EXPLORING THE EFFECT OF ARTIFICIAL INTELLIGENCE ON AUDIT QUALITY REPORTING: EVIDENCE FROM FOOD AND BEVERAGES FIRMS IN NIGERIA

Abstract

This study investigates the effect of artificial intelligence (AI) adoption on audit quality reporting in Nigeria’s food and beverages sector, against the backdrop of growing digitalization in audit practices. A survey research design was adopted, and primary data was collected through structured questionnaires administered to 193 accountants and auditors with practical exposure to AI-enabled auditing processes. The sample size satisfies established requirements for multiple regression analysis and ensures sufficient statistical power. Audit quality reporting was specified as the dependent variable, while AI adoption was decomposed into machine learning, cloud accounting, and natural language processing. Audit tenure, audit fees, and audit experience were incorporated as control variables to isolate the net effect of AI adoption on audit quality reporting. Data analysis was conducted using descriptive statistics, correlation analysis, and ordinary least squares regression. The empirical results indicate that cloud accounting has a strong and statistically significant positive effect on audit quality reporting, reflecting its role in enhancing audit efficiency, data accessibility, and reporting transparency. Machine learning also exhibits a positive and statistically significant influence, although its magnitude is relatively modest. In contrast, natural language processing does not demonstrate a statistically significant effect on audit quality reporting. The control variables remain significant, confirming the continued relevance of traditional audit characteristics in determining audit quality outcomes. The study concludes that cloud accounting constitutes the most impactful AI component for improving audit quality reporting in the sector. It recommends that audit firms prioritize cloud-based technologies, strengthen machine learning capabilities through professional training, and adopt structured AI implementation frameworks to enhance audit reporting quality.