Artificial intelligence, job seeker, and career trajectory: How AI-based learning experiences affect commitment of fresh graduates to be an accountant?

Integrating Artificial Intelligence (AI) into the accounting professions is reshaping traditional roles and skill requirements, prompting a reassessment of how graduates are prepared for these changes. However, a significant gap exists in understanding how AI-based learning in higher education curricula influences graduates' readiness and commitment to be accountants. Addressing this gap, this study aims to answer two pivotal questions: how do AI learning experiences affect AI self-efficacy and career commitment, and how do literacy, motivations, and competency factors mediate this relationship? This study grounds in Self-determination Theory (SDT) and Social Cognitive Career Theory (SCCT) to answer the questions and utilizes a multiple mediation model with partial least squares structural equation modeling (PLS-SEM) to analyze survey data gathered from 698 fresh graduates in accounting and finance program across the country (Indonesia). The finding confirms that AI-based learning experiences in higher education influence fresh graduates’ AI self-efficacy and career commitment through the mediating role of AI literacy, competency, and motivations. This study demonstrates that AI-based learning enhances students' literacy and competencies in AI/accounting software while boosting intrinsic and extrinsic motivation to master AI skills for future career benefits. Ultimately, increased motivation, literacy, and competencies strengthen graduates' self-efficacy and confidence, supporting their commitment to a career in accounting. This study, therefore, contributes a novel insight by providing empirical considerations for higher education and the accounting industry to strengthen AI-based curricula for future workforce supply.