AI ADOPTION AND FRAUD DETECTION: THE MODERATING ROLE OF AUDITOR EXPERTISE

Abstract

The growing complexity of financial fraud and rapid digitization of financial reporting have accelerated artificial intelligence (AI) adoption in auditing. The purpose of this study is to examine the impact of AI adoption on fraud detection effectiveness and the moderating role of auditor expertise between AI adoption and fraud detection effectiveness in Pakistan. Primary data were collected through a structured questionnaire from auditors employed by accounting firms recognized by ICAP, including Big Four, internationally affiliated and local firms. Of 670 questionnaires distributed, 550 were returned and 418 valid responses were retained after eliminating incomplete responses. The Purposive sampling technique was employed. The proposed relationships were tested by using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 4. The result of measure model validated satisfactory reliability, convergent and discriminant validity. The results of structural model indicate that AI adoption significantly and positively influences fraud detection effectiveness. Moreover, auditor expertise significantly strengthens this relationship, indicating an expertise-amplification effect. These findings propose that Artificial Intelligence technologies and auditor expertise function as complementary capabilities rather than substitutes one. This study contributing to the emerging economy literature on AI-enabled auditing and provides practical implications to audit firms, regulators and accounting educators seeking to improve fraud detection and the effective implementation of AI in Pakistan economy.