NSF 26-513: U.S. National Science Foundation State and Regional Artificial Intelligence Infrastructure Hubs:
Program Solicitation
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- Posted: July 31, 2026
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Program Solicitation NSF 26-513
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U.S. National Science Foundation |
Full Proposal Deadline(s) (due by 5 p.m. submitting organization's local time):
November 04, 2026
November 03, 2027
First Wednesday in November, Annually Thereafter
Important Information and Revision Notes
- Only one award per state or multi-state region will be made.
- States or regions that need additional time to develop their consortia strategies are encouraged to submit planning proposals in accordance to the PAPPG Chapter II.F.1.
- Collaborative proposals submitted as simultaneous submission of proposals from different organizations, with each organization requesting a separate award are not allowed. Collaborative proposals must be submitted as a single proposal, in which a single award is being requested (with subawards administered by the lead organization). See the PAPPG Chapter II.E.3 for more information.
Proposals must be prepared in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG). Use the version of the guide that is in effect on the proposal's due date.
Summary of Program Requirements
General Information
Program Title:
U.S. National Science Foundation State and Regional Artificial Intelligence Infrastructure Hubs: Expanding Access to Compute for Scientific Discovery (AI Infrastructure Hubs)
Synopsis of Program:
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.
NSF Priorities
NSF welcomes submissions from all researchers, particularly those earlier in their careers and those working in research areas aligned with agency and administration priorities. NSF also expects the highest standards of scientific rigor, integrity, and adherence to tenets of Gold Standard Science in proposals, as appropriate for the field of science and research modality.
Cognizant Program Officer(s):
Please note that the following information is current at the time of publishing. See program website for any updates to the points of contact.
- AI Infrastructure Hubs Program Team, email: AIInfrastructureHubs@nsf.gov
Applicable Catalog of Federal Domestic Assistance (CFDA) Number(s):
- 47.070 --- Computer and Information Science and Engineering
- 47.076 --- STEM Education
- 47.084 --- NSF Technology, Innovation and Partnerships
Award Information
Anticipated Type of Award: Cooperative Agreement
Estimated Number of Awards: 10
The program anticipates 10 awards in each award cycle. In addition, the program also anticipates supporting planning grants as described in the PAPPG Chapter 2.F.1.
Anticipated Funding Amount: $40,000,000 to $100,000,000
Approximately $100,000,000 is available for this program. Only one award per state or multi-state region will be made.
NSF anticipates typical proposals to State and Regional AI Infrastructure Hubs Program should request 5 years and between $4,000,000 - $12,000,000 total budget.
Proposal Preparation and Submission Instructions
A. Proposal Preparation Instructions
- Letters of Intent: Not required
- Preliminary Proposal Submission: Not required
- Full Proposals:
- For proposals submitted via Research.gov, PAPPG guidelines apply.
- For proposals submitted via Grants.gov, NSF Grants.gov Application Guide guidelines apply.
B. Budgetary Information
- Cost Sharing Requirements:
Inclusion of voluntary committed cost sharing is prohibited.
- Indirect Cost (F&A) Limitations:
Not Applicable
- Other Budgetary Limitations:
Not Applicable
C. Due Dates
- Full Proposal Deadline(s) (due by 5 p.m. submitting organization's local time):
November 04, 2026
November 03, 2027
First Wednesday in November, Annually Thereafter
Proposal Review Information Criteria
Merit Review Criteria:
National Science Board approved criteria. Additional merit review criteria apply. Please see the full text of this solicitation for further information.
Award Administration Information
Award Conditions:
Standard NSF award conditions apply.
Reporting Requirements:
Standard NSF reporting requirements apply.
I. Introduction
As advances in data and artificial intelligence (AI) transform scientific discovery, maintaining U.S. leadership in fundamental and translational research requires that researchers and students across the country to have access to cutting-edge AI infrastructure, including computing, data, and software. Today, access to this infrastructure is highly uneven across the nation. The NSF State and Regional AI Infrastructure Hubs Program will support state or multi-state regional hubs, each structured as a coalition of institutions of higher education working in partnership with private industry, philanthropy, and state and local governments to provision the necessary AI infrastructure, develop the scientific and technical workforce equipped to leverage these capabilities, and accelerate AI-enabled scientific discovery.
