FREESUMMARY
Feder
alAr
t
i
fici
al
I
nt
el
l
i
gence
Landscape,
2021
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Federal Market Analysis
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1
Deltek’s Federal Artificial Intelligence Landscape, 2021 assesses
the state of Artificial Intelligence (AI) and Machine Learning (ML)
adoption within the federal government. The report takes an in-depth
look at the factors shaping the strategic and budgetary priorities
governing artificial intelligence procurement.
This report provides:
»
»
»
»
About This Report
»
Analysis of the emerging AI policies and guidance directing the
federal government’s strategic direction.
Insight into planned and requested budgets for AI initiatives.
Analysis of AI contracting patterns to date.
Use cases of early AI efforts and insight into potential
opportunities.
Recommendations to help contractors maximize opportunities
within the federal AI space.
Report Deliverables
»
»
»
Federal Market Analysis
128 - slide PowerPoint® Report
34 - slide PowerPoint® Executive Summary
Excel® Workbook
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2
© Deltek, Inc. All Rights Reserved.
» Introduction
» Artificial Intelligence Policy
Landscape
» Artificial Intelligence Budget
Environment
» Artificial Intelligence
Investment Trends
Table of Contents
» Artificial Intelligence Use
Cases and Opportunities
» Conclusions and
Recommendations
» Appendix
To purchase the full report visit GovWin.com
Key Findings
» Agency applications of artificial intelligence based on machine learning technology is accelerating, focusing on
cyber offense and defense, robotics and autonomy, border security and health care.
» Agencies are investing in artificial intelligence solutions, especially those that support services, to improve
mission effectiveness, make evidence-based decisions and automate repetitive tasks.
» The National Science Foundation’s FY 2021 budget request of $850M supports AI research and use for agency
mission advancement while also promoting U.S. leadership in the technology. Agencies beyond the NSF are
identifying additional funds to pilot AI projects.
» Federal AI policies have evolved from vision-based initiatives to action-oriented guidance. Recent policies such
as NITRD’s updated AI R&D Strategy, the First Year Action Plan and NIST’s AI standards development plan,
place emphasis on specific steps agencies should take to advance the research, understanding and adoption
of AI.
» Although many of the larger, more visible AI investments are occurring at NASA and across the DOD, multiple
civilian agencies are also investing in AI pilot projects, such as the IRS’ AI Pilot initiative and HHS’ Intelligent
Automation/Artificial Intelligence (IAAI) solutions contract.
» Spending in AI has expanded beyond science-focused agencies typically viewed as front-runners in the use of
emerging technology. Investments across diverse agencies, such as the State Department, Transportation and
Agriculture have grown from isolated prototypes to well-funded and established programs.
Federal Market Analysis
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4
Federal Artificial Intelligence Policy Landscape
EO 13859: Maintaining
Leadership in AI
Infrastructure and Technology
FY 2020 NDAA
(Becomes Law)
GSA’s AI Center of
Excellence Announced
American AI
Initiative: Year One
Report
National AI R&D
Strategic Plan Update
AI in Government
Act and AI Initiative
Act (Introduced)
NIST Draft
Adversarial
Machine Learning
2019
Jan Feb
Mar
Apr
May
Jun
Jul
NIST Guidance to
Agencies in AI
Technical Standards
Development
Federal Market Analysis
2020
Aug
Sep
Oct
Nov
NITRD 2016-2019
Progress Report
2nd White House
AI Summit
Dec
Jan
Feb
Mar
Apr
May
Jun
OMB Memo to
Agencies on
Regulating AI
First Year
Action Plan
under Federal
Data Strategy
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AI in Federal
Administrative
Agencies Report
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5
Update: National AI R&D Strategic Plan
In June 2019, the Networking and Information Technology Research and Development (NITRD) Select Committee on AI released
an update to the 2016 National AI R&D Strategic Plan. The update includes additional focus areas under each of the original
strategies to reflect priorities from the past three years. The update also adds an eighth strategy, placing emphasis on the
strength of private-public relationships, recognizing the fast rise of privately funded and rapid adoption of AI by industry.
Shared Public Datasets and Training/
Testing Environments
Long-Term AI Research Investments
Knowledge discovery, AI system
capabilities, scalability, hardware
Data accessibility, training and testing
environments, open source software
Human-AI Collaboration
AI Standards and Benchmarks
Human-aware AI, human augmentation,
visualization and interfaces, NLP systems
.
