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AI in MedTech Product Development

Part 2 of 3 — Human Factors in the Digital MedTech Era

AI in MedTech Product Development

Part 2 of 3 — Human Factors in the Digital MedTech Era

In MedTech, usability challenges are far easier to address when they surface during development. Too often, they don't — becoming visible only once products reach real clinical environments, where they're costly and complex to fix. AI enables faster iteration and broader exploration, but understanding real-world use and product fit within existing workflows still depends on direct human insight.

This chapter of the webinar explores:

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How AI is reshaping the MedTech development process
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Why faster cycles increase the need for early usability insight
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Where AI can support design, testing and research workflows
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Why real-world use still requires direct observation

What’s Changing

Late-stage usability failures in MedTech aren't just costly. They're often unacceptable. Teams are working with simulation, synthetic data and AI-assisted design to test ideas faster and explore more options earlier — that’s a real advantage.

But speed doesn't automatically close the gap between how a product is designed to be used and how it's actually used. Clinical environments are shaped by time pressure, divided attention and routines that are difficult to fully anticipate — and that gap is where usability failures tend to hide.

Here’s what that looks like in practice:

Early human factors work can challenge the core assumptions behind a product — in one case, leading to a decision to stop development before significant investment was made.

In another, observing clinicians under time pressure revealed something no simulation had caught: a system designed for two-handed use was routinely used with one, introducing usability and safety risks that only became visible through direct observation.

What This Means

The earlier teams can test their assumptions against real-world behavior, the more room they have to act on what they find. AI is helping to compress that timeline — but the quality of learnings still depends on the quality of observation. How that plays out in practice is explored in the discussion below.

Meet the Speakers

  • Elizabeth Scheurell

Associate Director, Innovation Consulting

  • Renee Paquette-Glaude

Director of Society Engagement, Surgical Medical Education, Hologic

  • Vaishnavi Kishore

Product Owner, Eyetelligence Platform, Bausch + Lomb

  • Simon Shamoun

Human Factors Consultant and Owner, Defensible Research Design LLC

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