Article Sidebar

Download
PDF

Main Article Content

Abstract

The rapid adoption of artificial intelligence (AI) is reshaping organizational structures and employment landscapes, raising concerns about job insecurity and employee well-being. This study examines the effect of AI-induced job insecurity on burnout among frontline employees in Indonesia, drawing on the Job Demands–Resources (JD-R) framework. Specifically, it investigates job stress and meaningfulness of work as mediating mechanisms and self-efficacy in AI learning as a moderating resource. A cross-sectional survey was conducted with 325 frontline employees across sectors where AI adoption is increasing, and data were analyzed using Structural Equation Modeling in Jamovi. The results indicate that AI-induced job insecurity significantly increases employee burnout, both directly and indirectly. Job stress was confirmed as a positive mediator, while meaningfulness of work functioned as a negative mediator, highlighting the dual role of demands and resources in shaping burnout. Furthermore, self-efficacy in AI learning moderated the insecurity–burnout relationship, such that employees with higher efficacy were less adversely affected. These findings extend the JD-R model by integrating AI-related job insecurity and demonstrating the dual processes of stress elevation and resource erosion. The study offers practical implications for organizations to prioritize transparent communication, reskilling initiatives, and meaning-enhancing practices to safeguard employee resilience in the era of digital transformation.

Keywords

AI-induced job insecurity Job Demands–Resources model Job Stress Burnout Frontline employees.

