Auditor Behavior Toward Artificial Intelligence (AI) Development: A Literature Review - Sari, Agustin Rusiana; Prijanto, Budi (Universitas Dharma Wacana, 2025)
The integration of Artificial Intelligence (AI) has fundamentally reshaped the auditing profession by enhancing efficiency, analytical precision, and audit quality. This study aims to explore auditors’ behavioral responses toward AI adoption, emphasizing individual, organizational, and ethical dimensions. Using a systematic literature review approach of scholarly articles published between 2020 and 2025, the paper synthesizes findings from contemporary research focusing on the drivers, impacts, and governance challenges of AI implementation in auditing. The results show that willingness to learn, performance expectancy, and AI readiness are the most influential individual factors determining auditors’ intention to adopt AI, while top management support and technological infrastructure play key organizational roles. AI-based systems significantly improve anomaly detection accuracy and operational efficiency; however, algorithmic bias, limited transparency, and accountability gaps remain critical ethical concerns. The study also highlights that AI cannot replace human professional judgment—ethical reasoning, contextual interpretation, and moral accountability must remain central to the audit process. Future auditors are expected to evolve from compliance examiners to strategic advisors equipped with multidisciplinary competencies in data analytics, digital governance, and ethics. Therefore, the synergy between human insight and AI-driven analytics is essential for ensuring trustworthy, transparent, and sustainable audit practices in the digital era.