Is AI Usage Relevant to Audit Effectiveness: Correlation Findings from the Big Four Firms

The article aims to quantify and describe the relationship between the penetration of Artificial Intelligence (AI) in the auditing industry and audit effectiveness, with a focus on examining the heterogeneity of whether AI is adopted among companies in different years. The article is based on panel data from the Big Four accounting firms (20202025), with audit effectiveness scores as the dependent variable, AI adoption (binary) as the core independent variable, controlling for the impact of compliance violations and total revenue, and incorporating year effects. Methodologically, a robust OLS model incorporating year effects was first constructed. Subsequently, a firm-fixed effects model was also established. Additionally, an AI year interaction term was included in the FFE framework, with marginal effects and annual mean plots used to characterize the temporal dimension, and standard errors were robustly adjusted. The results indicate a positive overall association, with periodic fluctuations over time. In conclusion, the paper defines the findings as evidence of a correlation, suggesting that AI's explicit impact on audit effectiveness is time- and context-dependent.