The Role of Artificial Intelligence in Enhancing the Quality of External Audit Reports: Evidence from Libya

Abstract

This study examines the role of Artificial Intelligence (AI) in enhancing the quality of external audit reports in Libya, an emerging economy where the digital transformation of auditing remains at an early stage. Drawing upon agency theory and the Technology Acceptance Model (TAM), the study conceptualizes AI adoption as a multidimensional construct comprising analytical accuracy, efficiency, and reliability and credibility, and investigates their influence on perceived overall audit quality.

A quantitative cross-sectional survey design was employed, targeting 147 external auditors in Libya using purposive sampling. Data were analysed using descriptive statistics, correlation analysis, and multiple regression analysis. The findings reveal moderately positive perceptions of AI adoption across all three dimensions. Regression results indicate that AI-enabled analytical accuracy, efficiency, and reliability and credibility each have a statistically significant positive effect on perceived overall audit quality (R² = 0.441, p < 0.001). Among these predictors, analytical accuracy emerged as the strongest determinant, followed by reliability and credibility, while efficiency exerted a comparatively weaker but still significant influence.

The study contributes to the growing body of literature on AI in auditing by providing empirical evidence from a North African context, where research on technological adoption in audit practice remains limited. The findings suggest that AI enhances audit quality primarily by strengthening detection capability and reinforcing report credibility, thereby supporting the modernization of external auditing in emerging economies.