EXECUTIVE SUMMARY
JANUARY 2017
A FUTURE THAT WORKS:
AUTOMATION, EMPLOYMENT,
AND PRODUCTIVITY
CopyrightMcKinsey & Company 2017
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JANUARY 2017
A FUTURE THAT WORKS:
AUTOMATION, EMPLOYMENT,
AND PRODUCTIVITY
IN BRIEF
A FUTURE THAT WORKS: AUTOMATION,
EMPLOYMENT, AND PRODUCTIVITY
Advances in robotics, artifcial intelligence, and machine
learning are ushering in a new age of automation, as
machines match or outperform human performance in a
range of work activities, including ones requiring cognitive
capabilities. In this report, part of our ongoing research
into the future of work, we analyze the automation
potential of the global economy, the factors that will
determine the pace and extent of workplace adoption,
and the economic impact associated with its potential.
to improve performance, by reducing errors and
improving quality and speed, and in some cases
achieving outcomes that go beyond human
capabilities. Automation also contributes to
productivity, as it has done historically. At a time
of lackluster productivity growth, this would give a
needed boost to economic growth and prosperity
and help offset the impact of a declining share of the
working-age population in many countries. Based
on our scenario modeling, we estimate automation
could raise productivity growth globally by 0.8 to
1.4percent annually.
$16trillion in wages to do in the global economy
have the potential to be automated by adapting
currently demonstrated technology, according
to our analysis of more than 2,000 work activities
across 800 occupations. While less than 5percent
of all occupations can be automated entirely using
demonstrated technologies, about 60percent of all
occupations have at least 30percent of constituent
activities that could be automated. More occupations
will change than will be automated away.
physical activities in highly structured and predictable
environments, as well as the collection and processing
of data. In the United States, these activities make up
51percent of activities in the economy accounting for
almost $2.7trillion in wages. They are most prevalent
in manufacturing, accommodation and food service,
and retail trade, and include some middle-skill jobs.
the pace and extent of automation. Continued
technical progress, for example in areas such
as natural language processing, is a key factor.
Beyond technical feasibility, the cost of technology,
competition with labor including skills and supply and
demand dynamics, performance benefts including
and beyond labor cost savings, and social and
regulatory acceptance will affect the pace and scope
of automation. Our scenarios suggest that half of
today’s work activities could be automated by 2055,
but this could happen up to 20years earlier or later
depending on the various factors, in addition to other
wider economic conditions.
machines to produce the growth in per capita GDP
to which countries around the world aspire. Our
productivity estimates assume that people displaced
by automation will fnd other employment. The
anticipated shift in the activities in the labor force is
of a similar order of magnitude as the long-term shift
away from agriculture and decreases in manufacturing
share of employment in the United States, both of
which were accompanied by the creation of new types
of work not foreseen at the time.
are relatively clear, but the issues are more
complicated for policy-makers. They should embrace
the opportunity for their economies to beneft from the
productivity growth potential and put in place policies
to encourage investment and market incentives to
encourage continued progress and innovation. At the
same time, they must evolve and innovate policies
that help workers and institutions adapt to the impact
on employment. This will likely include rethinking
education and training, income support and safety
nets, as well as transition support for those dislocated.
Individuals in the workplace will need to engage
more comprehensively with machines as part of their
everyday activities, and acquire new skills that will be
in demand in the new automation age.
Automation will boost global
productivity and raise GDP
G19 plus Nigeria
Five factors affecting pace and
extent of adoption
12345
TECHNICAL
FEASIBILITY
Technology
has to be
invented,
integrated,
and adapted
into solutions
for specic
case use
COST OF
DEVELOPING
AND
DEPLOYING
SOLUTIONS
Hardware
and software
costs
LABOR
MARKET
DYNAMICS
The supply,
demand, and
costs of
human labor
affect which
activities will
be automated
ECONOMIC
BENEFITS
Include higher
throughput
and increased
quality,
alongside
labor cost
savings
REGULATORY
AND SOCIAL
ACCEPTANCE
Even when
automation
makes
business
sense,
adoption can
take timeLast 50 yearsNext 50 yearsGrowth aspirationNext 50 years Potential impact of automation
1.7
1.8
2.8
0.10.10.1
Required to
achieve
projected growth
in GDP per capita
Historical
2.93.5
0.8
1.4
Early
scenario
Late
scenario
0.91.5
Productivity growth, %
Automation can help provide some of the productivity needed
to achieve future economic growth
Employment growth, %
will slow drastically because of aging
204020302050206020652020
100
80
60
40
20Scenarios around time spent on current work activities, %
Adoption, Early scenarioAdoption, Late scenarioTechnical automation potential, Early scenarioTechnical automation potential, Late scenario
Technical,
economic,
and social
factors affect
pace of
adoption
Technical
automation
potential
must precede
adoption
Technical automation potential by adapting currently demonstrated technologies
A global force that will transform economies and the workforce
Labor associated with technically
automatable activities
Million full-time equivalents (FTEs)
Remaining
countries China
Japan
India
Big 5 in Europe1
United States
1 France, Germany, Italy, Spain, and the United Kingdom.
332
54
394
60
35
233
100% =
1.1B
Wages associated with technically
automatable activities
$ trillion
India1.1
Japan
1.7
Big 5 in Europe1
China1.1
5.1
4.1
United States
2.7Remainingcountries
100% =
$15.8T
About 60% of occupations have
at least 30% of their activities
that are automatable
<5% of occupations consist
of activities that are
100% automatable
While few occupations are fully automatable, 60 percent of all occupations
have at least 30 percent technically automatable activities
Technical automation potential
%
Share of roles
100% = 820 roles1030
40
50
60
70
80
90
100
0102030405060708090100
ACTIVITIES WITH HIGHEST
AUTOMATION POTENTIAL:
Predictable physical activities 81%
Processing data 69%
Collecting data 64%
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