Automation has the potential to impact over 50% of activities across the global economy. While certain occupations such as assembly line workers and food service workers have high potential for automation due to predictable physical activities, most occupations will see only some activities automated. The pace and extent of automation will be determined by factors like technology progress, labor costs, and social acceptance. If realized to its full potential, automation could boost global productivity and GDP growth, but also risks some job and wage losses without appropriate policies to support retraining and new job creation.

1. AI Frontiers presentation | January 2017
A FUTURE THAT WORKS:
AUTOMATION, EMPLOYMENT, AND PRODUCTIVITY
CONFIDENTIAL AND PROPRIETARY
Any use of this material without specific permission of McKinsey & Company is strictly prohibited

2. 2McKinsey & CompanySOURCE: Source
What is the technical potential of
automation in the workplace?

3. 3McKinsey & Company
Our approach focuses on activities and the capabilities of currently demonstrated technologies
SOURCE: Expert interviews; McKinsey analysis
NOTE: Analysis based on currently available of demonstrated technology capabilities as of 2016.
Occupations
Retail salespeople Social1
Linguistic2
Cognitive3
Sensory perception4
Physical5▪ ...
▪ …
▪ …
~800 occupations
Teachers
Health practitioners
Food and beverage
service workers
Activities
Greet customers
▪ ...
▪ …
▪ …
Process sales and
transactions
~2,000 activities assessed
across all occupations
Clean and maintain work
areas
Demonstrate product
features
Answer questions about
products and services
?
Capabilities
Based on currently demonstrated
technology capabilities as of 2016

4. 4McKinsey & Company
Most susceptible activities
▪ 51% of US economy
▪ $2.7 trillion in wages
Some activities have higher technical automation potential
7 14 16 12 17 16 18
Process
data
Predictable
physical
Collect
data
Manage Expertise Interface Unpredictable
physical
Time spent on activities that can be automated by adapting currently demonstrated technology
%
9
18 20
26
64
69
81
Time spent
in all US
occupations
%
Total wages
in US, 2014
$ billion
596 1,190 896 504 1030 931 766
BASED ON DEMONSTRATED TECHNOLOGY

5. 5McKinsey & Company
Some sectors have more automatable activities than others
Time spent in US occupations, %
50 25 10 5 1
Ability to automate, %
0 50 100
Sectors by activity type
Manufacturing
Agriculture
Transportation and warehousing
Retail trade
Mining
Other services
Construction
Utilities
Wholesale trade
Finance and insurance
Arts, entertainment, and recreation
Real estate
Administrative
Health care and social assistances
Information
Professionals
Management
Accommodation and food services
Educational services
Manage InterfaceExpertise
Unpredictable
physical Collect data Process data
Predictable
physical
BASED ON DEMONSTRATED TECHNOLOGY
Automation
potential
44%
43%
49%
36%
41%
51%
53%
47%
39%
44%
40%
36%
35%
27%
35%
58%
73%
60%
57%
Most
automatable
Least
automatable
Inthemiddle

6. 6McKinsey & Company
Automation potential spans from high to low wage occupations
120100
60
4020
40
600
20
100
80
80
0
Hourly wage
$ per hour
Ability to technically automate
Percentage of time on activities that can be automated
by adapting currently demonstrated technology
BASED ON DEMONSTRATED TECHNOLOGY
File
clerks
Chief
executives
Landscaping and
grounds-keeping workers

7. 7McKinsey & Company
A small percentage of occupations can be fully automated by adapting current technologies, but
almost all occupations have some activities that could be automated
Example
occupations
100
91
73
62
51
42
34
26
18
81
>20>30>70 >50>80>90 >60100 >40
Percent of automation potential
% of roles
(100% =
820 roles)
>0%>10
SOURCE: US Bureau of Labor Statistics; McKinsey Global Institute analysis
 Sewing machine
operators
 Assembly line workers
 Stock clerks
 Travel agents
 Dental lab technicians
 Bus drivers
 Nursing assistants
 Web developers
 Fashion designers
 Chief executives
 Statisticians
 Psychiatrists
 Legislators
While about
5%
of occupations could have
100%
of tasks automated,
More will have portions of their tasks automated e.g.
60%
of occupations could have
30%
of tasks automated