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Amirah, A. A., Herachwati, N. ., & Fiona Niska Dinda Nadia. (2025). From Ai-Induced Job Insecurity to Burnout: A Job-Demands Resource Model of Job Stress, Meaningfulness of Work, And Self-Efficacy in Ai Learning Among Front-Line Employees in Indonesia. Amkop Management Accounting Review (AMAR), 5(2), 547–566. https://doi.org/10.37531/amar.v5i2.3273
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Allan, B. A., Batz-Barbarich, C., Sterling, H. M., & Tay, L. (2019). Outcomes of Meaningful Work: A Meta-Analysis. Journal of Management Studies, 56(3), 500–528. https://doi.org/10.1111/joms.12406
  2. Alwi, A. (2025). Analysis Of Accounting Information Systems For Price Changes At Indomaret In Sungai Selayur Village, Kalidoni Palembang. EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi Dan Bisnis, 13(2), 1277–1288. https://doi.org/10.37676/ekombis.v13i2.7956
  3. Baadshah, M. (2025). Navigating Job Loss Due to Artificial Intelligence: Global Trends, Asian Perspectives, and the Indian Scenario. Journal of Advanced Management Studies, 2(3), 37–53. https://doi.org/10.36676/jams.v2.i3.45
  4. Bakker, A. B., & Demerouti, E. (2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273–285. https://doi.org/10.1037/ocp0000056
  5. Baltasar, S., & Marbun, T. (2025). The Role of Artificial Intelligence in Human Capital Management: A Review at PT. Pos Indonesia. International Journal of Cyber and IT Service Management (IJCITSM), 5(1), 31–44. https://doi.org/10.34306/ijcitsm.v5i1.175
  6. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
  7. Bansal, A., Mukherjee, S., & Prayag, G. (2025). From crisis to care: Redesigning work and jobs for employee well-being in hospitality and tourism. Tourism and Hospitality Research, 14673584251321038. https://doi.org/10.1177/14673584251321038
  8. Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2022). Does remote work flexibility enhance organization performance? Moderating role of organization policy and top management support. Journal of Business Research, 139, 1501–1512. https://doi.org/10.1016/j.jbusres.2021.10.069
  9. De witte, H., Pienaar, J., & De cuyper, N. (2016). Review of 30 Years of Longitudinal Studies on the Association Between Job Insecurity and Health and Well‐Being: Is There Causal Evidence? Australian Psychologist, 51(1), 18–31. https://doi.org/10.1111/ap.12176
  10. Fan, W., & Qian, Y. (2023). State Contexts, Job Insecurity, and Subjective Well-being in the Time of COVID-19. Journal of Happiness Studies, 24(6), 2039–2059. https://doi.org/10.1007/s10902-023-00669-9
  11. Fournier-Tombs, E., Lee, J. H., Suriyawongkul, A., Raghunath, P., Dailey, M., Chatterjee, J. S., Doneys, P., Suthorn, W., Thongprasert, S., Villanueva, K., & Belda, F. (2023). Gender-sensitive AI Policy in Southeast Asia.
  12. Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
  13. George, D. A. S., Baskar, D. T., & Siranchuk, D. N. (2025). Navigating the AI Disruption: Strategic Frameworks for Workforce Transformation and Innovation in the Age of Intelligent Automation. Partners Universal International Innovation Journal, 3(3), 83–95. https://doi.org/10.5281/zenodo.15758083
  14. Goodwin, N., Harris, J. M., Nelson, J. A., Rajkarnikar, P. J., Roach, B., & Torras, M. (2022). Macroeconomics in Context (4th ed.). Routledge. https://doi.org/10.4324/9781003251521
  15. Greenhalgh, L., & Rosenblatt, Z. (1984). Job Insecurity: Toward Conceptual Clarity. Academy of Management Review, 9(3), 438–448. https://doi.org/10.5465/amr.1984.4279673
  16. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  17. Hobfoll, S. E., Halbesleben, J., Neveu, J.-P., & Westman, M. (2018a). Conservation of Resources in the Organizational Context: The Reality of Resources and Their Consequences. Annual Review of Organizational Psychology and Organizational Behavior, 5(Volume 5, 2018), 103–128. https://doi.org/10.1146/annurev-orgpsych-032117-104640
  18. Hu, Q., Schaufeli, W. B., & Taris, T. W. (2011). The Job Demands–Resources model: An analysis of additive and joint effects of demands and resources. Journal of Vocational Behavior, 79(1), 181–190. https://doi.org/10.1016/j.jvb.2010.12.009
  19. Huo, L., Zhou, Y., Li, S., Ning, Y., Zeng, L., Liu, Z., Qian, W., Yang, J., Zhou, X., Liu, T., & Zhang, X. Y. (2021). Burnout and Its Relationship With Depressive Symptoms in Medical Staff During the COVID-19 Epidemic in China. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.616369
  20. Jiang, L., & Lavaysse, L. M. (2018). Cognitive and Affective Job Insecurity: A Meta-Analysis and a Primary Study. Journal of Management, 44(6), 2307–2342. https://doi.org/10.1177/0149206318773853
