Beginning with the FY2020 budget request, NITRD has annually reported consolidated Federal nondefense investments in AI R&D. This reporting began in response to Executive Order 13859, “Maintaining American Leadership in Artificial Intelligence”, which required a standardized approach to accurately account for AI R&D investments across the Federal government. At that time, NITRD worked with Federal agencies to create a new Program Component Area (PCA) for AI and also account for investments in AI R&D that are captured under other PCAs (refer to Table 1, footnote 4, for examples of distinctions between AI and other PCAs). This accounting aligns AI R&D investments with the key strategies in The National Artificial Intelligence Research and Development Strategic Plan: 2019 Update and enables tracking of nondefense AI R&D investments from year to year. The National AI Initiative Act of 2020 also requires consistent reporting of AI R&D investments, to include investment in National AI Research Institutes, which were included for the first time in the FY 2022 report.
Table 1 shows two types of AI R&D investments: (1) Core AI: those with a primary emphasis on AI R&D, which are reported under the AI PCA, and (2) AI Crosscut: those with primary emphases in areas other than AI, which are reported in other PCAs (source: NITRD and NAIIO Supplement to the President’s FY2025 Budget).
For more information on Federal efforts in AI R&D, please refer to AI.gov.
Chart 1: Federal Budget for AI R&D, FYs 2021-2025
Chart 2: AI R&D FY2025 Budget Request by Agency
Table 1. Agency Budgets by NITRD PCA for AI R&D FYs 2019–2025
The NITRD agencies’ requested investment in AI R&D for FY 2025 is $3316.1 million.
| Agency | Fiscal Year | AI | ACNS | CHuman | CNPS | CSP | EdW | ENIT | EHCS | HCIA | IRAS | LSDMA | SPSQ | Totals |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Fiscal Year | AI | ACNS | CHuman | CNPS | CSP | EdW | ENIT | EHCS | HCIA | IRAS | LSDMA | SPSQ | TOTALS |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FY 2023 Actual | 1914.2 | 50.5 | 162.7 | 29 | 84.4 | 63.6 | 9.5 | 81 | 109 | 66.2 | 466.8 | 85.1 | 3121.9 |
| FY 2023 Suppl. | 75.6 | 5.4 | – | – | 3.8 | – | – | – | – | – | – | – | 84.7 |
| FY 2024 Enacted | 1789.0 | 37.4 | 167.8 | 30.4 | 78.9 | 60.5 | 8.7 | 81.9 | 109.1 | 69.1 | 466.5 | 78.2 | 2977.5 |
| FY 2024 Suppl. | 16.5 | 13.4 | – | – | 5.8 | – | – | – | – | – | – | – | 35.7 |
| FY 2025 Request | 1954.5 | 69.5 | 180.8 | 59.3 | 93.5 | 85.7 | 11.2 | 89.8 | 113.8 | 77.4 | 493 | 87.7 | 3316.1 |
Notes for Table 1:
- Amounts are in U.S. dollars in millions.
- Budget supplemental figures for FY2024 and FY2025 have not been used to calculate changes between the FY2024 and FY2025 budget numbers.
- Totals might not sum exactly as a result of rounding.
- (1) Examples of AI R&D investments reported under the AI PCA are R&D on general methods for machine vision; (primarily) machine learning; cybersecurity challenges unique to AI (e.g., ability to exploit flaws in an AI system’s goals); algorithms for computational linguistics; and neuromorphic computing architectures or chips optimized for neural nets.
(2) Examples of AI investments reported in other PCAs are R&D on robots (reported in IRAS); the data analysis and management ecosystem (reported in LSDMA); broad issues of human-machine interaction (reported in CHuman) and cybersecurity research (reported in CSP); and general neuromorphic computing (reported in EHCS).
Table 2. Agency Budgets for NSF-Led National AI Research Institutes, FYs 2023–2025
NSF-led National AI Research Institutes are requesting a total of $72.3 million for FY 2025, including NSF, DoD, Department of Education Institute of Education Sciences (ED-IES), NIST, and Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA) investments.
| FY | AGENCIES | TOTALS | |||||
| NSF | DOD | ED-IES | USDA-NIFA | NIST | |||
| FY 2023 Actual | 64.4 | 7.2 | 2.2 | 40 | 4.7 | 118.5 | |
| FY 2024 Enacted | 52.3 | 3 | 4.4 | 8 | 1.3 | 69 | |
| FY 2025 Request | 61.9 | 2 | 4.4 | 4 | – | 72.3 | |
Notes for Table 2:
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