In our latest research on automation, we examine work that can be automated through 2030 and jobs that may be created in the same period. We draw from lessons from history and develop various scenarios for the future. While it is hard to predict how all this will play out, our research provides some insights into the likely workforce transitions that should be expected and their implications. Our key findings:
– Automation technologies including artificial intelligence and robotics will generate significant benefits for users, businesses, and economies, lifting productivity and economic growth. The extent to which these technologies displace workers will depend on the pace of their development and adoption, economic growth, and growth in demand for work. Even as it causes declines in some occupations, automation will change many more—60 percent of occupations have at least 30 percent of constituent work activities that could be automated. It will also create new occupations that do not exist today, much as technologies of the past have done.
– While about half of all work activities globally have the technical potential to be automated by adapting currently demonstrated technologies, the proportion of work actually displaced by 2030 will likely be lower, because of technical, economic, and social factors that affect adoption. Our scenarios across 46 countries suggest that between almost zero and one- third of work activities could be displaced by 2030, with a midpoint of 15 percent. The proportion varies widely across countries, with advanced economies more affected by automation than developing ones, reflecting higher wage rates and thus economic incentives to automate.
– Even with automation, the demand for work and workers could increase as economies grow, partly fueled by productivity growth enabled by technological progress. Rising incomes and consumption especially in developing countries, increasing health care for aging societies, investment in infrastructure and energy, and other trends will create demand for work that could help offset the displacement of workers. Additional investments such as in infrastructure and construction, beneficial in their own right, could be needed to reduce the risk of job shortages in some advanced economies.
– Even if there is enough work to ensure full employment by 2030, major transitions lie ahead that could match or even exceed the scale of historical shifts out of agriculture and manufacturing. Our scenarios suggest that by 2030, 75 million to 375 million workers (3 to 14 percent of the global workforce) will need to switch occupational categories. Moreover, all workers will need to adapt, as their occupations evolve alongside increasingly capable machines. Some of that adaptation will require higher educational attainment, or spending more time on activities that require social and emotional skills, creativity, high-level cognitive capabilities and other skills relatively hard to automate.
– Income polarization could continue in the United States and other advanced economies, where demand for high-wage occupations may grow the most while middle-wage occupations decline— assuming current wage structures persist. Increased investment and productivity growth from automation could spur enough growth to ensure full employment, but only if most displaced workers find new work within one year. If reemployment is slow, frictional unemployment will likely rise in the short-term and wages could face downward pressure. These wage trends are not universal: in China and other emerging economies, middle-wage occupations such as service and construction jobs will likely see the most net job growth, boosting the emerging middle class.
– To achieve good outcomes, policy makers and business leaders will need to embrace automation’s benefits and, at the same time, address the worker transitions brought about by these technologies. Ensuring robust demand growth and economic dynamism is a priority: history shows that economies that are not expanding do not generate job growth. Midcareer job training will be essential, as will enhancing labor market dynamism and enabling worker redeployment. These changes will challenge current educational and workforce training models, as well as business approaches to skill-building. Another priority is rethinking and strengthening transition and income support for workers caught in the cross- currents of automation.
Peter Gumbel: You did say that there are going to be some difficult transitions. How difficult will they be? What sort of transitions we talking about?
James Manyika: We’re going to see a few different kinds of transitions. The first one is that the mixture of occupations is going to shift. We know that when you take into account the activities that are easy to automate, relatively, and the ones that are relatively harder to automate, it will result in some occupations growing more than others.
What do I mean by that? For example, occupations that involve a lot of data gathering, data processing, or physical work are going to decline. The relatively harder occupations, and activities to automate, like care work and work that requires empathy, judgment, and so forth, those occupations are going to rise.
The mix of occupations is going to shift substantially. That means that people are probably going to have to move and be transitioned from certain occupations into new occupations, ones that are going to be growing. So that’s one kind of transition.
Another kind of transition is going to be the skill requirements. We know that the skill requirements are going to shift for a couple reasons. One, because people are moving to new occupations that are going to require higher skills, often, in order to do those occupations; we know the skill requirements are going to go up, if only because people are going to be working alongside highly capable and increasingly capable machines.
In order for people to keep up, adapt, and work alongside effectively with highly capable machines, they will require a very different set of skills. So the skill transitions are going to be quite substantial. That’s why we’re having a conversation now, and we’re starting to have a conversation about retraining and reskilling, especially for mid-career workers, who may have grown up in one environment with a certain set of skills and are now having to move into new occupations. Or, even if they’re in the same occupation, that occupation now requires a higher level of skills in order to be valued and continue to be effective. The skill transitions are quite substantial. A third transition that I think we’re going to have to think about is the potential impact of all of this on incomes and wages.
We know that the occupations that are going to be growing are the ones that historically haven’t had the highest wage structures associated with them. We know that work in manufacturing always had slightly higher wages compared with, for example, work in activities like care work, where there are teachers or elder-care workers, and so forth. And so, we know that the mix of occupations that are growing—unless we change our minds on how we think about the value of that work—have not historically had higher wage structures associated with them.
We’re going to have to deal with that. We’re also going to have to deal with the fact that as workers transition from one occupation to another, they may require all kinds of support—like dislocation support—as they move from where they are to where they’re going to be. We’re going to have to rethink that.
That’s particularly important at a time when, historically, most economies in the OECD [Organisation for Economic Co-operation and Development] have not always supported worker transitions as robustly as they could. In fact, worker-dislocation support has declined over the last 30 years.
At a time when we’re probably going to need it even more, we’re going to have to change our minds about how we think about worker-dislocation support. So all of these are some of the transitions that I think we’re going to have to grapple with. And this is a matter not just for governments and policymakers but also for businesses and private-sector leaders, who are going to have to think about they will retrain their workforce.
How do they help redeploy their workforce as occupations and work change? How do they redesign work structures inside companies, to support different and new kinds of ways of work, so that there’s enough work for everybody to do, as we manage our way through these transitions?
I’m relatively less worried about the question of whether there will be enough work for everybody. Of course, one can imagine scenarios where that would be the case. But I’m more worried, and focused on, these transition questions for workers, around skills, occupations, and the income and wage effects. I think that’s where the real hard work’s going to be.
Chosen excerpts by Job Market Monitor. Read the whole story at Jobs lost, jobs gained: Workforce transitions in a time of automation