#439: MedTech AI Trends 2025: Scaling Regulatory Intelligence with Michelle Wu

In this episode, Etienne Nichols sits down with Michelle Wu, Founder and CEO of Nyquist AI and one of the top 100 women in AI, to discuss the transformative state of artificial intelligence within the MedTech regulatory and quality space. Reflecting on her recent personal experience as a surgical patient, Michelle shares a unique perspective on the critical importance of the devices and quality systems that keep the industry running.

The conversation dives deep into the "Great Rewiring" of the medical device industry. Michelle outlines how we have moved past the initial phase of AI skepticism and "AI fatigue" into a period of hyper-acceleration. With the introduction of the FDA’s ELSA and the implementation of the EU AI Act, the industry has reached a point where AI is no longer a side project but a fundamental requirement for operational longevity.

Finally, the episode provides a roadmap for both organizations and individual contributors. Michelle introduces her "Holy Trinity" framework for AI implementation—Data, Workflow, and Agents—and explains why the next two years will be defined by the "Invisible Colleague" or AI copilot. For junior professionals, the message is clear: knowledge is now a commodity, and the real value lies in the ability to ask high-quality, strategic questions.

Key Timestamps

• 00:00 – Introduction and Michelle Wu’s background in MedTech and AI.
• 03:45 – A founder’s perspective: Michelle’s personal experience in the OR seeing her clients' devices.
• 08:12 – The 2025 Inflection Point: FDA ELSA, EU AI Act, and global AI expectations.
• 11:50 – From billable hours to value-based output: How AI is disrupting the consulting business model.
• 15:35 – Micro-timestamp: 2026 Predictions. The shift toward universal AI Copilots and Agents for every MedTech role.
• 18:22 – The Holy Trinity of AI: Breaking down Data Layers, Workflow Automation, and AI Agents.
• 22:10 – Case Study: How a top-tier MedTech company automated 17,000 quality and regulatory tasks.
• 27:45 – The 56.8% Salary Premium: Why AI literacy is the most important skill for young RAQA professionals.
• 31:15 – Shifting from memorization to "Clarity of Mind" and high-quality inquiry.

Quotes

"Knowledge is a commodity now. Previously, regulatory consultants or professionals stood out by their knowledge. Now, with AI leveling the field, the capability lies in those who can ask high-quality questions." - Michelle Wu, Nyquist AI

Takeaways

• AI Literacy is a Financial Multiplier: LinkedIn data shows that non-engineering knowledge workers with AI literacy can command a salary premium of up to 56.8%.
• The 80/20 Rule of Automation: Approximately 80% of current RAQA tasks are tedious, manual, or administrative. Successful teams are using AI to automate that 80%, allowing humans to focus on the 20% that is strategic and high-value.
• The Three-Layer AI Strategy: To effectively implement AI, companies should look at the Data Layer (intelligence), the Workflow Layer (automation of specific tasks), and the Agent Layer (autonomous "employees").
• Value-Based Billing: As AI reduces the time required for regulatory submissions and gap analyses, the industry is moving away from the "billable hour" toward pricing based on the value and quality of the output.

References

• Nyquist AI: Michelle Wu’s platform specializing in global regulatory intelligence and AI-driven workflow automation for MedTech.
• FDA ELSA: The FDA’s internal AI tool that marked a significant shift in the agency's embrace of the technology.
• IMDRF GMLP: Good Machine Learning Practice guidelines for AI-enabled medical devices.
• EU AI Act: The first comprehensive legal framework for AI, affecting MedTech compliance timelines.
• Etienne Nichols: Connect with Etienne on LinkedIn.

MedTech 101: AI Agents vs. AI Chatbots

While many people are familiar with AI Chatbots (like the early versions of ChatGPT), the industry is moving toward AI Agents.

Think of a Chatbot like a very smart encyclopedia. You ask it a question about a 510(k) submission, and it gives you information.

An AI Agent, however, is like an AI Intern. It doesn't just give you information; it performs a multi-step task. For example, you can tell an Agent to "find the three most relevant predicates for this new device, summarize their 510(k) summaries, and draft a gap analysis table." The Agent "thinks" through the steps and delivers a finished product, not just a response.

Sponsors

This episode is brought to you by Greenlight Guru. As Michelle and Etienne discussed, the future of MedTech is driven by data and efficiency. Whether you are navigating the complexities of the EU AI Act or scaling your R&D, Greenlight Guru’s QMS (Quality Management System) and EDC (Electronic Data Capture) solutions provide the structured data foundation necessary to leverage AI effectively. By integrating quality and clinical data, Greenlight Guru helps you move from "reactive" compliance to "proactive" innovation.

Feedback Call-to-Action

We want to hear from you! How is your team currently leveraging AI in your regulatory or quality workflows? Are you feeling the "AI fatigue," or are you seeing the "salary premium" Michelle mentioned?

Send your thoughts, guest suggestions, or specific questions to podcast@greenlight.guru. Etienne personally reads and responds to listener feedback, and we would love to feature your insights in a future episode.