Source: PwC estimates for the UK based on OECD PIAAC data

John Hawksworth, chief economist at PwC, commented:

“We don’t believe that automation will lead to mass technological unemployment by the 2030s, any more than it has done in the decades since the digital revolution began. In the long run, AI, robotics and related technologies should not only make a significant contribution to UK GDP of up to 10%, but should also generate enough new jobs to broadly offset the potential job losses associated with automation.

“But we should not be complacent about the coming waves of automation: there will be challenges to many workers to adapt to these changes through enhancing their skills and retraining for new careers in some cases. Governments, businesses, trade unions and educational providers will all have a role to play in helping people through this transition.”

Algorithm wave - to early 2020s

The algorithm wave is already well underway and involves automating structured data analysis and simple digital tasks, such as credit scoring. Only a relatively small proportion of jobs in the UK, between 2-3%, are likely to be impacted during this time, as many of the technologies are still at an early stage of development. PwC finds financial, professional and technical services, and information and communications sectors are likely to be the most affected at around 6-8%. Women could be more exposed than men at this stage due to their higher representation in clerical tasks in the more affected sectors.

Augmentation wave - to late 2020s

The augmentation wave is focused on automation of repeatable tasks and exchanging information, as well as further developments of aerial drones, robots in warehouses and semi-autonomous vehicles. PwC estimates the share of potential jobs affected could rise to up to 20% by the end of the 2020s, as the use of AI systems becomes much more widespread and robotics technologies advance and mature. Over this period, the effects will be felt across all industry sectors, although financial services is still expected to be the most impacted sector. Women are still marginally more exposed than men in this second wave, although the gap is narrowing. Level of education also starts to become a determining factor, with low and medium education levels (i.e. below graduate level) starting to show higher automation risk levels, than those with higher education levels (i.e. graduates and above).

Autonomy wave - by mid-2030s

In the final wave, PwC predicts that AI will be able to analyse data from multiple sources, make decisions and take physical actions with little or no human input. The share of jobs that could be impacted by automation is estimated to rise to 30% by the mid-2030s, as autonomous robots and driverless vehicles roll out more widely across the economy. PwC analysis suggests that this is the phase when many more manual tasks could become capable of being automated, pushing sectors like transport, manufacturing and retail to the top of the likely automation list. This is also the phase when men are likely to be more impacted than women, due to their greater share of employment in manual jobs in areas such as driving, factories and warehouses. This is also true for less-educated workers, as the variation between education level widens.

However, PwC predicts that AI and other related new technologies will also boost productivity, income and wealth. As this additional income and wealth is spent or invested, it will generate increased demand for human labour in less automatable sectors. PwC’s economic modelling suggests that this job creation effect will broadly offset the potential job losses associated with automation in the long run.

Euan Cameron, UK Artificial Intelligence leader at PwC, said:

“Our research shows that the impact from automation and AI will be felt in waves, with more routine and data tasks hit first. But just because businesses and people aren’t feeling the impacts right now, there is no excuse not to start planning for the future.

“AI technology is getting more sophisticated every day and businesses need to understand how, where and when their people are likely to be affected in the future. Those that understand the risks and opportunities can start upskilling their people and adapting their businesses, rather than simply reacting when it’s too late.”

Ends.

Notes to editors:

The full report is available online here.