As artificial intelligence reshapes every facet of society, the U.S. National Science Foundation (NSF) is expanding its long-standing efforts to ensure the U.S. remains globally competitive while ensuring that AI innovation is secure and accessible to all.
During The Learning Agency’s most recent Ask-Me-Anything event, Tess deBlanc-Knowles, Special Assistant to the Director for Artificial Intelligence at NSF, outlined how the agency is adapting its AI investments and infrastructure in response to administration priorities, the executive order on Advancing Artificial Intelligence Education for America’s Youth, and the newly released AI Action Plan.
A Four-Part Strategy For An AI-Driven Future
NSF’s approach is built on four strategic pillars: (1) fostering breakthrough research, (2) translating research into impact, (3) building research infrastructure, and (4) growing the AI workforce. Together, these components guide roughly $700 million in annual NSF funding aimed at transforming research into real-world results.
First, NSF continues to fund foundational AI research across disciplines, from math and neuroscience to engineering and cognitive science, which deBlanc-Knowles called NSF’s “bread and butter.”
“We’re supporting that critical work to answer open questions in today’s technology, like, why did that model spit out that specific response? Or, how can today’s models be built to reduce expense — or truly reason?” deBlanc-Knowles said.
In addition to funding research to explore the boundaries of AI, NSF is also funding research that aims to better understand how AI will impact society more generally.
“We also support the critical work that is really striving to understand and forecast the economic and societal impacts of AI, so that we can position our country to better harness the opportunities, but also manage any challenges that are going to come from the more widespread adoption of AI,” she said.
Through its Technology, Innovation and Partnerships (TIP) Directorate, NSF is investing in the commercialization of AI breakthroughs by running programs that support innovators at every stage of the translation process by bridging the multiple “valleys of death that often stall ideas from becoming usable technologies. From early proof of concept to business planning, prototyping, and initial market offerings, NSF aims to provide support across the full cycle of innovation.
One avenue for doing that is the agency’s Small Business Innovation Research (SBIR) program, which funds over 400 startups annually, with $100 million currently backing AI-related ventures.
Through its Technology, Innovation and Partnerships (TIP) Directorate, NSF is investing in the commercialization of AI breakthroughs by running programs that support innovators at every stage of the translation process by bridging the multiple “valleys of death that often stall ideas from becoming usable technologies. From early proof of concept to business planning, prototyping, and initial market offerings, NSF aims to provide support across the full cycle of innovation.
Building The Infrastructure To Compete
NSF also aims to spread the benefits of AI beyond elite institutions and tech hubs. The Regional Innovation Engines program funds locally-led coalitions to advance AI solutions to specific problems in certain regions. Six of the nine inaugural “engines” feature a central AI component, with explicit goals for workforce training and job creation in the regions where they are based.
NSF recognizes that the most headline-grabbing AI models demand massive computing and data resources, far beyond what federal grants or university budgets can support. This makes it hard for researchers to stay competitive and push the technology further. The federally-supported National AI Research Resource (NAIRR) Pilot is an effort to level the playing field. The pilot, launched with 14 federal agencies and 26 private-sector partners, gives researchers access to cloud credits, datasets, pre-trained models, and user support. Already, it has supported over 440 projects across 48 states.
NSF also aims to spread the benefits of AI beyond elite institutions and tech hubs. The Regional Innovation Engines program funds locally-led coalitions to advance AI solutions to specific problems in certain regions. Six of the nine inaugural “engines” feature a central AI component, with explicit goals for workforce training and job creation in the regions where they are based.
Fostering A Workforce For The AI Era
Perhaps the most urgent shift in NSF’s strategy comes in response to President Trump’s executive order on AI education, Advancing Artificial Intelligence Education for American Youth. The order establishes a national AI Education Task Force, of which NSF’s Director is a key member.
The task force’s responsibilities include:
- Conduct a Presidential AI Challenge – Design and run a national AI competition over the next year, with activities for K-12 students and educators to spark excitement around AI innovation. More details will be announced later this summer.
- Forge Public-Private Partnerships – Coordinate with partners who’ve pledged AI education resources as part of the White House’s recent youth-focused initiative. It will work to ensure these resources are accessible and address delivery gaps.
- Leverage Federal Funding – Identify existing federal funding that can support K-12 AI education. NSF, in particular, will prioritize research on AI in education, expand teacher training, and work with the Department of Labor to grow high school AI coursework and certifications. Expect updates on NSF’s progress later this summer.
One of NSF’s most significant efforts is a network of 27 federally-funded AI Research Institutes, launched in 2020 through a public-private investment of over $500 million. These multi-institution consortia span nearly every state and apply AI to critical domains such as education, public health, and cybersecurity. Partnering with federal agencies like the Education Department, the institutes advance both foundational AI research and real-world applications. NSF has announced a public-private partnership investing $100 million in five AI Research Institutes.
One of NSF’s most significant efforts is a network of 27 federally-funded AI Research Institutes, launched in 2020 through a public-private investment of over $500 million. These multi-institution consortia span nearly every state and apply AI to critical domains such as education, public health, and cybersecurity. Partnering with federal agencies like the Education Department, the institutes advance both foundational AI research and real-world applications.
NSF’s EducateAI initiative – launched in 2023 – helps community colleges, high schools, and workforce training programs incorporate AI instruction with the goal of making AI educational experiences accessible nationwide. The initiative funds projects that help community colleges develop scalable strategies to engage both high school students and adult learners, while also creating clear pathways from two-year to four-year degrees in computer science and AI. These efforts build on existing NSF programs like Discovery Research K-12, Advanced Technological Education, and the Experiential Learning in Emerging Technologies fund.
Conclusion: A Federal AI Ecosystem by Design
As artificial intelligence accelerates, NSF is ensuring the United States is not just reacting, but proactively shaping the future. Its strategy goes beyond funding innovation by helping build the connective tissue that links cutting-edge research with real-world impact, from rural classrooms to next-generation startups.
By investing in infrastructure, workforce development, and broad access to AI tools, NSF is laying the groundwork for a national ecosystem where AI advancments benefit not just a few but all.
