Unfolding Emerging Relationship of AI-enabled Job Characteristics on High-Tech Employees IWB

Abstract

The relevance of AI-enabled systems has occupied the central space of innovation research for a decade. Research works have highlighted adoption of AI-enabled systems (AIS) in firms but there is scant empirical research on AI-enabled job characteristics of employees of high-tech firms pertaining to innovative work behavior (IWB). Therefore, the present attempt to address this research gap, by adopting the job design theory. Authors espouse a model that explains the roles AI- enabled task and knowledge characteristics demonstrate in employee’s IWB. Furthermore, the impact of AIS on human workforce replacement is currently a debatable area. Drawing on prospect theory, we tested the moderating role of perceived substitution crisis (PSC) triggered by AIS on IWB. The results indicated that AI-enabled task characteristics (job autonomy and skill variety) and knowledge characteristics (job complexity, specialization, and information processing) impact IWB and that AI-enabled job characteristics are strongly associated with IWB under differential effects of PSC. The implications of this study could be used by academicians and practitioners to design AI-enabled job characteristics.