PBESProceedings of Business and Economic Studies2209-26412209-265XBio-Byword Scientific Publishing Pty. Ltd.10.18063/PBES.v9i8.15161ArticleAudit Object Expansion and Theoretical Reconstruction in the Artificial Intelligence Era: From Information Assurance to Intelligent Governance Assurancehttps://artdesignp.com/journal/PBES/9/8/10.18063/PBES.v9i8.15161XiaoXia2026982026-08-31Artificial intelligence (AI) is changing both audit practice and the mechanisms that may require assurance. Recent research has developed along two related paths. AI for audit examines the use of AI, large language models, and intelligent agents in audit work. Audit of AI considers the auditability and independent evaluation of AI systems used by organizations. This paper connects these streams with established audit theory and develops Audit Object Expansion Theory. The central argument is that audit objects may expand when AI becomes material to an accountability relationship, its operation is difficult for users to observe, and suitable criteria and evidence make independent examination possible. In AI-enabled organizations, the audit boundary may extend from financial information and traditional controls to three nested objects: data, algorithms, and intelligent decision processes. Auditability determines whether this potential expansion can become actual audit scope. The paper then discusses theoretical reconstruction at three connected levels: audit object, audit process, and assurance objective. The final level extends the discussion from information assurance toward intelligent governance assurance. The basic logic of auditing remains unchanged, but its application changes when intelligent systems become part of the mechanisms that produce accountable outcomes.Artificial intelligence, Audit object, Auditability, Theoretical reconstruction, Intelligent governance assurance

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