THE ROLE OF ARTIFICIAL INTELLIGENCE IN AUDITING AND ASSURANCE

ABSTRACT : This study investigates the impact of Artificial Intelligence (AI) in auditing quality and assurance. As AI technologies become increasingly embedded in audit processes, understanding their influence on audit outcomes is critical for practitioners, regulators, and stakeholders. The study focuses on three key components of AI integration: AI-based data analytics, AI-assisted risk assessment, and AI-driven fraud detection, examining their individual and collective effects on audit quality. Grounded in the Technology Acceptance Model (TAM), the research employs a quantitative approach using survey data and multiple regression analysis to test hypotheses and evaluate relationships among variables. Findings reveal that all three AI components have a statistically significant positive impact on audit quality, with AI-based data analytics exerting the strongest influence. These results align with prior studies emphasizing AI’s ability to enhance audit efficiency, reduce human error, and improve anomaly detection. However, the study also recognizes challenges such as regulatory uncertainty, ethical concerns, and limited adoption in small and medium-sized firms due to cost and skill constraints. The study contributes to existing literature by providing empirical evidence on AI’s role in auditing, especially within diverse organizational contexts. It highlights the need for updated audit standards, greater investment in AI training, and stronger ethical frameworks to support responsible AI adoption. Practical recommendations are offered to guide audit firms, regulators, and educational institutions in navigating the transition to AI-enhanced audit environments. Ultimately, the study underscores that while AI cannot replace professional judgment, it serves as a powerful tool to augment audit quality and assurance effectiveness