AI is moving into life sciences quality and manufacturing work, and FDA is showing how existing GMP expectations apply when AI is used to support regulated activities.
FDA has already used enforcement to make clear that AI-generated GMP documents still require appropriate review and control. The issue is no longer theoretical.
That is the point companies should focus on. This is not about treating AI as automatically unacceptable, and it is not about waiting for a new AI-specific GMP regulation before taking action. The issue is more practical: when AI helps create or support GMP work, the company still has to control the process and own the output.
That includes SOPs, specifications, deviation summaries, CAPA support, training content, supplier documentation, production records, investigation summaries, and inspection preparation. AI may help teams draft faster, compare records, organize information, or identify gaps, but none of that changes the basic quality expectation.
The output still has to be accurate. The rationale still has to be defensible. The record still has to reflect the actual process. The Quality Unit still has to review and approve GMP-impacting outputs within its area of responsibility.
The exposure is not that a company used AI. The exposure is using AI informally, inconsistently, or without a defined review pathway. That is where a useful tool can become an uncontrolled input into a regulated process.
Before AI becomes routine inside quality or manufacturing operations, companies should be able to answer a few basic questions:
• Where is AI allowed to be used?
• What activities are off limits?
• Which outputs require Quality Unit review?
• How is accuracy verified?
• How are sources, assumptions, and key decisions documented when the output supports regulated work?
• How is confidential or regulated data protected?
• Who owns the final decision?
The companies that benefit most from AI will not be the ones that move the fastest. They will be the ones that put enough structure around AI use to make the output reliable, reviewable, and defensible.
MEDVACON LIFE SCIENCES, LLC builds the structure that makes AI use in regulated quality systems defensible, documented, and inspection-ready.
AI can support the work.
It cannot replace control.