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Effects of Artificial Intelligence on Tax Administration in Lagos State

Author

Listed:
  • Akanji Rafiu Bankole

    (Lagos State University)

  • Ifeoma Patricia Osamor

    (Lagos State University)

  • Adeniyi Emmanuel Bamgboye

    (Lagos State University)

Abstract

Despite global interest in employing AI to enhance tax systems, a significant study gap persists about its specific effects in Lagos State. This paper addressed this gap by presenting empirical evidence regarding the effectiveness of AI technologies, including natural language processing (NLP), blockchain technology (BT), predictive analytics (PA), and machine learning (ML) in improving tax administration. The research utilizes a quantitative design, collecting primary data through a structured questionnaire, distributed to 152 participants inside the department overseeing AI and tax consultants/payers in LIRS. The data are analyzed using regression analysis to determine the relationships among the independent variables (NLP, BT, PA, ML) and the dependent variable (efficiency of tax administration). The findings demonstrate that AI technologies markedly improve the efficiency of tax administration. Predictive analytics has the most significant influence, succeeded by natural language processing, blockchain technology, and machine learning. These technologies enhance processing speed, correctness of tax evaluations, taxpayer compliance, and diminish administrative expenses. The study therefore concluded that AI has effects on tax administration in Lagos State. It was recommended that governments augment investment in AI infrastructure, facilitate training for tax officials, and advocate for the implementation of blockchain to improve security and transparency.

Suggested Citation

  • Akanji Rafiu Bankole & Ifeoma Patricia Osamor & Adeniyi Emmanuel Bamgboye, 2025. "Effects of Artificial Intelligence on Tax Administration in Lagos State," The Journal of Accounting and Management, Danubius University of Galati, issue 2(15), pages 144-160, August.
  • Handle: RePEc:dug:jaccma:y:2025:i:2:p:144-160
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