Responsible AI Leadership and Employee Green Innovative Work Behavior: The Mediating Role of AI Learning Self-Efficacy and the Moderating Role of Environmental Commitment
Shahzad Ahmada, Moazzamb, Mudassar Hussainc, Sujawal Hussaind, Ali Ijaze
- aLecturer, Institute of Business, Management and Administrative Sciences, Faculty of Management Science and Commerce, The Islamia University of Bahawalpur, 63100, Punjab, Pakistan
- bLecturer, Department of Management Sciences, University of Engineering and Technology (UET) Lahore, Narowal Campus
- cAssistant Professor, Department of Management Sciences, University of Engineering and Technology (UET) Lahore, Narowal Campus
- dLecturer, Department of Management and Administrative Sciences, Thal University Bhakkar
- e
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Abstract
Artificial Intelligence (AI) is becoming a more integral component of businesses' operations, which leads to a pertinent sustainability challenge: How can the responsible use of AI be translated into sustainable behavior of employees? Responsible AI symbolization by leaders (L-RAIS) is examined as a predictor of green innovative work behavior (GIWB) and AI learning self-efficacy (AILSE) is explored as a mediator between the two variables. Environmental commitment (EC) is explored as a moderating variable for the relationship between L-RAIS and GIWB. Using partial least squares structural equation modeling (PLS-SEM), the data were gathered from 529 employees of the five conventional commercial banks spread across Pakistan, and tested based on Social Cognitive Theory and Signaling Theory. The results show that L-RAIS has a significant positive effect on AILSE (β = 0.504, p < 0.001) and GIWB (β = 0.307, p < 0.001), while AILSE also positively influences GIWB (β = 0.432, p < 0.001). The partial mediation of the relationship between L-RAIS and GIWB supports the assertion that responsible AI leadership contributes to green innovation, in part by growing their confidence in learning and using AI technologies. Furthermore, EC positively moderates the relationship between AILSE and GIWB (β = 0.136, p < 0.001), suggesting that the more committed employees are to the environment, the stronger the relationship between their confidence in AI and their green innovative behavior. The study advances responsible AI research towards sustainable employee outcomes, and identifies the complementary contribution of responsible leadership, AI related psychological capability, and environmental motivation in the context of sustainable digital transformation. The results can be applied in practice for banks looking to harmonize the implementation of AI, staff training, and environmental sustainability goals.