Artificial Intelligence, Accounting Automation, and the Changing Nature of Audit Work in Nigerian Audit Firms

This study investigates the transformative impact of artificial intelligence and accounting automation technologies on the nature, scope, and quality of audit work in Nigerian audit firms, contributing original empirical insights to the rapidly growing international literature on technology-driven audit transformation. AI-enabled audit tools, including machine learning-based anomaly detection, natural language processing for contract review, and robotic process automation for sampling and reconciliation, are reshaping the global audit profession. However, the pace, extent, and implications of this transformation in an African professional services context have not been studied. This study uses a sequential explanatory mixed-method design, beginning with a survey of 240 auditors at various seniority levels in 25 Nigerian audit firms, followed by 20 in-depth interviews with audit partners and technology leaders. AI adoption levels, audit task automation rates, and perceived quality and efficiency outcomes are assessed quantitatively. Thematic analysis of interviews explores implementation challenges, skill displacement concerns, and quality assurance implications. Results reveal significant disparity in AI adoption between Big Four and non-Big Four firms, with most mid-tier and small firms relying entirely on manual processes. AI-adopting firms report significant productivity gains and anomaly detection improvements but also identify staff upskilling and client data quality as critical barriers. The study contributes an original AI-audit transformation typology for the Nigerian professional context and recommends that the Institute of Chartered Accountants of Nigeria embed AI literacy in its professional qualification curriculum and establish technology adoption support resources for small and mid-tier audit practices.

Keywords: artificial intelligence, audit automation, RegTech, Nigerian audit firms, professional development.