AI Infrastructure Hubs combine contributions from:
- State and Regional Consortia: Consortia are responsible for separately raising the funding for the AI infrastructure, including computing, data, and software, through partnerships with the private sector, philanthropy and state and local governments.
- NSF: Building on this infrastructure, NSF's investments will (i) fund support from AI infrastructure professionals with the technical expertise to support researchers, students, and educators in applying AI infrastructure for scientific discovery; (ii) connect meritorious research with AI Infrastructure Hubs in their regions, and (iii) support faculty and educator training and instructional material development to expand the next-generation AI infrastructure and science and engineering workforce.
AI Infrastructure Hubs will engage with the broader regional ecosystem as appropriate. For example, Hubs can support formal workforce development offerings and make available AI resources to complement the experiential learning afforded by the Tech Access: AI-Ready America Coordination Hubs. The AI Infrastructure Hubs will also be expected to engage with the National AI Research Resource (NAIRR) initiative to share resources, experiences, and lessons learned.
NSF intends to make only one award per state or multi-state region. Potential submitters are encouraged to collaborate within their state or multi-state regions. Planning grant proposals are accepted to assist in planning. State and Regional AI Infrastructure Hubs is led by the CISE Directorate in partnership with the TIP Directorate and the EDU Directorate.
II. Program Description
The NSF State and Regional AI Infrastructure Hubs program will expand access to the AI infrastructure, including compute, data, and software, required for AI-enabled scientific discovery, transforming research and workforce development opportunities for students. Hub resources may enable autonomous laboratories and AI-enabled research experiences across degree and certificate programs, as well as stackable credits that build a technical workforce equipped to leverage AI for scientific discovery.
NSF does not provide funding for acquisition of AI infrastructure, including computing, data, software, networking, storage, cloud services, or other AI systems or services, leaving that responsibility to regional and state consortia. Instead, NSF serves the catalytic role of prompting consortia to aggregate the necessary funding for procuring, deploying, operating, and maintaining AI infrastructure through partnerships with research institutions, industry, philanthropy, and state and local governments. AI infrastructure resources are the foundation of a successful AI Infrastructure Hub, access to which enables speed-to-science for meritorious research and AI infrastructure workforce development funded by NSF.
Key goals of the State and Regional AI Infrastructure Hubs Program are to:
- Expand Access to Compute: Empower and incentivize state or regional consortia to provide AI infrastructure to researchers and students by leveraging funding, expertise, and economies of scale across institutions and other stakeholders.
- Accelerate AI-Enabled Scientific Discovery: Expand access to AI methods, tools, computing, and data infrastructure across STEM research. Consortia may leverage state or regional initiatives such as the NSF AI-Ready America Coordination Hubs, and support initiatives that increase faculty experience, knowledge, and use of AI and AI infrastructure resources in STEM courses, instructional material, and research.
- Develop an AI for Science Workforce: Build a skilled technical workforce trained to use advanced computing and data resources to accelerate research, including degree and certificate programs with stackable credits reflecting in-demand skills.
An AI Infrastructure Hub proposal consists of five elements:
- Hub consortium stakeholders, vision, and key deliverables.
- Computing, data, and AI infrastructure.
- Partnerships with regional stakeholders.
- Development of an AI infrastructure workforce.
- Faculty training and instructional material development to leverage AI infrastructure for scientific discovery.
A responsive proposal must address all five elements as outlined below.
- Hub consortium stakeholders, vision, and key deliverables
An AI Infrastructure Hub is a consortium of institutions of higher education that is strongly encouraged to include private industry, philanthropy, and state and local governments to provide sufficient funding and resources. The Hub should have an agreed-upon governance structure and charter for serving researchers, faculty, educators, and students with AI infrastructure, including computing, data, and software.
