AI adoption drivers and innovative work behaviours

Purpose Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study aims to analyze the impact of performance expectancy (PE) and training (TR) on AI adoption (AIA). Moreover, our new conceptual model tests the moderating role of personal innovativeness (PI) as well as the final effect of AIA on innovative work behaviour (IWB). Design/methodology/approach A new theoretical conceptual model has been proposed and empirically validated through a “partial least squares structural equation modelling” (PLS-SEM) technique and using the data gathered from 278 employees and managers of information technology (IT) companies. Findings The results showed a positive impact of performance expectancy and training on AI adoption in the organizations. Training also played a mediating role, while personal innovativeness showed a moderating effect in the relationship. Finally, AI adoption led to innovative work behaviour, overall, empirically validating the proposed conceptual model. Research limitations/implications The present investigation extends the scope of UTAUT framework and examines the role of AI adoption in influencing employees' innovative work behaviours, while highlighting the differences in the adoption of technology by the employees. Additionally, this research is useful to managers who question themselves how to foster innovation by integrating AI efficiently with IT industry. However, the scope of this cross-sectional study is restricted by its geographical limitations. Originality/value The present study fills the existing research gap and found the role of an individuals in influencing AI adoption and IWB within the organization. The outcomes of the study would be beneficial for researchers and practitioners in identifying the key role of training and performance expectancy in increasing AI adoption and IWB at the organizational level.