8 AI R&D
Strategies
AI standards, testbeds, community
engagement in standards development
Ethical, Legal and Societal Implications
AI R&D Workforce Needs
Fairness, transparency, accountability,
ethical design/build
Needs of those working on and alongside
AI systems
AI System Safety and Security
Public-Private Partnerships
Trust, verification and validation, security
Advancing the AI innovation ecosystem
Federal Market Analysis
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6
NITRD AI Progress Report
In November 2019,
NITRD delivered a
progress report to
underscore the
progress agencies have
made AI R&D. The
progress report outlines
examples of individual
agency programs,
organized by the eight
strategies from the AI
R&D Strategic Plan.
Overall, the report finds
that the federal
government is
substantially investing
in a depth of AI
concepts, benefitting
greatly by the diversity
of those investments,
and have reached
breakthroughs in AI
R&D to revolutionize
the nation.
Federal Market Analysis
Long-term
investments
Human-AI
Collaboration
Ethical, Legal
Implications
System Safety
and Security
Shared Public
Datasets
Standards and
Benchmarks
R&D Workforce
Needs
Public-Private
Partnerships
NIH National Library of Medicine
Developed DeepSeeNet, an AI algorithm to help the screening of age-related
eye disease, saving hours of manual work by doctors.
Defense Advanced Research Projects Agency
The Explainable AI (XAI) program aims to designs systems to explain their
reasoning in understandable terms.
National Science Foundation
The agency performed various studies on systems exhibiting discriminatory
behavior by using AI systems with built-in quantitative measures of fairness.
Department of Energy
Researchers instilled big data with reinforcement learning to train an AI
system to detect cyber threats, succeeding in rapidly detecting new threats.
NASA
The NASA’s Earth eXchange-AI (NEX-AI) is an extension of NASA’s large
public database, making predictions from the data with deep learning.
National Institute of Standards and Technology
The Materials Genome Initiative references a set of data and AI techniques to
help crease advanced materials for manufacturing.
National Science Foundation
Developed a new Advanced Placement exam in Computer Science Principles,
with a curriculum and associated teacher professional development.
Department of Veterans Affairs
Implemented an AI Tech Sprint with a U.S.-international health tech firm to
link companies to federal data and create cutting-edge data tools.
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7
GSA’s Artificial Intelligence Center of Excellence
GSA’s Technology Transformation Service created a sixth Center of Excellence (CoE) to help agency partners employ AI
technologies. The AI CoE enables agencies to “develop AI solutions to meet unique business challenges by incorporating machine
learning, computer vision, natural language processing, intelligent process design, and robotic process automation.”
AI CoE Service Catalog
» AI Assessment of
Government and Enablers
AI CoE Benefits
»
»
» Use Case Discovery and
Selection
»
» Workflow Mapping and
Process Automation
»
» Lean Innovation Process
Design
» AI Solutions Identification
and Implementation
Federal Market Analysis
»
»
»
»
»
Increase agility of acquisition
processes to adopt AI
Understand true cost of
ownership
Establish customer-centric
approach
Identify unknown trends and
patterns
Transition to high-value work
Increase labor hour capacity
Develop library of reusable tools
Reduce time to task completion
Promote AI best practices
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AI CoE Agency Partners
DOD Joint AI Center (JAIC)
The CoE is helping JAIC
Stand-Up
implement new
acquisition
New AI such
methods for AI capabilities
as enterprise-scale
DevSecOps
CoE
and data integration.
Department of Labor
The CoE aids Labor in
improving acquisition methods
for robotics process automation
and AI.
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8
Addressing Adversarial Machine Learning (AML)
In October 2019, NIST's National Cybersecurity Center of Excellence (NCCoE) released a draft report A Taxonomy
and Terminology of Adversarial Machine Learning in an effort toward securing AI applications against adversarial
manipulations by developing a taxonomy and terminology of Adversarial Machine Learning (AML). The taxonomy
is arranged in a conceptual hierarchy that includes key types of attacks, defenses and consequences. Details of
each dimension in the taxonomy are summarized in sections below.
Future AI Standards
The terminology and
taxonomy are intended to
inform future standards and
best practices for assessing
and managing the security
of AI and ML components
by establishing a common
language and
understanding of the rapidly
developing AML landscape.
