Anticipating Technological Unemployment among Accounting Students in the AI Era

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.