No Match Found
Potential boost to global GDP from AI by 2030
of jobs at potential risk of automation by early 2020s
of jobs at potential risk of automation by mid-2030s
of workers with low education at risk of automation by mid-2030s
AI, robotics and other forms of smart automation have the potential to bring great economic benefits, contributing up to $15 trillion to global GDP by 2030 according to PwC analysis. This extra wealth will also generate the demand for many jobs, but there are also concerns that it could displace many existing jobs.
We have analysed in detail the tasks involved in over 200,000 existing jobs across 29 countries to assess what the potential for automation may be at various points over the next 20 years. We identify three waves of automation that might unfold over this period:
During the first wave, we expect relatively low displacement of existing jobs, perhaps only around 3% by the early 2020s. But job displacement could increase in later waves as these technologies mature and are rolled out across the economy in increasingly autonomous form.
By the mid-2030s, up to 30% of jobs could be automatable, with slightly more men being affected in the long run as autonomous vehicles and other machines replace many manual tasks where their share of employment is higher. During the first and second waves, however, women could be at greater risk of automation due to their higher representation in clerical and other administrative functions (see chart).
These estimates are median values across 29 countries, with the UK being very close to the average. Long-term automation could be lower at only around 20-25% in Asian and Nordic countries, but could be higher at over 40% in some Eastern European countries according to our analysis. Explore the results further for your country using our data analysis tool. You can also download the full report for more detailed analysis and commentary.
Our analysis highlights significant differences in the degree of automatability of jobs by industry sector, but these effects will also vary over time (see chart).
In the short term, the largest impacts could be on sectors like financial services where algorithms can lead to faster and more efficient analysis and assessments. In the longer term, however, the development of autonomous driverless vehicles could mean that the largest impacts are seen in the transport sector.
In contrast, while no sector will be unaffected by these technologies, areas like health may be relatively less affected due to a greater reliance on social skills and the human touch. AI and robots will have an important role in health care in future, but more working alongside human doctors and nurses than replacing them. The same would be true in the education sector based on our analysis.
In the short term, the impact of automation may be low for workers of all education levels, but in the long run our estimates show that those with lower education levels could be much more vulnerable to being displaced by machines (see chart).
Governments and business need to work together to help people adjust to these new technologies through retraining and career changes. A culture of adaptability and lifelong learning will be crucial for spreading the benefits of AI and robotics widely through society, particularly with an ageing population where we need people to be able to work for longer.
Improved STEM skills will be important in allowing people to take the high technology jobs that will arise out of AI and robotics, but soft skills will also be important in making people adaptable and employable throughout their working lives.