Regulatory and Ethical Governance Framework for Implementing Artificial Intelligence in External Auditing: A Systematic Literature Review
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This research aims to identify regulatory and ethical challenges in the application of artificial intelligence (AI) to external audit practices, as well as to develop a governance framework that ensures transparency, accountability, and algorithmic fairness. Using the Systematic Literature Review (SLR) approach based on the PRISMA 2020 model, this study examined 21 Scopus indexed scientific articles for the period 2020–2025 that were relevant to the issues of regulation, governance, and AI auditing policies. The selection process involves identifying, screening, assessing the eligibility, and inclusion of articles that fit the thematic criteria. Data analysis was carried out through thematic synthesis to group the findings into four main themes: (1) regulatory and ethical challenges, (2) gaps in international audit standards, (3) regulatory governance mechanisms, and (4) trustworthy and explainable AI policy drafts. The results show that although AI improves audit efficiency, there is no legal and professional framework capable of regulating the complexity of algorithmic decisions. In addition, auditors still face moral dilemmas and the risk of algorithmic bias due to delays in updating global audit standards. The study concludes that AI-assisted audit governance should be integrative, balancing technological efficiency and ethical responsibility through a co-auditing model that combines human oversight and algorithmic system transparency.
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Copyright (c) 2025 Fony Abdullah, Herwin Mopangga, Silveny Ismail, Yasir M. Pidu
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