Source: NIST
Federal Market Analysis
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9
AI-Related Provisions in the FY 2020 NDAA
The National Defense Authorization Act for Fiscal Year 2020 became Public Law No: 116-92 on December 20, 2019.
Sec. 212: Updates to the Department of
Defense Personnel Management Authority to
Attract Experts in Science and Engineering
»
Provides 5 new scientific and engineering positions for the DOD’s Joint Artificial
Intelligence Center and gives the Director the authority to recruit experts to fill
those positions.
»
Directs the Secretary of Defense to develop a strategy for educating service
members in relevant fields on matters relating to artificial intelligence.
»
The strategy should include a curriculum covering AI design; software coding;
potential military applications for AI; the impact of AI on military strategy and
doctrine; AI decision-making via machine learning and neural networks; ethical
issues relating to AI; the potential biases of AI; potential weaknesses in AI
technology; AI opportunities and risks; and any other matters the Secretary
determines to be relevant.
Sec. 260: Biannual Report on the Joint Artificial
Intelligence Center
»
Instructs the Secretary of Defense to submit a report to congressional defense
committees on the activities and investments of the Joint Artificial Intelligence
Center every 2 years through FY 2023.
Sec. 1735: Extension of the National Security
Commission on Artificial Intelligence
»
Extends the National Security Commission on Artificial Intelligence from October
1, 2020 to October 1, 2021.
Sec. 5711: Analysis of Periodic Briefings on
Major Initiatives of Intelligence Community in
Artificial Intelligence and Machine Learning
»
Directs the Director of National Intelligence to submit analysis of major artificial
intelligence and machine learning initiatives in the intelligence community to
congressional intelligence committees, with biannual briefings to provide an
update on those initiatives through FY 2023.
Sec. 256: Artificial Intelligence Education
Strategy
Federal Market Analysis
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10
Draft Agency Regulations of Industry AI
OMB issued the draft Guidance for Regulation of
Artificial Intelligence Applications for public
comment in January 2020. The guidance
stipulates the considerations federal agencies
should take into account when forming regulatory
and non-regulatory methods in the design,
creation and implementation of AI systems. Public
comments were collected through March 13th.
» In potential non-regulatory instances, the
memo directs agencies to consider approaches
such as existing statuary authority, pilot
programs and consensus standards in their
use of AI.
» In cases of regulatory approaches, the draft
memo describes ten principles agencies should
consider when it comes to AI:
Federal Market Analysis
Benefits and
Costs
Public Trust in
AI
Public
Participation
Scientific
Integrity and
Information
Quality
Safety and
Security
Flexibility
Risk
Assessment
and
Management
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Fairness and
NonDiscrimination
Interagency and
Coordination
Disclosure and
Transparency
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11
American AI Initiative: Year One Progress
Report
February 2019, President Trump launched the American AI Initiative promoting U.S. leadership in AI. A year later the
White House OSTP published a progress update, highlighting the key areas of emphasis and progress.
Invest in AI R&D
»
»
»
»
2-year doubling of
non-defense AI
R&D in the FY
2021 budget
Updated AI R&D
strategic plan
Developed the
first progress
report on the
impact of federal
R&D investments
Published the
first-ever reporting
of governmentwide non-defense
AI R&D spending
Unleash AI
Resources
»
»
Federal Market Analysis
Called federal
agencies to
identify new
opportunities to
increase access
to and use of
federal data and
models
OMB established
the Federal Data
Strategy as a
framework for
operational
principles and
best practices
Remove Barriers
to AI Innovation
Proposed AI
Regulatory
Principles aimed at
advancing
innovation NIST
issued the first-ever
strategy for federal
engagement in the
development of AI
technical standards
Train an AI-ready
Workforce
»
»
All federal
agencies directed
to prioritize AIrelated
apprenticeship
and job training
programs
NSF’s new
National AI
Research
Institutes program
will contribute to
workforce
development,
particularly of AI
researchers
Promote
International
Support of U.S. AI
Innovation
»
»
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U.S. led efforts at
the OECD to
develop the first
international
agreements on
principles for
trustworthy AI.
