U.S. National Science Foundation State and Regional Artificial Intelligence Infrastructure Hubs:
🏛 U.S. National Science Foundation (NSF)
✓ Free, no account · Source: Grants.gov · Last verified Oct 18, 2026
Can you apply?
This grant is for institutions of higher education and research organizations seeking to build state or regional AI infrastructure consortia. Eligible applicants include two- and four-year colleges, community colleges, independent museums, observatories, and research laboratories located in the U.S. All institutions must be accredited and have U.S. campuses.
The grant funds coordination, workforce development, and faculty training for AI infrastructure hubs. Consortia must include partnerships with state/local governments, research institutions, private sector, and philanthropies. The consortium itself covers all costs for computing, data, and AI resources.
Proposals are submitted by institutions on behalf of their faculty and partners. International branch campuses may be included if benefits are justified and activities cannot occur at U.S. campuses.
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Program description
The NSF State and Regional AI Infrastructure Hubs program aims to expand access to the compute required for AI-enabled scientific discovery and to transform the research, education, and training opportunities offered by institutions of higher education. AI Infrastructure Hubs will connect researchers to new compute infrastructure that leverages contributions from state governments, research institutions, industry, and philanthropy, accelerating AI-enabled discovery across science and engineering and developing a skilled technical workforce for AI use in the scientific enterprise.
The program responds to a core tenet of Science: A New Golden Age to renew America’s research and development (R&D) for changes in today’s scientific enterprise, including the role of AI in laying the foundation for a new era of scientific discovery and the growing role of industry and philanthropy in funding R&D. In response, the Administration’s FY28 R&D Priorities Memorandum called for investing in AI for science as a national mission and expanding the scale of, and flexible access to, advanced compute and data infrastructure that researchers now require for frontier scientific discovery.
Each AI Infrastructure Hub will be organized as a flexible state or regional consortium of state and local governments, research institutions, philanthropies, and the private sector. Consortia will be responsible for all funding for new or expanded computing, data, and AI resources, whether on-premises or cloud-based. NSF will fund each Hub’s consortium coordination, AI infrastructure workforce development, and faculty training and coursework development in leveraging AI for science.
Who can apply
Eligible applicants
How to apply
Application links
Key dates & requirements
Required documents
- Project Narrative/Proposal
- Budget and Budget Justification
- Biographical Sketches (key personnel)
- Letters of Commitment (from consortium partners)
- Data Management Plan
- Institutional Endorsement/Certification
Program contact
- 👤 U.S. National Science Foundation
- 📧 grantsgovsupport@nsf.gov
- 📞 703-292-4203
Funding track record
Recent awards under CFDA 47.084 from the last 3 years — real organizations that won funding through this same program.
Top 10 Largest Recent Awards
-
$33,821,660
-
$33,168,625
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$31,976,680
-
$30,513,596
-
$30,163,581
-
Icamr, Inc. FL$29,938,673
-
$29,869,465
-
$29,494,884
-
$28,841,053
-
$27,448,182
Top States by Funding
- NY 11 awards $120.7M
- CA 11 awards $115.4M
- MA 11 awards $93.2M
- IL 8 awards $89.8M
- NC 4 awards $74.6M
Source: USAspending.gov — federal spending transparency. Data covers last 3 years.
Funding history
Annual funding for this program — Federal obligations (CFDA 47.084). How funding has trended year over year.
| 2024 | $607,870,000 | |
| 2025 | $609,179,999 | |
| 2026 est. | $346,570,000 |
FAQ
Who can apply for this grant?
Accredited U.S. colleges, universities, community colleges, and nonprofit research organizations can apply. Applicants must be located in the U.S. with a physical campus or facility here.
What costs does NSF fund?
NSF funds hub coordination, AI workforce development, and faculty training. The consortium itself (not NSF) must fund all new or expanded computing infrastructure and data resources.
Can international institutions participate?
Yes, U.S. branch campuses of international institutions can participate. You must justify the benefits and explain why work cannot occur at the U.S. campus.
What is the deadline?
The deadline is November 4, 2026 (fixed date). Plan to submit well before the deadline to allow time for institutional review.
How much funding is available?
NSF allocated $100 million total for this program across all AI Infrastructure Hubs nationwide. Individual hub awards have not been specified publicly.
💡 Tips for applicants
- Build your consortium early. Partner with state/local government, industry, and philanthropy before writing your proposal. NSF expects genuine collaboration.
- Show clear workforce development plans. Emphasize how your hub will train faculty and students in AI for scientific discovery, not just technology skills.
- Explain your governance structure. Be specific about how decisions will be made and how partners will contribute resources and expertise to the consortium.
- Connect to regional research strengths. Demonstrate how your AI infrastructure aligns with existing research capabilities and fills gaps in your state or region.
- Focus on access and flexibility. Show how your hub will make AI computing available to researchers across disciplines and institution types in your area.
⚠️ Common mistakes
Underestimating consortium coordination demands. Reviewers expect detailed plans for managing multi-sector partnerships and ensuring equitable access to infrastructure.
Proposing computing infrastructure costs without clear non-NSF funding. NSF will not fund hardware or cloud resources; your consortium partners must cover these expenses fully.
Vague workforce development plans. Generic training proposals fail. Detail specific courses, faculty development programs, and student pathways in AI for science.
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