On 6 January 2026, the US state of Utah crossed a symbolic line: it authorised an AI to renew routine prescriptions for chronic conditions.[2] In May 2026, the French National Ethics Committee (CCNE) organised a colloquium at ENS Paris entitled "What medicine in the AI era?"[4] Both events tell the same story: medical AI is no longer a distant promise. It is here. The real question is: how far will it go?
To be honest: in certain precise domains, AI already surpasses humans. In radiology, in breast cancer screening, Google Health's algorithm reduced false positives by 5.7% (US) and 1.2% (UK) and false negatives by 9.4% and 2.7% compared with radiologists.[1] In dermatology, neural networks match dermatologist performance on melanoma detection from photos. In cardiology, some algorithms predict heart attacks 24 hours in advance from ECGs that appear normal to the human eye.
In 2026, these tools are leaving the experimental phase and entering hospitals to assist caregivers and free up their time with patients.[6]
Artificial intelligence will never replace human diagnosis. Its goal has never been to substitute healthcare professionals, but to work alongside them.[5]
Why? Because medicine is not just about data. A patient coming to a consultation is not a set of symptoms to be optimised. They carry a history, anxieties, a family situation, values. Medical decision-making integrates all of this. AI, however powerful, cannot see the patient trembling, hear their hesitation, sense that they are hiding something.
In 2026, the question is no longer whether AI will transform medicine. It already is. The real question is more nuanced: what can and should a physician truly delegate to AI, and what remains irreducibly human in the act of care?
Here is the figure that should give pause: according to the DREES (France), 25–35% of French physicians' time is devoted to administrative and documentary tasks.[3] Time stolen from patients. Time that fuels physician burnout. Time where nobody wins — neither the doctor nor the patient.
This is precisely where AI can — and should — intervene as a priority. Not to replace diagnosis, but to free physicians from tasks that do not require their human expertise: writing the consultation note, structuring the report, generating the referral letter, coding acts.
What medical AI concretely does in practice in 2026
Automatic consultation documentation · SOAP note generation · Drug interaction alerts · Referral letters · Prescribing assistance for chronic conditions · Detection of warning signals in lab results
In January 2026, Utah authorised an AI to renew routine prescriptions for stable chronic conditions — controlled diabetes, managed hypertension.[2] It is a world first. And it deeply divides the medical community.
The EU AI Act sets the framework for Europe: AI systems that are medical devices, or safety components of medical devices, subject to a notified body are classified as "high risk" (Art. 6(1), Annex I), with obligations — including mandatory human oversight — applying from 2 August 2027. A tool that only structures the physician's dictation is not high-risk in itself. In Italy, Law 132/2025 (Art. 7) adds that the decision always remains with the physician.
No — if they know how to adapt. Yes — if they ignore what is coming. The medicine of tomorrow will not be medicine without doctors. It will be medicine where doctors do more of what drove them to choose this profession — caring for people — and less of what administratively exhausts them.
See also our articles on how to choose your medical AI and on liability in the event of AI-related medical error.
Can AI already make diagnoses?
Yes, in specific and delimited domains. In dermatology, algorithms match dermatologist performance on melanoma detection from photos. In radiology, in breast cancer screening, Google Health's AI reduced false positives by 5.7% and false negatives by 9.4% compared with radiologists (US dataset, McKinney et al., Nature 2020). In cardiology, AI systems predict heart attacks 24 hours in advance from ECGs. But these performances concern very specific tasks on structured data — not the global medical diagnosis of a patient with their comorbidities, history and context.
Which doctors are most threatened by AI?
The most exposed specialties are those where work consists primarily of analysing visual or numerical data: radiology, anatomical pathology, dermatology (imaging). These specialties will not disappear, but their scope will transform — radiologists will increasingly supervise algorithms rather than directly reading each image. Conversely, specialties built on human relationships, touch and contextual decision-making (general practice, psychiatry, geriatrics) are far less exposed.
What do medical AI systems concretely do in practice in 2026?
The most deployed uses in 2026 are: automatic documentation (transcription and structuring of consultations), prescribing assistance (drug interaction alerts), detection of warning signals in biological data, and generation of referral letters.
Can a physician be held liable for following an incorrect AI diagnosis?
Yes. Medical liability remains full regardless of the tool used. A physician who follows an AI diagnosis without exercising critical judgement engages their professional responsibility. Under the EU AI Act, AI systems that are medical devices are classified as 'high risk', with mandatory human oversight (obligations from August 2027); in Italy, Law 132/2025 (Art. 7) leaves the decision to the physician. In practice, AI must be treated as a support tool — like a lab result or imaging — not as a final decision.
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