Impact of artificial intelligence-enabled job characteristics and perceived substitution crisis on innovative work behavior of employees from high-tech firms. (June 2022) - Verma, Surabhi
Abstract: The importance of artificial intelligence (AI)-enabled systems has been at the forefront of innovation research for the past ten years. The literature has reported the use of AI-enabled systems (AIS) in firms, but there has been a paucity of empirical research on AI-enabled job characteristics of employees of high-tech firms in regard to innovative work behavior (IWB). To address this gap, drawing on job design theory, we proposed a model that describes the roles that AI-enabled task and knowledge characteristics play in employees' IWB. Furthermore, the effects of AIS on human workforce replacement have been a highly debated topic. Drawing on prospect theory, we tested the moderating role of perceived substitution crisis (PSC) triggered by AIS on IWB. We used the partial least square (PLS) technique to test the hypotheses using data from 486 responses collected from an online survey completed by high-tech professionals. 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. Highlights: Job-design theory and prospect theory adopted to understand AI-enabled work design. AI-enabled task characteristics impact innovative work behavior. AI-enabled knowledge characteristics impact innovative work behavior. AI-enabled job characteristics impact innovative work behavior under differential effects of perceived substitution crisis.