Document Type
Article
Publication Title
Florida Tax Review
Publication Date
2024
Abstract
Tax return preparers play a pivotal role for millions of taxpayers, and
their number ranges in the hundreds of thousands. Despite preparers'
importance in the tax return submission process and their numerical size,
they are largely unregulated. Because of this lack of oversight, a significant
number of tax returnp reparersp ut their ownfinanciali nterests and
those of their clients ahead of the government's financial interests.
In the past, there have been calls for increased regulatory
oversight to keep wayward practitioners' actions in check. Therefore,
a decade and a half ago, Congress, in conjunction with the Treasury
Department, mandated that every paid tax return preparer secure a
Preparer Tax Identification Number (PTIN) and affix it to the face of
the tax returns that they prepare.
Enter artificial intelligence (AI) with its unparalleled ability
to process and analyze an immense amount of data combined with
electronic tax returnfilings. With immediate access to PTINs and other
information or characteristics associated with such returns, Al is ideally
situated to identify tax return preparers who are derelict in their
professional duties. Once identified, the Internal Revenue Service can
hold these practitioners accountable for their mistakes and misdeeds.
Unlike the prior academic papers that have championed regulatory
oversight well beyondPTIN registration (e.g., mandatory annual education courses and exams), this analysis stands apart. Instead, it recognizes AI's power and what it can accomplish if properly brought
to bear to the problem of unregulated tax return preparers. Seizing this
opportunity would most likely result in increased tax compliance, the
collection of billions more in revenue without raising taxes, and a narrowing
of the tax gap (i.e., the difference between what taxpayers pay
in tax and what they owe). Furthermore, the foregoing may be accomplished
without adding needless administrative burdens.
Recommended Citation
Linda Galler and Jay A. Soled,
AI and the Regulation of Tax Return Preparers, 28 FLA. TAX REV. 1
(2024)
Available at: https://scholarlycommons.law.hofstra.edu/faculty_scholarship/1673