The Role of Artificial Intelligence in Taxation and Compliance: Challenges and Future Prospects

Muhammed Zakir Hossain, Latul Hasan, Refat Ara Kumu, Muhim Bepari and Samia Sultana
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Muhammed Zakir Hossain: Associate Professor, Department of Business Studies, State University of Bangladesh, Bangladesh
Latul Hasan: International American University, USA
Refat Ara Kumu: Westcliff University, Irvine Campus, USA
Muhim Bepari: Pacific States University, USA
Samia Sultana: Southern California State University, USA

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Abstract: This paper examines the role of Artificial Intelligence (AI) in taxation and compliance, examining its current applications, the challenges encountered during implementation, and its potential future developments. The growing complexity of global tax frameworks, coupled with the demand for increased efficiency, has led to the adoption of AI by tax authorities and businesses alike. This technology is being utilized to streamline tax filing processes, identify fraudulent activities, perform audits, and oversee international taxation matters. Nonetheless, the incorporation of AI into tax systems presents several challenges, including regulatory concerns, significant implementation costs, data privacy issues, and resistance from traditional tax professionals. The paper highlights the significant advantages of AI, including increased efficiency, precision, and cost savings, while also discussing the challenges that must be addressed for effective implementation. Furthermore, it examines potential future avenues for artificial intelligence in predictive tax analytics, the harmonization of global tax systems, and the design of tax policies driven by AI. This study offers valuable insights for tax authorities, businesses, and policymakers on utilizing AI to enhance tax compliance and administration.

Keywords: Tax Policy; AI Implementation; Fraud Detection; Tax Compliance; Artificial Intelligence (search for similar items in EconPapers)
Date: 2025-10-27
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Published in European Journal of Science and Modern Technologies, 2025, 1 (6), pp.73-85. ⟨10.59324/ejsmt.2025.1(6).08⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05736412

DOI: 10.59324/ejsmt.2025.1(6).08

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