AI has gained significant traction as an innovative tool for automating tasks, enhancing data analytics, and reducing the risk of errors in auditing processes. This study investigated the impact of adopting artificial intelligence (AI) on the quality of audit practice in Nigeria, focusing on data mining, machine learning, and image recognition as proxies for the independent variable. Population was 251 accounting firms in southwest Nigeria, with a sample size of 159, purposively determined. The study utilized structured questionnaires for data collection, with regression analysis, and correlation matrices adopted for the analysis. The findings revealed a significant positive relationship between data mining and image recognition with the quality of audit practice in Nigeria. Machine learning, however, showed an insignificant negative relationship. This suggests that AI, particularly data mining and image recognition, can enhance audit quality in Nigeria. As a result, the study recommended that Nigerian audit professionals and firms should consider incorporating data mining techniques into their audit processes to improve effectiveness and error detection.
Keywords: Artificial Intelligence, Data mining, Quality of audit practice., image recognition, machine learning
