BETTER DIAGNOSES. Personalised support for patients. Faster drug discovery. Greater efficiency. Artificial intelligence (AI) is generating excitement and hyperbole everywhere, but in the field of health care it has the potential to be transformational. In Europe analysts predict that deploying AI could save hundreds of thousands of lives each year; in America, they say, it could also save money, shaving $200bn-360bn from overall annual medical spending, now $4.5trn a year (or 17% of GDP). From smart stethoscopes and robot surgeons to the analysis of large data sets or the ability to chat to a medical AI with a human face, opportunities abound.

There is already evidence that AI systems can enhance diagnostic accuracy and disease tracking, improve the prediction of patients’ outcomes and suggest better treatments. It can also boost efficiency in hospitals and surgeries by taking on tasks such as medical transcription and monitoring patients, and by streamlining administration. It may already be speeding the time it takes for new drugs to reach clinical trials. New tools, including generative AI, could supercharge these abilities. Yet as our Technology Quarterly this week shows, although AI has been used in health care for many years, integration has been slow and the results have often been mediocre.