Every entry here reached a human, was measured against something, and names the date it happened — not the date it was published.
A registry of measured AI benefits to people. Each sentence below is graded on the evidence behind it, on how much of the result the AI can claim, and on whether the benefit happened inside the last twelve months. We also keep what did not work and what is not yet proven.
16 because · 3 not because · 4 not yet
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Because of AI, the Hurricane Center called a Category 5 landfall in Jamaica about three days out, while Melissa was still a Category 1.
~3 days' warning on a Cat 5AchievedOct 25–28, 2025PublishedEffectLowest season track and intensity error of any model; roughly one extra day of forecast accuracy in 2023–2025 hindcasts
NHC forecasters explicitly forecast Category 5 intensity while Melissa was an 80-mph Category 1, largely on the strength of Google DeepMind's cyclone model, which posted the lowest track and intensity errors of any model for the 2025 Atlantic season and kept the official forecast below its five-year average error while NOAA's GFS had its worst year in two decades.
There is no lives-saved number and cannot be; the measured outcome is forecast skill, and the final call was made by human forecasters using the model.
Primary source: NWS: AI hurricane forecasting Q&A (2025 season) (weather.gov)UpdatedBecause of AI, there were an estimated 841 fewer injury-causing crashes across 270 million driverless miles.
82% fewer injury crashesAchievedJan 2019 – Jun 30, 2026PublishedEffect82% fewer injury crashes; 95% fewer serious-or-worse (0.67 injury crashes per million miles vs ~3.77 benchmark; 841 fewer injury crashes lifetime)
Waymo's safety hub through June 2026 reports 82% fewer injury-causing crashes and 95% fewer serious-or-worse crashes than a geographically matched human benchmark, with roughly 134 of the 841 avoided injury crashes accruing in Q2 2026 alone (841 minus the 707 reported through March 2026).
Company-produced, modeled comparison against an estimated human benchmark with an adjustment for roughly 32% underreporting of human injury crashes; not a randomized comparison of identical trips.
Primary source: Waymo Safety Impact hub (waymo.com)UpdatedBecause of AI, a baby girl was born to a couple who had been told there was no sperm to work with.
2 sperm found in 2.5M imagesAchievedMar–Dec 2025PublishedEffect~40x more sperm recovered than manual search across cases reported by the team (1 live birth; sperm found in ~30% of azoospermia patients tested)
Columbia's STAR system scanned 2.5 million images of a 3.5 mL sample in about two hours and found viable sperm where manual microscopy found none; the resulting pregnancy was confirmed in 2025, published in The Lancet in October 2025, and a healthy daughter was born in late 2025.
One case; STAR finds sperm in just under 30% of men diagnosed with azoospermia, and larger trials are still underway.
Primary source: Columbia / The Lancet: First clinical pregnancy following AI-based microfluidic sperm detection (press release) (eurekalert.org)UpdatedBecause of AI, 1,660 TB cases were found in Ethiopia between January 2025 and March 2026 in screening programs that had no radiologist to read the X-rays.
1,660 TB cases foundAchievedJan 2025 – Mar 2026PublishedEffectCommunity AI screening yield >5% vs <0.1% routine clinical screening (program figures) (1,660 cases, Jan 2025–Mar 2026)
AI-read chest X-rays (CAD) served as the triage reader in MSH's Eliminate TB Project across four regions, contributing to 1,660 detected cases including asymptomatic infectious cases that symptom screening misses.
Program report, not a controlled comparison; "contributed to" means the AI flagged people for confirmatory testing, so the counterfactual is how many would have been found by symptom screening alone.
Primary source: MSH technical brief: AI-powered chest X-ray screening for TB case finding, Ethiopia (msh.org)UpdatedBecause of AI, TB case notifications rose 80% in a tribal district of Chhattisgarh, India, including 20 confirmed cases in people with no symptoms.
+80% TB notificationsAchievedFrom Apr 2023, end not yet verifiedPublishedpublished 2 yr 9 mo after the benefit beganEffect+80.21% notifications (p<.001) (162 confirmed cases; 44.6% positivity among AI-flagged)
A prospective multi-centre study of qXR v3 chest X-ray reading found an 80.21% increase in TB notifications versus the Aug 2022–Mar 2023 baseline; of 51 asymptomatic people the AI flagged, 20 were confirmed to have TB, and over 40% of all AI-flagged patients were confirmed.
Before-and-after design in a high-burden setting; national notifications were also rising from other case-finding efforts.
Primary source: Evaluating AI-based chest X-ray screening for TB in tribal Chhattisgarh (PMC) (ncbi.nlm.nih.gov)UpdatedBecause of AI, about a third of urgent skin-cancer referrals at some NHS hospitals got a same-day all-clear without waiting weeks for a dermatologist.
