Artificial Intelligence and the Enhancement of Audit Quality: An Empirical Investigation

Abstract

The rapid evolution of information technologies has positioned artificial intelligence (AI) as a key element of the sustainable revolution in the fields of accounting and auditing. This research aims to study the effect of AI integration on audit quality and to understand how company-specific characteristics influence the efficiency of its integration. Using a quantitative approach based on panel data regression, the study focuses on 60 observations of company-years from 2017 to 2022. Validated indicators are used to assess audit quality, and company-specific characteristics are considered as control and moderation variables. The findings indicate that the use of AI significantly enhances the value of audits by improving the detection of irregularities and fraud, minimizing human error, facilitating sophisticated data analysis, and increasing the efficiency and accuracy of audit procedures. Furthermore, company-specific attributes mitigate the impact of AI, highlighting the need for an organizational framework to fully realize its benefits. This research enriches the literature on artificial intelligence in the field of auditing by providing empirical evidence of its beneficial effect on audit quality. It also highlights its practical implications for auditors, regulatory bodies, and policymakers seeking to increase the transparency, trust, and credibility of financial information systems.