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.
That’s the prediction of consultancy PwC in its latest UK Economic Outlook report, which delves into task composition of jobs in different industry sectors and occupations, using machine learning techniques to model the potential impact of AI on our economy using OECD data.
As a result, PwC says the UK (30%) has a lower proportion of existing jobs at potential high risk of automation than the US, at 30% versus 38%, but more than Japan’s 21%.
The likely impact of automation varies significantly across industry sectors, the study goes on to say.
Thus 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.
But there’s some good news for chunks of the public sector, at least potentially, as 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.
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On average, PwC thinks 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%), reflecting 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, it says, female workers are more concentrated in occupations requiring higher levels of social skills – and often higher average education levels – such as health and education.
“Just because it is technically feasible to replace a human worker with a robot, doesn’t mean it’s economically attractive to do so,” said PwC chief economist John Hawksworth.
“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 [but] this may not be a bad thing, if it gives existing workers and businesses more time to adapt to this brave new world.”
