Pengaruh Penggunaan Artificial Intelligence terhadap Kinerja Karyawan di Era Transformasi Digital

Purwatiningsih Purwatiningsih; Alan Budi Kusuma

doi:10.59024/jumek.v4i3.792

Authors

Purwatiningsih Purwatiningsih Universitas Bina Sarana Informatika
Alan Budi Kusuma Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.59024/jumek.v4i3.792

Keywords:

Artificial Intelligence, Digital Competence, Employee Performance, Digital Transformation, PLS-SEM

Abstract

This research was conducted in response to the increasing pace of digital transformation, which has accelerated the adoption of Artificial Intelligence in the workplace and emphasized the importance of employees' digital competencies. The study aims to examine the influence of Artificial Intelligence and digital competence on employee performance. A quantitative method with an explanatory research design was applied. Data were obtained through a questionnaire survey involving 96 employees who utilize Artificial Intelligence as part of their work activities. The collected data were analyzed using SmartPLS 4 based on the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The findings reveal that Artificial Intelligence exerts a positive and statistically significant influence on employee performance. Likewise, digital competence is found to positively and significantly contribute to employee performance. These results suggest that greater adoption of Artificial Intelligence, together with higher levels of digital competence, enhances employees' ability to achieve better work quality, productivity, timeliness, effectiveness, and target accomplishment. The study highlights the importance for organizations to invest in Artificial Intelligence implementation while continuously developing employees' digital capabilities to support improved performance in the context of ongoing digital transformation.

References

Amstrong, M. (2014). ARMSTRONG’S HANDBOOK OF HUMAN RESOURCE MANAGEMENT PRACTICE i (13th ed.). Ashford Colour Press Ltd. www.koganpage.com

Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99–120.

Barney, J., Wright, M., & Ketchen, D. J. (2001). The resource-based view of the firm: Ten years after 1991. Journal of Management, 27(6), 625–641. https://doi.org/10.1177/014920630102700601

Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., Boselie, P., Lee Cooke, F., Decker, S., DeNisi, A., Dey, P. K., Guest, D., Knoblich, A. J., Malik, A., Paauwe, J., Papagiannidis, S., Patel, C., Pereira, V., Ren, S., … Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. In Human Resource Management Journal (Vol. 33, Number 3, pp. 606–659). John Wiley and Sons Inc. https://doi.org/10.1111/1748-8583.12524

Ferrari, A., Punie, Y., & Brečko, B. N. (n.d.). DIGCOMP: A Framework for Developing and Understanding Digital Competence in Europe. https://doi.org/10.2788/52966

Hair, J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Second Edition.

Kusworo, A. D. B. (2026). Artificial Intelligence–Based Human Resource Management and Employee Performance. International Journal of Business, Law, and Education, 7(1), 21–26. https://doi.org/10.56442/ijble.v7i1.1328

Madanchian, M., Taherdoost, H., & Mohamed, N. (2023). AI-Based Human Resource Management Tools and Techniques; A Systematic Literature Review. Procedia Computer Science, 229, 367–377. https://doi.org/10.1016/j.procs.2023.12.039

Malik, A., Budhwar, P., & Kazmi, B. A. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. In Human Resource Management Review (Vol. 33, Number 1). Elsevier Ltd. https://doi.org/10.1016/j.hrmr.2022.100940

Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699

Prikshat, V., Islam, M., Patel, P., Malik, A., Budhwar, P., & Gupta, S. (2023). AI-Augmented HRM: Literature review and a proposed multilevel framework for future research. Technological Forecasting and Social Change, 193. https://doi.org/10.1016/j.techfore.2023.122645

Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/AMR.2018.0072

Russell, T., Allen, M., Ford, L., Carretta, T., & Kirkendall, C. (2023). Development of a performance taxonomy for entry-level military occupations. Military Psychology, 35(4), 283–294. https://doi.org/10.1080/08995605.2022.2050163

van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588. https://doi.org/10.1016/j.chb.2017.03.010

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. In Journal of Strategic Information Systems (Vol. 28, Number 2, pp. 118–144). Elsevier B.V. https://doi.org/10.1016/j.jsis.2019.01.003