When knowledge conversion pays off: knowledge utilization and ethical AI climate for Generation Z employees’ job performance

Purpose While organizational knowledge conversion (OKC) is central to value creation, its translation into individual employee performance remains insufficiently understood, particularly in artificial intelligence (AI)-enabled contexts where knowledge is abundant but must be appropriately adapted and ethically applied to generate meaningful outcomes. Against this backdrop, this study aims to empirically examine how OKC influences employee job performance (efficiency, effectiveness and quality) through customization knowledge utilization (CKU). Moreover, this study aims to investigate the moderating role of ethical AI climate (EAIC) among Gen Z employees working in AI-enabled hospitality workplaces. Design/methodology/approach A two-wave, time-lagged survey was conducted among 423 employees working in 3-, 4- and 5-star hotels in India. Data were analyzed using covariance-based structural equation modeling in AMOS for measurement model, hierarchical regression and Hayes’ PROCESS macro to test mediation and moderated-mediation effects. Findings The results show that OKC significantly enhances employees’ job efficiency, effectiveness and quality. CKU partially mediates these relationships, indicating that knowledge should be adapted to task-specific contexts for greater performance outcomes. Furthermore, EAIC strengthens the indirect effects of OKC on performance via CKU, suggesting that ethical norms surrounding AI use enhance responsible and effective knowledge application. Originality/value This study extends the knowledge-based view and socialization, externalization, combination and internalization model by linking knowledge conversion to individual-level performance outcomes. It introduces CKU as a key mediating mechanism and positions EAIC as a critical boundary condition in AI-enabled work environments. By focusing on Gen Z employees, the study contributes to emerging knowledge management research on digital-native workforces in AI-enabled workplaces.