Artificial Intelligence And The Future Of Business Sales Tax Liability And Reporting In The U.S.

Is AI able to solve 3 leading issues complicating the automation of sales tax payment in the U.S., especially for companies in multiple states/jurisdictions?

PHILADELPHIA, PA, UNITED STATES, February 28, 2025 /EINPresswire.com/ -- Artificial intelligence, or AI, is arguably the hottest topic in business these days. When it comes to accounting and tax collection, discussion about integrating AI into processes and systems is everywhere. Numerous studies show that well over 80% of large and medium-sized businesses are exploring their use of AI in accounting and in other applications. Yet when it comes to implementing AI, the U.S. Census Bureau reports that barely 5% of businesses are actively utilizing AI at this time.

Bill Flick, a Managing Partner at EisnerAmper Advisory Services and a thought leader in sales tax policy and process, observes that, in general, artificial intelligence succeeds when there is a body of data, history and nexus to serve as its foundation. Flick observes that when it comes to AI and sales tax liability, data, history and nexus often lack coherence in creating a foundation that underpins AI.

Especially following the Supreme Court’s Wayfair decision of 2018, sales tax jurisdictions have grappled with their definitions of sales tax nexus in defining a company’s eligibility and overlap for sales tax liability, often defined as some combination of location, dollar volume and number of transactions. More recently, because it has been demonstrated that the “number of transactions" criterion often hurts smaller companies, more taxing entities are just using location and dollar volume and continuing to change nexus definitions. Flick observes that with over 500 sales tax law changes in 2024 alone, the sales tax knowledge base is updating with great inconsistency and at a hyper-speed that seems to defy solidifying an AI-compatible base of information.

Flick asks, “How is AI able to solve or improve three of the leading issues complicating the automation of sales tax payment in America, especially for companies doing business in multiple states and jurisdictions? I’m not sure it can in its present iteration.” Those 3 key issues to which Flick refers are:
- inconsistent information models and formatting, from over 10,000
sales tax jurisdictions in the U.S.
- inconsistent data flows that overlap inconsistently.
- random and unpredictable pacing of changes and updates affects
the knowledge base quality and consistency.
Flick believes that, for the near future, there is little chance of this situation improving and becoming more AI useable.

“Another factor affecting AI usage and sales taxes is privacy,” says Flick. AI succeeds because it is based on accessing a continually updating global body of public information. Because sales taxes often reflect company trade secrets relating to volumes, products, vendors, costs and even geographical locations of procurement, it is unlikely that companies will want to go public with this information, thereby limiting the AI knowledge base.

In addition, Flick notes that this limited completeness of information will skew the effectiveness of AI’s guidance. He points out that when it comes to sales and use tax compliance, much of AI’s body of knowledge will be flawed, because corporations themselves often manage sales tax payments incorrectly, which frequently never gets corrected.

Off the record, out of court sales tax settlements also limit AI’s body of knowledge. Since AI’s recommendations are based on incomplete or inaccurate past knowledge, the advice and recommendations have a high propensity to be flawed. “For many questions of sales tax presented to AI, one will receive a different answer each time one asks a question,” says Flick.

Says Flick, "In a perfect world, the sales tax process would seem to be a simple one since AI would merely need to analyze the data, compare it with the laws and subtract out the overlap. However, in the real world, when it comes to actual sales tax application, that foundational learning becomes challenging because of privacy limits, look-back relevance, speed of tax law changes and complexity in analyzing exceptions and overlap, limiting AI’s potential to add value to the forensic and analytical processes,” he said.
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ABOUT: EisnerAmper Advisory Group
EisnerAmper, one of the largest business consulting groups in the world, is comprised of EisnerAmper LLP, a licensed independent CPA firm that provides client attest services; and EisnerAmper Advisory Group LLC, an alternative practice structure that provides business advisory and non-attest services in accordance with all applicable laws, regulations, standards and codes of conduct. Having recently joined the EisnerAmper family, FM Cost Containment is one of the leading forensic tax recovery firms in the United States, specializing in tax confirmation and recovery of overpayments of sales and use taxes, as well as tax audit defense, utilizing proprietary research and knowledge of little-known technicalities in the tax laws of each of the 50 states, including over 10,000 tax entities throughout the United States.

For more information, please contact:
Bill Flick
EisnerAmper Advisory Group LLC
40 Lloyd Ave.
Suite 308
Malvern, PA 19355

Phone: 484-580-8907
Email: william.flick@eisneramper.com
Website: https://www.eisneramper.com/about-us/professional-directory/bill-flick/
LinkedIn: https://www.linkedin.com/in/williamflick
Twitter: https://www.x.com/BillFlickJr

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Leo Levinson
GroupLevinson Public Relations
+1 215-545-4600
leo@grouplevinson.com
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