Artificial intelligence could significantly boost productivity in the U.S. federal workforce, potentially providing $532 billion in annual benefits by 2028. However, federal workers will need training to take full advantage of AI's benefits. The study found AI could automate around 30% of average federal workers' tasks by 2028 if investment increases as projected. To maximize AI's benefits, the document recommends federal agencies prioritize reskilling workers, aligning AI with strategic objectives, and ensuring accessible and trusted data.

1. WHEN, WHERE &
HOW AI WILL BOOST
FEDERAL WORKFORCE
PRODUCTIVITY –
And how federal agencies
can prepare

2. 2Copyright © 2020 Accenture. All rights reserved.
Accenture Research found Artificial Intelligence (AI)
could unleash a productivity windfall for the U.S. federal
government, worth up to $532 billion annually by 2028
However, federal workers need to be empowered to get
the most from AI for this to happen

3. Investment is projected to grow rapidly
AI IS A STRATEGIC PRIORITY FOR THE U.S.
FEDERAL GOVERNMENT
3Copyright © 2020 Accenture. All rights reserved.
According to IDC, the global public sector trails only the
media & entertainment industry in rate of AI investment
Source: IDC Worldwide Semiannual Artificial Intelligence Systems Spending Guide -2018H2 (published August 2019)
$0.00
$200.00
$400.00
$600.00
$800.00
$1,000.00
$1,200.00
2018 2019 2020 2021 2022 2023
U.S. Federal Government
Projected AI Systems Spending, in millions

4. Groundbreaking economic model quantified AI’s workforce impact across the G20
ACCENTURE RESEARCH FOUND PREVIOUSLY
THAT AI WILL BOOST WORKER PRODUCTIVITY
4Copyright © 2020 Accenture. All rights reserved.
of daily work activities will be
impacted by AI
Impact varies dramatically by role
90%
$11.5T
of GDP at risk across 14 G20
countries without effective reskilling
U.S. may forgo $975B in economic
growth over 10 years

5. Produce quantitative data to support strategic planning by
federal agencies
Create an economic value model using workforce, investment
and role-based functional data to forecast the anticipated
impact of AI on workforce productivity and roles
NEW STUDY DESIGNED TO ASSESS AI’S
IMPACT ON THE U.S. FEDERAL GOVERNMENT
5Copyright © 2020 Accenture. All rights reserved.
01. Analyzed occupations by tasks
02. Assessed the impact of AI on workers’ time
03. Collected data on workforce composition and
AI investment trends
04. Developed economic model using sourced data

6. AUTOMATABLE TASKS
Tasks that potentially can be performed
by machines (algorithms, programs,
robots, etc.) with minimal intervention
from human workers
E.g., Simple manual or routine tasks that
can be automated
NEW STUDY DESIGNED TO ASSESS AI’S
IMPACT ON THE U.S. FEDERAL GOVERNMENT
6Copyright © 2020 Accenture. All rights reserved.
Focused on two potential impacts:
AUGMENTABLE TASKS
Tasks that can be performed by human
workers more effectively through
upgraded core capabilities and/or the way
in which work is processed
E.g., Cognitive tasks that can be
augmented with intelligent technologies
to inform or improve decision-making

7. 0
200
400
600
800
1,000
1,200
2018 2021 2023 2028
AI IS POISED TO BOOST U.S. FEDERAL
WORKFORCE PRODUCTIVITY DRAMATICALLY
7Copyright © 2020 Accenture. All rights reserved.
U.S. federal government can gain $364B or more of value-added productivity by
investing in AI and reskilling its workforce 1
Source: Accenture Research analysis of US federal government employment data, BEA, Oxford Economics and
IDC Worldwide Semiannual Artificial Intelligence Systems Spending Guide -2018H2 (published August 2019)
If the U.S. federal government
invests in AI as forecasted and
provides necessary workforce
training programs, it could gain
up to $364B in additional value-
added (VA) productivity by 2028
U.S.$Billions
$84.4
$143
$364
Baseline VA Additional VA due to impact of AI

8. 0
100
200
300
400
500
600
INCREASING AI INVESTMENTS CAN
PRODUCE EVEN GREATER IMPACT
8Copyright © 2020 Accenture. All rights reserved.
Accelerated spending can yield up to $532B of value-added productivity 2
U.S.$Billions
Slow investment
(20% CAGR)
2021 2023 2028
Baseline investment
(31% CAGR)
Intensive investment
(40% CAGR)
Source: Accenture Research analysis of US federal government employment data, BEA, Oxford Economics and
IDC Worldwide Semiannual Artificial Intelligence Systems Spending Guide -2018H2 (published August 2019)

