Two AI Compliance Checks Quality Managers Must Run Before Anything Else

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A supplier quality professional at a contract manufacturer has outlined two critical checks for anyone using AI in quality management systems: whether AI communicates with humans without identifying itself, and whether AI-generated external content is published without named human review. The author argues that both gaps create serious legal, regulatory, and compliance risks, particularly under standards like ISO 13485 and 21 CFR Part 820, which require traceable records and defined accountability. Common failure modes include assuming polished AI output is inherently reliable and allowing automated outbound communications without a human sign-off on record. To address these risks, the author recommends practical, low-effort fixes such as labeling AI-generated drafts, blocking autonomous external publishing, logging prompt and response provenance, and requiring named human approval with a timestamp. These controls are designed to integrate into existing QMS workflows covering document control, change control, and CAPA without requiring months of implementation.

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