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Take up artificial intelligence now or lose out, warns UK review

Industry should sponsor qualifications in artificial intelligence and help break down stereotypes and broaden participation in leading technology, suggests a new review

AI in the UK

UK industry needs to take up artificial intelligence now if it is to compete with overseas companies, warns an independent government review.

Artificial intelligence (AI) matters now because the UK is one of a group of countries leading in the field. That advantage could be built on successfully, or it could be lost, say report authors professor Dame Wendy Hall and Jérôme Pesenti.

“Industry outside the UK is taking up AI. UK industry will need to, to compete,” they say.

The report Growing the Artificial Intelligence Industry in the UK, for the Department for Digital, Culture, Media & Sport and the Department for Business, Energy & Industrial Strategy, suggests industry should sponsor a major programme of Masters degrees in artificial intelligence to meet the growing need from employers and to ensure the UK remains competitive and a global leader in the field.

Helping people adapt to changes in work will also be necessary to protect people and share the benefits of artificial intelligence (AI), to gain public acceptance of AI and to ensure employers can fill the new, different roles that will be needed for working with AI.

Industry, government, business and the workforce will all need to respond to changes resulting from automation of processes, including by providing and taking up opportunities for retraining.

“We are at the threshold of an era when much of our productivity and prosperity will be derived from the systems and machines we create,” say Hall and Pesenti.

“We are accustomed now to technology developing fast, but that pace will increase and AI will drive much of that acceleration. The impacts on society and the economy will be profound, although the exact nature of those impacts is uncertain.

“We have a choice. The UK could stay among the world leaders in AI in the future, or allow other countries to dominate. We start from a good position in many respects but other leading countries are devoting significant resources to growing and deploying AI. The UK will need to act in key areas and to sustain action over a long period and across industry sectors, to retain its world leading status, and to grow our AI capability as well as deploying it much more widely.”

It is estimated AI could add an additional £630 bn (USD $814 bn) to the UK economy by 2035, increasing the annual growth rate of GVA from 2.5 to 3.9%.

To achieve this, the UK needs to make a “step-change” in training, say Hall and Pesenti, who suggest the initial cohort for an industry-sponsored Masters level course should comprise 300 students. The model proposed is a 15 month programme, designed to become recognised as a best-in- class training platform for machine learning graduates, funded by industry and providing skills directly to funding businesses.

The first 12 months would be university training, assessed and accredited. The last three months of the programme would be an internship with one of the sponsoring businesses. A matching algorithm, like the deferred acceptance algorithm, will be used to ensure that each business gets a number of interns proportionate to their funding without having to identify the interns initially.

“Demand for talent already outstrips supply, and average remuneration for data scientists and machine learning experts has increased substantially,” say the authors.

“The UK also needs to remain an attractive destination for the best talent from around the world, at levels from undergraduate upwards, and including through visa categories and numbers that meet industry needs. This is an opportunity to show that the UK is open to international talent, and committed to staying among the global leaders in AI.”

Supply can be increased by:

● Creating additional courses and places for generating new talent in the UK

● Incentivising and improving the capacity to teach AI in the UK

● Improving the responsiveness of the skills training system to changing demand

● Attracting the best talent from other countries to the UK

● Reducing the gap between industry and academia

The authors also recommend that government, industry and academia must embrace the value and importance of a diverse workforce for artificial intelligence (AI), and should work together to develop public information aimed at breaking down stereotypes and broadening participation.

Report recommendations

The Masters programme and embracing diversity are two of 18 recommendations in the report. Among the others are:

  1. To facilitate the sharing of data between organisations holding data and organisations looking to use data to develop AI, government and industry should deliver a programme to develop Data Trusts – proven and trusted frameworks and agreements – to ensure exchanges are secure and mutually beneficial
  2. Universities should encourage the development of advanced credit-bearing AI MOOCs and online continuing professional development courses leading to MScs for people with STEM qualifications to gain more specialist knowledge
  3. An International fellowship programme for AI in the UK should be created in partnership with the Alan Turing Institute: the Turing AI Fellowships. This should be supported by a targeted fund for identifying and recruiting the best talent, and by ensuring that the UK is open to any and all of the eligible experts from around the world
  4. Government should work with industry and experts to establish a UK AI Council to help co-ordinate and grow AI in the UK
  5. The Information Commissioner’s Office and the Alan Turing Institute should develop a framework for explaining processes, services and decisions delivered by AI, to improve transparency and accountability
  6. The Department for International Trade should expand its current support programme for AI businesses
  7. TechUK should work with the Royal Academy of Engineering, the Digital Catapult, and key players in industry sectors, to develop practical guidance on the opportunities and challenges of successful adoption of AI across the UK economy
  8. Government, drawing on the expertise of the Government Digital Service, the Data Science Partnership and experts working with data in other Departments, should develop a programme of actions to prepare the public sector and spread best practice for applying AI to improve operations and services for citizens
  9. Government should ensure that challenges addressed by the Industrial Strategy Challenge Fund (ISCF) and Small Business Research Initiative (SBRI) are designed to attract and support applications of AI across the full range of challenge areas and set funded challenges which use public sector data for AI
  10. Uptake of AI varies significantly by sector and within sectors, says the report. Businesses and sectors that have digitised operations and services can take up AI more easily and effectively than those that have not. Organisations that have good data capability (collection, retention, curation, analysis, protection) have a head-start in becoming AI-ready.

The authors point to accountancy, law firms and retailers such as Ocado as among those taking a lead in experimenting with AI for services and operations, while in the public sector HMRC is using AI to help identify call centre priorities and the Government Digital Service (GDS) is using machine learning to help automate and process user comments from surveys on gov.uk, and for predicting peak traffic demands to the most popular content searched for by the public. GDS is working with the Pensions Regulator to improve efficiency using is also highlighted as a company using AI effectively.

Over 100 experts from academia, industry and government were involved in this Review through a series of workshops and meetings used to inform, develop, refine and test these recommendations. This report also makes use of a wide range of industry and expert sources of evidence and insight, published and unpublished.


We are at the threshold of an era when much of our productivity and prosperity will be derived from the systems and machines we create. The impacts on society and the economy will be profound, although the exact nature of those impacts is uncertain

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