9. ROLE CLUSTERS WERE USED TO ASSESS
AI’S IMPACT ACROSS THE WORKFORCE
9Copyright © 2020 Accenture. All rights reserved.
Empirical groupings of common work tasks & skillsets used to identify 10 role
clusters; workers within each cluster will feel similar impact
Management & leadership Supervises and makes decisions Human resources managers, purchasing managers
Empathy & support Provides expert support and guidance Registered nurses, occupational therapists
Science & engineering Conducts deep, technical analysis Economists, environmental engineers
Process & analysis Processes and analyzes information
Bookkeeping, accounting and auditing clerks,
construction and building inspectors
Analytical subject-matter expertise Examines and applies experience with complex
systems
Detectives and criminal investigators, financial
examiners
Relational subject-matter expertise Applies expertise in environments that demand
human interaction
Tax examiners and collectors, revenue agents
Technical equipment maintenance Installs and maintains equipment and
machinery
Aircraft mechanics and service technicians,
maintenance workers
Machine operation & maneuvering Operates machinery and drives vehicles Firefighters, bus drivers, forklift operator
Physical manual labor Performs strenuous physical tasks in specific
environments
Packers and packagers, cleaners of vehicles and
equipment
Physical services Performs services that demand physical
activity
Cooks, personal care and service workers
ROLECLUSTER TYPICALACTIVITIES ILLUSTRATIVEOCCUPATIONS

10. EXPERTS RATED CORE TASKS FOR AI’S
POTENTIAL TO AUTOMATE OR AUGMENT
10Copyright © 2020 Accenture. All rights reserved.
More than three hundred activities assessed overall
AUGMENTABLE AUTOMATABLE NO IMPACT
• Respond to customer
problems or inquiries
• Perform recruiting or hiring
activities
• Consult legal materials or
public records
• Analyze market or industry
conditions
• Notify others of emergencies
or problems
• Research historical or social
issues
• Process digital or online data
• Compile records,
documentation, or other data
• Collect fares or payments
• Gather information from
physical or electronic sources
• Calculate financial data
• Perform administrative or
clerical activities
• Communicate with others
about operational plans or
activities
• Confer with clients to
determine needs or order
specifications
• Counsel others about
personal matters
• Direct scientific or technical
activities
• Discuss legal matters with
clients, disputants, or legal
professionals or staff

11. 29%
36%
37%
47%
48%
48%
49%
49%
51%
59%
49%
53%
54%
34%
41%
27%
34%
39%
24%
39%
19%
34%
18%
10%
29%
12%
25%
17%
12%
25%
11%
22%
17%
Physical Manual Labor
Process and Analysis
Technical Equipment Maintenance
Relational Subject-Matter Expertise
Machine Operation and Maneuvering
Physical Services
Management and Leadership
Science and Engineering
Analytical Subject-Matter Expertise
Empathy and Support
All occupations
AI’S BIGGEST POTENTIAL WORKFORCE
IMPACT IS AUGMENTING TASKS
11Copyright © 2020 Accenture. All rights reserved.
Percentage of worker time potentially augmented / automated by AI
Source: Accenture Research analysis of US federal government employment data
Note: Weighted average across occupation
Proportion of
worker time that
is augmentable
Proportion of
worker time that
is automatable
Proportion of
worker time not
impacted

12. 3%
4%
4%
5%
6%
6%
6%
6%
6%
7%
6%
25%
32%
32%
41%
42%
43%
43%
45%
45%
52%
44%
6%
6%
4%
5%
3%
4%
4%
3%
4%
2%
4%
47%
47%
30%
36%
24%
30%
34%
21%
34%
17%
30%
18%
10%
29%
12%
25%
17%
12%
25%
11%
22%
17%
Physical Manual Labor
Process and Analysis
Technical Equipment Maintenance
Relational subject-matter expertise
Machine Operation and Maneuvering
Physical Services
Management and Leadership
Science and Engineering
Analytical subject-matter expertise
Empathy and Support
All occupations
AI HAS MODEST IMPACT (10%) ON MOST
ROLES THROUGH 2021
12Copyright © 2020 Accenture. All rights reserved.
Percentage of federal worker time potentially augmented /
automated by AI over 3 years (2018-2021) 3
Source: Accenture Research analysis of US federal government employment data and IDC Worldwide
Semiannual Artificial Intelligence Systems Spending Guide – 2018H2 (published August 2019)
Note: Weighted average across occupation
Proportion of worker time
that is augmentable in 3 years
Proportion of worker time
that is automatable in 3 years
Proportion of worker time not
impacted
Proportion of worker time
that is augmentable beyond
the 3-year horizon
Proportion of worker time
that is automatable beyond
the 3-year horizon

