Anticipating Technological Unemployment among Accounting Students in the AI Era
Keywords:
Artificial intelligence, Technological unemployment, Qualitative descriptive study, Accounting students, Career adaptationAbstract
This study examines how accounting students perceive artificial intelligence (AI) driven automation and how these perceptions shape career anxiety, role preferences, and adaptive strategies through the lens of Technological Unemployment Theory (TUT). Based on survey data from 370 undergraduate accounting students in Indonesia, this study identifies a clear mechanism in which perceived task automatability increases anticipatory unemployment anxiety, leading to career reorientation. Students primarily associate AI with the automation of routine, standardized, and entry-level accounting tasks, generating concerns about reduced job opportunities and intensified competition before labor market entry. Rather than disengaging from the profession, students respond through adaptive career reorientation toward analytical, judgment-based, and technology-integrated roles, alongside proactive strategies such as upskilling, digital competence development, and intentions to pursue further education as human capital investment. Theoretically, this study extends TUT by demonstrating that technological unemployment operates as a pre-employment cognitive process, not solely as an observed labor market outcome. By highlighting anticipatory perceptions in a developing-economy context, the findings underscore the importance of aligning accounting education with AI responsive career pathways to support adaptive, rather than fear-driven, workforce preparation.
References
Acemoglu, D., & Restrepo, P. (2020). Robots and Jobs: Evidence from US Labor Markets. 128(6).
Aditya, B. R., Ferdiana, R., & Kusumawardani, S. S. (2021). Barriers to Digital Transformation in Higher Education: An Interpretive Structural Modeling Approach. Volume 18,. https://doi.org/10.1142/S0219877021500243
Anita, & Julyanna. (2021). Kinerja Perusahaan di Era Ekonomi Digital: Pengaruh IT Governance, Karakteristik Dewan, dan Investasi Modal. 5(3), 2779–2803.
Ballantine, J., Boyce, G., & Stoner, G. (2024). Critical Perspectives on Accounting A critical review of AI in accounting education : Threat and opportunity. Critical Perspectives on Accounting, 99(January), 102711. https://doi.org/10.1016/j.cpa.2024.102711
Bewersdorff, A., Hornberger, M., Nerdel, C., & Schiff, D. S. (2025). Computers and Education : Artificial Intelligence AI advocates and cautious critics : How AI attitudes , AI interest , use of AI , and AI literacy build university students ’ AI self-efficacy. Computers and Education: Artificial Intelligence, 8(October 2024), 100340. https://doi.org/10.1016/j.caeai.2024.100340
Bin-nashwan, S. A., Li, J. Z., Jiang, H., Bajary, A. R., & Ma’aji, M. M. (2025). Does AI adoption redefine financial reporting accuracy, auditing efficiency, and information asymmetry? An integrated model of TOE-TAM-RDT and big data governance. Computers in Human Behavior Reports, 17(September 2024), 100572. https://doi.org/10.1016/j.chbr.2024.100572
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. https://doi.org/10.1191/1478088706qp063oa
Dewi, S., Gary, Hashim, H. I. C., & Tanujaya, K. (2025). The Moderating Effect of Artificial Intelligence and ICT Adoption on Tax Evasion. 29(01), 88–106.
Diponegoro, R. A. D. N. S., & Ilham, R. (2023). Pengaruh Formalisasi Pengembangan, Keterlibatan Pemakai SIA, Kemampuan Personal Dan Dukungan Manajemen Puncak Terhadap Kinerja SIA. 11(3), 138–147.
Elnakeeb, S., & Elawadly, H. S. H. (2025). Automation and Artificial Intelligence in Accounting: A Comprehensive Bibliometric Analysis and Future Trends. https://doi.org/10.1108/JFRA-09-2024-0639
Frank, M. R., Ahn, Y.-Y., & Moro, E. (2025). AI exposure predicts unemployment risk: A new approach to technology-driven job loss. PNAS Nexus, 4(4), 1–11. https://doi.org/10.1093/pnasnexus/pgaf107
Godollei, A. F., & Beck, J. W. (2023). Computers in Human Behavior Reports Insecure or optimistic ? Employees ’ diverging appraisals of automation , and consequences for job attitudes ☆ ¨ d o. 12(October). https://doi.org/10.1016/j.chbr.2023.100342
Hemati, H., Schreyer, M., & Borth, D. (2022). Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting Data. July 2019.
