This month, two of the hottest AI companies in San Francisco announced a major push into healthcare — moves that experts say were not only inevitable, but also timely and high-stakes.
These AI rivals — Anthropic and OpenAI, the makers of the widely used large language models Claude and ChatGPT, respectively — unveiled new suites of tools for healthcare organizations and everyday consumers. These moves reflect a shift in how patients are accessing medical guidance — one that experts agree is simultaneously expanding access to information while raising new questions about trust and control.
What these healthcare expansions could mean for startups
Anthropic and OpenAI’s healthcare buildouts are forcing startups across the health tech market to reassess where they truly have defensible advantages, one investor pointed out.
Kamal Singh, senior vice president at WestBridge Capital, thinks consumer wellness and nutrition startups are the most vulnerable, saying that these types of broad, chat-based platforms are likely to be commoditized.
Startups offering nutrition or wellness advice without deep specialization now face weakened value propositions — given that Claude and ChatGPT have massive distribution and habitual usage, he pointed out. Some examples include apps like Noom, Fay and Zoe.
Others will probably remain insulated — or even strengthened — depending on how robust their models are, Singh said. In his view, companies focused on specialized clinical areas, such as chronic disease management, will be far more resilient to large tech incumbents entering the space.
These types of companies rely on deep patient data, longitudinal insights and disease-specific expertise — capabilities that we still don’t know if general purpose tech companies will be able to replicate at scale, Singh remarked.
He also pointed to care coordination and care management as areas where startups can maintain an edge, particularly when they combine AI with human clinicians. Rather than competing directly with large language models, Singh believes startups should differentiate by prioritizing outcomes and delivering end-to-end care experiences.
Another emerging battleground is AI-driven primary care. Singh said this category sits between consumer wellness and specialized medicine — sophisticated enough to resist full commoditization, but still vulnerable to pressure from popular AI platforms.
“On the startup side, you don’t really have any winners yet — there are a couple of companies like Counsel Health, who are kind of inching towards that goal, but these announcements make it a very interesting dynamic there,” he declared.
Counsel Health is a virtual care company that combines AI with human physicians to give users quick, personalized medical advice.
To survive, Singh said startups in this space will need creative business models, including hybrid approaches that integrate real clinicians with AI-powered guidance.
The inevitable rise of AI as healthcare’s front door
It was inevitable that OpenAI and Anthropic would deepen their presence in healthcare. Trends in user activity made this unavoidable — hundreds of millions of people per week were turning to their chatbots to answer their health-related inquiries.
“Almost 5% of their traffic is healthcare-related. There are about 40 million unique healthcare questions asked by users in a day. Given that, it really does seem that they’re in the healthcare business, and so if they’re seeing that much traffic to their sites related to healthcare, they had to increase their capabilities in that space,” explained healthcare AI expert Saurabh Gombar.
So what did the Anthropic and OpenAI actually roll out?
OpenA launched two new offerings. One is ChatGPT Health, a dedicated health experience within ChatGPT that combines a user’s personal health information with the company’s AI, with the promise of helping people better manage their health and wellness. The other is OpenAI for Healthcare, a suite of AI tools designed to help healthcare providers reduce administrative burnout and improve care planning.
OpenAI also announced its acquisition of medical records startup Torch this month — a deal that is reportedly worth $100 million.
Anthropic followed with a healthcare splash of its own, unveiling a new suite of Claude tools. The company is releasing new agent capabilities for tasks like prior authorization, healthcare billing and clinical trial workflows, as well as letting its paid users connect and query their personal medical records to get summaries, explanations and guidance for doctor visits.
Gombar, the AI expert mentioned above, believes that large language models are becoming the new “front door” to healthcare.
“The LLMS are now becoming the front door for medical advice and treatment options, and the actual provider is becoming the second opinion. Because chatbots are easier to interact with, and they’re free, and you don’t have to schedule around them,” Gombar stated.
Gombar is a clinical instructor at Stanford Health Care and chief medical officer and co-founder of Atropos Health, a healthcare AI startup that generates real-world evidence at the bedside. In his eyes, tech companies developing public-facing chatbots are already in the healthcare business, whether they formally acknowledge it or not.
This could fundamentally alter the physician-patient relationship. Gombar noted that clinicians are already beginning to see more and more patients who arrive already convinced they need specific tests or treatments based on chatbot advice.
He thinks traditional providers have limited control over this shift, given consumer behavior is clearly changing at a rapid pace. Not only has the use of chatbots like ChatGPT and Claude skyrocketed in the past couple of years, but Americans are also finding it more difficult to access healthcare amid sweeping Medicaid cuts and a worsening labor shortage.
