Artificial intelligence is no longer approaching medicine. It is already embedded inside it. It drafts our notes. It summarizes research. It suggests differentials. It triages messages. It promises efficiency, scale, and relief from burnout. Physicians are adopting it quickly. That speed should give us pause.
The greatest threat facing physicians in 2026 is not resisting artificial intelligence. It is allowing artificial intelligence in health care to be designed without us. Every major structural shift in modern health care has reshaped physician authority. Hospital consolidation. Insurance intermediation. Pharmaceutical marketing expansion. Private equity optimization. Wall Street financialization. Each layer introduced efficiencies. Each layer also redistributed power. Physicians and patients increasingly became units inside larger revenue architectures.
If physicians do not design AI in medicine, they will practice inside systems designed by others, and history will repeat itself.
The accountability test
The conversation about AI in health care is often dominated by performance metrics. Accuracy rates. Model size. Speed benchmarks. Funding announcements. Those are secondary questions. The primary question is far more uncomfortable: Can I defend this system in a malpractice deposition?
When something goes wrong, the algorithm will not sit beside you in court. The responsibility will rest with the physician. Trust in medicine is not emotional. It is structural. It is operational. It is legal. It is ethical. It is reputational. And it is slow to earn and fast to lose. That is why governance must precede adoption. We must ask ourselves: What makes this AI system trustworthy for me to adopt in my practice of medicine?
Five structural characteristics of trustworthy AI
After building and deploying AI in live clinical environments, I have come to believe that trustworthy AI systems share several non-negotiable characteristics. These are not marketing features. They are structural safeguards.
1. AI must augment clinical judgment, not impersonate it. Some AI tools present conclusions with polished authority. They rank diagnoses. They generate confident recommendations. They communicate as if they possess clinical agency. They do not.
In medicine, responsibility never transfers to software. Liability does not transfer. Ethical accountability does not transfer. Professional duty does not transfer. Any system that subtly shifts decision ownership away from the clinician is not reducing risk. It is redistributing it invisibly. Trustworthy AI functions as structured decision support. It clarifies patterns. It surfaces risk. It organizes information. It never replaces judgment.
2. AI must define explicit data boundaries. Physicians generate extraordinarily valuable intellectual capital every day. Clinical reasoning. Documentation. Protocol refinement. Pattern recognition developed over decades. Too many AI vendors cannot clearly answer basic questions. What was this trained on? Will my inputs be reused? Who owns the outputs? Where is the data stored? What happens if I leave the platform?
Ambiguity in these areas is not technical complexity. It is governance failure. Transparency is not a marketing slide. It is a contractual and ethical requirement.
3. AI must be narrow enough to be reliable. The market is saturated with platforms promising to manage documentation, triage, messaging, analytics, research, and business operations simultaneously. In complex systems, breadth often conceals fragility. Clinical medicine demands reliability. Reliability improves when tools are modular, purpose-built, and tightly scoped. Narrow systems can be audited, tested, stress-tested, and replaced if necessary. Sprawling monoliths embedded everywhere become systemic vulnerabilities.
Medicine respects specialization. AI infrastructure should as well.
4. AI must be explainable and auditable. Physicians are trained to demand reasoning. We expect differentials. We expect citations. We expect reference ranges. We expect documentation of the thought process. Yet some clinicians are integrating black-box outputs into patient care without interrogation. If a system cannot expose its logic pathways, triggers, and escalation thresholds, it cannot be responsibly integrated into clinical workflows.
Trustworthy AI allows inspection, override, and audit. It does not require blind acceptance.
5. AI must create leverage, not just speed. Speed is seductive. But speed alone does not improve medicine. Many tools accelerate documentation without improving diagnostic quality. They reduce keystrokes but not cognitive load. The real question is leverage. Does the system reduce blind spots? Does it improve protocol adherence? Does it expand safe access? Does it reduce meaningful cognitive friction?
Acceleration without leverage fuels burnout. Leverage with clarity strengthens practice.
The deeper issue: governance over hype
Trustworthy AI is not primarily a model problem. It is a governance problem. It requires:
- defined clinical scope
- explicit accountability boundaries
- embedded compliance architecture
- escalation pathways
- continuous audit
- physician oversight by design, not as an afterthought
In short, our profession must shape the technology, not the other way around. We have already experienced what happens when business architecture outruns clinical stewardship. Hospitals consolidated. Insurance intermediated. Pharma marketed. Private equity optimized. Wall Street financialized. Physicians and patients became components inside larger financial systems. We should be careful not to repeat that pattern as artificial intelligence becomes the next structural layer of care delivery. Big tech, technology firms, and venture capital are rapidly building AI systems for health care. Some are thoughtful. Some are not. None carry the bedside liability and clinical knowledge and decision-making that physicians do.
If we remain passive consumers, we will practice inside systems built around someone else’s priorities.
The choice before us
Artificial intelligence should not replace physicians. But physicians who surrender design responsibility will find themselves practicing inside systems that were never built to protect their judgment. When designed responsibly, AI does not diminish physicians. It multiplies capacity. It allows clinical reasoning to extend across broader populations without diluting oversight. That is leverage with integrity. But that outcome is not automatic. It is the result of intentional physician leadership in architecture, governance, and implementation.
The future of medicine will include artificial intelligence. That is not in question.
The real question is whether physicians will be architects of that future or downstream users of systems designed without them. Trust will not be built on enthusiasm or venture funding. It will be built through deliberate architecture, disciplined governance, and unwavering accountability.
If physicians do not design AI in medicine, they will practice inside someone else’s priorities.
Now is the moment to lead.
Tod Stillson is a board-certified family physician, medical device inventor, and health care entrepreneur focused on redesigning how care is delivered in the digital age. He is the founder and CEO of ChatRx, a national asynchronous telemedicine company providing safe, efficient, direct-to-consumer care for common acute conditions. Through ChatRx, Dr. Stillson developed an FDA-listed software medical device that combines structured clinical pathways with AI-supported decision tools to preserve physician judgment while reducing friction for patients.
Dr. Stillson holds an academic affiliation with the Indiana University School of Medicine and a hospital affiliation with McPherson Center for Health. After nearly three decades practicing rural family medicine, he shifted from traditional employment to building physician-led digital systems that expand access, efficiency, and professional autonomy.
He is the author of Doctor Incorporated: Stop the Insanity of Traditional Employment and Preserve Your Professional Autonomy and has published more than 400 essays on physician entrepreneurship, micro-business, digital health, and the future of medical practice. He contributes nationally to conversations on AI-enabled care delivery and physician leadership in digital transformation.
Dr. Stillson shares ongoing insights on LinkedIn, Facebook, Instagram, and YouTube.