U.S. also worked
with its
international
partners in the G7
and G20 to adopt
similar AI
principles
Leverage AI for
Government
Services and
Missions
GSA established
an AI Center of
Excellence to
enable agencies to
determine best
practices for
incorporating AI
into their
organizations
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12
Review of Agency AI Use – Progress and
Challenges
In February 2020, the Administrative Conference of the United States (ACUS) released a report Government by
Algorithm: Artificial Intelligence in Federal Administrative Agencies, conducted by researchers at Stanford University
and New York University that examined how agencies are currently using AI systems. Findings include:
Depth and Breadth
Early Stages
Nearly half of the federal agencies studied (45%) have experimented with AI and related ML tools.
Moreover, AI tools are already improving agency operations across the full range of governance tasks.
Despite wide agency embrace of AI, the government still has a long way to go. The study
rated only 12% of agency use cases as high in sophistication, which could limit the ability to
realize gains in accuracy and efficiency and widen the public-private technology gap.
Accountability Challenges
Internal Technical Know-how
The law generally requires agencies to explain any denial-of-benefit decisions, etc. Yet many AI
tools are not fully explainable. A crucial question is how to subject such tools to meaningful
accountability and fidelity to legal norms of transparency, rationale and non-discrimination.
While many agencies rely on private contractors to build out AI capacity, 53% of use
cases are the product of in-house efforts by agency technologists. This underscores the
critical importance of internal agency capacity building as AI continues to proliferate.
Growing agency use creates a risk that AI systems will be gamed by groups with greater
Risk of Manipulation & Resistance resources and know-how that allow them to reverse-engineer the agency’s model to their
advantage. Any perception of rigged systems will erode public support of agency AI use.
Federal Market Analysis
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13
AI in the FY 2021 Budget Request
The budget supports AI research and use AI for agency mission advancement, while also promoting U.S.
leadership in the AI domain in order to maintain national and economic security.
Policies
Supporting AI
Cited in the
Budget
» Executive Order “Maintaining American Leadership in Artificial Intelligence” released in February 2019
directing agencies to prioritize AI investments in their R&D programs.
» PMA initiative for Modernizing Government for the 21st Century has led to a number of agency efficiency
projects, including 30 initiatives using robotic process automation, artificial intelligence, and/or other
innovative software.
Agency Specifics
National
Science
Foundation
» $850M for AI R&D at the National Science
Foundation, a 70% increase over FY 2020.
» Includes creation of several National AI
Research Institutes, in collaboration with
USDA, DHS, Transportation, and VA.
Agriculture
» Provides an additional $100M for AI and ML
grants to promote advanced manufacturing in
the food and agricultural sciences, including
robotics and big data sciences.
Energy
Other
» $5M for Energy’s new Artificial Intelligence
and Technology Office to provide departmentwide guidance and oversight and to enhance
AI R&D projects already underway.
The following agency budget summaries
mention AI, but provide no specific funding
amounts:
» Commerce
» Defense
Federal Market Analysis
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14
AI in DOD’s FY 2021 RDT&E and Procurement Budget Requests
Observations
Sources: FY 2021 DOD Budget Request, Deltek
» DOD’s proposed total RDT&E and Procurement funding
for programs with an AI and ML component averages
$2.25B per year from FY 2021 to FY 2025.
» AI and ML-related funding in DOD’s FY 2021 Procurement
budget is $114.5M with Army ($53.2M) and the Defense
Agencies ($11.6M) requesting the highest amounts. Navy
and Air Force requested $3.9M and $3.3M, respectively.
Federal Market Analysis
» DOD’s total FY 2021 request for AI and ML-related RDT&E
project funding is $3.3B. Defense Agencies requested the
highest amount ($1.4B), followed by Army ($684M), Navy
($662M) and Air Force ($564M).
» Applied Research continues to attract the highest AI and
ML-related funding in FY 2021 ($928.3M). DOD also
requested $296.6M on related Software and Digital
Technology Pilot Programs and $95.6M for
Communications and Electronics Equipment related to AI
and ML initiatives.
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15
Sample AI Procurement Opportunities
Agency
Name
AIR FORCE
AIR FORCE
AIR FORCE
AIR FORCE
ARMY
ARMY
Development of Weather Data Processing Software
and Web Services
C4ISR Technical and Engineering Research and
Sustainment Support
Health Care Information Management Information
Technology Support Services for HQ PACAF SG
Global Theater Security Cooperation Management
Information System Phase 3 (G-TSCMIS)
USACE Development and Application of Predictive
Mathematical Models
Artificial Intelligence Systems for Innovative
Manufacturing
Status
Value
($K)
Est.
