<![CDATA[The increasing use of artificial intelligence (AI) in auditing practices is driven by growing data complexity and volume, yet its adoption also raises ethical challenges related to algorithmic transparency, technological bias, data confidentiality, and auditor accountability. This study employs a systematic literature review approach with meta-interpretation technique and a deontological perspective to evaluate the relevance of the five IESBA ethical principles-integrity, objectivity, professional competence and due care, confidentiality, and professional behavior-in AI-based audit environments. Literature searches were conducted through Google Scholar, Scopus, and ScienceDirect using the Publish or Perish application for the period 2018–2025. A total of 1,159 articles were identified, and after an inclusion-exclusion filtering process, 29 articles met the eligibility criteria. The findings indicate that these ethical principles remain normatively relevant as the foundation of the auditing profession; however, their application becomes increasingly ambiguous in AI-based auditing practice. Practical ethical issues such as algorithmic bias, lack of transparency, and risk of data leakage threaten auditor integrity, objectivity, and accountability. Furthermore, the absence of explicit regulations amplifies uncertainty regarding professional responsibility. Therefore, clarification of operational implementation, enhancement of auditors' technological competence, and strengthening of professional judgment over AI system outputs are necessary. This study concludes that the IESBA Code of Ethics does not require replacement of its fundamental principles, but rather clearer application guidance and regulatory support to ensure that AI-based auditing practices in the digital era remain ethical and trustworthy.]]>
