Artificial Intelligence and Audit Quality in Multinational Audit Firms in Nigeria

Audit quality in African countries faces numerous challenges that undermine the effectiveness and reliability of financial reporting. A prominent issue is the shortage of qualified audit professionals, which limits the capacity to conduct timely and thorough audits. This deficiency hinders the establishment of robust audit systems and adversely impacts the overall quality of financial reporting across the continent. This study specifically examined AI and audit quality in multinational audit firms in Nigeria, with a focus on the role of emerging technologies in enhancing audit quality. Data were collected through structured questionnaires administered to respondents from multinational audit firms in Nigeria.The population of this study is 500 audit professionals (partners, managers, and senior auditors) in multinational audit firms in Nigeria, The sample size for this study was determined using Yamane’s (1967) formula 255 respondents. Using simple regression analysis, the study assessed the influence of various technological tools on audit quality. The findings revealed that Machine Learning Algorithms, Data Mining, Robotic Process Automation, Predictive Analysis, and Image Recognition each have a statistically significant positive effect on audit quality. These results suggest that integrating ethical standards with advanced technological innovations can significantly improve audit quality and strengthen financial reporting in Nigeria. The study recommends greater investment in digital transformation and ethical training to bridge existing gaps in audit capacity and performance