RFP
Date
Est.
Award
Date
Opp
ID
Pre-RFP
35,000
11/2020
03/2021
178089
Forecast Pre-RFP
79,001
02/2022
06/2022
178856
Forecast Pre-RFP
17,349
10/2020
02/2021
165418
Forecast Pre-RFP
TBD
10/2020
06/2021
185518
Forecast Pre-RFP
7,000
03/2021
09/2021
161006
Pre-RFP
TBD
08/2020
12/2020
189892
ARMY
Field Information Communications System
Pre-RFP
TBD
07/2020
10/2020
179297
NASA
Capital Area Information Technology Integration
Support Services (CAITISS)
Pre-RFP
206,000
11/2020
12/2021
189612
Source: Deltek
Federal Market Analysis
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16
Artificial Intelligence Contract Awards
Prominent AI Contract Awards
HHS
IAAI
Solutions
$49M
In May 2019, HHS established a new contract vehicle that offers AI, RPA, microservices,
machine learning and blockchain solutions, services and products. The contract vehicle is
called the Intelligent Automation/Artificial Intelligence (IAAI) solutions contract. The $49M
contract vehicle was awarded to 28 small businesses and 29 large businesses and is
designed so agencies can buy and scale across HHS. Ultimately, HHS wants to establish a
larger GWAC for these types of solutions. IAAI is a starting point.
In September 2019 IRS awarded contracts to five companies for the Pilot IRS initiative, which
will allow IRS to quickly deploy and test emerging technologies such as AI. Pilot IRS is
intended to promote innovative responses to the challenges that the IRS faces; to broadly
communicate IRS’s areas of interest in the innovative solutions and technologies arena; and to
create a streamlined progression from concept to prototype, testing, and limited deployment
that allows for incremental funding decisions for promising solutions and technologies.
Federal Market Analysis
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Treasury
Pilot IRS
$3.25M
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17
Artificial Intelligence Contract Awards (Cont.)
Prominent AI Contract Awards
DOD and IC
eMAPS
$885M
In July 2018, Booz Allen Hamilton won a five-year contract through GSA to help DOD
and the intelligence community (IC) “rapidly employ artificial intelligence, neural and
deep neural networks.” The contract is meant to aid agencies in handling and using
large amounts of reconnaissance data. The technology is called Enterprise Machine
Learning Analytics and Persistent Services (eMAPS).
In September 2018, NGA awarded seven contracts for advanced geospatial
analytics research under Topic 6 of the Boosting Innovative GEOINT Broad
Agency Announcement. Awardees will research the application of AI, ML and deep
learning technologies to automate, extract and detect geospatial datasets for
DOD. Several large companies including Booz Allen, Raytheon and SRI
International have won small awards under the BAA.
Federal Market Analysis
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NGA
Boosting
Initiative
BAA
$29M
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18
Artificial Intelligence Contract Awards (Cont.)
Prominent AI Contract Awards
NASA
ISRDS-2
$400M
The incumbent, SGT LLC, won an eight-year contract in February 2020 for Intelligent Systems
Research and Development Support 2 (ISRDS-2) with NASA’s Ames Research Center to
support R&D in areas of AI, neural networks, and autonomous and adaptive controls.
CACI International holds the current contract for Simulation and Software Technology III
(SST III) to support the Software, Robotics, and Simulation Division (SRSD) at NASA’s
Johnson Space Center. SST III is expected to perform with simulation analysis, math
models and applications, as well as virtual reality. The current contract expires in
December 2021 and a follow-on acquisition is expected before then.
NASA
PACE V
$114M
Federal Market Analysis
NASA
SST III
$143M
Peerless Technologies holds the current contract for Professional, Administrative,
Computational, Engineering 5 (PACE V) with NASA’s Glenn Research Center. In
addition to previous requirements, the follow-on contract is expected to expand
capabilities in artificial intelligence, machine learning and data analytics. The follow-on
solicitation is pending with an expected contract start date in February 2021.
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19
Artificial Intelligence Contract Awards (Cont.)