13. 10%
13%
13%
17%
17%
17%
18%
18%
18%
21%
18%
18%
23%
24%
30%
31%
31%
32%
32%
33%
38%
32%
19%
19%
12%
15%
10%
12%
14%
9%
14%
7%
12%
34%
34%
22%
26%
17%
22%
25%
15%
25%
12%
22%
18%
10%
29%
12%
25%
17%
12%
25%
11%
22%
17%
Physical Manual Labor
Process and Analysis
Technical Equipment Maintenance
Relational subject-matter expertise
Machine Operation and Maneuvering
Physical Services
Management and Leadership
Science and Engineering
Analytical subject-matter expertise
Empathy and Support
All occupations
AI MAY IMPACT 30% OF AVERAGE
FEDERAL WORKER’S TIME BY 2028
13Copyright © 2020 Accenture. All rights reserved.
Source: Accenture Research analysis of US federal government employment data and IDC Worldwide
Semiannual Artificial Intelligence Systems Spending Guide – 2018H2 (published August 2019)
Note: Weighted average across occupation
Percentage of federal worker time potentially augmented/
automated by AI over years (2018-2028) 4
Proportion of worker time that
is augmentable in 10 years
Proportion of worker time that
is automatable in 10 years
Proportion of worker time not
impacted
Proportion of worker time
that is augmentable beyond
the 10-year horizon
Proportion of worker time
that is automatable beyond
the 10-year horizon

14. MOST FEDERAL WORKERS ARE IN
HIGHLY AUGMENTABLE ROLES
14Copyright © 2020 Accenture. All rights reserved.
Upskilling efforts would create value for both business and people 5
Source: Accenture Research analysis of US federal government employment data
Analytical subject-
matter expertise
Empathy and
Support
Machine Operation and Maneuvering
Management and
Leadership
Physical Manual
Labor
Physical Services
Process and Analysis
Relational subject-
matter expertise
Science and
Engineering
Technical Equipment
Maintenance
25%
30%
35%
40%
45%
50%
55%
60%
10% 20% 30% 40% 50% 60% 70%
Workertimepotentiallyaugmented
Worker time potentially automated
35%
43%
Highly-augmentable role
Human-centered role
Highly-automatable role
Note: Weighted average across occupation
Note: Size of bubbles reflects
size of workforce

15. 0
10
20
30
40
50
60
70
80
2021 2023 2028
U.S.$Billions
Source: Accenture Research analysis of US federal government employment data, BEA, Oxford Economics and
IDC Worldwide Semiannual Artificial Intelligence Systems Spending Guide -2018H2 (published August 2019)
$66B OF AI BENEFITS ARE AT RISK
WITHOUT EFFECTIVE TRAINING
15Copyright © 2020 Accenture. All rights reserved.
U.S. federal government may forgo $66B in productivity improvements 6
U.S. federal government
risks losing up to $66.46B
of projected value-add
over ten years if it fails to
effectively upskill/reskill
the workforce for AI.
$15.32B
$26B
$66.46B

16. An earlier Accenture study found that while federal workers are confident in their
personal readiness for AI, a majority have concerns over lack of clarity
FEDERAL WORKFORCE SEEKS HELP RESKILLING
16Copyright © 2020 Accenture. All rights reserved.
are confident their technical skills and
abilities make them an attractive worker
in a “government of the future”
said their agency has
communicated the potential
impact of AI poorly or very poorly
were worried about lack of
technical support and user training
78%
But
73%
61%

