Why Most Radiology AI Fails

Why Most Radiology AI Fails

From Med Tech Gurus by Tom Hickey

June 10, 2026 · 45 min

About this episode

Khan Siddiqui discusses the challenges of AI adoption in radiology and the importance of integrating AI into clinical workflows.

AI can detect lung nodules in milliseconds—so why hasn't radiology been transformed? In this episode of Med Tech Gurus, we sit down with Khan Siddiqui, radiologist, serial entrepreneur, and CEO of HOPPR, to unpack why most AI tools in medical imaging struggle to survive beyond pilot studies. Dr. Siddiqui explains that detection isn't the real problem—workflow is. As imaging volumes surge and radiologist shortages intensify, AI must deliver measurable ROI in time savings, reporting efficiency, and reduced cognitive load. Tools that add clicks or increase reading time simply won't scale. We explore HOPPR's AI-native platform, which accelerates model development, enables local fine-tuning, and integrates AI directly into existing clinical workflows. Khan also shares powerful lessons on fundraising, identifying "hair-on-fire" customers, building A-player teams, and scaling innovation responsibly in regulated healthcare environments. If you care about AI in healthcare, radiology innovation, or moving from hype to real-world adoption, this episode delivers practical insight from one of the field's pioneers.

People in this episode

Host: Tom Hickey

Guest: Khan Siddiqui

Topics covered

  • radiology
  • AI in healthcare
  • medical imaging
  • workflow efficiency
  • innovation in healthcare

Keywords

  • radiology AI
  • workflow
  • HOPPR
  • cognitive load
  • ROI
  • medical imaging
  • innovation
  • fundraising

Mentioned in this episode

Organizations: HOPPR

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