Prominent AI Contract Awards
DOJ
Health Care
Data Analytics
for BOP
$2.2M
Chirality Capital Consulting, LLC was awarded a sole source contract for
an enterprise-wide analytics platform which will support inmate health and
operations data for improved medical treatment services.
The Department of Energy awarded a task order to Z, Inc. to support the
completion of the model development effort for the Transportation
Module/Autonomous Vehicle Model Development in the National Energy
Modeling System (NEMS).
DOC
Steller Sea Lion
Count Program
$235K
Federal Market Analysis
DOE
Autonomous
Vehicle Model
Development
$885K
The National Oceanic Atmospheric Administration (NOAA) awarded a twoyear contract to KitWare Inc. for a machine learning algorithm to detect,
count and classify sea lions.
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20
Artificial Intelligence Contract Awards (Cont.)
Prominent AI Contract Awards
DHS
3D Object
Recognition
$200K
DHS’s Science and Technology Directorate awarded Synthetik
Applied Technologies a contract to develop a proof-of-concept for
an artificial intelligence-based 3D object recognition capability for
TSA under the Silicon Valley Innovation Program (SVIP).
DHS S&T contracted KickView Corporation to adapt their multi-sensor AI software
platform kvSonata to provide CBP with real-time data analysis of passenger flow
in the international customs processing areas of airports. The award falls under
the SVIP High Fidelity Counting and Measuring of CBP Queues and Service
Times at Ports of Entry solicitation.
DHS
Object ID
Engine
$200K
Federal Market Analysis
DHS
Analysis of
Passenger
Flow
$147K
Analytical AI was contracted by DHS S&T to generate deep learning
algorithms to develop an object identification engine that can rapidly and
accurately detect common Stream of Commerce (SoC) items to enhance
TSA detection and screening capabilities.
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21
Total Artificial Intelligence Contract
Obligations, FY 2017–2019
AI ramps up in the federal government.
Total AI spending rose 360% between FY 2017 and FY 2019. The steep incline
reflects the federal government’s intent to incorporate AI technologies throughout
agency missions and operations. As AI policies and initiatives continue taking shape,
and understanding and trustworthiness of the technology grows, a rise in federal AI
spending is expected for the foreseeable future.
Observations:
» AI-related services spending
outpaced that of AI products.
Services represented 89% of total
spending in AI from FY 2017 to 2019.
» Though 28 out of 33 agencies
increased AI spending from FY
2018 to 2019, NASA increased the
most from $80M to $443M.
» Both Defense and Civilian
spending grew incrementally from
FY 2017 to 2019. Civilian agencies
spent $709M and Defense spent
$656M in that time frame.
» R&D spending represented 79% of
total AI spending from FY 2017 to
2019, revealing the federal
government’s commitment to
innovative approaches in AI.
Source: Deltek, FPDS
Federal Market Analysis
See appendix for keywords used to identify relevant contract obligations.
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22
AI Contract Obligations – Top Ten
Agencies, FY 2017–2019
The scope of federal agency spending on AI is expanding. Investment
in AI technologies continues to spread across the federal government. A majority of the
agencies consistently spent money on AI all three years, edging from previous sporadic
spending on AI. Moreover, agencies outside of centralized research missions are beginning
to expand into the AI market. For example, the Marine Corps reported its first AI spending in
FY 2019 with $16M.
Observations:
» The top ten agencies account for
97% of total AI spending in FY 2017
to 2019. DOD and NASA lead the
federal space with 69% of the total.
» Defense Agencies and Military
Departments all appear in the top
ten agencies, with each reporting
increases in spending from FY 2018
to 2019.
» Agencies not focused on research
missions continued to expand their
AI spending from FY 2017 to 2019:
» Justice, from $24K to $2.0M
» State, from $34K to $6.0M
» Treasury, from 955K to $6.0M
» Four agencies saw the largest drop
in AI spending from FY 2017 to
2019: HHS (-$4.0M), DOI (-$1.0M),
VA (-$624K) and SSA (-$418K).
Source: Deltek, FPDS
Federal Market Analysis
See appendix for keywords used to identify relevant contract obligations.
To purchase the full report visit GovWin.com
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23
AI Contract Obligations – Top Contract
Vehicles, FY 2017 - 2019
Observations:
» Orders under Defense Systems
Technical Area Tasks (DS TATs)
centered on autonomous weapons
system design, systems engineering
and experimentation for Defense
($74M) and Navy ($68M) between FY
2017 and 2019.
