Insights from the Frontier of Healthcare AI

Every major health-tech conference this year had one thing in common: every booth, every banner, and every pitch deck claimed to have AI. Predictive AI. Generative AI. Diagnostic AI. Conversational AI. Ambient AI. The buzzword density has never been higher — and for hospital CTOs tasked with evaluating these tools, separating genuine clinical value from sophisticated marketing has never been harder. The challenge is real. Healthcare AI is a market projected to exceed $180 bil

The stethoscope didn't replace the doctor. Neither will AI. But just like no physician works without a stethoscope today, no clinician will work without an AI assistant by the end of this decade. Five years ago, AI in healthcare was a research paper sitting in an academic journal that most practising physicians never read. Today, it's reading radiology scans in real-time, flagging sepsis six hours before vitals crash, triaging emergency department patients faster than any man

A single patient can have data scattered across 14 different systems. When clinicians can't see the full picture, patients pay the price — and hospitals pay the bill. Imagine this scenario. It plays out in hospitals every single day. A 62-year-old patient arrives at the emergency department with chest pain. The attending physician checks the hospital's EHR and sees a clean cardiac history. No red flags. She orders a standard workup — troponin, ECG, chest X-ray — and based on