The evolution of artificial intelligence (AI) has significantly influenced various fields, including internal auditing. AI has driven substantial growth and innovation across the internal audit function, transforming traditional audit practices. Its integration into internal auditing enhances data analytics, strengthens risk management, and improves the reliability of financial information. This study aims to explore the application of AI in internal auditing through a bibliometric analysis. By examining research published from 1986 to 2024 and utilizing data visualization software (VOSviewer), we identify key trends, emerging themes, and critical discussions within the field. Our analysis of 122 articles indexed in the Scopus database provides valuable insights into how AI is reshaping internal audit functions, offering a comprehensive overview of its implications on reshaping internal audit practices, and highlighting emerging trends and critical areas of study.