Healthcare has historically been a service, with costs tied to licensed professionals. AI models like Gemini and ChatGPT are changing this by providing medical advice, effectively turning healthcare into a product. This shift, currently tolerated by regulators, could dramatically lower costs and increase access, just like software products.

When an AI agent errs in a medical or financial context, it is legally unclear who is liable: the AI lab, the deploying company, or the end-user. This novel legal problem, which challenges a century of precedent, creates significant friction and will slow agent adoption in regulated industries.

AI's most significant impact won't be on broad population health management, but as a diagnostic and decision-support assistant for physicians. By analyzing an individual patient's risks and co-morbidities, AI can empower doctors to make better, earlier diagnoses, addressing the core problem of physicians lacking time for deep patient analysis.

To overcome resistance, AI in healthcare must be positioned as a tool that enhances, not replaces, the physician. The system provides a data-driven playbook of treatment options, but the final, nuanced decision rightfully remains with the doctor, fostering trust and adoption.

Reid Hoffman argues AI models are so capable that patients with major medical issues are making a "huge mistake" if they don't use one for a second opinion. He suggests it's becoming "almost malpractice" for doctors not to use these tools to double-check themselves.

A key risk for AI in healthcare is its tendency to present information with unwarranted certainty, like an "overconfident intern who doesn't know what they don't know." To be safe, these systems must display "calibrated uncertainty," show their sources, and have clear accountability frameworks for when they are inevitably wrong.

As AI allows any patient to generate well-reasoned, personalized treatment plans, the medical system will face pressure to evolve beyond rigid standards. This will necessitate reforms around liability, data access, and a patient's "right to try" non-standard treatments that are demonstrably well-researched via AI.

While AI is a powerful tool for accelerating research and diagnostics, it cannot replace the essential human touch in patient care, such as end-of-life discussions. Physicians have a responsibility to get involved and proactively define where AI should be used to ensure technology serves, rather than dictates, patient care.

Society holds AI in healthcare to a much higher standard than human practitioners, similar to the scrutiny faced by driverless cars. We demand AI be 10x better, not just marginally better, which slows adoption. This means AI will first roll out in controlled use cases or as a human-assisting tool, not for full autonomy.