The majority of people accept that we need to pay tax. However, we do so on the reasonable expectation that this money will be used to provide high-quality public services.

In reality though, this contract between the public and the state is frequently broken. Hard earned money is handed over, but the standard of service received is not up to scratch. Anyone who has tried to get an appointment with their GP or enquired about council services in their local area can testify to this. A lack of improvement in the quality of services is particularly galling when the tax burden continues to rise.

There is a solution: automation. In our new paper, the TaxPayers’ Alliance calls for a much greater embrace of automation in the public sector. This will result in public services services being delivered in a better and more cost effective way. Not only will this mean that taxpayers get a better deal, but it will also benefit public sector workers, businesses, and the economy as a whole.

Automation is already improving public services around the world. For example, Norway’s Welfare and Pensions Administration (NAV) has automated 65 per cent of sickness benefit claims and payments processing, replacing a manual procedure involving thousands of paper forms. The project has increased efficiency, agility, and accuracy, and had a positive impact on staff. More than 350 employees who previously handled the claims paperwork have now been moved to the front office to help citizens face to face.

Then there is the ChatBot lawyer in the United States. It is helping refugees from around the country to fill out important forms so that they can receive the help they need.

The above examples are just a small selection that illustrate the current versatility and potential of automation to transform the delivery of public services. If the technologies available and on the horizon are enthusiastically embraced by the public sector the standard of services improve dramatically, while at the same time the cost of their provision is substantially reduced.