25,000+ cancers found; ~1/3 discharged same dayAchievedOngoing since Jan 2022Publishedpublished 4 yr 9 mo after the benefit beganEffectDischarge-without-appointment rate 26% with dermatologist second read → 37% autonomous (one hospital) (250,000+ assessed; 25,000+ cancers confirmed)
Skin Analytics' DERM, the only AI with Class III CE certification for autonomous use, has assessed 250,000+ NHS patients, identified 25,000+ histology-confirmed cancers, and is expanding to all 18 NHS South East trusts (about 9 million more people) from autumn 2026.
Operational data from the vendor and trusts; at one district hospital the autonomous pathway discharged 37% of referrals and missed one basal cell carcinoma.
Primary source: NICE early value assessment of DERM (May 2025) (healthtechdigital.com)UpdatedBecause of AI-assisted decision support, 10 fewer stroke patients per 1,000 had another stroke, heart attack, or vascular death within three months.
26% fewer vascular eventsAchievedJan 2021 – Jun 2023Publishedpublished 2 yr 9 mo after the benefit endedEffect26% relative reduction (HR 0.71) (3.9% → 2.9%: 10 fewer events per 1,000 patients)
GOLDEN BRIDGE II (BMJ, March 2026) cluster-randomized 77 Chinese hospitals and 21,603 acute ischemic stroke patients; new vascular events at three months were 2.9% with the AI-imaging decision-support system vs 3.9% with usual care (adjusted HR 0.71), with the benefit holding through 12 months.
Hospitals, not patients, were randomized, and the intervention bundled AI image analysis with guideline-based treatment prompts, so the AI's isolated contribution isn't separable; enrollment ran January 2021 to June 2023.
Primary source: BMJ 2026;392:e085810 (press release with trial figures) (eurekalert.org)UpdatedBecause of AI (plus tablets and pair work), junior secondary students in Sierra Leone gained about 0.26 standard deviations in math in eight weeks.
+0.26 SD in 8 weeksAchievedOct–Dec 2025PublishedEffect+0.258 SD (described as ~1.2–1.7 years of typical progress)
A preregistered classroom-level cluster RCT of 1,763 Grade 7–8 students in 48 classrooms across 12 Port Loko schools had treatment classes use Gemini's Guided Learning in pairs for about two of four weekly math lessons; the treatment group gained +0.258 SD on independently administered tests.
The control arm got neither tablets nor structured pair work, so the package was tested, not the AI; results are a Google DeepMind/Fab AI technical report, not a peer-reviewed paper.
Primary source: Google DeepMind & Fab AI technical report (May 2026) (storage.googleapis.com)UpdatedBecause of AI, Swedish mammography screening found 29% more cancers with 44% less radiologist reading time, and 12% fewer cancers surfaced between screens.
29% more cancers, 44% less workloadAchievedApr 2021 – Dec 2022Publishedpublished 3 yr 1 mo after the benefit endedEffect12% fewer interval cancers (n.s.); 29% more screen-detected cancers; 44% workload reduction (1.55 vs 1.76 interval cancers per 1,000 (0.21 per 1,000 difference))
MASAI, the first RCT of AI in cancer screening (105,934 women; Lancet, Jan 2026), reported interval cancers of 1.55 vs 1.76 per 1,000 with AI-supported reading vs standard double reading, with fewer invasive, T2+, and non-luminal-A interval cancers, on top of earlier results showing higher detection and lower workload at the same specificity.
The trial was designed for non-inferiority; the 12% interval-cancer reduction was not statistically significant (ratio 0.88, 95% CI 0.65–1.18, p=0.41), mortality wasn't measured, and screening took place in 2021–2022.
Primary source: Lancet 2026;407:505-514 (ScienceDirect) (sciencedirect.com)UpdatedBecause of AI, a man with ALS has spoken with his family and kept working from home for two years through a brain implant, at up to 99% word accuracy.
2 years of independent speechAchievedOngoing since Jul 2023Publishedpublished 2 yr 11 mo after the benefit beganEffectUp to 99% word accuracy; ~2 years independent home use
UC Davis's intracortical BCI uses deep-learning brain-to-text and cursor decoders with continuous fine-tuning; Nature Medicine (June 2026) documented Casey Harrell's near-daily unassisted use at home for roughly two years.
One participant, an experimental device implanted in 2023, not commercially available; some BCIs in other ALS patients have later stopped working.
Primary source: Nature Medicine: Long-term independent use of an intracortical BCI for speech and cursor control (nature.com)UpdatedBecause of AI, stroke patients in England were 57% more likely to get a thrombectomy and reached specialist centres 64 minutes faster.
