Model quality is commoditizing. The decisive factor is now whether a system can be trusted at healthcare scale. To understand where the market is heading, look closely at the vendors quietly winning enterprise traction right now. 4 trust layers in healthcare0:00/762.3238321× A useful way to understand where
For years, data scientists built trust by decomposing probabilistic systems into measurable tasks. That discipline still matters. But once agents act across tools, workflows, and decisions at machine velocity, task telemetry and analysis alone is no longer a sufficient baseline. Baseline Decision Telemetry0:00/845.5330151× For decades, trustworthy AI
Most large healthcare organizations have solved the C-suite buy-in problem. The harder problem — the one that actually determines whether an AI program scales or plateaus — are the layers directly below.
How Surest rewired member decision-making without rewriting provider contracts — and what the next wave of plan innovators is actually competing for.
The healthcare organizations making real progress with AI are not the ones running the most experiments. They are the ones building an operating model for intake, readiness, governance, and execution.
I had have several conversations about AI leadership over the last few month. I recognize the role of IA and Technology leaders are evolving, but there is a structured way to approach this rather than jumping on the "AI train". Copy what CIOs already know what to do.
Over the past few years, I have evaluated Voice AI across established vendors, Generative AI startups, healthcare incumbents, and I see a field moving fast, but not always safely. Now we will talk about how the answer is about where to focus and how to build trust in healthcare, to move faster.
I have launched haupt.ai as a new AI Advising service for folks wants to cut through the AI hype and have a practical path to outcomes.
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Why this newsletter exists Summit Evidence AI exists because healthcare leaders deserve more than vendor narratives and conference slides. Every briefing starts with the evidence — research, real deployments, governance outcomes — and distills it into 10–15 minutes of useful signal for executives, data leaders, and practitioners navigating AI in high-stakes