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Radiology just admitted what we’ve been ignoring about AI.
The Journal of the American College of Radiology’s March 2026 Focus Issue dropped a truth bomb: workflow integration, not algorithm accuracy, determines AI success.
Think about that for a second.
We’ve spent years obsessing over which AI is smartest. Which one catches the most cancers. Which has the best sensitivity scores.
But Dr. Gelareh Sadigh and the JACR research team just flipped the script.
Their findings? Poor AI integration doesn’t just slow things down. It degrades safety. It perpetuates bias. It burns out radiologists even faster.
The three biggest roadblocks killing AI adoption right now:
• Insufficient infrastructure (hospitals can’t support the tech)
• Strict institutional regulations (compliance nightmares)
• Zero insurance reimbursement (who’s paying for this?)
Here’s what’s fascinating: The most successful AI programs in 2026 aren’t using the fanciest algorithms. They’re the ones that seamlessly fit into existing workflows.
AI handling triage and worklist prioritization. Radiologists focusing on complex interpretations. Quality assurance backing everything up.
Simple. Effective. Human-centered.
The market sees it too. AI radiology workflow optimization is exploding at 33.8% CAGR, heading toward $9 billion by 2031.
But here’s my take: We need to stop asking “which AI is best?” and start asking “which AI actually helps our radiologists?”
Because the smartest algorithm in the world is worthless if it makes a radiologist’s day harder.
Workflow isn’t a secondary benefit. It’s the whole point.
♻️ Repost if AI should enhance workflows, not complicate them.
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Author:
Jonathan Govette is a seasoned healthcare and technology executive with more than two decades of experience building, scaling, and advising digital health companies. He is the Co-Founder and CEO of Oatmeal Health, an AI-driven Lung Cancer Screening and Diagnostics company focused on expanding access to early detection for underrepresented populations, particularly patients served by Federally Qualified Health Centers and value-based health plans.
With a background in engineering, product development, and strategic partnerships, Jonathan has founded and led multiple health technology ventures across clinical care delivery, regulated medical software, and AI-enabled diagnostics. His work sits at the intersection of medicine, technology, and health equity, with a consistent focus on translating complex clinical problems into scalable, real-world solutions.
Jonathan has spent much of his professional life dedicated to improving outcomes for marginalized and underserved communities. He has designed and implemented frameworks that align clinical quality, reimbursement, and technology to sustainably advance health equity at scale. This mission is deeply personal and informs his leadership philosophy and long-term vision for healthcare transformation.
In addition to his operating experience, Jonathan is an author and long-time writer in the healthcare domain, with over 20 years of published work covering digital health, medical innovation, and healthcare systems. He is a frequent mentor to early-stage founders and regularly advises startups on product strategy, partnerships, and go-to-market execution in regulated healthcare environments.
Before entering industry full-time, Jonathan nearly pursued a career in medicine with an early path toward cardiothoracic surgery, an experience that continues to shape his clinical perspective and respect for frontline care delivery.
CEO | Oatmeal Health | AI Lung Cancer Startup | Engineer | Writer | Almost Became a Doctor (Cardiac Thoracic Surgeon) | 3x Health Tech Founder | Startup Mentor | Follow to share what I’ve learned along the way.
