AUDIT EFFICIENCY

This study examines the impact of artificial intelligence (AI) technologies on audit efficiency, with a specific focus on selected professional organizations in Benin City, Nigeria. Employing a survey research design, the study gathered data from 50 respondents across various industries using structured questionnaires. The analysis utilized both correlation and linear regression techniques to assess the relationship between AI components—Machine Learning, Natural Language Processing (NLP), Robotic Process Automation (RPA), and Predictive Analytics—and audit efficiency. The findings reveal that Machine Learning and Predictive Analytics significantly enhance audit efficiency, as evidenced by their strong positive correlations and statistically significant regression coefficients. These technologies contribute to improved financial reporting accuracy, enhanced fraud detection, and reduced audit risks. Conversely, NLP and RPA did not show statistically significant effects, suggesting that their integration into audit workflows may be limited or at a developmental stage