This section of the proposal should address:
- Stakeholders: Describe an initial group of institutions of higher education and other stakeholders capable of providing capital for AI infrastructure, and an achievable plan to engage additional stakeholders across the state or region over time. Consortia should demonstrate strong commitment from senior leadership at member organizations. State-government-level support and funding is strongly encouraged, but is not required. Multi-state consortia must demonstrate the ability to work together successfully. An external advisory board is strongly encouraged.
- Vision: Demonstrate how the Hub will expand access to compute across a range of institution types and sizes, including smaller institutions and community and technical colleges. The proposal should also describe how the Hub will accelerate AI-enabled scientific discovery and develop a workforce with in-demand AI for science skills (e.g., data engineering and curation, research software engineering, model deployment, GPU programming) across the breadth of institutions large and small in the state or region. It should describe how the consortia will expand to support additional researchers, faculty, educators, students, and institutions over time. Of note, partnering industry and philanthropy should be engaged in workforce development activities to ensure they are driven by regional job market needs.
- Key deliverables: Describe key deliverables along three axes (compute, AI for science, and AI infrastructure workforce development) and timelines to achieve them.
- Computing, data, and AI infrastructure
Proposals should describe the computing, data, software, and other AI infrastructure to be acquired, built, operated, and/or maintained by the consortium. Proposers should show that they have the necessary resources in hand to support the consortia's compute requirements or are acquiring them, and should include a detailed timeline for acquiring resources and/or building infrastructure. Described resources must be available and suitable for the full duration of the 5-year award. Proposers may access funding from university, state, philanthropy, industry and/or other sources. On-premise resources, cloud-computing, or a combination of both are acceptable models. Proposers are encouraged to configure resources to best support the needs of consortium members and that will provide researchers and students with access to multiple technologies, architectures, or approaches.
- Partnerships with regional stakeholders
Beyond the consortium's partners for computing, data, and other AI infrastructure, each Hub should coordinate with the broader regional ecosystem and describe innovative ways it will partner with regional industry, philanthropy, and/or state or local governments to drive AI for science research and AI infrastructure workforce development.
Examples of partnerships could include:
- Research partnerships and collaboration between regional industries and researchers leveraging the consortium's resources.
- Workforce development partnerships such as with high-school dual-enrollment programs, particularly for high-performing students interested in AI-enabled scientific research, or AI infrastructure retraining programs or other hands-on technical training, such as internships, apprenticeships, co-op placements, and research experiences
- Engagement with Tech Access: AI Ready America Coordination Hubs. Hubs can leverage AI infrastructure workforce development efforts and make AI resources available for scientific research conducted through the AI-Ready America Coordination Hubs.
The Hub proposal should also describe how the consortium plans to engage with the National AI Research Resource (NAIRR) initiative to share resources, experiences, and lessons learned.
- Development of an AI infrastructure workforce
NSF will fund AI infrastructure professionals to support the Hubs' infrastructure, including systems administrators, system and storage architects, cybersecurity specialists, network, performance and software engineers, and training and user support experts. The workforce development will prioritize AI for science facilitators who work closely with researchers to accelerate research on computational systems by providing expert advice and training on software and tools for AI-enabled science research, while gaining experience with both domain scientists and AI infrastructure.
Proposers are encouraged to leverage student employees and interns from across a variety of institutions in the consortia for hands-on experiences using AI infrastructure for science, creating a pipeline of expertise from universities into industry. Hubs are also encouraged to engage relevant NSF AI initiatives and existing national structures such as CARCC for workforce development.
- Faculty training and instructional materials development to leverage AI infrastructure for scientific discovery.
AI Infrastructure Hubs will support faculty and educators in developing instructional materials, labs, workshops, and training programs for students to use computing and data resources for scientific research, spanning postsecondary education, and continuing/professional education. These materials should expose students to using AI in scientific research and engineering domains. Examples of eligible activities include training programs for educators, including train-the-trainer programs, and course refactoring or development. These efforts should advance educator's skills, proficiency, and knowledge in using computing, data, and software systems to accelerate AI-enabled scientific discovery.
