Two head-to-head studies of medical AI came out weeks apart and reached opposite conclusions — one says general-purpose AI wins, the other says OpenEvidence does. Neither answers the question every doctor is actually asking: which one should I use in my practice?

The FDA just cleared UpDoc, software that adjusts medication doses between doctor visits — close to what Doctronic has been running in Utah. In both, AI does what only a licensed prescriber used to, and both stay inside the system for now. Sustaining innovation for the system, potentially disruptive for the doctor.

A surgeon posted on on LinkedIn that Silicon Valley, incorrectly, believes AI will be practicing medicine "momentarily." But AI has been diagnosing diabetic retinopathy with no physician since 2018, and this year another began renewing prescriptions in Utah. Both AI vendors carry malpractice insurance — because both AI systems are practicing medicine.

Five months into Utah's Doctronic pilot — the first US program authorizing AI to recommend prescription renewals — the state just released outcome data. The AI's renewal recommendations are statistically indistinguishable from a second physician's. And when the AI defers to a human, it defers more often than a human would.

40% of U.S. physicians use OpenEvidence. DoxGPT had 300,000 clinician users last quarter. UpToDate just launched Expert AI. Not one of these tools appears to have been independently tested for accuracy or safety. A profession built on evidence-based medicine is adopting AI with no evidence.

Medicine has a well-established model for distributing liability across physicians and tools: whoever caused the failure bears the liability. AI vendors have quietly opted out of it — and the contracts they're asking health systems to sign reflect that.

OpenAI and Anthropic both launched enterprise healthcare AI offerings last month. OpenAI's is more complete — a ready-to-use product for clinicians plus an API for developers. Anthropic's is developer-focused, with connectors to healthcare databases like CMS and ICD-10. Both will eventually offer the full stack. The question is what you need now.

In the first week of January 2026, Utah, and OpenAI each drew a different line around health AI—and liability. Utah’s Doctronic pilot treats AI like a clinician, with malpractice coverage and preserved remedies. OpenAI adds medical-record syncing under unchanged disclaimers and a $100 cap.

For the last 50 years, the engine of technology innovation has been a consumer engine. Consumers have steadily accumulated new health capabilities—including diagnosis, treatment, and monitoring—much faster than healthcare organizations. This has caused a decades-old, large-scale migration of health-related activity from the healthcare system to the consumer tech system. But in my experience speaking with hundreds of healthcare CEOs and board members, these migrations remain largely invisible to healthcare leadership.

The FDA just updated its General Wellness guidance, allowing consumer devices to measure clinical parameters for coaching—no clearance required. The same week, Utah let AI renew prescriptions with no doctor. Both are doing the same thing: moving healthcare tasks out of traditional systems and into consumer channels.

AI health coaches aren’t just for athletes anymore. They’re starting to handle the day-to-day interpretation, advice, and treatment adjustments that once required doctors. From glucose monitoring to hypertension management, technologies like Dexcom, Teladoc, and Omada are quietly taking over the work of routine clinical decision-making. This new generation of digital health coaches marks the next step in a long trend — technology shrinking healthcare by making us need it less.

Lawmakers are moving to ban AI-only insurance denials, requiring human sign-off for every case. It sounds compassionate, but it locks us into the same slow, opaque, costly system. The smarter move is AI with guardrails — transparency, audits, and contestable rationales — for faster, clearer, more accountable decisions.

The naturalist John Muir saw how everything in nature is connected — and today AI is showing us the same truth inside the body. From Apple Watch studies on atrial fibrillation to new hypertension alerts, hidden links in long-collected data are transforming how we understand health.