June 2026 Newsletter – AI for medical device development, compliance, regulatory, and quality operations
AI is rapidly transforming how we approach medical device development and quality and regulatory work. I’m sharing here some of what I’ve learned through conversations with software vendors, consultants, webinars, and industry events. In the 1990’s the rise of the internet reshaped business operations and in 2026 AI tools are changing how teams manage documentation, risk analysis, product support, regulatory monitoring, and decision-making. The impact of AI technology is widespread and evolving rapidly.
My goal is to help raise awareness of what’s now possible, share practical best practices, and highlight the growing variety of AI tools that quality and regulatory professionals can begin using today.
Here are some examples of how medical device professionals are now using AI (in addition to writing code):
- Creating draft documents (much faster than starting with a blank page but always make sure someone with adequate training and expertise completes each document)
- Creating templates and forms for particular SOPs
- Running audits of QMS procedures against regulations and standards
- Creating test cases/test protocols for V&V testing
- Generating draft design FMEAs
- Checking DHF documentation for consistency and traceability
- Creating quizzes for QMS training
- Monitoring and analyzing post-market signals
- Analyzing impacts of product changes
- Supporting complaint handling
In most cases these activities require specialized AI tools and I expect the number of specialized tools to increase rapidly over the next year.
Also, FDA reviewers have already started using AI to scan submissions (and I know at least one Notified Body doing so as well: Scarlet https://www.scarlet.cc/ ). That means errors buried in documents will be found so product teams need their own AI tools to check documents before submitting.
Not sure where to start? Here are a couple of good articles I’ve come across recently that I think provide useful insights for properly leveraging AI in quality and regulatory work.
AI for QARA – A Practical Guide for Medical Device Professionals
In this white paper by Qalico, they summarize the results of interviews with dozens of industry professionals on how they are using AI and what they expect in the near future. The paper includes practical examples to get started, with recommendations about what to do (and not do) when implementing AI at your company, including considerations for security and software validation. And the authors include some insightful quotes such as this one from Martin King:
“AI does not make us more intelligent. It lets us reach further, faster, with what we already understand. That is what the Stone Age axe did, and the printing press, and every communication tool since. The question is not whether QARA professionals will use AI. It is whether they will use it well. There is no real debate here. The new technology is on the block. People just have to work out how to use it safely and effectively.”
Qalico whitepaper: AI for QARA – A Practical Guide for Medical Device Professionals
[Note: you have to enter your name and email to download the white paper but I think it’s worth it.]
Productivity AI vs. Engineered AI
This article by Justin Dierking of myqms.ai makes some very important points about how best to leverage AI tools at a medical device company. He describes how many efforts to use AI tools may result in little to no productivity benefits because they only focus on isolated tasks. Instead, he encourages managers to look at the whole process workflow and utilize “Engineered AI” for real gains in quality and efficiency.
What I learned at the “Validated AI” conference in April 2026
In April, I attended the “Validated AI” conference in Boston where I learned a lot about how regulated companies in medtech and biotech are figuring out how best to manage AI in their products and operations. Some key takeaways from this conference:
- Everyone’s using AI to write code for their regulated products and processes
- No matter how sophisticated the AI tools, there must always be a human in the loop
- Manual review steps (human in the loop) can quickly become the bottleneck in an AI-accelerated development environment; organizations need to adapt accordingly
- Adopting AI in software development changes roles throughout the company, not just software engineers, and it changes the product development process (SDLC, etc.)
- Companies should focus on applying AI tools to improve overall business processes and not just individual tasks and activities
- AI can be used to optimize manufacturing processes for biopharmaceuticals with the potential to cut costs by orders of magnitude!
- The technology is evolving very rapidly; what you thought was not possible/practical a year ago may no longer apply
For more information, use this link on the Ketryx website to request access to recordings of the presentations:
https://www.ketryx.com/gen/validated-ai-conference
Patient-Centered Risk Management
I’ve been meeting regularly with a group of consultants to discuss best practices for risk management and recently we teamed up to write an article summarizing our recommendations.
In the article we present a detailed comparison of traditional versus recommended approaches, illustrated through an example with a hypothetical medical device: a VR headset for migraine treatment. We encourage companies to use risk management proactively, integrated into all phases of medical device development, so it can drive the product design instead of being performed after the fact for compliance.
https://naveenagarwalphd.substack.com/p/stop-managing-risk-after-the-fact
Upcoming Events
Let’s Talk Risk podcast – JUN 19, 2026 at 11AM Eastern/8AM Pacific
A panel discussion of the highlights of the recent International MedTech Safety Conference
https://www.linkedin.com/events/7470533864684240896