AI, automation, and the future of
work: Ten things to solve for PART II
IN PART I WAS COVERED
1. Accelerating progress in AI and automation is creating
opportunities for businesses, the economy, and society
2. How AI and automation will affect work
IN PART II WILL
COVER
3. Key workforce transitions and challenges
4. Ten
things to solve for
3. Key
workforce transitions and challenges
While we expect there
will be enough work to ensure full employment in 2030 based on most of our scenarios,
the transitions that will accompany automation and AI adoption will be
significant. The mix of occupations will change, as will skill and educational
requirements. Work will need to be redesigned to ensure that humans work
alongside machines most effectively.
Workers will need different skills to thrive
in the workplace of the future
Automation will accelerate the shift in required workforce skills we have seen over the past 15
years. Demand for advanced technological skills such as programming will grow
rapidly. Social, emotional, and higher cognitive skills, such as creativity,
critical thinking, and complex information processing, will also see growing
demand. Basic digital skills demand has been increasing and that trend will
continue and accelerate. Demand for physical and manual skills will decline but
will remain the single largest category of workforce skills in 2030 in many countries.
This will put additional pressure on the already existing workforce-skills
challenge, as well as the need for new credentialing systems. While some
innovative solutions are emerging, solutions that can match the scale of the
challenge will be needed.
Many workers will likely need to change
occupations
Our research suggests
that, in a midpoint scenario, around 3 percent of the global workforce will
need to change occupational categories by 2030, though scenarios range from
about 0 to 14 percent. Some of these shifts will happen within companies and
sectors, but many will occur across sectors and even geographies. Occupations
made up of physical activities in highly structured environments or in data
processing or collection will see declines. Growing occupations will include
those with difficult to automate activities such as managers, and those in
unpredictable physical environments such as plumbers. Other occupations that
will see increasing demand for work include teachers, nursing aides, and tech
and other professionals.
Workplaces and workflows will change as more
people work alongside machines
As intelligent machines
and software are integrated more deeply into the workplace, workflows and
workspaces will continue to evolve to enable humans and machines to work
together. As self-checkout machines are introduced in stores, for example,
cashiers can become checkout assistance helpers, who can help answer questions
or troubleshoot the machines. More system-level solutions will prompt
rethinking of the entire workflow and workspace. Warehouse design may change
significantly as some portions are designed to accommodate primarily robots and
others to facilitate safe human-machine interaction.
Automation will likely put pressure on
average wages in advanced economies
The occupational mix
shifts will likely put pressure on wages. Many of the current middle-wage jobs
in advanced economies are dominated by highly automatable activities, such as
in manufacturing or in accounting, which are likely to decline. High-wage jobs
will grow significantly, especially for high-skill medical and tech or other
professionals, but a large portion of jobs expected to be created, including
teachers and nursing aides, typically have lower wage structures. The risk is
that automation could exacerbate wage polarization, income inequality, and
the lack of income advancement that has characterized the past decade across
advanced economies, stoking social, and political tensions.
In the face of these looming challenges,
workforce challenges already exist
Most countries already
face the challenge of adequately educating and training their workforces to
meet the current requirements of employers. Across the OECD, spending on worker
education and training has been declining over the last two decades. Spending
on worker transition and dislocation assistance has also continued to shrink as
a percentage of GDP. One lesson of the past decade is that while globalization
may have benefited economic growth and people as consumers, the wage and
dislocation effects on workers were not adequately addressed. Most analyses,
including our own, suggest that the scale of these issues is likely to grow in
the coming decades. We have also seen in the past that large-scale workforce
transitions can have a lasting effect on wages; during the 19th century
Industrial Revolution, wages in the United Kingdom remained stagnant for about
half a century despite rising productivity—a phenomenon known as “Engels’ Pause,” after
the German philosopher who identified it.
In the search for
appropriate measures and policies to address these challenges, we should not
seek to roll back or slow diffusion of the technologies. Companies and
governments should harness automation and AI to benefit from the enhanced
performance and productivity contributions as well as the societal benefits.
