The lawsuits making headlines aren't really about bad models. They're about who owns the tool, how it's wired into the work, and whether anyone is watching. That's a fixable operations problem. Most healthcare AI governance failures trace back to one question a room like this can't always answer: who owns the output? Healthcare AI Governance Failure Conversations Twelve months ago, most healthcare AI conversations were about potential: which model, which pilot, which vendor d

A JAMA Study Every Healthcare Executive Must Read Healthcare executives spend millions every year on management consultants. The pitch is familiar: better margins, smoother operations, happier patients, stronger quality scores. But what if the data showed that none of it was actually happening? That's exactly what a new study published in JAMA on May 4, 2026 revealed. And the findings should fundamentally change how every healthcare leader evaluates consulting engagements goi

The question isn't whether your AI passed the test. It's whether the test was asking the right questions. Every week, another healthcare organization announces it is deploying AI. Ambient clinical documentation. Revenue cycle automation. Front desk AI. Predictive risk stratification. The pace of adoption is accelerating and that is, in many ways, exciting. But here is the question we are not asking loudly enough: How do we actually know if these AI tools are safe, accurate, a