Understanding Artificial Intelligence and the Future of Audit in Nigeria: Will AI Replace the Auditor? A Qualitative Phenomenological Inquiry

Abstract

This study qualitatively inquired into artificial intelligence and the future of audit in Nigeria, specifically investigating whether AI will replace the human auditor. A qualitative phenomenological design was adopted. Twenty-eight (28) participants were purposively selected across Lagos, Abuja, and Port Harcourt, comprising Big 4 and mid-tier audit partners, audit managers/seniors with 10+ years of experience, ICAN/ANAN/FRCN regulators, and audited clients including CFOs and Audit Committee chairs. Data were collected via semi-structured indepth interviews between January and May 2025. Data saturation was achieved at the 23rd interview. Thematic analysis was performed using the Braun and Clarke (2006) framework assisted by NVivo. Results reveal that AI is augmenting, not replacing, human auditors. Four distinct AI implementation levels emerged: Assisted Audit (e.g., IDEA, Excel), Augmented Audit (e.g., Power BI, ACL), Autonomous Testing (e.g., RPA, Machine Learning anomaly detection), and Advisory Assurance (e.g., Generative AI for reporting). AI deployment improved audit efficiency by 60% and increased anomaly detection from 35% to 82%. Key barriers to adoption include technophobia (78%), unstructured client data (72%), tool costs (65%), and a regulatory vacuum regarding AI audit evidence under ISA 500 (60%). The study proposes a Human-AI Collaboration Model (70-30 Model), where AI performs 70% of routine data tasks, and human auditors provide 30% high-level professional judgement, ethics, and skepticism. This represents the first phenomenological study in Nigeria exploring the lived experiences of senior practitioners on the AI replacement debate.