future orientation moderated the relationship between GenAI acceptance and knowledge elaboration, such that this relationship was stronger among employees with higher future orientation. The significant index of moderated mediation indicated that the estimated indirect association between GenAI acceptance and service performance through knowledge elaboration was stronger at higher levels of future orientation.
The findings suggest that the association between GenAI acceptance and service performance involves employees’ cognitive engagement with AI-generated knowledge and is stronger among employees with higher future orientation. This study advances understanding of psychological adaptation in AI-integrated work settings by highlighting knowledge elaboration as a key cognitive mechanism and future orientation as an important psychological boundary condition.
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