Kolaborasi Pegawai Dengan AI dan Efikasi Diri AI Terhadap Inovasi Melalui Work Engagement
DOI:
https://doi.org/10.55587/jseb.v1i3.461Keywords:
Employee AI Collaboration, AI Self Efficacy, Work Engagement, Innovative Work Behavior, Local GovernmentAbstract
Purpose: This study examines employee–AI collaboration and AI self-efficacy in relation to innovative work behavior through work engagement at the Kutai Kartanegara Regency Transportation Agency.
Method: The analysis uses 50 complete responses comprising 26 indicators. The data collector confirmed that the survey was conducted on 23–28 August 2026. Reflective Mode A PLS path modeling with path weighting and 5,000 bootstrap resamples was used, alongside measurement diagnostics and a sensitivity analysis using average item scores.
Findings: Collaboration and AI self-efficacy met the stated composite reliability and convergent validity criteria. Work engagement had an average variance extracted below 0.50, while innovative work behavior showed inadequate internal consistency and convergent validity. The HTMT ratio between engagement and innovation exceeded the strict threshold of 0.85. Exploratory estimates indicated positive collaboration–innovation and engagement–innovation paths, but a negative collaboration–engagement path and indirect association. The self-efficacy paths were inconclusive.
Downloads
References
AlMunthiri, O., Bani Melhem, S., Mohd Shamsudin, F., & Al-Naqbi, S. A. (2024). Does leading with inclusiveness promote innovative behaviours? Examining the role of work engagement and psychological safety. International Journal of Organizational Analysis, 32(10), 2468–2493. https://doi.org/10.1108/IJOA-09-2023-4003
Bakker, A. B., Demerouti, E., & Sanz-Vergel, A. (2023). Job Demands–Resources Theory: Ten Years Later. Annual Review of Organizational Psychology and Organizational Behavior, 10(1), 25–53. https://doi.org/10.1146/annurev-orgpsych-120920-053933
Bankins, S., & Formosa, P. (2023). The Ethical Implications of Artificial Intelligence (AI) For Meaningful Work. Journal of Business Ethics, 185(4), 725–740. https://doi.org/10.1007/s10551-023-05339-7
Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S. L. D., & Woo, S. E. (2024). A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior, 45(2), 159–182. https://doi.org/10.1002/job.2735
Becker, J.-M., Cheah, J.-H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023). PLS-SEM’s most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321–346. https://doi.org/10.1108/IJCHM-04-2022-0474
Brynjolfsson, E., Li, D., & Raymond, L. (2025). Generative AI at Work. The Quarterly Journal of Economics, 140(2), 889–942. https://doi.org/10.1093/qje/qjae044
Cheng, B., Lin, H., & Kong, Y. (2023). Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting. Journal of Business Research, 164, 113987. https://doi.org/10.1016/j.jbusres.2023.113987
Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290. https://doi.org/10.1126/sciadv.adn5290
Jia, N., Luo, X., Fang, Z., & Liao, C. (2024). When and How Artificial Intelligence Augments Employee Creativity. Academy of Management Journal, 67(1), 5–32. https://doi.org/10.5465/amj.2022.0426
Khan, A. N., Soomro, M. A., & Pitafi, A. H. (2025). AI in the Workplace: Driving Employee Performance Through Enhanced Knowledge Sharing and Work Engagement. International Journal of Human–Computer Interaction, 41(17), 10699–10712. https://doi.org/10.1080/10447318.2024.2436611
Kim, B.-J., & Lee, D.-g. (2025). Self-efficacy in using artificial intelligence as a shield: mitigating the detrimental effects of organizationally prescribed perfectionism on employee stress and anxiety. Current Psychology, 44(3), 1805–1831. https://doi.org/10.1007/s12144-024-07234-4
Kousina, E., & Voudouris, I. (2023). The ambidextrous leadership‐innovative work behavior relationship in the public sector: The mediating role of psychological ownership. Public Administration Review, 83(6), 1478–1495. https://doi.org/10.1111/puar.13650
Lakens, D. (2022). Sample Size Justification. Collabra: Psychology, 8(1), 33267. https://doi.org/10.1525/collabra.33267
Madan, R., & Ashok, M. (2023). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly, 40(1), 101774. https://doi.org/10.1016/j.giq.2022.101774
Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187–192. https://doi.org/10.1126/science.adh2586
OECD. (2025). Governing with artificial intelligence: The state of play and way forward in core government functions. OECD Publishing. https://doi.org/10.1787/795de142-en
Podsakoff, P. M., Podsakoff, N. P., Williams, L. J., Huang, C., & Yang, J. (2024). Common Method Bias: It's Bad, It's Complex, It's Widespread, and It's Not Easy to Fix. Annual Review of Organizational Psychology and Organizational Behavior, 11(1), 17–61. https://doi.org/10.1146/annurev-orgpsych-110721-040030
Ringle, C. M., Sarstedt, M., Sinkovics, N., & Sinkovics, R. R. (2023). A perspective on using partial least squares structural equation modelling in data articles. Data in Brief, 48, 109074. https://doi.org/10.1016/j.dib.2023.109074
Srirahayu, D. P., Ekowati, D., & Sridadi, A. R. (2023). Innovative work behavior in public organizations: A systematic literature review. Heliyon, 9(2), e13557. https://doi.org/10.1016/j.heliyon.2023.e13557
Tang, P. M., Koopman, J., Mai, K. M., De Cremer, D., Zhang, J. H., Reynders, P., Ng, C. T. S., & Chen, I.-H. (2023). No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence. Journal of Applied Psychology, 108(11), 1766–1789. https://doi.org/10.1037/apl0001103
Vaccaro, M., Almaatouq, A., & Malone, T. (2024). When combinations of humans and AI are useful: A systematic review and meta-analysis. Nature Human Behaviour, 8(12), 2293–2303. https://doi.org/10.1038/s41562-024-02024-1
van Noordt, C., & Misuraca, G. (2022). Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), 101714. https://doi.org/10.1016/j.giq.2022.101714
Wang, Y.-Y., & Chuang, Y.-W. (2024). Artificial intelligence self-efficacy: Scale development and validation. Education and Information Technologies, 29(4), 4785–4808. https://doi.org/10.1007/s10639-023-12015-w
Yin, M., Jiang, S., & Niu, X. (2024). Can AI really help? The double-edged sword effect of AI assistant on employees’ innovation behavior. Computers in Human Behavior, 150, 107987. https://doi.org/10.1016/j.chb.2023.107987
Zahari, N., & Kaliannan, M. (2023). Antecedents of Work Engagement in the Public Sector: A Systematic Literature Review. Review of Public Personnel Administration, 43(3), 557–582. https://doi.org/10.1177/0734371X221106792
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Siti Ulfa, Herman Alfian
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