The risks of chatbots in medicine
The rise of large language models in healthcare is already well underway, but that doesn’t mean there aren’t risks involved. Asking for medical guidance from an intelligent software program is very different than asking for a recipe — wrong answers can cause real harm.
Traditional healthcare providers have accountability mechanisms — such as medical malpractice rules, audit trails and liability protocols — while chatbots rely heavily on disclaimers that say their outputs should not be considered medical advice, Gombar pointed out.
However, in practice, many users treat chatbot responses as actual medical advice, often without cross-checking with other sources or their providers, he added.
Gombar hopes companies like Anthropic and OpenAI move beyond disclaimers and take greater responsibility for how their tools handle medical information. In the future, he would like to see them be more transparent about the limitations of their systems — including how often they hallucinate, when answers are not grounded in strong evidence and when medical evidence itself is uncertain or incomplete.
He also suggested that large language models be designed to more clearly communicate uncertainty and gaps in knowledge, rather than presenting speculative answers with unwarranted confidence, he said.
Aside from accuracy, there are also concerns related to data privacy, as consumers’ growing distrust of Big Tech companies and their data privacy practices remains an ongoing issue.
Anthropic said that its new health products are designed with strict safeguards around user consent and data protection.
“Users give express consent to integrate their data with full information about how Anthropic protects that data in our consumer health data privacy policy. Anthropic does not train on user health data. Period. We also protect sensitive health data from inadvertent sharing to other integrated model context protocols by requiring user consent to each integration in conversations where integrated health data is being discussed. Users can disconnect the integration any time in settings,” an Anthropic spokesperson explained in an emailed statement.
Even before it rolled out ChatGPT Health, OpenAI had been building user data protections across ChatGPT, including permanent deletion of chats from OpenAI’s systems within 30 days and training its models not to retain personal information from user chats, a company spokesperson said in a statement.
For its new consumer health offering, OpenAI has added more encryption protections, as well as isolated the chats to keep health conversations and memory protected and compartmentalized. Conversations in ChatGPT Health are not used to train its foundation models, the spokesperson said.
As for OpenAI’s new platform for healthcare providers, customers will have full control over their data. When clinicians enter patient information, for example, it will stay within the organization’s secure workspace and will not be used for model training.
Making AI work for clinicians and patients
By releasing tools for consumers as well as for healthcare providers, OpenAI is signaling that it understands consumers have different needs and goals than hospitals. Patients want general guidance and convenience, while providers need accurate, actionable information that can be safely integrated into the clinical record, noted Kevin Erdal, senior vice president of transformation and innovation services at Nordic, a health and technology consultancy.
When deploying new large language models, he recommended hospitals watch out for shadow workflows.
“Clinicians may start informally relying on patient-generated summaries or AI-assisted interpretations without clear standards for validation or documentation. If no one validates where patient-reported information came from, or oversees how that information is reviewed, incorporated or rejected, risk quietly accumulates,” Erdal said.
When it comes to Anthropic and OpenAI’s consumer-facing healthcare tools, the biggest risk isn’t misinformation so much as missing context, he remarked.
“Context, intent and reasoning can live in a chat while the clinical record captures only the outcome, weakening care continuity and the trust between patient and provider,” Erdal stated.
This gap in context underscores why consumer-facing chatbots are ill-suited for clinician use.
For hospitals and other providers, Erdal thinks the right response to the rise of consumer-facing healthcare AI is integration.
“It will look like health systems accepting that these tools already exist, and designing responsible ways to absorb their output without fragmenting care. The bar is continuity, and the patient/provider relationship is what’s at stake,” he declared.
If consumer-facing AI models help patients walk into healthcare interactions more informed and better prepared, but then their providers are unprepared to integrate that into the healthcare conversation in a thoughtful or deliberate way, access to healthcare information improves while trust drops off, Erdal explained.
At a deeper level, OpenAI and Anthropic’s healthcare push reflects a broader shift in the healthcare industry.
The question is no longer whether AI will become part of the patient journey — it’s clear that the shift is already underway. The real question is who will control it, who will be accountable for it, and how much influence it will have over decisions that were once firmly in the hands of clinicians.
Experts agree that the companies that adapt — by integrating AI thoughtfully, strengthening trust and clarifying responsibility — may help build a more accessible healthcare system. Those that don’t may find themselves left behind.
Photo: Pakorn Supajitsoontorn, Getty Images
