Is there FDA guidance on using AI to write drug labeling?

Not directly. The FDA's main AI guidance for drugs, a January 2025 draft, covers AI used to produce information or data that supports regulatory decisions about safety, effectiveness or quality. It says it doesn't address AI used for operational efficiencies, and it names drafting or writing a regulatory submission as an example, as long as that use doesn't affect patient safety, drug quality or study results.

This page is general information, not legal or regulatory advice.

What the draft guidance covers

The draft is titled Considerations for the Use of Artificial Intelligence To Support Regulatory Decision-Making for Drug and Biological Products. It sets out a risk-based framework for judging whether an AI model is credible for a particular use. It's a draft, so it is non-binding and not for implementation yet.

What it leaves out

The guidance says it does not address AI in drug discovery, or AI used for operational efficiencies such as internal workflows, resource allocation, or drafting and writing a regulatory submission, when that use doesn't affect patient safety, drug quality or the reliability of study results. The FDA encourages sponsors to talk to it early if they're unsure whether a use is in scope.

So the guidance doesn't set rules for AI-drafted labeling text. It also doesn't say labeling written with AI is exempt from anything else. The labeling rules and your quality system still apply to the words on the label, however they were drafted.

Where the clearer expectation comes from

A plainer regulator statement on AI-drafted product information comes from Europe. In its reflection paper on AI in the medicinal product lifecycle, the European Medicines Agency (EMA) writes, in section 2.3.5 (Product information):

AI/ML applications used for drafting, compiling, editing, translating, tailoring, or reviewing medicinal product information documents should be used under close human supervision. Given that generative language models are prone to include plausible but erroneous or incomplete output, quality review mechanisms need to be in place to ensure that all model-generated text is both factually and syntactically correct before submission for regulatory review.

What that means for a labeling team

AI drafts are fluent, and fluent text can carry a correctly spelled wrong word as easily as a person can. A read for meaning on the high-stakes lines is still your best check. See AI-drafted labeling and human review, does AI drafting make wrong-word errors moot, and real cases on the case index.

Sources

• FDA: Considerations for the Use of Artificial Intelligence To Support Regulatory Decision-Making for Drug and Biological Products
• EMA: Reflection paper on the use of AI in the medicinal product lifecycle

Last reviewed: October 14, 2026

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Is there FDA guidance on AI for drug labeling?

Not directly. The FDA's January 2025 draft guidance on AI for regulatory decision-making does not address AI used for drafting or writing a regulatory submission when it doesn't affect patient safety, quality or study results.

What does the FDA's AI draft guidance cover?

AI used to produce information or data that supports regulatory decisions about a drug's safety, effectiveness or quality, with a risk-based framework for judging model credibility.

Does AI-drafted labeling escape labeling rules?

No. The guidance's scope doesn't change the labeling rules or your quality system, which apply to the words on the label however they were drafted.