A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership

Abstract

Purpose

This paper aims to explore employee perceptions of companies engaged in services and banking of the role of change leadership on the application of artificial intelligence (AI) that will impact the performance and work engagement in conditions that are experiencing rapid changes.

Design/methodology/approach

This study has used a quantitative research approach, and data analysis uses an approach structural equation modeling (SEM) supported by program computer software AMOS 22.0. A total of 357 respondents were involved in this study, but only 254 were qualified. In this study, the respondent is an employee of companies engaged in the services and banking sector in the East Java, Indonesia region.

Findings

The results reveal that AI has a significant positive effect on employee performance and work engagement. Change leadership positively moderates the influence of AI on employee performance and work engagement.

Originality/value

The development of this model has a novelty by including the moderating variable of the role of change leadership because, in conditions that are experiencing rapid changes, the role of leaders is essential. After all, leaders are decision-makers in the organization. The development of this concept focuses on studies of companies engaged in services and banking. Employee performance is an essential determinant in the organization because it will improve organizational performance. In addition, the application of AI in organizations will experience turmoil, so that the critical role of leaders is needed to achieve success with employee work engagement.

Citation

Wijayati, D.T., Rahman, Z., Fahrullah, A., Rahman, M.F.W., Arifah, I.D.C. and Kautsar, A. (2022), "A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership", International Journal of Manpower, Vol. 43 No. 2, pp. 486-512. https://doi.org/10.1108/IJM-07-2021-0423