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Welcome to Automating Quality, the life sciences–focused show exploring how quality, risk, and technology intersect to modernize regulated environments.
In Part 2 of this two-part series, Philippe Gaudreau continues the conversation with Dr. John Salvato, founder of Design Quality Services and an ISO 13485 lead auditor with more than 30 years of experience in medical device and automotive engineering. Having covered the foundations of design controls and FMEA in Part 1, the conversation now turns to where artificial intelligence fits into risk management and design documentation, and where it does not.
Salvato distinguishes what AI can responsibly accelerate in FMEA from what it cannot. Once a methodology is structured around clear rubrics, he explains, AI can apply it almost instantly. Weighing the benefit of a device against its residual risk, however, remains a human judgment shaped by each organization's own risk tolerance, not something AI can determine.
He also warns against "AI slop," content that looks polished and authoritative in design file generation but may not hold up to scrutiny. To guard against it, Salvato recommends building skill documents, akin to work instructions, that teach an AI tool a defined methodology, paired with the subject-matter expertise needed to recognize whether the output is sound.
As AI takes on drafting work once done by junior engineers, Salvato frames the professional's role as shifting toward reviewing, distilling, and ultimately approving what the tool produces. Evaluating an AI-generated DFMEA or safety risk analysis, he stresses, demands the same depth of training and experience organizations have always needed to sign off on that work.
AI can speed up the paperwork of risk management, but it cannot own the judgment behind it.
Key Takeaways
0:00 Looking back at Part 1 and introducing today's topic: AI and FMEA
1:45 Reintroducing guest John Salvato, founder of Design Quality Services
4:35 Where AI can responsibly speed up FMEA today
7:45 Why AI cannot weigh benefit against residual risk
10:45 AI slop and the risk of polished but unreliable design file content
15:30 How AI is reshaping the engineer's role from creator to reviewer
20:00 Training quality professionals to evaluate AI-generated output
Contact us at solabs-podcast@solabs.com
Contact Dr. John Salvato here: https://www.linkedin.com/in/john-salvato-ph-d-987b1b6/.
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