Orly Mazur (SMU; Google Scholar) & Adam Thimmesch (Nebraska; Google Scholar), Transforming Tax Communications With Large Language Models, 185 Tax Notes Fed. 757 (Oct. 28, 2024):
In this installment of Academic Perspectives on SALT, Mazur and Thimmesch explore how to improve the efficiency and equity of tax administration through the strategic use of large language models and related artificial intelligence.
Conclusion
LLMs have the potential to significantly transform tax communications by simplifying taxpayer interactions, enhancing the efficiency of tax communications’ personalized support, and making tax agency resources more widely accessible. This article has highlighted just a few of the ways LLMs can revolutionize the IRS and state tax agencies’ communication functions — from enhancing external communications with taxpayers to improving internal training and promoting fairness.
However, realizing these benefits requires a careful approach that addresses the limitations of AI technology, emphasizes the importance of human oversight, and fosters collaboration with stakeholders. By navigating these considerations thoughtfully, the IRS and state taxing agencies can leverage LLMs to advance their missions while safeguarding the integrity and effectiveness of their communications with the public.
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