07 June 2019
The pace of economic change all but guarantees that a single degree or qualification earned in your teens or twenties will no longer be sufficient for your whole working life. Students graduating from high school today will have many, many jobs in their professional lives; some predictions place this number as high as 15. More troubling, we have no idea what many of those jobs will be: imagine trying to explain to someone 20 years ago the skills necessary to be an SEO specialist or to be the system administrator for a crypto-currency exchange.
So what does structural change, including but not limited to automation, mean for the future of work? And what does it mean for the skills that individuals will need to thrive in this emerging labour market? These are the questions that we have addressed in our research “Future of Skills: Employment in 2030”.
First, we reviewed what the literature says about long-run trends impacting on the UK and US labour markets. Then, armed with this information, we asked experts to debate the future of 30 occupations and label whether they expected them to rise or fall in demand by 2030. In addition, they were asked to state how certain or uncertain they were in making these judgments.
Finally, we fed these results into an algorithm that generated predictions for all occupations. Specifically, we exploited a rich data set of 120 skills, abilities and knowledge requirements.
As a result, our model not only predicts which occupations are most likely to grow or decline, but which skills are most likely to be in demand as well, and skills are something that, whatever job you’re in, there’s something that you can do about. If you invest in the right skills you can leave yourself in a better place to benefit from the opportunities of the future.
First, let’s look at our predictions about employment. The graph below shows the results of thousands of simulations predicting that a specific occupation will employ more (or less) than it does today. The x-axis estimates the probability that each occupation group will experience higher relative demand, and the y-axis shows the number of predicted jobs in that occupation for each simulation. Thus the areas on the right of the distribution are occupations where we expect rising demand, those on the left are expected to decline.
The model forecasts that only one in five workers are in occupations that will shrink. This figure is much lower than recent studies of automation have suggested. Occupations related to agriculture, trades and construction, which in other studies have been forecast to decline, exhibit more interesting and heterogeneous patterns with our research, suggesting that there may be pockets of opportunity throughout the skills ladder.
These jobs are in sectors such as education and healthcare, where the overriding effect of technology is likely to be an improvement in outcomes, not a reduction in workforce. Therefore, as trends such as demographic change raise demand for these services, the prospect for employment is also likely to rise. Finally, the model forecasts that seven in ten workers are in jobs where there is great uncertainty about the future.