Up to 30% of existing UK jobs could be impacted by automation by early 2030s, but this should be offset by job gains elsewhere in economy

Published at 00:01 AM on 24 March 2017

  • Up to around 30% of existing UK jobs are susceptible to automation from robotics and Artificial Intelligence (AI) by the early 2030s, but in many cases the nature of jobs will change rather than disappear
  • This is lower than the US at 38% and Germany at 35%, but higher than Japan at 21%
  • The likelihood of automation appears highest in sectors such as transport, manufacturing, and wholesale and retail, and lower in education, health and social work
  • Male workers could be at greater potential risk of job automation than women, but education is the key differentiating factor for individual workers
  • Automation will also boost productivity and wealth, leading to offsetting additional job gains elsewhere in the economy  - but income inequality may rise
  • Economic, legal and regulatory constraints may restrict the pace and extent of  increases in automation in practice

Up to around 30% of existing UK jobs could face automation over the next 15 years, but new AI-related technologies will also boost productivity and generate additional jobs elsewhere in the economy, according to new analysis by PwC in its latest UK Economic Outlook report. This involves looking in detail at the task composition of jobs in different industry sectors and occupations, using machine learning techniques to model the potential impact of AI in the future based on OECD data.

The study estimates that the UK (30%) has a lower proportion of existing  jobs at potential high risk of automation than the US (38%) and Germany (35%), but more than Japan (21%).

Screen Shot 2017-03-23 at 18.36.07

PwC’s analysis finds the likely impact of automation varies significantly across industry sectors: transportation and storage (56%), manufacturing (46%) and wholesale and retail trade (44%) have the highest proportion of jobs facing potential high risks of automation among the larger sectors. Education and health and social work are estimated to face the lowest risks of automation given the relatively high proportion of tasks that are hard to automate (see table below).

Employment shares and the estimated proportion of jobs at potential high risk of automation by early 2030s for all UK industry sectors 

Industry

Employment share of total jobs (%)

Job automation (% at potential high risk)

Wholesale and retail trade

14.8%

44.0%

Manufacturing

7.6%

46.4%

Administrative and support services

8.4%

37.4%

Transportation and storage

4.9%

56.4%

Professional, scientific and technical

8.8%

25.6%

Human health and social work

12.4%

17.0%

Accommodation and food services

6.7%

25.5%

Construction

6.4%

23.7%

Public administration and defence

4.3%

32.1%

Information and communication

4.1%

27.3%

Financial and insurance

3.2%

32.2%

Education

8.7%

8.5%

Arts and entertainment

2.9%

22.3%

Other services

2.7%

18.6%

Real estate

1.7%

28.2%

Water, sewage and waste management

0.6%

62.6%

Agriculture, forestry and fishing

1.1%

18.7%

Electricity and gas supply

0.4%

31.8%

Mining and quarrying

0.2%

23.1%

Domestic personnel and self-subsistence

0.3%

8.1%

Total for all sectors

100%

30%

Sources: ONS workforce jobs survey for employment shares (2016); PwC estimates for last column using PIAAC data from OECD. High risk of automation is defined as 70% or over based on technical feasibility considerations only.

John Hawksworth, chief economist at PwC, commented:

“A key driver of our industry-level estimates is the fact that manual and routine tasks are more susceptible to automation, while social skills are relatively less automatable. That said, no industry is entirely immune from future advances in robotics and AI. 

“Automating more manual and repetitive tasks will eliminate some existing jobs, but could also enable some workers to focus on higher value, more rewarding and creative work, removing the monotony from our day jobs. By boosting productivity - a key UK weakness over the past decade - and so generating wealth, advances in robotics and AI should also create additional jobs in less automatable parts of the economy as this extra wealth is spent or invested.

“The UK employment rate is at its highest level now since comparable records began in 1971, despite all the advances in digital and other labour-saving technologies we have seen since. It is not clear that the future will be radically different from the past in terms of how automation will affect overall UK employment rates.”

The potential impact of job automation also varies according to the characteristics of individual workers. On average, PwC estimates that a higher proportion of male jobs (35%), particularly those of men with lower levels of education, are at higher potential risk of automation than female jobs (26%). This reflects the fact that relatively highly automatable sectors such as transportation and storage and manufacturing tend to have high proportions of men working in them. In contrast, female workers are more concentrated in occupations requiring higher levels of social skills - and often higher average education levels - such as health and education.

Could automation increase inequality and how should governments respond?

While automation related to AI and robotics should boost productivity and will not necessarily reduce total employment in the long run, it could also widen income inequality because a greater proportion of the economic pie will go to those with the knowledge and skills needed to thrive in an ever more digital economy. This would put a premium not only on education levels when entering the workforce, but also the ability to adapt over time and re-skill throughout working life in the face of an accelerating pace of technological change.

Jon Andrews, head of technology and investments at PwC, said:

“There’s no doubt that AI and robotics will rebalance what jobs look like in the future, and that some are more susceptible than others. What’s important is making sure that the potential gains from automation are shared more widely across society and no one gets left behind. Responsible employers need to ensure they encourage flexibility and adaptability in their people so we are all ready for the change.

“In the future, knowledge will be a commodity so we need to shift our thinking on how we skill and upskill future generations. Creative and critical thinking will be highly valued, as will emotional intelligence. It’s impossible to predict what jobs there will even be in the future, so life-long learning and a positive attitude to embracing change needs to be a fundamental aspect of the UK’s future success. The government’s digital strategy acknowledges the challenges and  is a step in the right direction towards creating the right environment to support UK businesses’ exploration of emerging technology to drive growth.”

What economic, legal and regulatory constraints might automation face?

While the bulk of PwC’s analysis focuses on the technical feasibility of automation, it also recognises the economic, legal and regulatory constraints that might restrict the pace and extent of future increases in automation in practice.

John Hawksworth concluded:

“Just because it is technically feasible to replace a human worker with a robot, doesn’t mean it’s economically attractive to do so. Levels of automation will depend on the relative cost and productivity of robots compared to human workers in carrying out different types of tasks. We expect this balance to shift in favour of robots over time, but there should still be many areas where humans retain a comparative advantage.

“In addition, legal and regulatory hurdles, organisational inertia and legacy systems will slow down the shift towards AI and robotics even where this becomes technically and economically feasible. And this may not be a bad thing if it gives existing workers and businesses more time to adapt to this brave new world.”

Ends.

Notes for editors.

For media enquiries please contact tilly.parke@pwc.com. This research, which was written by John Hawksworth, chief economist at PwC, and Richard Berriman, a machine learning specialist in PwC’s data analytics practice, is available online here: http://www.pwc.co.uk/services/economics-policy/insights/uk-economic-outlook.html

The research forms part of PwC’s latest UK Economic Outlook report, which will be published on Friday 24th March. As well as the research on automation, this report includes updated UK economic projections for 2017-18 and an in-depth look at consumer spending prospects after Brexit.

 


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