EVT odds 1.57x; 64 min faster transferAchieved2019 – 2024Publishedpublished 1 yr after the benefit endedEffectOR 1.57 for thrombectomy; OR 1.16 for good outcome (Good outcome 47.1% vs 45.6% (15 more per 1,000); DIDO 64 min shorter)
Across ~453,000 stroke admissions at 107 English hospitals over five years, patients whose imaging was reviewed with Brainomix 360 had higher thrombectomy odds (OR 1.57), median door-in-door-out of 128 vs 192 minutes, and a good outcome (mRS 0–2) at discharge of 47.1% vs 45.6% (OR 1.16).
Observational, not randomized; long-term outcomes couldn't be evaluated and reasons for non-use of the AI in some cases weren't captured.
Primary source: Lancet Digital Health: AI imaging decision support for acute stroke in England (thelancet.com)UpdatedBecause of AI, 30 hearing-aid users understood far more words in heavy noise — according to the company that makes the device.
31% → 80% words understood (company trial)AchievedFrom Nov 2025, end not yet verifiedPublishedEffect9.2 dB vs 3.1 dB SNR improvement; ~19x odds of correct word recognition (company figures) (Company-reported: 69%→90%, 31%→80%, 7%→50% words correct across noise levels)
Fortell's neural source-separation hearing aid (launched Dec 2025) reports a pre-registered double-blind 30-person trial against Phonak's Audéo Infinio Sphere showing a 9.2 dB vs 3.1 dB signal-to-noise improvement on QuickSIN, alongside a 20-person blinded preference study published in the International Journal of Audiology (May 2026).
Both studies are Fortell-funded with a Fortell employee as first author, the control device also uses neural-network noise reduction, and the 30-person intelligibility trial was posted on the company's site rather than confirmed in a journal as of October 2026.
Primary source: IJA: Spatial AI consistently preferred to state-of-the-art hearing aids in multitalker noise (tandfonline.com)UpdatedBecause of AI, Northumbrian Water stopped losing about 6.4 million litres of drinking water a day.
~6.4 ML/day savedAchievedNov 2025 – May 2026PublishedEffect~6.4 ML/day (~25,000 bathtubs)
A six-month trial starting November 2025 placed FIDO Tech acoustic sensors on pipes, with AI classifying which underground sounds are leaks and directing crews; the utility reported early results of nearly 6.4 megalitres per day saved.
Operational report, no controlled comparison, and the saving is attributable to the detect-and-repair package; FIDO had already delivered a 37% leakage reduction across 15 target DMAs at the same utility in 2022–23.
Primary source: Northumbrian Water: AI technology helps to hunt down leaks (nwg.co.uk)UpdatedBecause of AI, Oman screened 43,000 diabetics for retinopathy, flagged 12,000 for treatment, and cut specialist waiting lists by 87%.
Waitlists cut 87%AchievedBy Aug 2026, start not yet verifiedPublishedEffect−87% waiting list; −43.2% operating cost (43,000+ screened; 12,000+ referred)
Oman's national AI diabetic-retinopathy screening program reported 43,000+ patients screened, ~30% referred for specialist examination, an 87% reduction in eye-clinic waiting lists, and 43.2% lower annual operating costs.
Ministry-reported program figures with no comparison group; vision outcomes (sight saved) are not yet measured.
Primary source: Muscat Daily: Oman turns to AI to tackle diabetes-related blindness (muscatdaily.com)UpdatedBecause of AI, physicians using ambient scribes reported modestly less burnout, exhaustion, and task load in a 238-physician randomized trial.
Modest burnout reduction (RCT)AchievedNov 4, 2024 – Jan 3, 2025PublishedEffectModest improvements on burnout, exhaustion, task load (see paper for effect sizes)
NEJM AI (Dec 2025) randomized 238 outpatient physicians across 14 specialties to Microsoft DAX, Nabla, or usual care for two months; either scribe improved burnout, exhaustion, and task load, and Nabla reduced time-in-note.
Effects were modest, only one vendor saved documentation time, occasional note inaccuracies required vigilance, and the trial ran Nov 2024–Jan 2025.
Primary source: NEJM AI: Ambient AI Scribes in Clinical Practice — A Randomized Trial (PMC) (pmc.ncbi.nlm.nih.gov)UpdatedBecause of AI, 284 UCLA clinicians reported modestly lower task load and burnout from a chart summarizer — while saving no time and mostly not recommending it.
Lower task load, zero time savedAchievedFeb–May 2026PublishedEffectModest task-load reduction (primary endpoint met)
A pragmatic RCT (Feb–May 2026) of Epic's generative chart summarization tool among 284 ambulatory clinicians found modestly reduced physician task load and lower burnout, no time savings, declining engagement, and a net promoter score of −22.
Preprint (medRxiv, Aug 2026), self-reported outcomes, three-month window, one health system.
Primary source: medRxiv: A pragmatic randomized trial of an EHR-integrated generative AI chart summarization tool (medrxiv.org)Updated