» Obligations related to Pega software
represented 57% of AI investments
under SEWP V from FY 2017 to 2019,
chiefly for VA ($9.0M), Commerce
($8.0M) and USDA ($2.0M).
» TSA obligated $1.0M under the
FIRSTSOURCE II vehicle in the three
year period for advanced analytics
and robotic process automation
software.
» Top agency customers of GSA
Schedule 70 in AI-related spending
included: Treasury ($3.0M), USDA
($1.0M) and Justice ($1.0M).
Source: Deltek, FPDS
Federal Market Analysis
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AI Contract Obligations – Top Ten
Contractors, FY 2017 - 2019
Observations:
» The top ten contractors listed here
earned 67% of total federal AI spending
between FY 2017 and 2019.
» The California Institute of
Technology provided support to
NASA’s JPL for autonomous rotoRcraft
flight technology and the PUFFER
robot.
» Lockheed Martin’s earnings increased
from $364K in FY 2018 to $100M in FY
2019 due to $99M awarded by the
Missile Defense Agency for
autonomous cyber radar to optimize
BMDS defense capabilities.
» Obligations made to ECS Federal
decreased from $49M in FY 2018 to
$23M in FY 2019 due to fewer
investments in R&D for Project Maven
at DOD.
» SGT provided support for the NASA
Ames ISRDS-2 contract. ISRDS-2
lacked reported FY 2019 spending due
to the recompete of the contract.
Source: Deltek, FPDS
Federal Market Analysis
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Conclusions
» Agency applications of AI based on machine learning technology is accelerating, focusing on cyber offense
and defense, robotics and autonomy, border security and health care.
» Agencies are investing more in AI solutions, especially services, to improve mission effectiveness, make
evidence-based decisions and automate repetitive tasks.
» The FY 2021 budget request supports AI research and use AI for agency mission advancement, while also
promoting U.S. leadership in the AI domain.
» Federal AI policies have evolved from vision-based initiatives to action-oriented guidance. Recent policies
such as NITRD’s updated AI R&D Strategy, the First Year Action Plan and NIST’s AI standards development
plan, place emphasis on specific steps agencies should take to advance the research, understanding and
adoption of AI.
» Agency AI-centered strategies are emerging throughout the federal government, from DOD to NOAA,
revealing a commitment to AI adoption at individual mission and operational levels.
» Most of DOD’s AI and machine learning work continues to be performed at defense laboratories, giving
contractors with R&D experience a competitive advantage for contract awards.
» Although many of the larger more visible AI investments are occurring at NASA and in the defense realm,
civilian agencies are also investing in AI in smaller increments and with the use of pilot projects, such as IRS’
Pilot initiative and HHS’ Intelligent Automation/Artificial Intelligence (IAAI) solutions contract.
Federal Market Analysis
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Conclusions (Cont.)
» The federal government reported nearly $1.4B in AI-related obligations from FY 2017-2019, with a 360%
increase in spending in the three year time period.
» Spending in AI has expanded beyond those agencies viewed as front-runners in the technology.
Investments have grown from appearing as sporadic prototypes among agencies, to grounded and
consistent use in AI.
» AI R&D contract spending has surged particularly in the area of autonomous vehicles, including space
and ground-based.
» The AI federal market is friendly to small business, with AI spending growing 136% for small businesses from
FY 2017-2019.
Federal Market Analysis
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© Deltek, Inc. All Rights Reserved.
27
Recommendations
» Data quality and management are key to implementing AI. Assist agencies with data discovery, inventory,
digitization, standardization and management as a precursor to employing an AI solution.
» Participate in federal and agency-specific AI working groups to understand needs and uncover opportunities
to assist agencies with AI implementation.
» Look for agency tech sprints, challenges and pilot projects involving AI to demonstrate capabilities and
solutions to agencies.
» Keep pace with issued federal regulations in AI implementation that agencies will need to adhere to in the
technology’s acquisition.
» The federal government continues to seek input in assessing AI’s definition, risks and trustworthiness.
Vendors should take part in assisting NIST with the formulation of these standards as much as possible.
» Track AI-related research projects at federal agencies to be prepared for their development and
operationalization into the market.
Federal Market Analysis
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© Deltek, Inc. All Rights Reserved.
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