Materials developed as part of the State and Regional AI Infrastructure Hubs program are encouraged to be made available through the NAIRR.
Hubs can leverage cyberinfrastructure investments made through NSF's Office of Advanced Cyberinfrastructure. Hubs with on-site resources are encouraged to integrate with national resources through mechanisms such as the NRP or PATh. Advantages to integration include the opportunity to access system administration support and services, the ability to surge to utilize additional resources beyond local capacity periodically, and the ability to share underutilized resources when available.
Awards are anticipated to range between $4,000,000-$12,000,000 for each Hub. NSF expects that the size of award will scale with the proposed populations of students and scientists served and scale of resources of the AI Infrastructure Hub. NSF investments will specifically support elements 1), 3), 4), and 5); each AI Infrastructure Hub will identify resources for 2).
Measures of Success
Proposals should advance one or more of the following measures of success:
Discovery and Innovation
- Scientific output attributable to the AI Infrastructure Hub's resources
- New technologies, tools, or techniques established
- Follow-on funding and translational work
STEM Education and Workforce
- Improvements in student educational and career outcomes
- Faculty, instructors, undergraduate and graduate students trained in a specific critical area (e.g. data engineering and curation, research software engineering, model deployment, GPU programming, access control and secure research environments, and research computing facilitation)
- Formation of communities of practice among AI infrastructure educators, professionals, employers, and workforce intermediaries
- AI infrastructure and AI for science curriculum developed and shared
Research Infrastructure
- New infrastructure built
- Usage of legacy and new infrastructure
III. Award Information
The anticipated funding amount is subject to the availability of funds. Only one award per state or multi-state region will be made.
IV. Eligibility Information
Who May Submit Proposals:
Proposals may only be submitted by the following:
- Institutions of Higher Education (IHEs): Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the U.S., acting on behalf of their faculty members. Special Instructions for International Branch Campuses of U.S. IHEs: If the proposal includes funding to be provided to an international branch campus of a U.S. institution of higher education (including through use of sub-awards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the U.S. campus.
- Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.
Who May Serve as PI:
There are no restrictions or limits.
Limit on Number of Proposals per Organization: 1
An institution may appear as a participant in at most one proposal. If more than one proposal contains an institution as a participant then only the first one will be reviewed. All others will be returned without review.
Limit on Number of Proposals per PI or co-PI: 1
An individual may participate in at most one State and Regional AI Infrastructure Hubs proposal as PI, co-PI, or Senior/Key Personnel for each deadline. If an individual exceeds this limit, only the first proposal received will be accepted, and the remainder will be returned without review. This rule does not apply to advisory roles.
V. Proposal Preparation and Submission Instructions
A. Proposal Preparation Instructions
Full Proposal Preparation Instructions: Proposers may opt to submit proposals in response to this Program Solicitation via Research.gov or Grants.gov.
You must prepare your proposal according to Chapter II.D.2 of the PAPPG, unless this solicitation specifies different instructions. Always use the version of the PAPPG in effect on your proposal's due date.
- For proposals submitted via Research.gov, PAPPG guidelines apply.
- For proposals submitted via Grants.gov, NSF Grants.gov Application Guide guidelines apply.
In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following:
Collaborative Proposals
Collaborative proposals submitted as simultaneous submission of proposals from different organizations, with each organization requesting a separate award are not allowed. Collaborative proposals must be submitted as a single proposal, in which a single award is being requested (with subawards administered by the lead organization). PAPPG Chapter 2.E.3.a
Proposal Titles
Proposal titles should begin with "AI-Infrastructure-Hubs" followed by a colon, then the title of your proposal. If you are submitting a planning proposal, your title should begin with "AI-Infrastructure-Hubs-Planning" followed by a colon, then the title of your proposal.