These technologies will create the economic surpluses that will help societies
manage workforce transitions. Rather, the focus should be on ways to ensure
that the workforce transitions are as smooth as possible. This is likely to
require actionable and scalable solutions in several key areas:
·
Ensuring
robust economic and productivity growth. Strong growth is not the magic answer for all the
challenges posed by automation, but it is a prerequisite for job growth and
increasing prosperity. Productivity growth is a key contributor to economic
growth. Therefore, unlocking investment and demand, as well as embracing
automation for its productivity contributions, is critical.
·
Fostering
business dynamism. Entrepreneurship and
more rapid new business formation will not only boost productivity, but also
drive job creation. A vibrant environment for small businesses as well as a
competitive environment for large business fosters business dynamism and, with
it, job growth. Accelerating the rate of new business formation and the growth
and competitiveness of businesses, large and small, will require simpler and
evolved regulations, tax and other incentives.
·
Evolving
education systems and learning for a changed workplace. Policy makers working with
education providers (traditional and nontraditional) and employers themselves
could do more to improve basic STEM skills through the school systems and
improved on-the-job training. A new emphasis is needed on creativity, critical
and systems thinking, and adaptive and life-long learning. There will need to
be solutions at scale.
·
Investing
in human capital. Reversing the trend
of low, and in some countries, declining public investment in worker training is critical. Through tax benefits and other
incentives, policy makers can encourage companies to invest in human capital,
including job creation, learning and capability building, and wage growth,
similar to incentives for private sector to invest in other types of capital
including R&D.
·
Improving
labor-market dynamism. Information signals
that enable matching of workers to work, credentialing, could all work better
in most economies. Digital platforms can also help match people with jobs and
restore vibrancy to the labor market. When more people change jobs, even within
a company, evidence suggests that wages rise. As more varieties of work and income-earning
opportunities emerge including the gig economy, we will need to solve
for issues such as portability of benefits, worker classification, and wage
variability.
·
Redesigning
work. Workflow design and
workspace design will need to adapt to a new era in which people work more
closely with machines. This is both an opportunity and a challenge, in terms of
creating a safe and productive environment. Organizations are changing too, as
work becomes more collaborative and companies seek to become increasingly agile
and nonhierarchical.
·
Rethinking
incomes. If automation (full
or partial) does result in a significant reduction in employment and/or greater
pressure on wages, some ideas such as conditional transfers, support for
mobility, universal basic income, and adapted social safety nets could be
considered and tested. The key will be to find solutions that are economically
viable and incorporate the multiple roles that work plays for workers,
including providing not only income, but also meaning, purpose, and dignity.
·
Rethinking
transition support and safety nets for workers affected. As work evolves at higher rates
of change between sectors, locations, activities, and skill requirements, many
workers will need assistance adjusting. Many best practice approaches to
transition safety nets are available, and should be adopted and adapted, while
new approaches should be considered and tested.
·
Investing
in drivers of demand for work. Governments will need to consider stepping up
investments that are beneficial in their own right and will also contribute to
demand for work (for example, infrastructure, climate-change adaptation). These
types of jobs, from construction to rewiring buildings and installing solar
panels, are often middle-wage jobs, those most affected by automation.
·
Embracing
AI and automation safely.
Even as we capture the productivity benefits of these rapidly evolving
technologies, we need to actively guard against the risks and mitigate any
dangers. The use of data must always take into account concerns including data
security, privacy, malicious use, and potential issues of bias, issues that
policy makers, tech and other firms, and individuals will need to find
effective ways to address.
There is work for
everyone today and there will be work for everyone tomorrow, even in a future
with automation. Yet that work will be different, requiring new skills, and a
far greater adaptability of the workforce than we have seen. Training and
retraining both midcareer workers and new generations for the coming challenges
will be an imperative. Government, private-sector leaders, and innovators all
need to work together to better coordinate public and private initiatives,
including creating the right incentives to invest more in human capital. The
future with automation and AI will be challenging, but a much richer one if we
harness the technologies with aplomb—and mitigate the negative effects.
By James Manyika and Kevin Sneader
https://www.mckinsey.com/featured-insights/future-of-organizations-and-work/ai-automation-and-the-future-of-work-ten-things-to-solve-for?cid=other-eml-alt-mgi-mgi-oth-1806&hlkid=fef27548a93e47cabe7e20d7257731da&hctky=1627601&hdpid=a19bd4f9-16e4-4d2f-94f1-4eb3131423ec
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