How Artificial Intelligence Is Making Lifelong Learning a Career Success Imperative

Just as intangible assets like software supplanted in value hard assets like desks or real estate, so ostensibly 'soft skills' like interpreting complex data from disparate sources are becoming as, or more, important than supposedly 'hard skills' like coding that will soon be done by machines.

In the digital economy, the larger point is that finishing school or training will signal not the end of professional learning, but the beginning. JL


Jacques Bughin and colleagues report in Harvard Business Review:

With the advent of AI, basic skills, such as reading and  numeracy, will not suffice, while demand for advanced technological skills, such as coding and programming, will rise by 55% in 2030. The need for social and emotional skills including initiative taking and leadership will rise by 24%. Creativity and complex information and problem solving will become more important. These are “soft” skills that education systems are not set up to impart. Yet in a more automated future, when machines are capable of taking on many more rote tasks, these skills will become increasingly important.
President Emmanuel Macron together with many Silicon Valley CEOs will kick off the VivaTech conference in Paris this week with the aim of showcasing the “good” side of technology. Our research highlights some of those benefits, especially the productivity growth and performance gains that automation and artificial intelligence can bring to the economy — and to society more broadly, if these technologies are used to tackle major issues such as fighting disease and tackling climate change. But we also note some critical challenges that need to be overcome. Foremost among them: a massive shift in the skills that we will need in the workplace in the future.
To see just how big those shifts could be, our latest research analyzed skill requirements for individual work activities in more than 800 occupations to examine the number of hours that the workforce spends on 25 core skills today. We then estimated the extent to which these skill requirements could change by 2030, as automation and artificial technologies are deployed in the workplace, and backed up our findings with a detailed survey of more than 3,000 business leaders in seven countries, who largely confirmed our quantitative findings. We grouped the 25 skills into five categories: physical and manual (which is the largest category today), basic cognitive, higher cognitive, social and emotional, and technological skills (today’s smallest category).
The findings highlight the major challenge confronting our workforces, our economies, and the well-being of our societies. Among other priorities, they show the urgency of putting in place large-scale retraining initiatives for a majority of workers who will be affected by automation — initiatives that are sorely lacking today.
Shifts in skills are not new: we have seen such a shift from physical to cognitive tasks, and more recently to digital skills. But the coming shift in workforce skills could be massive in scale. To give a sense of magnitude: more than one in three workers may need to adapt their skills’ mix by 2030, which is more than double the number who could be displaced by automation under some of our adoption scenarios — and lifelong learning of new skills will be essential for all. With the advent of AI, basic cognitive skills, such as reading and basic numeracy, will not suffice for many jobs, while demand for advanced technological skills, such as coding and programming, will rise, by 55% in 2030, according to our analysis.The need for social and emotional skills including initiative taking and leadership will also rise sharply, by 24%, and among higher cognitive skills, creativity and complex information and problem solving will also become significantly more important. These are often seen as “soft” skills that schools and education systems in general are not set up to impart. Yet in a more automated future, when machines are capable of taking on many more rote tasks, these skills will become increasingly important — precisely because machines are still far from able to provide expertise and coaching, or manage complex relationships.
While many people fear that automation will reduce the number of jobs for humans, we note that the diffusion of AI will take time. The need for basic cognitive skills as well as physical and manual skills will not disappear. In fact, physical and manual skills will remain the largest skill category in many countries by hours worked, but with different importance across countries. In France and the United Kingdom, for example, manual skills will be overtaken by demand for social and emotional skills, while in Germany, higher cognitive skills will become preeminent. These country differences are the result of different industry mixes in each country, which in turn affect the automation potential of economies and the future skills mix. While we based our estimates on the automation potential of sectors and countries today, this could change depending on the pace and enthusiasm with which AI is adopted in companies, sectors, and countries. Already, it is clear that China is moving rapidly to become a leading AI player, and Asia as a whole is ahead of Europe in the volume of AI investment.
We see retraining (or “reskilling” as some like to call it), as the imperative of the coming decade. It is a challenge not just for companies, which are on the front lines, but also for educational institutions, industry and labor groups, philanthropists, and of course, policy makers, who will need to find new ways to incentivize investments in human capital.
For companies, these shifts are part of the larger automation challenge that will require a thorough rethink of how work is organized within firms — including what the strategic workforce needs are likely to be, and how to set about achieving them. In our research, we find some examples of companies that are focusing on retraining, either in-house — for example, Germany’s SAP — or by working with outside educational institutions, as AT&T is doing. Overall, our survey suggests that European firms are more likely to fill future staffing needs in the new automation era by focusing on retraining, while US firms are more open to new hiring. The starting point for all of this will be a mindset change, with companies seeking to measure future success by their ability to provide continuous learning options to employees.
The skill shift is not only a challenge, it is an opportunity. If companies and societies are able to equip workers with the new skills that are needed, the upside will be considerable, in terms of higher productivity growth, rising wages, and increased prosperity. M. Macron’s point about technology being a force for good will become a self-fulfilling prophecy. Conversely, a failure to address these shifting skill demands could exacerbate income polarization and stoke political and social tensions. The stakes are high, but we can already see the outlines of what needs to be done — and we have a little time to work on solutions.