17. 22%
26%
35%
38%
39%
39%
40%
42%
44%
46%
48%
48%
51%
52%
63%
44%
49%
43%
41%
43%
35%
48%
37%
39%
40%
44%
36%
34%
33%
40%
29%
21%
37%
34%
35%
33%
22%
26%
13%
24%
21%
18%
12%
18%
18%
18%
8%
19%
16%
19%
17%
Agriculture
Accommodation and food service
Manufacturing
Construction
Transportation and storage
Mining and quarrying
Utilities
Business services
Trade
Arts, recreation, unions, etc
ICT
Public admin. and soc. security*
Financial activities
Human health and social work
Education
All industries
US Federal Government
AI’S PRODUCTIVITY IMPACT WILL VARY
DRAMATICALLY ACROSS INDUSTRIES
17Copyright © 2020 Accenture. All rights reserved.
U.S. federal government trails only education, health & social work, and financial
activities in potential augmentable impact within the U.S.
Note: Weighted average across occupation
Source: Accenture Research analysis of US federal government and BLS employment data
* Public administration
and social security
sector comprises also
Federal government
Proportion of
worker time that
is augmentable
Proportion of
worker time that
is automatable
Proportion of
worker time not
impacted

18. SECTORS WITH CONSULTATIVE & ANALYTICAL
ROLES MOST IMPACTED BY AUGMENTATION
18Copyright © 2020 Accenture. All rights reserved.
Percentage of worker time potentially augmented / automated by AI by industry
Source: Accenture Research analysis of US federal government and BLS employment data
Agriculture
Accommodation and food service
Manufacturing
Construction
Transportatio…
Mining and
quarrying
Utilities
Business services
Trade
Arts, recreation,…
ICT
Public admin.…
Financial activitiesHuman health and
social work
Education
US Federal government
15%
25%
35%
45%
55%
65%
75%
15% 20% 25% 30% 35% 40% 45% 50% 55%
Proportion of work subject to automation
Proportionoftimesubjecttoaugmentation
Note: Size of
bubbles reflects
size of workforce
Note: Weighted average across occupation

19. ACTION 01:
Emphasize Training
Provide access to more
continuous and targeted
training to give workers
the skills needed to make
the most of AI
MAKING THE MOST OF AI
19Copyright © 2020 Accenture. All rights reserved.
Three actions would greatly empower federal workers and executives to maximize
the benefits of artificial intelligence
ACTION 02:
Prioritize Strategy
Work with program leaders to
prioritize strategic mission and
business objectives that can be
advanced with AI, and don’t overlook
frontline workers as they are often
the source of the most valuable ideas
ACTION 03:
Rethink Data
Ensure data is readily
accessible, trusted and
relevant to power the
mission while exploring
new ways to augment

20. CHRISTINA BONE
Senior Manager,
Growth & Strategy
Accenture Federal Services
20Copyright © 2020 Accenture. All rights reserved.
Accenture.com/FederalAIBoom
EXPLORE FURTHER
IRA ENTIS
Managing Director and
Growth & Strategy Lead
Accenture Federal Services
BRYAN RICH
Managing Director and
Applied Intelligence Lead
Accenture Federal Services
SANGITA SHAHA
Senior Manager,
Growth & Strategy
Accenture Federal Services
KRISTEN VAUGHAN
Managing Director and
Human Capital Lead
Accenture Federal Services

21. 21
ENDNOTES
Copyright © 2020 Accenture. All rights reserved.
1 Scenario is based on forecasted AI investments by the U.S. federal government: $599.7M in 2021, $976.2M in 2023 and
$3,762.5M in 2028 (Investment source: IDC - 2018-2023; Accenture Research estimate – 2028)
2 Scenarios are based on assumptions of investments in AI by the U.S. federal government in terms of CAGR of AI
investment per worker
• Baseline scenario is 31% CAGR (based on IDC forecast) with total investment reaching $3.8B in 2028
• Intensive investment is 40% CAGR with total investment reaching $7.4B in 2028
• Slow investment is 20% CAGR with total investment reaching $1.6B in 2028
3 Scenario is based on forecasted AI investments by the U.S. federal government: $599.7M in 2021
4 Scenario is based on assumption about CAGR of AI investment per worker: it is assumed at 31% (as in 5-year IDC
forecast) and level reaches $3762.5M in 2028
5 Quadrants defined according to the average worker; worker time augmentation and automation refers to
maximum possible impact
6 Scenario is based on forecasted AI investments by the U.S. federal government: $599.7M in 2021, $976.2M in 2023
and $3,762.5M in 2028
Planning assumptions and scenarios used in specific analysis

22. Accenture Federal Services, a
wholly owned subsidiary of
Accenture LLP, is a U.S. company
with offices in Arlington, Virginia.
Accenture’s federal business has
served every cabinet-level
department and 30 of the largest
federal organizations. Accenture
Federal Services transforms bold
ideas into breakthrough outcomes
for clients at defense, intelligence,
public safety, civilian and military
health organizations. Visit us at
www.accenturefederal.com.
About Accenture Federal
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