A few weeks ago, I watched a colleague pull up ChatGPT mid-rounds to look something up. My instinct was immediate: why are you using that? Use Open Evidence. Use Doximity. Use UpToDate. Those tools were built for us! ChatGPT was not.
Now OpenAI has launched ChatGPT for Clinicians, which is a free, verified platform aimed squarely at physicians, NPs, PAs, and pharmacists.
I’m not surprised by the launch of ChatGPT for Clinicians. AI medical search is becoming a commodity. The same way ambient scribes went from novelty to baseline expectation over the course of my residency, AI-powered clinical knowledge tools are heading the same direction. If you don't offer it, you're already behind.
So, in this article, I'll recap what ChatGPT for Clinicians actually is, map where it fits in an increasingly crowded market, and explain what it takes to win in a space that's quickly turning into table stakes.
What is ChatGPT for Clinicians?
ChatGPT for Clinicians is free for verified U.S. clinicians (physicians, NPs, PAs, and pharmacists) and takes about five minutes to set up via NPI verification. It offers citation-backed clinical search, a deep research mode across the medical literature, repeatable documentation workflows (prior auth letters, patient instructions), and CME credit tied to evidence review. HIPAA support is available, but only through a business associate agreement—it's not on by default (big FYI!).
This is OpenAI's third healthcare product in rapid succession. ChatGPT Health launched in early 2026 for consumers—patients linking medical records and getting personalized answers. ChatGPT for Healthcare is the enterprise B2B version, with governed security controls. ChatGPT for Clinicians fills the individual clinician layer. They're building a full healthcare stack, one user segment at a time.
genAI depiction of OpenAI health stack.
AI Medical Knowledge Tools Are Becoming a Commodity
When a feature becomes so widely available that its presence is expected and its absence is a liability, it has commoditized. That's where AI medical search is right now.
Two years ago (nearly the entirety of my residency) platforms like Open Evidence and DoxGPT were novel. A lot of us were experimenting with them, and the concept still felt new. Today, nearly every major clinical platform has layered in some version of AI medical search. When Heidi launched Heidi Evidence earlier this year, it barely registered as a surprise because of course they did. And now OpenAI. The market has saturated, and the message is quite clear that if you don't offer this, you're already behind.
For completeness, I’m going to copy and paste my brief market analysis of the key players below. I also recorded a quick video where I take ChatGPT for Clinicians, Doximity, OpenEvidence, and UpToDate’s Expert AI, then copy and paste the same clinical question into each to see how they present and structure the evidence.
Market
UpToDate Expert AI (Wolters Kluwer): The longstanding gold standard in clinical decision support, now layering generative AI on top of its physician-reviewed content. Its moat is trust, EHR integration, and the fact that most of us already have it open during rounds. I wrote a deep dive on Expert AI if you want the full breakdown.
Doximity + Pathway Medical: Doximity acquired Pathway Medical to build out DoxGPT, which bundles clinical Q&A, scribe, and documentation tools into one physician-facing platform. Its advantage is distribution—Doximity reaches over 80% of U.S. physicians. Check out my deep dive here.
Open Evidence: The fastest-growing platform in this space. Open Evidence went from a $1 billion valuation in February 2025 to $12 billion by January 2026, raising roughly $700 million across four rounds in under a year. It has content deals with NEJM and JAMA, and its focus on medicine-only answers with primary research citations has made it a daily driver for many physicians, myself included.
Heidi Evidence: Heidi’s scribe platform now includes a free, citation-backed medical search tool.
ClinicalKey AI (Elsevier): Pairs Elsevier's premium medical content with generative AI, often bundled into enterprise deals with health systems.
DynaMed / Dyna AI (EBSCO): An evidence-curated database with AI-enhanced natural language queries and EHR integrations. Competes directly with UpToDate in the institutional market.
AMBOSS: Expanding beyond medical education into clinical decision support with an AI "medical co-pilot." Strong editorial credibility and a loyal user base among trainees and early-career physicians. I’ve been experimenting with this platform some more!
The broader AI in healthcare market was estimated at $36.7 billion in 2025 and is projected to top $500 billion by 2033 (39% CAGR), with healthcare AI spending nearly tripling in 2025 to $1.4 billion. Within that wave, AI clinical decision support (a decent proxy for AI medical search) reached roughly $2.8 billion in 2025 and is projected to hit $15.3 billion by 2033.
Dashevsky’s Dissection
When I first saw OpenAI’s announcement, my knee-jerk reaction was, "Great, another player crowding the medical AI search space." That reaction is part of what makes AI medical search feel like a commodity now.
OpenAI knows the market is saturated, so this move feels strategic. They can collect clinician identity data, see what we search, and learn how we search. That can translate into targeted ads, product strategy, or both. Making it free also turns it into a front door: get clinicians using the tool, anchor habits, and then lean on those clinicians to push their organizations toward the enterprise version of ChatGPT for Healthcare. And ChatGPT already has massive reach among Americans, including physician-users, so the distribution advantage is obvious.
As I’ve stated before in my course on AI and Healthcare Utilization (enroll here), in a saturated market, platforms win on three things: distribution, trust, and frictionless workflows.
On distribution, OpenAI is hard to beat. It was the first generative AI platform I used. I no longer use it regularly, but the point stands: it’s everywhere, on everyone’s phone and computer.
Trust is a different question. Up until now, if I saw a colleague using ChatGPT to look up medical information, I’d give them a slap on the back of the head, telling them to use Open Evidence, Doximity, or UpToDate instead (see my opening sentence). Those products are built for clinicians, rely on primary sources, and (in UpToDate’s case) sit on top of content written and reviewed by experts. I do not trust OpenAI the same way. I’m especially skeptical after recent reporting in The New York Times and The New Yorker on the company’s history. And when I say “trust,” I mean trust with health information. I’m not convinced, even with promises that queries will not be used to train models. If OpenAI eventually goes public, the pressure to maximize shareholder value will shape what happens next.
Then there's workflow—and this is where I think people underestimate the switching cost.
"Frictionless" doesn't require EHR integration per se. It just requires that a tool already lives where physicians are. I open Doximity multiple times a day: to dial a patient, send a message, look something up, draft a prior auth letter. The clinical search is already there, already trusted, already one tap away. This is a habit, now, and habits in clinical medicine are sticky by necessity. We are trained to build them because consistency under pressure matters.
For ChatGPT to displace that, it would need to offer something meaningfully better at a moment when I already have a tool open. Not marginally better… truly meaningfully better. The bar to interrupt an established workflow is high, and OpenAI hasn't cleared it for me—at least not yet. What could change that? If it proved more accurate on specific clinical question types, if it integrated into a platform I already use, or if an institution mandated it. Short of that, most physicians will keep doing what they already do. Inertia is underrated as a market force in healthcare.
In summary, ChatGPT for Clinicians matters less because it is a breakthrough product and more because it signals where the market is headed: AI medical search is becoming table stakes, and the winners will be the platforms that earn clinician trust, minimize workflow friction, and control distribution as this capability turns into a baseline expectation.
