America’s decades-long leadership in AI research and development (R&D) has resulted in cutting-edge, transformative technologies that are improving lives, growing innovative industries, empowering workers, and increasing national security. These successes are the result of a strong, long-term emphasis on visionary, competitive, and high-payoff fundamental research programs that advance the frontiers of AI. AI R&D investments in the United States are measured not only by the amount of financial investment, but also in the quality and impact of the results.
Federal investments in AI R&D emphasize the broad spectrum of challenges in AI, including core AI research, use-inspired and applied AI R&D, computer systems research in support of AI, and cyberinfrastructure and datasets needed for AI. Cross-disciplinary AI investments focus on the wide range of applications of importance to the Nation, including science, medicine, communication, manufacturing, transportation, agriculture, and security. AI investments are prioritized in agency budgets and coordinated across the Federal government to leverage the efficiencies of shared interests, while also identifying and filling gaps in the investment portfolios.
The U.S. approach strengthens and leverages the unique and vibrant American R&D ecosystem, combining the strengths of government, academia, and industry. Special emphasis is placed on innovative public-private partnerships that accelerate AI discoveries. The result is a thriving R&D enterprise that maintains American leadership in AI technologies.
National AI Research and Development Strategic Plan
Guiding the Nation’s AI R&D investments is the National AI R&D Strategic Plan: 2019 Update, which identifies the critical areas of AI R&D that require Federal investments. Released by the White House Office of Science and Technology Policy’s National Science and Technology Council (NSTC), the Plan defines eight key areas of priority focus for the Federal agencies that invest in AI. These areas of strategic AI R&D focus include: continued long-term investments in AI; effective methods for human-AI collaboration; understanding and addressing the ethical, legal, and societal implications for AI; ensuring the safety and security of AI; developing shared public datasets and environments for AI training and testing; measuring and evaluating AI technologies through standards and benchmark; better understanding the National AI R&D workforce needs; and expanding public-private partnerships to accelerate AI advances.
The National AI R&D Strategic Plan: 2019 Update defines the priorities for the overall portfolio for Federal AI R&D investments. Federal agencies take these priorities into account when developing their own budget proposals and agency plans, as appropriate to their respective agencies’ missions. The Nation benefits significantly from the broad spectrum of Federal agencies that invest in AI from their unique mission perspectives, consistent with the national AI R&D strategy. To document the impactful progress the Nation has made in AI through Federal R&D investments, NSTC issued the 2016-2019 Progress Report: Advancing Artificial Intelligence R&D in November 2019. This report illustrates the considerable breadth and depth of Federal investments that are leading to transformative advancements in the state of the field.
National AI Research Institutes
Since 2020, NSF and its partners have announced a combined $360 million investment over five years in 18 new National AI Research Institutes across the country, including researchers based across 40 states and the District of Columbia. Each award supports multidisciplinary research and education institutes that focus on a range of AI R&D.
The first seven AI Research Institutes announced in August 2020 were:
- NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (led by University of Oklahoma, Norman Campus)
- USDA-NIFA AI Institute for Next Generation Food Systems (led by University of California, Davis)
- NSF AI Institute for Foundations of Machine Learning (led by University of Texas at Austin)
- NSF AI Institute for Student-AI Teaming (led by University of Colorado Boulder)
- USDA-NIFA AI Institute for Future Agricultural Resilience, Management, and Sustainability (AIFARMS) (led by University of Illinois at Urbana-Champaign)
- Molecule Maker Lab Institute (MMLI): NSF AI Institute for Molecular Discovery, Synthetic Strategy, and Manufacturing (led by University of Illinois at Urbana-Champaign)
- NSF AI Institute for Artificial Intelligence and Fundamental Interactions (led by Massachusetts Institute of Technology)
The next 11 AI Research Institutes announced in July 2021 were:
- NSF AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (led by Georgia Institute of Technology)
- NSF AI Institute for Advances in Optimization (led by Georgia Institute of Technology)
- NSF AI Institute for Learning-Enabled Optimization at Scale (Led by University of California San Diego)
- NSF AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (Led by Ohio State University)
- NSF AI Institute for Future Edge Networks and Distributed Intelligence (Led by Ohio State University)
- NSF AI Institute for Edge Computing Leveraging Next-generation Networks (Led by Duke University)
- NSF AI Institute for Dynamic Systems (Led by University of Washington)
- NSF AI Institute for Engaged Learning (Led by North Carolina State University)
- NSF AI Institute for Adult Learning and Online Education (Led by Georgia Research Alliance)
- USDA-NIFA Institute for Agricultural AI for Transforming Workforce and Decision Support (Led by Washington State University)
- The AI Institute for Resilient Agriculture (Led by Iowa State University)
Additional AI Research Institutes are anticipated in the coming years, with the next round of funding announced for Fiscal Year 2022. These Institutes are creating hubs for collaboration and partnerships across academia, industry, and government. As noted by NSF, these Institutes “comprise the Nation’s most significant single Federal investment in AI to date and will advance national competitiveness in AI by accelerating research, transforming society, and growing the American workforce”.
AI R&D Budget
In September 2019, agencies for the first time reported their nondefense R&D investments in AI, through the NITRD Supplement to the President’s FY2020 Budget, and most recently through the NITRD and NAIIO Supplement to the President’s FY2022 Budget (see Table 2). This AI R&D reporting process provides an important mechanism for consistently tracking America’s prioritization of AI R&D going forward. This report also provides insight into the diverse and extensive range of nondefense Federal AI R&D programs and initiatives. Under this reporting mechanism, AI investments are categorized into two primary categories – those where AI is the primary emphasis and those where AI contributes to another primary emphasis (such as high-capability computing, intelligent robotics and autonomous systems, or cybersecurity). The National AI Initiative Act of 2020 also requires reporting of investments in National AI Research Institutes, which are included for the first time in the FY 2022 report. For more information on Federal AI R&D investments, refer to the NITRD AI R&D Investment Dashboard.