The Potential of Employing Artificial Intelligence Technologies in Enhancing the Effectiveness of Audit Committees to Mitigate Earnings Management Practices (An Empirical Study)

Abstract

This study aimed to explore the potential of employing artificial intelligence (AI) technologies to enhance the effectiveness of audit committees in limiting earnings management practices in the Libyan environment. The study adopted a descriptive-analytical approach, combining a review of relevant literature, professional reports, and standards with a field study using a questionnaire distributed to a sample of 100 specialists in accounting, finance, and regulatory fields. The data were analyzed using arithmetic means, the t-test, the F-test, and Cronbach’s alpha coefficient.

The results revealed statistically significant positive attitudes toward employing AI technologies to enhance audit committee effectiveness and limit earnings management, with arithmetic means ranging from 3.89 to 3.95 and a significance level of 0.000. The integration of AI technologies with audit committees ranked first, with a mean of 3.95, followed by enhancing financial reporting transparency (3.92), limiting earnings management practices (3.91), and providing accurate information and analytics and detecting indicators of manipulation in financial statements, with a mean of 3.89 for each. These findings indicate a high level of awareness of the potential of AI among respondents, rather than reflecting its actual level of implementation in Libyan institutions.

The study concluded that AI represents an important opportunity to support audit committees, improve the quality and transparency of financial reporting, detect indicators of manipulation, and limit earnings management practices. However, realizing these benefits requires developing digital infrastructure, enhancing specialized competencies, improving data quality, and establishing clear policies and controls for the use of AI technologies.