AI and the IRS: What Tax Teams Need to Know

AI in R&D tax credits is gaining attention. Tax teams are exploring tools that can scan project records, tag qualified research expenses (QREs), and even draft documentation. But there’s a question every tax leader must ask: How will the IRS view AI-generated documentation?

The IRS has not released specific guidance on AI, but its expectations for R&D documentation remain clear. Agents want verifiable evidence, alignment with the four-part test, and proof that qualified individuals performed the work. AI output alone cannot deliver that.

In this article, we’ll explore how the IRS may approach AI in audits, the risks of over-automation, and how tax teams can prepare.

Why the IRS Cares About AI in R&D Credits

The IRS has one goal in reviewing R&D claims: ensure taxpayers comply with the law. AI introduces both opportunity and risk in that process.

On one hand, AI can strengthen claims by producing contemporaneous documentation and reducing human error. On the other, it can generate summaries that lack the detail auditors require.

The IRS is watching this trend closely. With Form 6765 updates requiring more granular reporting, companies must provide more detail than ever before. That means AI-driven shortcuts will not pass muster if they fail to show uncertainty, experimentation, and qualified activity.

Audit Expectations

The IRS does not relax its standards for new technology. Whether records are AI-generated or human-written, they must meet the same requirements.

Detail

Auditors expect clear descriptions of what was tested, how it was tested, and what uncertainty was resolved. Generic summaries—AI or otherwise—will not suffice.

Evidence

The IRS favors contemporaneous documentation. AI can help collect this, but teams must retain the original project records, not just the AI-processed output.

Four-Part Test Alignment

Every activity must tie back to the statutory test: permitted purpose, elimination of uncertainty, process of experimentation, and technological nature. AI tools cannot apply this framework on their own.

Risks of Over-Automation

Tax teams that rely too heavily on AI face several risks.

• False confidence: Believing AI output is “proof” without human validation.
• Misclassification: AI may flag routine tasks as research, creating exposure in an audit.
• Audit gaps: Agents may reject AI summaries unless supported by contemporaneous source records.

At MASSIE, we’ve seen companies lean too heavily on automation, only to face difficult conversations during IRS examinations.

How IRS Auditors May Treat AI Output

While there is no formal IRS position on AI yet, auditors are likely to treat it as a tool—useful for organizing data but insufficient as standalone proof.

In fact, IRS agents often request “original evidence.” That means tickets, lab reports, test results, or time records—not a generated summary.

AI output may even raise scrutiny if it appears boilerplate or disconnected from the facts. To auditors, defensibility comes from real, verifiable evidence.

For companies looking to reduce risk, IRS programs like the Pre-Filing Agreement (PFA) can help establish clarity before filing.

Building Defensibility with AI Tools

The best approach is hybrid: AI plus human oversight.

SME Validation

Engineers and technical leads must confirm whether flagged projects truly qualify. AI can surface the data; SMEs provide the judgment.

Documentation Standards

Tax teams should retain original records, even if AI tools generate summaries. These records prove the claim meets IRS requirements.

Governance Framework

Establish policies for how AI is used, how outputs are validated, and how source records are preserved. This reduces audit exposure and demonstrates control.

At MASSIE, we apply AI thoughtfully within the MASSIE Method. Every AI-assisted document goes through SME review and professional validation before it is filed.

The MASSIE Perspective on Audit Readiness

AI can make R&D tax credit studies faster and more efficient. But IRS scrutiny is not going away—it is increasing.

For companies exploring AI, the path forward is not full automation. It’s balance. Use AI to capture and organize data. Then apply human expertise to interpret, validate, and defend it. That is how companies reduce risk and build claims that hold up under audit.

Want to talk about how to use AI within your tax team? Reach out. We’d love to talk.

Stephen Whiteaker, CPA

As MASSIE’s Director of Controversy, Stephen specializes in audit risk assessment and quality review. His proficiency in navigating complex tax law makes him an essential resource in addressing tax technical challenges for clients. His exten...