The Impact of Artificial Intelligence (AI) and Tax Revenue Compliance in Nigeria Revenue Service

Abstract

This study examined the impact of artificial intelligence on tax revenue compliance in the Nigeria Revenue Service, with particular emphasis on machine learning as the dimension of artificial intelligence and Companies Income Tax (CIT) and Value Added Tax (VAT) as measures of tax revenue compliance. The study adopted a qualitative research approach based on a narrative literature review. The reviewed literature was analysed thematically to establish how machine learning can support tax administration and improve compliance with CIT and VAT obligations. The review indicates that machine learning can assist tax authorities in analysing large volumes of taxpayer data, identifying unusual transaction patterns, assessing taxpayer risk, detecting possible cases of non-compliance, and supporting targeted tax audits. The study further found that the application of machine learning has the potential to improve Companies Income Tax compliance by helping to identify inconsistencies in corporate tax declarations and improve VAT compliance through better monitoring of taxable transactions and returns. However, the effectiveness of machine learning depends on reliable data, adequate technological infrastructure, skilled personnel, data security, and appropriate human oversight. The study concludes that the effective adoption of machine learning can strengthen tax administration and contribute to improved tax revenue compliance in Nigeria. It recommends that the Nigeria Revenue Service should strengthen the use of machine learning in CIT and VAT monitoring, improve taxpayer data integration, and provide continuous training for tax officials to ensure effective use of AI-based tax administration systems.