The piece examines how tax authorities in South Carolina are adopting AI‑driven systems to screen returns and identify potential noncompliance more quickly, while taxpayers, policymakers, and privacy advocates debate how far this technology should go. It focuses on SCDOR’s plan to integrate machine‑learning models into its GenTax platform, the promise of faster and more targeted business tax audits, and the broader policy discussion over whether algorithmic risk scoring can make audits more efficient without undermining taxpayer rights.
Key Takeaways:
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South Carolina’s Department of Revenue is deploying AI and advanced data analytics on top of its existing GenTax system to flag higher‑risk returns—starting with business taxes—so auditors can focus on cases where underpayment is more likely.
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State officials say the goal is to reduce low‑value “no‑change” audits and modernize enforcement, but experts warn that opaque algorithms and biased training data could make it harder for taxpayers to understand or challenge why they were selected.
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The legal and policy framework around AI in tax administration is still developing, as South Carolina and other jurisdictions experiment with these tools under existing tax and privacy laws, leaving the long‑term shape of AI‑assisted audits to ongoing regulatory and political debates.
Read the article.
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