8. 8McKinsey & Company
Automatability across economies
Employee weighted overall % of activities that can be automated
All countries could be fundamentally impacted by automation
<45 45–47 47–49 49–51 >51 No data
Employee weighted overall % of activities
that can be automated by adapting
currently demonstrated technologies

9. 9McKinsey & Company
Technical automation potential concentrated in countries with large populations and/or high wages
Wages associated with technically automatable activities
$ trillion
Labor associated with technically automatable activities
Million FTE
1.7
United States
Japan
China
Big 5 in Europe
2.7
1.1
4.1
India
1.1
Remaining
countries
5.1
United States
India
394
233
China
54
332
Big 5 in Europe
Remaining
countries
60
Japan
35
Potential impact due to automation, adapting currently demonstrated technology (46 countries)
100% =
$15.8 trillion
100% =
1,109 FTEs

10. 10McKinsey & CompanySOURCE: Source
What factors affect the pace and
extent of automation?

11. 11McKinsey & Company
Five factors impact the pace and extent of automation
Cost of labor
and related
supply-demand
dynamics
Benefits
including and
beyond
labor
substitution
Regulatory
and
social
acceptance
Technical
progression
Cost of
developing
and
deploying

12. 12McKinsey & Company
Pace of the automation, Global
% of time spent on activities that will potentially be automated
Pace and extent of automation could play out over decades
2016
Adoption Early scenario
Late scenario
Technical automation
potential
Early scenario
Late scenario
20
30
75
10
90
0
40
70
60
20
80
2100
50
90
100
85 95805525 655040 45 6035 7030

13. 13McKinsey & CompanySOURCE: Source
How will automation impact
productivity and economic growth?

14. 14McKinsey & Company
40
450
2515
270
05 202000 10 3530 6050
90
360
0
180
20706545 55
FTEs required to
maintain current GDP per capita
FTEs to achieve projected
GDP growth
Projected FTE
FTE automation output (United States example, 2000-2065)
Millions
Automation can contribute to growth in GDP per capita
Year
SOURCE: The Conference Board Total Economy Database; International Labor Organization; United Nations Population Division; McKinsey Global Institute analysis
FTEs
Automation will be a
significant contributor to
the productivity boost
needed to projected GDP
per capita growth
Assuming zero productivity growth, based on demographic
trends, the projected FTEs will be less than the FTEs
required to maintain current level of GDP per capita

15. 15McKinsey & Company
Benefits Challenges
Benefits and challenges of automation
 Better performance,
outcomes, quality, speed
 Overcome human limits,
Solve new problems,
create new opportunities
and innovations
 Improve safety, utility,
quality of life
For companies
and users
For economies
 Boost productivity
growth GDP growth, and
per capita GDP
 Counter aging or
shrinking workforce
 Solve “moonshot”
problems (e.g., climate)
 Jobs and wages
 Skills and training
 Dislocation and
transitions
 Acceptance and safety
Social and
economic
 Transparency, openness
and competition
 Cybersecurity
 Biases
 New capital-labor mix
implications
Other Policy
issues

16. 16McKinsey & Company
Imperatives for all
Policymakers IndividualsCompanies
▪ Embrace automation to
capture the benefits
▪ Create jobs and reshape
jobs the enable people to
work with machines
▪ Play role in redeploying
labor through retraining
and skill-raising programs
▪ Support development of
automation technologies
▪ Promote measures to raise
skills and promote job
creation
▪ Rethink incomes and
social safety nets
▪ Focus on acquiring skills
throughout lifetime
▪ Make education and career
choices, based on skills
that will still be in demand
in an automation world
▪ Become an AI scientist!

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