Artificial Intelligence in Auditing: An Empirical Investigation of the Technology Acceptance Model in BPK Papua
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Abstract
The adoption of Artificial Intelligence (AI) in auditing practices has gained attention due to its potential to improve audit quality, efficiency, and fraud detection. This study investigates the factors that influence auditors' perceptions of AI adoption at the Audit Agency of Papua Province (BPK Papua). Using the Technology Acceptance Model (TAM), the study explores the roles of Perceived Ease of Use (PEU), Perceived Usefulness (PU), and Perceived Cyber Risks (PCR) in shaping auditors' attitudes toward AI adoption. Data were collected through a survey of 92 auditors, and the findings reveal that all three factors—PEU, PU, and PCR—significantly affect Audit Practice (Y). The study shows that auditors are more likely to adopt AI if they perceive it as easy to use and useful in enhancing audit performance. However, concerns over cyber risks pose a significant barrier to full AI adoption. The results suggest that AI tools must be user-friendly, demonstrate clear benefits, and address cybersecurity concerns to promote adoption. These findings have important implications for AI developers and audit firms and offer guidance on how to integrate AI effectively into auditing practices. Future research could explore additional factors that influence AI adoption in auditing, including organizational culture and regulatory frameworks.
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