AUDIT EFFICIENCY

This study investigates the impact of Artificial Intelligence (AI) on audit efficiency within the private sector. The rapid advancement of AI technologies has transformed traditional auditing processes by enhancing data accuracy, speed, and decision-making. The objectives of this research are to examine the effect of AI on audit efficiency, evaluate the challenges auditors face in adopting AI-driven tools, ascertain the implications of AI integration on the future roles and skills required of auditors, and determine how AI supports auditors’ professional judgment and decision-making during audits. The study adopts a quantitative research approach through the administration of structured questionnaires to auditors in selected private organizations. The data collected were analysed using descriptive and inferential statistical tools. Findings reveal that the adoption of AI significantly improves audit efficiency by automating repetitive tasks, reducing human error, and enabling real-time data analysis. However, the study also identifies key challenges, including high implementation costs, lack of technical expertise, data security concerns, and resistance to technological change. Furthermore, the integration of AI necessitates the acquisition of advanced digital and analytical skills among auditors to remain relevant in the evolving audit environment. The study concludes that while AI serves as a strategic tool for improving audit quality and efficiency, adequate training and organizational support are essential for its effective implementation.