In a year thick with demos, headlines, and understandable caution, it’s hard to separate signal from noise in health AI. Duke is taking a different approach: pair scientific rigor with real operational build, and invite the people who will live with these systems to co‑design them.
On October 8–9 at the North Carolina Biotechnology Center (RTP), the Duke Summit on AI for Health Innovation—hosted by Duke AI Health, the Center for Computational & Digital Health Innovation, and the Duke Clinical Research Institute (DCRI)—will convene that conversation in the open.
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I’ll be speaking about how AI-driven workflows close care gaps and improve patient experience, with a focus on agentic systems that escalate intelligently, create auditable loop closure, and support value-based care without adding burden. I’m honored to share the stage with leaders who collectively shape how a health system evaluates, deploys, and governs technology: Richard Shannon, MD (Chief Medical & Quality Officer), Matthew Roman, MMCi (Chief Digital Strategy Officer), and Eric Poon, MD, MPH (Chief Health Information Officer). If you’ve ever wondered how decisions actually get made inside a health system—where safety, equity, and ROI meet—this is that room.
What sets this Summit apart is its span. From evaluation science and governance (Michael Pencina, PhD) to enterprise informatics and EHR modernization (Jeffrey Ferranti, MD, MS), from biomedical engineering and data fusion (Jessilyn Dunn, PhD; Amanda Randles, PhD) to computational and clinical machine learning (Monica Agrawal, PhD; Ricardo Henao, PhD), and from surgical AI and clinical translation (Ozanan Meireles, MD; Allan Kirk, MD, PhD) to emergency medicine and global implementation (Catherine Staton, MD, MSc) and biostatistics at scale (Chris Lindsell, PhD; DCRI). We’ll also explore the engineering and commercialization bridge with Jerome Lynch, PhD, Steve McClelland, and Jonathan Owens, MBA, and hear from industry voices such as Kurt Schmidt (NVIDIA)—a reminder that trustworthy AI needs both clinical depth and robust infrastructure. Guiding the ecosystem view is Shelley Rusincovitch, MMCi (Duke AI Health), whose work sits at the intersection of research, operations, and workforce development.
The through line is responsible AI with measurable outcomes: surgical innovation that helps in the OR and on the ward; computational medicine that moves beyond novelty to reproducibility; human‑centered design that earns trust; and breakout work that turns into artifacts you can use Monday. Duke is signaling that leadership in this space isn’t about hype or paralysis—it’s about building together with accountability.
Who should come? Clinicians and care team leaders trying to reduce avoidable utilization; engineers and data scientists seeking clinical context; operators and product leaders translating pilots into programs; Investors looking to understand how innovation translates to care transformation; students looking for a front-row seat to how health systems decide; and anyone interested in how adoption really happens.
If that’s you, I hope you’ll join us in Durham. Registration (with nonprofit and student discounts) is available now. Come for the signal—and help us build what lasts.
Register Here for the Duke Summit on AI for Health Innovation
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