Project Description
Proposals must include Sections 1 - 5 below. For each section, items to be addressed are provided as guidance for consideration.
- Hub Stakeholders, Vision, and Key Deliverables
Proposals should address:
- Consortium governance structure and roles of the governance body, including what shared activities and resources the governance body will oversee and how key decisions will be made.
- Initial consortium members and an achievable plan for expanding consortium participation to a wider array of institutions, state and local government, industry, and philanthropic partners.
- The mechanism for requests and allocation of AI infrastructure resources from members.
- The outreach, communications and engagement strategy for the consortia.
- Evidence of strong support and engagement from senior leaders from the consortia institutions. The PI and co-PI institutions are encouraged to include a letter of support, up to one page, from a senior administrator or state leadership.
- Key deliverables for the consortia across compute infrastructure, scientific research enablement, and AI infrastructure workforce development, and the timelines for achieving them.
- Computing, Data, and AI Infrastructure
Proposals should address:
- A high-level description of the proposed resources, in no more than 1-2 pages. Hubs proposing on-site resources should include the system architecture and scale, including compute nodes, network, data and AI services and file systems, and software and services. Hubs proposing to use cloud resources should describe the acquired services and access mechanisms. Any vendor quotes or additional material can be included in the supplemental documents section of the proposal.
- Why the resources that will be made available are appropriately sized for scope and scale of research activities proposed by consortium members.
- Sufficient documentation (e.g., letters of commitment or vendor quotes) to indicate the commitment of university, philanthropic, state or other partners to fund compute resources for the five-year duration of the award. Letters of commitment and quotes may be included in the Supplementary Document.
- Partnerships with Regional Stakeholders
Proposals should address:
- At least one regional industry or non-profit partner through which the hub will engage and describe the goals and the relevant activities. A letter of collaboration is encouraged.
- Coordination and on-going collaboration plans with any other state, regional, or national partners, for example: AI-Ready America if applicable.
- Development of an AI Infrastructure Workforce
Proposals should address:
- A description of the structure and composition of the proposed AI infrastructure team(s), including the approach to engagement, interactions, and partnerships with users of the consortium's infrastructure and engagement of student employees and interns.
- A workforce development plan for AI infrastructure professionals and AI for science facilitators that draws from the talent of institutions across the consortia.
- How the AI Infrastructure Hub will scale the pipeline of AI infrastructure professionals, including expected skillsets acquired, hands-on training and credential opportunities, and engagement with industry or other organizations. Proposals should clearly articulate pathways spanning postsecondary education and continuing/professional education.
- Faculty Training and Instructional Material Development on AI for Science
Proposals should address:
- A brief description of 5-10 new or enhanced courses, workshops, or other activities from faculty in the region who are prepared to refactor or develop instructional materials, projects, or research that will benefit from the hub's resources, including the desired skillset, outcome, or capability an activity is intended to promote and the student population it is intended to support.
- How additional faculty beyond those identified in the proposal will be trained to use and develop instructional materials and conduct research leveraging the hub resources.
- How instructional materials and lessons learned will be shared across the consortia.
Special Information and Supplementary Documentation
- Letters of collaboration for personnel not listed as PI, co-PI, or Senior/Key Personnel should be included.
- Proposals must include a Roles and Responsibilities document, including a table for each organization listing all PIs, co-PIs, and Key Personnel with their roles for each funding year.
- Proposals must include a list of all participating institutions as a separate document.
B. Budgetary Information
Cost Sharing:
Inclusion of voluntary committed cost sharing is prohibited.
Budget Preparation Instructions:
NSF anticipates typical proposals to State and Regional AI Infrastructure Hubs Program should request 5 years and between $4,000,000 - $12,000,000 total budget.
Proposals should include funds to support travel of a representative to the NAIRR annual meeting (or future workshop) and plan to engage with other NAIRR events to share best practices and learn from other hubs.
C. Research.gov/Grants.gov Requirements
You can submit proposals in response to this solicitation through Research.gov or Grants.gov, unless otherwise noted.