  21. Kim, B.-J., & Lee, J. (2024). The safety implications of work overload: The sequential mediating roles of the meaningfulness of work and perceived organizational support, and the moderating effect of coaching leadership. Current Psychology, 43(41), 31933–31954. https://doi.org/10.1007/s12144-024-06710-1
  22. Kim, N. Y. (2024). Linking Creative Self-Efficacy and Emotional Exhaustion: Mediation Through Cognitive Reappraisal. Psychological Reports, 00332941241276397. https://doi.org/10.1177/00332941241276397
  23. Konkel, M., & Heffernan, M. (2021). How job insecurity affects emotional exhaustion? A study of job insecurity rumination and psychological capital during COVID-19. The Irish Journal of Management, 40(2), 86–99. https://doi.org/10.2478/ijm-2021-0009
  24. Lazarus, A. A. (1966). Behaviour rehearsal vs. Non-directive therapy vs. Advice in effecting behaviour change. Behaviour Research and Therapy, 4(1), 209–212. https://doi.org/10.1016/0005-7967(66)90068-4
  25. Li, X., Seah, R. Y. T., & Yuen, K. F. (2025). Mental wellbeing in digital workplaces: The role of digital resources, technostress, and burnout. Technology in Society, 81, 102844. https://doi.org/10.1016/j.techsoc.2025.102844
  26. Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job Burnout. Annual Review of Psychology, 52(Volume 52, 2001), 397–422. https://doi.org/10.1146/annurev.psych.52.1.397
  27. Peng, B., & Potipiroon, W. (2022). The Effect of Job Insecurity on Bank Employees’ Job Stress and Job Burnout During COVID-19: A Moderated Mediation Model. ABAC Journal, 42(3), 38–56. https://doi.org/10.14456/abacj.2022.19
  28. Rosso, B. D. (2014). Creativity and Constraints: Exploring the Role of Constraints in the Creative Processes of Research and Development Teams. Organization Studies, 35(4), 551–585. https://doi.org/10.1177/0170840613517600
  29. Shukla, A., & Srivastava, R. (2016). Development of short questionnaire to measure an extended set of role expectation conflict, coworker support and work-life balance: The new job stress scale. Cogent Business & Management, 3(1), 1. https://doi.org/10.1080/23311975.2015.1134034
  30. Singh, R. P. (2000). Entrepreneurial Opportunity Recognition Through Social Networks. Psychology Press.
  31. Soren, A., & Ryff, C. D. (2023). Meaningful Work, Well-Being, and Health: Enacting a Eudaimonic Vision. International Journal of Environmental Research and Public Health, 20(16), 6570. https://doi.org/10.3390/ijerph20166570
  32. Steger, M. F., Dik, B. J., & Duffy, R. D. (2012). Measuring Meaningful Work: The Work and Meaning Inventory (WAMI). Journal of Career Assessment, 20(3), 322–337. https://doi.org/10.1177/1069072711436160
  33. Sverke, M., Hellgren, J., & Näswall, K. (2002). No security: A meta-analysis and review of job insecurity and its consequences. Journal of Occupational Health Psychology, 7(3), 242–264. https://doi.org/10.1037/1076-8998.7.3.242
  34. Tien, J. M. (2020). Toward the Fourth Industrial Revolution on Real-Time Customization. Journal of Systems Science and Systems Engineering, 29(2), 127–142. https://doi.org/10.1007/s11518-019-5433-9
  35. Üngüren, E., Tekin, Ö. A., Avsallı, H., & Kaçmaz, Y. Y. (2021). The Moderator Role of Financial Well-Being on the Effect of Job Insecurity and the COVID-19 Anxiety on Burnout: A Research on Hotel-Sector Employees in Crisis. Sustainability, 13(16), 9031. https://doi.org/10.3390/su13169031
  36. Van Doorn, J., Smailhodzic, E., Puntoni, S., Li, J., Schumann, J. H., & Holthöwer, J. (2023). Organizational frontlines in the digital age: The Consumer–Autonomous Technology–Worker (CAW) framework. Journal of Business Research, 164, 114000. https://doi.org/10.1016/j.jbusres.2023.114000
  37. Vivek, S., & Ahmed, M. S. (2023). Social Listening Using Machine Learning and NLP to Make Sense of Frontline Employees Experiences and Learning. 2023 33rd International Conference on Computer Theory and Applications (ICCTA), 95–98. https://doi.org/10.1109/ICCTA60978.2023.10969431
  38. 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
  39. Wicaksana, P. (2024). Exploring the Impact of Burnout and Job Insecurity on Turnover Intention During the Covid-19 Pandemic. Acta Psychologia, 2(4), 141–149.
  40. Wu, T.-J., Liang, Y., & Wang, Y. (2024). The Buffering Role of Workplace Mindfulness: How Job Insecurity of Human-Artificial Intelligence Collaboration Impacts Employees’ Work–Life-Related Outcomes. Journal of Business and Psychology, 39(6), 1395–1411. https://doi.org/10.1007/s10869-024-09963-6
  41. Yavorsky, J. E., Qian, Y., & Sargent, A. C. (2022). The Gendered Pandemic: The Implications of COVID-19 for Work and Family. In Working in America (5th ed.). Routledge.