A cluster-randomized controlled trial of a large-language-model assistant in Kenyan primary care, published in Nature Medicine, is the most demanding evidence yet gathered on whether AI help for clinicians reaches patients — and it found that it did not. Across 16 clinics run by the operator Penda Health in Nairobi and Kiambu counties, 103 clinical officers were randomly assigned to an electronic medical record with or without 'AI Consult', a tool that read what they typed and flagged concerns green, yellow or red. Some 9,691 patients were enrolled between April and July 2025. The trial's primary measure was treatment failure within 14 days — a patient returning with unresolved symptoms, needing escalated care, or suffering a related adverse event. It occurred in 102 of 4,693 patients (2.2 percent) where the AI was switched on and 94 of 4,654 (2.0 percent) where it was off: an adjusted odds ratio of 0.77, with a confidence interval from 0.55 to 1.08 that comfortably spans no effect. What did move was the quality of the clinician's work. A blinded panel of six Kenyan family physicians reviewing 2,000 encounters found the assisted clinicians markedly more likely to record an appropriate diagnosis, a comprehensive note and an appropriate treatment plan — odds ratios near 1.7 on all three, each significant beyond the 0.001 level. Yet none of the trial's specific clinical targets shifted: antibiotic and antimalarial prescribing, hypertension diagnosis and treatment, child malnutrition referral all showed no difference, and the one statistically significant result ran the other way, with patients in the AI arm slightly less likely to be flagged as at risk of type 2 diabetes. The result cannot rule out a small benefit — the trial was built to detect a halving of treatment failure and saw nothing of that size — but it rules out a large one, and the authors put a price on settling the question: detecting a modest difference in outcomes this rare would take more than 100,000 patients, and they chose not to continue. Running the model cost about four U.S. cents per consultation. Its evidence level is as high as deployment evidence gets: registered with the Pan-African Clinical Trials Registry before it began, with its protocol and analysis plan deposited publicly a year before the results, reported against the CONSORT-AI standard, and overseen by an independent safety board. The qualification is that the tool was built by the same company whose clinics hosted the trial, and the trial's own paperwork discloses what a summary would not — 921 protocol deviations, among them a temporary configuration error that briefly exposed some control-arm clinicians to the AI. The University of Birmingham, whose researchers led the work, announced it under the headline 'AI clinical support tool improved clinician decisions in real-world primary care trial', disclosing the null patient result in the subheading beneath; the specific prescribing and diagnosis findings, including the diabetes result favouring the control group, appear only in the paper.