Artificial intelligence is changing tax preparation, but who is responsible when the technology gets it wrong?
Randy Johnston and Brian Tankersley examine a proposed AI tax risk framework discussed in materials associated with former IRS Commissioner Danny Werfel. They focus on five categories of risk for tax preparers: technical, practice, legal and regulatory, business, and workforce and strategic.
The hosts examine AI hallucinations, inaccurate document extraction, client data leakage, overtrust of AI-generated tax advice, and erosion of professional expertise. They also explain how AI-driven productivity can overwhelm conventional human review procedures. Other concerns include shadow AI, professional liability, client disclosure, vendor dependence, and preservation of institutional knowledge.
The discussion distinguishes risks faced by practitioners from risks facing tax authorities, identifying hallucinations, overtrust, skill erosion, data leakage, and vendor dependence as overlapping concerns. The practical message is that faster preparation does not eliminate professional accountability. Firms need independent verification, appropriate human oversight, reliable source documentation, protection of confidential taxpayer information, and thoughtful AI governance. The framework is discussed as a proposal, not as a binding new IRS rule.
Key takeaways
- Verify AI tax conclusions against authoritative sources.
- Preserve meaningful human review even as AI throughput increases.
- Protect taxpayer information from unauthorized tools and vendors.
- Clarify professional liability, disclosure, and governance responsibilities.
- Maintain tax expertise and contingency plans for vendor dependence.
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