Google AMIE medical AI reaches expert-level consultations

AMIE (Video) is a Gemini-based multi-agent system built to fuse three things that used to live in separate pipelines: low-latency dialogue, clinical reasoning, and real-time audio-visual perception, all inside a single conversational loop ^[1]. That's the technical leap behind the headline number - rather than parsing a typed symptom list, the system has to notice a cough, register a wince, or watch how a patient moves while simultaneously carrying a natural spoken conversation and reasoning toward a diagnosis in real time. It extends Google's original text-only AMIE, and its later single-image multimodal version, into a modality that behaves like an actual telehealth visit instead of a chat window with a camera bolted on.

The headline result comes from a randomized, OSCE-style (Objective Structured Clinical Examination) trial: 30 primary care physicians and 15 patient actors worked through 100 clinical scenarios, with AMIE (Video), AMIE (Text), and human PCPs each consulting via video, and evaluators scored AMIE (Video) on par with or better than PCPs on history-taking, diagnosis, management, and physical observation ^[2]. A related evaluation using the same format found AMIE matched or beat physicians on 29 of 32 clinical metrics and 7 of 9 multimodal-specific criteria ^[2]. Underneath that score sits a new training method: a companion approach called ResidencyRL trains AMIE-derived agents across 57,453 simulated clinical scenarios - telehealth cases, history-taking drills, and deliberately adversarial edge cases - rather than grading a fixed model against a static benchmark, and reports diagnostic accuracy in adversarial settings rising from 81.0% to 88.0%, with clinicians preferring the RL-trained agent in 87.6% of blinded comparisons ^[3]. Google's own paper authors are careful not to oversell the actor-based setup, noting that an OSCE evaluation using patient actors 'substantially under-represents the complexity of real-world care' ^[4], and a companion study on AMIE's disease-management skills goes further, stating plainly that 'the system remains experimental and untested in real clinical care' ^[5].

This is not a single breakthrough - it's the fourth rung on a ladder Google has been climbing since January 2024, when the original AMIE paper showed the system outperforming physicians in text-chat-only OSCE simulations across 149 scenarios in Canada, the UK, and India ^[6]. By May 2025, AMIE had gained multimodal vision - reading X-rays, skin images, and ECGs using Gemini 2.0 Flash - and was matching or outperforming PCPs in a 105-scenario study ^[7]. In June 2026, Google pushed AMIE from single-visit diagnosis into longitudinal disease management, matching or beating 21 board-certified PCPs across 100 simulated multi-visit scenarios in a Nature-published study ^[8]. The real-time video consultation result announced this month is the natural next step: text, then sight, then ongoing care, then a live conversation that looks like an actual doctor's visit.

Even in a study designed to flatter the system, AMIE (Video) didn't win everywhere. Patients still preferred physicians for rapport and partnership-building, and the researchers acknowledge gaps in 'fine anatomical precision, subtle affective nuances, and high-frequency movements' during physical exams ^[1]. That's likely why Google isn't waiting for a perfect video-consultation score before testing the technology on real patients: it's running a separate, prospective, consented, nationwide randomized controlled trial of AMIE-style AI in real-world virtual care with Included Health ^[9], building on earlier work with Beth Israel Deaconess Medical Center testing an AMIE-related 'AI co-clinician' that matched or exceeded PCP performance in 68 of 140 assessed areas - always under physician oversight, with a human safety supervisor tracking interruptions during AI-led encounters rather than letting the system operate autonomously ^[10]. Google researcher Vivek Natarajan frames the ambition as complementary rather than a replacement: 'There may be scenarios when people might benefit from interacting with systems like AMIE as part or in addition to their clinical journeys' ^[11]. Dartmouth medical educator Thomas Thesen, an outside voice, expects something similar over the next decade - AI streamlining physician work - but insists 'the expert judgment of a trained doctor will remain crucial for final diagnosis and treatment plans' ^[11].