Holmes, A. F., & Douglass, A. (2022). Artificial Intelligence: Reshaping the Accounting Profession and the Disruption to Accounting Education. Journal of Emerging Technologies in Accounting, 19(March), 53–68. https://doi.org/10.2308/JETA-2020-054
Innocenti, S., & Golin, M. (2022). Human capital investment and perceived automation risks: Evidence from 16 countries. Journal of Economic Behavior and Organization, 195, 27–41. https://doi.org/10.1016/j.jebo.2021.12.027
Karina, R., Siti-Nabila, A. K., & Jurnali, T. (2025). Big data integration in performance management andcontrol: a socio-technical perspective. Journal of Accounting & Organizational Change, January. https://doi.org/10.1108/JAOC-07-2024-0238
Karina, R., & Wijaya, M. P. (2021). Analisis Pengaruh Persepsi Mahasiswa Akuntansi terhadap Profesi Akuntan di Kota Batam. 1(1), 1701–1711.
Kautsar, H. F. Al, & Ilham, R. (2022). Analisis Niat Perilaku Dalam Menggunakan Software Akuntansi Pada Mahasiswa Akuntansi Universitas Hayam Wuruk Perbanas Di Surabaya. 10(03), 84–100.
Keynes, J. M. (1930). Economic Possibilities for Our Grandchildren.
Khaidar, A., & Taufiq, A. R. (2025). The Role of Balance Scorecard and Management Information Systems in Decision Making Through Company Performance. 13(2), 138–144.
Kim, B., & Kim, M. (2024). How artificial intelligence-induced job insecurity shapes knowledge dynamics: the mitigating role of artificial intelligence self-efficacy. Journal of Innovation & Knowledge, 9. https://doi.org/10.1016/j.jik.2024.100590
Kuzior, A. (2022). Technological Unemployment in the Perspective of Industry 4.0. Virtual Economics, 5(1), 7–23. https://doi.org/doi.org/10.34021/ve.2022.05.01
Nguyen, D., & Hekman, E. (2024). The news framing of artificial intelligence: a critical exploration of how media discourses make sense of automation. AI & SOCIETY, 39(2), 437–451. https://doi.org/10.1007/s00146-022-01511-1
Nie, Y., & Mastor, N. H. (2024). Accounting employability : a systematic review of skills , challenges , and initiatives. Cogent Business & Management, 11(1). https://doi.org/10.1080/23311975.2024.2433161
Pargmann, J., Riebenbauer, E., Flick-Holtsch, D., & Berding, F. (2023). Digitalisation in accounting: a systematic literature review of activities and implications for competences. Empirical Research in Vocational Education and Training, 1–37. https://doi.org/10.1186/s40461-023-00141-1
Rawashdeh, A. (2023). The consequences of artificial intelligence: an investigation into the impact of Aionjob displacement in accounting. Consequences of Artificial Intelligence. https://doi.org/10.1108/JSTPM-02-2023-0030
Salhab, R., & Aboushi, M. M. (2025). Influence of AI literacy and 21st-century skills on the acceptance of generative artificial intelligence among college students. September, 1–12. https://doi.org/10.3389/feduc.2025.1640212
Suhardjo, I., & Suparman, M. (2025). Sustainable Human Resource Practices in Indonesian Family-Owned Listed Companies. 22(1), 8–21. https://doi.org/10.22495/cocv22i1art1
Wael, H. Al, Abdallah, W., Ghura, H., & Buallay, A. (2024). Factors influencing artificial intelligence adoption in the accounting profession: the case of public sector in Kuwait. https://doi.org/10.1108/CR-09-2022-0137
Yigitbasioglu, O., Green, P., & Cheung, D. (2023). Digital Transformation and Accountants as Advisors. 0–39. https://doi.org/10.1108/AAAJ-02-2019-3894
Published
How to Cite
Issue
Section
Abstract views: 0
