AI Technologies in Modern Taxation: Applications, Challenges, and Strategic Directions

Abstract

The integration of artificial intelligence (AI) in tax administration represents a transformative technological shift in public finance management. This paper synthesizes recent research on AI applications in taxation, examining technological developments from 2014 to 2024. The analysis reveals significant advancements in compliance monitoring, fraud detection, and policy implementation through AI-enabled systems. Machine learning algorithms, blockchain technology, and natural language processing have enhanced tax authorities' capabilities in risk assessment, audit selection, and taxpayer service delivery. While these technologies demonstrate substantial benefits in administrative efficiency and compliance enforcement, they also present challenges in data privacy, system security, and cross-border coordination. The study identifies critical research gaps, particularly in long-term impact assessment, cross-cultural implementation, and the integration of emerging AI technologies. Future research directions should focus on developing robust governance frameworks, improving system transparency, and addressing the evolving needs of digital economy taxation. This comprehensive analysis provides valuable insights for researchers, practitioners, and policymakers working at the intersection of artificial intelligence and taxation.