The Role of Artificial Intelligence in Enhancing Audit Quality: The Mediating Role of Fraud Detection Capability and Audit Efficiency — Evidence from Emerging Markets.

Purpose – This study aims to examine the relationship between artificial intelligence (AI) adoption and audit quality among companies listed on the Egyptian Exchange (EGX 100) index. Additionally, it investigates the mediating roles of fraud detection capability and audit efficiency in this relationship. Design/methodology/approach – The study is based on a sample of 440 firm-year observations from 88 companies listed on the EGX 100 index during the period 2020–2024. Audit quality is proxied by audit firm size, audit efficiency is measured using audit report lag, and fraud detection capability is assessed based on the nature of the audit opinion issued. Findings – The results reveal that AI adoption has a significant positive impact on audit quality, audit efficiency, and fraud detection capability. Furthermore, both fraud detection capability and audit efficiency exhibit significant positive effects on audit quality. The analysis also confirms that fraud detection capability and audit efficiency partially mediate the relationship between AI adoption and audit quality. Originality/value – This study contributes to the growing literature on the application of AI in auditing, particularly within emerging markets such as Egypt. To the best of the author’s knowledge, this is the first empirical investigation to explore the relationship between AI adoption and audit quality, incorporating the mediating effects of fraud detection capability and audit efficiency in the context of the Egyptian capital market.