Physician and enterprise product leader. Author of the Agentic AI for Product Leaders series. Writes on AI, healthcare, and what changes when software starts acting. 15+ years at SAP, Walmart, and regulated health tech.
“AI in healthcare” is no longer a category, it’s a confusion. We treat mature, low-risk systems the same as experimental, high-risk ones. The real issue isn’t AI itself, it’s matching governance to actual risk and use.
At 11pm, patients don’t need a model. They need an answer. AI is already filling that gap, not because it’s better, but because it’s there. The risk isn’t just accuracy. It’s a new layer of care with no training, no accountability, and no clinician in the loop.
Medical information used to be hard to find. Then easy to find. Now it finds you. At each step we celebrated the progress. We are still figuring out what we lost.
In the 1990s, non-Jewish friend of mine wrote clinical notes for observant physicians who could not work on the Sabbath. Today, ambient AI does the same job. Who owns what the scribe writes?
Thirty years ago, in a small room at the Hebrew University School of Pharmacy in Jerusalem, a group of graduate students was simulating protein structures on Silicon Graphics workstations, the same machines Hollywood used for visual effects.
In 2018, the FDA cleared an AI to diagnose disease without a physician in the loop. A nurse captures two retinal images, the system delivers a clinical decision, and the company, not the clinic, carries the liability. That was seven years ago. The future we keep debating is already here.
In 2013, the FDA approved a machine that could sedate patients without an anesthesiologist. By 2016, it was dead. No safety scandal. No patient harm. It simply failed to sell.
When was the last time you trusted a machine with a life-or-death decision? If you’ve ever had an ECG, the answer is: already. Since 1982, ECG machines have printed automated interpretations, computers reading your heart and offering a clinical opinion long before we called it AI.
“The Second Eye” opens a five-part series. It traces healthcare AI to its real origins, in radiology, cardiology, anesthesiology, and other place, decades before today’s hype. I’m tired of reading that AI in healthcare is failing. Its not! It started long before Silicon Valley noticed.