Sector
Health
Health is where both the benefit and the risk are high. Every use needs evidence, oversight and clear limits.
Our predictions
Our view, with how sure we are. Each one links to the evidence it rests on.
What changes
A medicine whose target and molecule were found mainly with AI will be approved for patients by a major regulator.
What changes
AI will support diagnosis and triage in places with too few doctors, always under a clinician's oversight.
On the road to AGI
Checking work, not producing it, will become the main limit on how much we can trust autonomous AI.
Progress around the world
Public results from other teams that shape our view.
· Stanford Institute for Human-Centered AI
AI Index 2026: capabilities jump, but unevenly
Agent success on Terminal-Bench rose from 20% to 77.3% in a year, and agents solved 93% of cybersecurity tasks, yet robots succeeded at only 12% of real household tasks. AI data-centre power capacity reached 29.6 GW, and four in five US students use AI for schoolwork.
What it means for AGI: digital abilities are racing ahead while physical abilities and governance lag.
· Insilico Medicine and collaborators (published in Nature Medicine)
An AI-discovered drug shows results in a randomised phase 2a trial
Rentosertib, a drug whose target and molecule were found with generative AI, was tested in 71 patients with idiopathic pulmonary fibrosis. Safety was similar to placebo, and the highest dose showed a lung-function gain, though the trial was small.
What it means for AGI: AI-designed medicines have reached patient trials. Approval still requires larger trials.
Source: nature.com(opens external site)
· Google Research and Google DeepMind (published in Nature)
Conversational diagnostic AI compared with doctors
In a blinded study of text consultations with patient actors across 159 cases, specialists rated the AI system higher than primary care physicians on most measures. The authors say more research is needed before real-world use.
What it means for AGI: medical reasoning in conversation is strong in studies; real clinical evidence is the next test.
Source: nature.com(opens external site)
· Google researchers (arXiv)
Co-Scientist: a multi-agent system that proposes research hypotheses
Specialised agents generate, critique and rank hypotheses in a tournament. Drug-repurposing candidates it proposed for acute myeloid leukaemia were validated in lab (in vitro) experiments.
What it means for AGI: a team of agents, not a single model, did useful scientific work that was checked in a real lab.
Source: arxiv.org(opens external site)
· Google Research (published in Nature)
Language models encode clinical knowledge
A medical language model reached passing-level scores on US medical licensing style questions, while the authors stressed it was not ready for clinical use.
What it means for AGI: passing exams is not the same as being safe in practice. Evaluation has to follow real use.
Source: nature.com(opens external site)
· Google DeepMind (published in Nature)
AlphaFold predicts protein structures at near-experimental accuracy
A deep-learning system predicted the 3D shape of proteins with accuracy close to lab experiments, solving a problem biology had worked on for about 50 years.
What it means for AGI: AI can make real scientific progress in a narrow field. The open question is whether the same can happen across many fields at once.
Source: nature.com(opens external site)
· World Health Organization
WHO guidance on ethics and governance of AI for health
The WHO set out principles for AI in health, including protecting human autonomy, transparency and accountability.
What it means for AGI: rules for AI in high-stakes fields are arriving alongside the technology, and any general system must work within them.
Source: who.int(opens external site)
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