Beyond Automation in Tax Compliance Through Artificial Intelligence and Professional Judgment

Abstract

Tax compliance has evolved significantly with the integration of artificial intelligence (AI) technologies, transforming traditional manual processes into sophisticated automated systems. This review examines the intersection of AI automation and professional judgment in tax compliance, exploring how these elements complement rather than replace each other. The paper analyzes various AI applications including machine learning (ML), natural language processing (NLP), robotic process automation (RPA), and blockchain technology in tax administration and compliance functions. While AI demonstrates remarkable capabilities in processing vast amounts of tax data, identifying patterns, and automating routine tasks, professional judgment remains indispensable for interpreting complex tax regulations, assessing unique circumstances, and making ethical decisions. This review synthesizes recent research on intelligent automation systems, predictive analytics for tax risk assessment, and cognitive technologies that support tax professionals. The analysis reveals that optimal tax compliance outcomes emerge from hybrid approaches that leverage AI efficiency alongside human expertise. Key challenges include algorithmic transparency, regulatory adaptation, data quality, and the preservation of professional skepticism in automated environments. The findings suggest that successful tax compliance in the digital era requires reimagining professional roles, developing new competencies, and establishing governance frameworks that ensure responsible AI deployment. This comprehensive examination provides insights into the future of tax compliance where technology augments rather than diminishes the critical role of professional judgment.