By Soumoshree Mukherjee
Editor’s note: This article is based on insights from a podcast series. The views expressed in the podcast reflect the speakers’ perspectives and do not necessarily represent those of this publication. Readers are encouraged to explore the full podcast for additional context.
In the latest episode of the CAIO Podcast, host Sanjay Puri sits down with Dr. Girish Nadkarni, a physician-scientist whose journey from Mumbai to New York has positioned him at the forefront of enterprise AI transformation in healthcare. Today, Nadkarni serves as the Chair of the Weindrich Department of Artificial Intelligence and Human Health and Director of the Hasso Plattner Institute of Digital Health at Mount Sinai — roles that place him at the epicenter of the AI-driven shift reshaping modern medicine.
Dr. Nadkarni’s path, as he tells, was fueled by “serendipity” and a readiness to raise his hand for any challenge. Trained in medicine in India, he later pursued informatics and biostatistics at Johns Hopkins before “AI” was even the dominant term.
When he joined Mount Sinai 16 years ago, he found mentors like Dr. Erwin Bottinger, the CEO of the Weiss Institute to encourage him, “he was sort of instrumental in making me think about how. Not just how you could improve medicine now, but how you could sort of pull the future forward.”
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That future took shape dramatically during the COVID-19 pandemic, when Mount Sinai’s health system became the “epicenter of the epicenter.” According to Dr. Nadkarni, the crisis accelerated the institution’s evolution into a learning health system, a model that uses real-time data to continuously update clinical decisions, test new interventions, and scale what works. He tells, “(we were) discovering knowledge and applying it in real time. And that’s how sort of a learning health system evolves.”
A true learning system, as Nadkarni explains, demands more than data. It requires a culture that embraces experimentation, psychological safety, and the freedom to fail. Mount Sinai’s leadership, particularly Lisa Stump, the Chief Digital and Information Officer, “who believes in the experience-led model” has been instrumental in fostering this environment.
Stump’s AI adoption shift from a top-down directive to a bottom-up, user-driven movement, making clinicians not just users but evangelists. She also taught him, “that change management is critical… not because people are afraid of change, but people think that they will be left behind with that change”
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Much of the conversation explores change management, ROI, and governance, three areas that often frustrate AI leaders. Dr. Nadkarni emphasizes starting, “the first important thing is start off with the why. Why are you doing this? What is the problem that you’re trying to solve?,” demonstrating the technology to leadership, and expanding ROI metrics beyond finances to include clinician burnout, patient experience, and staff retention
In discussing AI bias, he insists on rigorous pre-deployment assurance testing, red teaming, and continuous post-deployment monitoring. For Dr. Nadkarni, the promise of AI lies in what he calls an “arbitrage of knowledge for time” giving clinicians precious minutes back to make wiser, more human decisions.
Wisdom, he reminds, remains uniquely human, “I think that’s a uniquely human characteristic because that’s bounded by, or not bounded, that’s informed and by ethics and morality and our innate humanness of things.”
As enterprises worldwide grapple with AI integration, Dr. Girish Nadkarni’s journey and insights offer a blueprint for transforming health systems not by replacing people, but by empowering them.
