Rather than building its own clinical services, ŌURA focuses on being a "health companion and intelligence layer." It partners with care providers like MIDI and Maven, empowering them with rich, continuous data. This strategy allows ŌURA to focus on its core competency while integrating into the broader healthcare ecosystem.

The most significant opportunity for AI in healthcare lies not in optimizing existing software, but in automating 'net new' areas that once required human judgment. Functions like patient engagement, scheduling, and symptom triage are seeing explosive growth as AI steps into roles previously held only by staff.

The widespread use of AI for health queries is set to change doctor visits. Patients will increasingly arrive with AI-generated analyses of their lab results and symptoms, turning appointments into a three-way consultation between the patient, the doctor, and the AI's findings, potentially improving diagnostic efficiency.

OpenAI's launch of ChatGPT Health, which integrates medical records, signals a clear strategy to move beyond general-purpose APIs. Foundation model companies are now building specialized, vertical-specific products, posing a direct threat to "wrapper" startups that rely on the underlying models' existing capabilities.

Singhal says medical care bundles diagnosis, physical exams, empathy, and legal liability that AI cannot fully provide. Even with pre-visit research, the human visit remains necessary for history-taking, physical interaction, comfort, and a second check. That limits AI's role to support rather than replace care.

Chronic disease patients face a cascade of interconnected problems: pre-authorizations, pharmacy stockouts, and incomprehensible insurance rules. AI's potential lies in acting as an intelligent agent to navigate this complex, fragmented system on behalf of the patient, reducing waste and improving outcomes.

OpenAI is tackling healthcare from three distinct angles: consumers (queries), clinicians (research), and hospital enterprises (integrations). The vision is not just to serve these groups independently but to build a unified platform where synergies emerge, enabling seamless information sharing and solving systemic bottlenecks.

The creation of ChatGPT Health was not a proactive pivot but a direct response to massive, organic user behavior. OpenAI discovered that 1 in 4 weekly active users—over 200 million people globally—were already using the general purpose tool for health queries, validating the immense market demand before a single line of dedicated code was written.

Karan Singhal says OpenAI adds specialized healthcare data to every training phase for ChatGPT, rather than forking a smaller medical-only model. A separate model would fall behind the frontier too quickly, so OpenAI hitches health expertise to scale and general reasoning improvements. That is the best-of-both-worlds approach he describes.