‘Significant variation’ in take-up of data technologies

The survey highlights significant variation in the penetration of data-driven technologies across sectors of the economy. While there is comparatively lower adoption of data-driven technologies in healthcare businesses ( 12%), the industry has the highest proportion of extensive AI use ( 10%). This contrasts with digital and communications businesses, where one-in-five ( 21%) businesses use data-driven technologies, but only one-in-20 ( 5%) extensively use these technologies.

The research reveals a range of barriers that, once overcome, will “enable the UK to grasp the opportunities presented by greater adoption of data-driven technologies”, according to the CDEI. Key barriers highlighted in the research relate to the access and sharing of data. Over two thirds          ( 70%) of businesses said they desired more information to help them navigate the complex legal requirements around data collection, use and sharing.

Nearly a quarter ( 23%) cited difficulty accessing quality data as a barrier to innovation, while almost half of businesses ( 43%) highlighted limited technological capabilities.

The CDEI has also published the second edition of its AI Barometer, an analysis of the most pressing opportunities and risks associated with AI and data use. Drawing on the insight of over 80 panellists, the report identifies areas where there are untapped opportunities for innovation in three key sectors that have been particularly affected by the Covid-19 pandemic.

In transport and logistics, these include opportunities to improve energy efficiency, drive down emissions, and yield better environmental outcomes, as well as smooth trade flows at borders. In recruitment and employment contexts, data-driven innovation has the potential to improve talent pipelines, enable greater access to job opportunities and reduce bias and discrimination. In education, data-driven innovation was seen to have the potential to reduce the administrative burden on teachers and increase social mobility.

Edwina Dunn, interim chair of the Centre for Data Ethics and Innovation, said: “Data and AI can help tackle some of the greatest challenges of our time. In order to achieve this, we need to overcome barriers to innovation, such as poor quality data, and address risks such as algorithmic bias.

“The CDEI is working in partnership with a range of organisations to help them overcome these barriers, mitigate risk and put high-level ethical principles, such as accountability and transparency, into practice. It’s practical work like this that will enable us to build greater public trust in how data and AI are used.”