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Yuana Jatu Nilawati
Universitas Trisakti
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Anticipating Technological Unemployment among Accounting Students in the AI Era Suparman, Meiliana; Meriyani, Susi; Hermawan, Singgih Bayu Indra; Octavia, Evi; Khomsiyah; Radianto, Wirawan Endro Dwi; Nilawati, Yuana Jatu
Jurnal Akuntansi Vol 14 No 02 (2026): AKUNESA (Januari 2026)
Publisher : Accounting Study Programme Faculty of Economics and Business Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/akunesa.v14n02.p195-204

Abstract

The increasing integration of artificial intelligence (AI) in the accounting profession has raised growing concerns about job displacement, particularly among student preparing to enter the workforce. This study examines how accounting students perceive 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, the study identifies a 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 prior to 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. By demonstrating that technological unemployment can operate as a pre-employment cognitive process, this study extends TUT beyond post-displacement labor outcomes and highlights the importance of aligning accounting education with AI-responsive career pathways to support adaptive, rather than fear-driven, workforce preparation.
Co-Authors Agustar, Gryara Anrasia Ali Gesang Widodo Budi Ali, Jati Kasuma Anita Roosmalina Matusin Arnolt Kristian Pakpahan, Arnolt Kristian Asep Hermawan Ayu Ekasari Banjarnahor, Erliana Budi, Ali Gesang Widodo Darmawati, Deni Elis Purwanti Entaresmen, R Ajeng Evi Octavia Febriana, Rahma Fithri Alvionita Nuryaman Harahap, Cicely Delfina Hasanah, Lailatun Hasnawati Hermawan, Singgih Bayu Indra Ika Wahyuni Kasuma Ali, Jati KHOMSIYAH Kristian Chandra Magetsari, Ovy Noviati Nuraini Mayangsari Mayangsari Mayangsari, Mayangsari Meriyani, Susi Muhammad Iqbal Bahrin MURTANTO MURTANTO MURTANTO Murtanto Murtanto Nisrina Dwi Setyoastuti Nuryaman, Fithri Alvionita Osni Erza, Osni Purwanti, Elis Santosa, Wahyuningsih Setyoastuti, Nisrina Dwi Sirait, Koramen H Suparman, Meiliana Victor Siagian Wahyuni, Lidia Wirawan ED Radianto