Microsoft Seeks Grip on Medical Decisions With AI

Microsoft’s MAI-DxO system correctly diagnosed complex medical cases 83% of the time in a simulation, more than twice the 36% rate for primary care doctors and general internists working individually with reference materials. The comparison excluded specialists and physician teams, who usually handle cases of that complexity. That gap matters: Microsoft is pitching its corporate system against a limited slice of human medical work as it prepares to move the product into hospitals.

Who Gets Counted as the Competition

Published Thursday in Science, the study drew cases from the New England Journal of Medicine. MAI-DxO, also called DxO, coordinates several AI agents that question patients, order tests and debate diagnoses. Microsoft tested it with models from OpenAI, Google, Anthropic, Meta and DeepSeek; OpenAI’s GPT-5 and GPT-5.5 delivered its best results.

The study data showed that more powerful underlying models accounted for much of the improvement, while Microsoft’s orchestration system added gains. DxO helped most on complex cases and with less capable models, but the gap between weaker and stronger models exceeded DxO’s boost. Microsoft researchers said accuracy gains naturally shrink as models approach the theoretical maximum.

The headline number isn’t a verdict on doctors. With a short, basic prompt, GPT-5 scored 78.9% on complex cases at an estimated cost of about $8,400 per case. DxO cut that cost by about $3,000 and raised accuracy by about four percentage points. On emergency department cases, GPT-5 with and without DxO showed little improvement in accuracy or cost.

Released in April 2026, GPT-5.5 scored 72% on complex cases on its own; with DxO, its accuracy rose to nearly 87% at a slightly lower cost. Both versions scored about 85% on emergency department cases at similar cost. Gemini 2.5 Flash scored 46.4% on its own and nearly 69% with DxO.

From Simulation to Hospital

Microsoft plans to evaluate DxO’s clinical reasoning across hospital settings through a new partnership with Beth Israel Deaconess Medical Center in Boston. Patients will receive standard treatment, including triage, time with a specialist, treatments, investigations and a decision on whether it’s safe to discharge. Patients who consent will also engage with DxO. Microsoft and its partners will compare its recommendations with those of human doctors.

Dominic King, vice president of Health at Microsoft AI, said the technology is ready for real-world evaluations and that the study would include emergency and urgent-care settings. He said the study would provide evidence by its end about whether the systems could be deployed at greater scale. Google published a clinical study with Beth Israel in The Lancet this month to evaluate its AMIE conversational diagnostic AI during real-world urgent-care visits, with human physicians monitoring interactions in real time.

Microsoft already sells dictation and radiology tools to clinicians, and sees DxO as an expansion of those products. The company is also working with the Mayo Clinic to train a healthcare foundation model, with release planned for next year. Its manifesto defines medical superintelligence as “the capacity to surpass the strongest contemporary human-led health systems in medical reasoning and coordination across the full arc of care.”

The Sales Pitch

Mustafa Suleyman, Microsoft AI’s CEO, called the result a step toward “medical superintelligence.” He said the company wants to move beyond benchmarking tasks such as answering medical exam questions and generating diagnoses, and integrate AI with clinicians and healthcare systems to improve outcomes.

Suleyman said generative AI’s use in healthcare was still at an early stage and predicted healthcare models would become “an order of magnitude better in capability within the next 24 to 36 months.” He also said, “I really believe that in 2027, we will be on the verge of a coding style breakthrough for medical records,” describing predictions about how a medical record might unfold as useful to clinicians.

The pitch comes with a commercial target. “We have to have the absolute number one state-of-the-art medical clinical decision support products over the next few years,” Suleyman said. King called the mismatch between demand and supply of medical expertise healthcare’s biggest challenge. Suleyman put the ambition plainly: “This is the kind of technology that everybody in the world wants, and that’s why we’re committed to doing everything we can to accelerate its introduction to the world.”