OpenAI and Anthropic Take Different Paths to Own Healthcare’s AI Stack

The artificial intelligence (AI) race has moved from the laboratory to the clinic, marking a pivotal shift in how the digital economy’s most valuable data — health information — is processed.

As OpenAI and Anthropic formalize their healthcare and life sciences divisions, they are doing more than just selling software; they are auditioning to become the foundational “operating system” for a multitrillion-dollar industry. While their goals are identical — capturing clinical workflows and research cycles — their strategies reveal a fundamental divergence over how a risk-averse sector will ultimately adopt generative AI.

OpenAI: Healthcare at Scale

OpenAI is approaching healthcare as an extension of its broader platform strategy. Its recently announced OpenAI for Healthcare initiative is framed as an enterprise AI stack designed to slot into existing health system workflows, helping organizations automate documentation, reduce administrative burden, and standardize care delivery while meeting HIPAA requirements.

Rather than offering a single healthcare product, OpenAI is emphasizing APIs, business associate agreements, and integrations that allow hospitals, insurers and software vendors to embed its models into clinical decision support tools, chart summarization, care coordination and analytics. The company has highlighted physician-led benchmarking efforts such as HealthBench to demonstrate that its models can meet clinical expectations for reliability and alignment.

At the same time, OpenAI is leveraging a consumer channel that few competitors can match. ChatGPT is already used at massive scale for health-related questions, from interpreting lab results to understanding symptoms and insurance options. That usage is now being formalized through ChatGPT Health, which allows users to securely connect personal health data so responses can be grounded in individual context.

On Monday (Jan. 12) OpenAI announced in a post on X that it acquired healthcare startup Torch, which unifies lab results, medications and visit recordings, and will combine it with ChatGPT Health. In its own blog post about the acquisition, Torch that by bringing together health information that is otherwise scattered, it builds “a medical memory for AI” that helps patients see the whole picture. OpenAI said in its post: “Bringing this together with ChatGPT Health opens up a new way to understand and manage your health.”

OpenAI is careful to position the consumer experience delivered by ChatGPT Health as informational rather than diagnostic, and it is not regulated under HIPAA. Still, the company has acknowledged that healthcare is already one of ChatGPT’s largest use cases, with tens of millions of health-related queries flowing through the system daily, as reported by PYMNTS. That demand effectively serves as a top-of-funnel for enterprise adoption, familiarizing patients and clinicians alike with AI as a default interface for medical information.

Anthropic: Bet on Specialization

Anthropic is taking a more targeted approach. Instead of extending a mass-market assistant into healthcare, it is building healthcare and life sciences offerings on top of the Claude model family, with an emphasis on tightly controlled, domain-specific deployments.

The company’s Claude for Healthcare product is designed for clinicians, insurers and healthcare administrators, with HIPAA-ready infrastructure and direct integrations into authoritative datasets such as ICD-10 coding systems, CMS coverage data, the National Provider Identifier Registry, and PubMed. These connectors enable concrete workflows like prior authorization, report generation, and medical coding interpretation, rather than broad conversational use.

Anthropic is also pushing deeper into life sciences. Through Claude for Life Sciences, the company is positioning its models as research partners embedded in scientific environments, connected to platforms like PubMed, Benchling and ClinicalTrials.gov. The focus is on tasks such as literature synthesis, hypothesis generation, clinical trial planning, and regulatory documentation, placing Claude closer to the core of biomedical research rather than at the patient-facing edge.

A central theme in Anthropic’s messaging is control. The company emphasizes that data accessed through healthcare and research integrations is not used to train its models, and it highlights customizable agent skills, including FHIR-based tool building, that allow organizations to define how Claude operates within strict boundaries. This reflects a view of healthcare as a market where trust, auditability and predictability matter more than rapid experimentation.

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