Almost 250,000 public sector workers could lose their jobs to robots over the next 15 years, according to a new report which claims machines would be more efficient and save billions of pounds. Reform, a right-of-centre thinktank, says websites and artificial intelligence "chat bots" could replace up to 90% of Whitehall's administrators, as well as tens of thousands in the NHS and GPs' surgeries, by 2030 – saving as much as £4bn a year. Even nurses and doctors could fall victim to the march of the machines, which the report says can outperform humans at some diagnoses and routine surgical procedures, and are more efficient at collecting information. The report argues that public services should become more flexible by embracing a gig economy where workers support themselves through a variety of flexible jobs acquired through online platforms. In remarks that seem set to infuriate unions, a Reform press release says: "Public services can become the next Uber, using the gig economy to employ locum doctors and supply teachers."

Whitehall could save £2.6 billion with automation. The report, which addresses the creation of a public services workforce organised around the needs of its users, advocates the reduction of staff in favour of automation and digital technology. Citing analysis by Oxford academics Frey and Osbourne, in which the academics said that admin roles have a 96% chance of being automated by current technology, the report applied their calculations to current public sector numbers. The report found that, over the next 10 to 15 years, central government departments could further reduce headcount by 131,962, saving £2.6 billion from the 2016-17 wage bill. The report sells automation as the'new approach' which is needed, saying: "Public services should deliver outcomes that matter to users, and meet expectations of interacting via technology. This approach would see services designed around users and render at least 248,860 administrative roles redundant. The accuracy of decision-making can be further improved by using artificial intelligence to make complex decisions and by understanding why mistakes that, for example, cause 10 per cent of hospital patients to suffer from medical error, are made."