Information on how to prepare and submit proposals is available on the Submitting Your Proposal page on NSF.gov.
VI. NSF Proposal Processing and Review Procedures
Information on NSF's proposal processing and review procedures is available on the Overview of the NSF Proposal and Award Process page on NSF.gov.
A. Merit Review Principles and Criteria
All NSF proposals are evaluated through use of the two National Science Board-approved merit review criteria:
- Intellectual Merit, which encompasses the potential to advance knowledge.
- Broader Impacts, which encompass the potential to benefit society and contribute to the achievement of specific, desired societal outcomes.
Information on NSF's merit review principles and process can be found on the How We Make Funding Decisions page on NSF.gov.
Additional Solicitation Specific Review Criteria
- To what extent will the consortium's governance structure and plan for reaching a wide array of institution types aid in meeting the program's goals?
- How strong are the AI infrastructure workforce development plans?
- Are the plans for regional engagement and partnerships with industry, philanthropy, and state and local governments well thought-out with committed partners?
- Will the faculty and educator training and instructional materials development plan significantly increase the number of students accessing advanced computing, data, and AI resources?
- Are the proposed computing, data and AI infrastructure resources adequate in scale and design to support the consortium's researchers, students, and proposed activities?
B. Review and Selection Process
Proposals submitted in response to this program solicitation will be reviewed by Ad Hoc Review and/or Panel Review.
After a proposal passes an initial compliance check, it will be reviewed by an NSF Program Officer. In most cases, three or more external experts will also review it (either as ad hoc reviewers, panelists or both).
Visit the Overview of the NSF Proposal and Award Process page for more information on the proposal review and selection process.
In alignment with Executive Order 14332 (Improving Oversight of Federal Grantmaking), all else being equal after merit review, NSF may give preference to institutions with lower indirect cost rates.
VII. Award Administration Information
A. Notification of the Award
Notification of an award is made to the submitting organization by an NSF Grants and Agreements Officer.
B. Award Conditions
Information on NSF award conditions can be found on the Award Terms and Conditions page on NSF.gov and Chapter VII of the PAPPG.
Administrative and National Policy Requirements:
Information on administrative and national policy requirements can be found on the National Policy Requirements for Recipients of NSF Awards page on NSF.gov.
Consistent with the requirements specified in 2 CFR § 200.332, recipients of NSF awards must adhere to the requirements for pass-through entities in establishing and managing subawards issued ensuring alignment with Administration and NSF policies and priorities.
In alignment with Executive Order 14332 (Improving Oversight of Federal Grantmaking), proposers should be aware that NSF awards offered under this funding opportunity may include termination for convenience provisions.
C. Reporting Requirements
Unless your award notice says otherwise, NSF requires the principal investigator of every grant to submit annual project reports and a project outcomes report for the general public. For complete reporting requirements, see Chapter VII of the PAPPG.
VIII. Agency Contacts
For questions related to the use of NSF systems contact:
- Research.gov: NSF IT Service Desk at rgov@nsf.gov or 1-800-381-1532. The Service Desk is open from 7 a.m. to 9 p.m. Eastern time, Monday through Friday (except for federal holidays).
For questions relating to Grants.gov contact:
- Grants.gov: The Grants.gov Contact Center at support@grants.gov or 1-800-518-4726. (Contact if the Authorized Organizational Representative (AOR) has not received a confirmation message from Grants.gov within 48 hours of submitting an application.)
IX. Other Information
For information on NSF directorates, programs and funding opportunities, go to NSF.gov.
About the National Science Foundation
The U.S. National Science Foundation is an independent federal agency created by the "National Science Foundation Act of 1950." More information about NSF can be found on NSF.gov.
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Privacy Act and Public Burden Statements
The information requested on proposal forms and project reports is solicited under the authority of the "National Science Foundation Act of 1950," as amended. More information can be found on the Privacy Act and Public Burden Statements page on NSF.gov.
