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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">PBES</journal-id><journal-title-group><journal-title>Proceedings of Business and Economic Studies</journal-title></journal-title-group><issn>2209-2641</issn><eissn>2209-265X</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/pbes.v8i6.12612</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Research on the Theoretical Logic and Development Path of Artificial Intelligence Audit</title><url>https://artdesignp.com/journal/PBES/8/6/10.26689/pbes.v8i6.12612</url><author>ZhuLei</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>8</volume><issue>6</issue><history><date date-type="pub"><published-time>2025-11-06</published-time></date></history><abstract>With the deep integration of digital technology and the real economy, AI auditing has emerged as a core paradigm that breaks through the pain points of traditional auditing, such as “sampling limitations, post-event lag, and reliance on manual labor”. This paper systematically reviews the theoretical connotations of AI auditing, reveals its current practical status, deeply analyzes four core challenges: data quality, ethical compliance, talent adaptation, and institutional synergy, and proposes feasible development paths from four dimensions: technological optimization, institutional construction, talent cultivation, and industry synergy. 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