Artificial Intelligence (AI) in tax accounting: Opportunities, challenges, and ethical implications for tax accounting professionals
Keywords:
artificial intelligence, tax accounting, systematic literature review, ethical AI, professional competencies, tax advisory, digital transformationAbstract
Artificial intelligence (AI) has emerged as a transformative technology that is reshaping tax accounting by automating routine processes, enhancing tax compliance, and supporting strategic decision-making. While existing studies have extensively examined AI applications in accounting, the literature remains fragmented regarding its opportunities, implementation challenges, ethical implications, and the evolving competencies required of tax accounting professionals. This study aims to systematically synthesize current research on AI adoption in tax accounting and develop an integrated understanding of its implications for professional practice. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Relevant publications were retrieved from major academic databases using predefined inclusion and exclusion criteria, followed by thematic synthesis to identify recurring patterns across the literature. The review reveals five major themes. First, AI enhances operational efficiency through the automation of repetitive tax processes, improved accuracy, and faster information processing. Second, AI strengthens tax compliance, risk management, and strategic tax advisory by leveraging machine learning, natural language processing, predictive analytics, and generative AI. Third, successful implementation is constrained by challenges related to data quality, system integration, cybersecurity, regulatory uncertainty, organizational readiness, algorithmic transparency, and AI literacy. Fourth, AI adoption raises important ethical issues concerning accountability, explainability, fairness, confidentiality, and professional judgment, emphasizing the need for robust AI governance and continuous human oversight. Finally, the review demonstrates that AI is redefining rather than replacing the tax accounting profession, shifting the required competency profile toward AI literacy, data analytics, critical thinking, ethical reasoning, strategic advisory capability, interdisciplinary collaboration, and lifelong learning. Based on these findings, this study proposes an integrated conceptual framework that positions responsible AI adoption as the result of balancing technological opportunities with organizational readiness, ethical governance, and future professional competencies. The study contributes to the accounting literature by integrating fragmented evidence into a comprehensive perspective on AI-assisted tax accounting and provides practical implications for organizations, professional accounting bodies, educators, and policymakers seeking to prepare the profession for an increasingly AI-enabled taxation environment.
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