NSF LEVEL UP AI

Overview

Join Us in Shaping the Future of AI Education

The NSF LEVEL UP AI (Launching an Educational Vision to Expand Leadership, Understanding, and Progress in Artificial Intelligence) initiative brings together educators, researchers, and professionals across the computing community to build a shared vision for expanding capacity and access to undergraduate AI education. Supported by the U.S. National Science Foundation (NSF) as part of NSF’s EducateAI program, this initiative plays a vital role in leading national efforts to create an AI-ready workforce.

Aligned with the National AI Research Resource (NAIRR) initiative, NSF LEVEL UP AI ensures broad access to computational tools, data, and training essential for delivering high-quality AI education across the U.S.

AI is reshaping our world, and it’s up to us to ensure that everyone can participate and benefit from these advances. NSF LEVEL UP AI will develop strategies to grow AI programs at educational institutions nationwide while keeping education accessible to all students.

A Community-Led Effort on AI Education

NSF LEVEL UP AI is a key part of the NSF EducateAI initiative, a nationwide effort to prepare the next generation of AI professionals.

Our work focuses on:

Increasing capacity by expanding AI curricula and building the infrastructure needed to deliver high-quality education.
Promoting access to ensure that students from all backgrounds have opportunities to participate in AI programs.
Building community consensus to develop actionable strategies that transform AI education across institutions.

Related Projects

CRA is proud to help lead NSF’s national effort to expand and improve AI education, working alongside NAIRR and other federal initiatives to broaden access to AI education resources. CRA is leading this project and two others in this effort:

Sign up for updates on NSF LEVEL UP AI, NAIRR Pilot Expansion Classroom Education conference dates and registration details, collaboration opportunities, and other key updates.

Spread the Word: Build Our Community

Help us expand the impact of NSF LEVEL UP AI by sharing this opportunity with your peers and colleagues. Download our PDF flyer and encourage a friend to join our network of educators, researchers, and professionals committed to shaping the future of AI education.

Download the Flyer

Activities

Engage, Collaborate, and Build the Future of AI Education

NSF LEVEL UP AI (Launching an Educational Vision to Expand Leadership, Understanding, and Progress in Artificial Intelligence) offers multiple opportunities for collaboration and discussion through virtual roundtables and in-person workshops, designed to build a shared vision for expanding capacity and access to AI education.

Virtual Roundtable Discussions

Virtual roundtables provide an interactive platform for participants from a wide range of institutions and professional backgrounds to exchange ideas.

These 1–1.5 hour online sessions foster dialogue around expanding AI education programs and promoting access for all.
No travel is required, allowing participants from different locations to connect conveniently.
The flexibility of the roundtables ensures broad participation, accommodating professional schedules, family responsibilities, and other commitments.

In-Person Workshops

Regional workshops on the East and West Coasts will bring together representatives from academia, industry, and government to develop actionable plans for AI education.

These workshops aim to build consensus and create strategies for increasing capacity and access to AI programs.
Agendas will be shaped by insights gathered from the virtual roundtables, ensuring continuity and alignment between the activities.
The outcomes of the workshops will contribute to a comprehensive roadmap for advancing AI education nationwide.

East Coast LEVEL UP AI Workshop – December 4-5, 2025

Agenda

West Coast LEVEL UP AI Workshop – January 7-8, 2026

Reports

Read the Full Report

As phase one of the NSF LEVEL UP AI initiative, CRA has convened experts committed to improving AI education from across the U.S. to advance national strategies for increasing capacity in undergraduate contexts. The publications below are the result of 32 moderated roundtable discussions with 202 experts representing a broad range of institutions and perspectives.

Discussions surfaced several cross-cutting resource deficiencies that shape the national conversation on AI education:

Infrastructure

A digital divide persists between well-resourced and under-resourced institutions, especially smaller colleges and universities.
Many institutions lack sufficient faculty with AI expertise, and existing faculty often have limited time and resources for reskilling.
Students and faculty often face inadequate access to computational infrastructure to develop and test AI.
Technical support for running AI software and hardware is frequently insufficient.
Institutions face a heavy burden in updating curricula and creating new programs to keep pace with rapid advances in AI.

Professional Development

Faculty need accessible, continuous opportunities to learn about AI, including its ethical and societal dimensions.
Professional development is particularly critical for under-resourced institutions with limited ability to recruit or retain faculty with established expertise.
To ensure all students benefit, faculty professional development must extend both within computing programs and across other disciplines where AI knowledge is increasingly important.

These deficiencies provide important context for the publications below.

Full Report

Developing Strategies to Increase Capacity in AI Education: Results of the NSF LEVEL UP AI Roundtable Discussions

September 2025

This comprehensive report synthesizes findings from phase one of NSF LEVEL UP AI convenings. It details challenges, opportunities, and strategies for building AI education capacity across U.S. higher education.

Read the Full Report »

How to Cite the Report

Cowit, N., Tadimalla, S.Y., Jones, S., Maher, M., Camp, T., Pontelli, E. (2025). Developing Strategies to Increase Capacity in AI Education: Results of the NSF LEVEL UP AI Roundtable Discussions. Washington, D.C.: Computing Research Association (CRA). https://cra.org/wp-content/uploads/2025/09/Developing-Strategies-to-Increase-Capacity-in-AI-Education-A-CRA-Report.pdf. https://doi.org/10.48550/arXiv.2509.21713

Two-Page Summary

Developing Strategies to Increase Capacity in AI Education: Opportunities, Challenges, and Strategies

July 2025

A concise overview of the four focus areas discussed in the roundtables, highlighting high-level recommendations and emerging themes. Originally presented at the 2025 CRA Summit in San Francisco.

Read the Two-Page Summary »

Contributors

NSF LEVEL UP AI Roundtable Participants

September 2025

The NSF LEVEL UP AI reports would not have been possible without the insights of 202 participants from institutions and organizations nationwide.

See the Full List of Contributors »

Resources

AI Education Resources collected during roundtable discussions are available via the button below. These resources may provide assistance at bringing AI education to your classroom or institution.

Sortable Resources

You will be prompted to make a copy of the resource table, which allows for sorting based on resource and topic.

Suggest a Resource

These resources do not represent recommendations by CRA in terms of quality, but rather a snapshot of a major landscape of resources documented during the roundtables. Each of the listed resources was grouped into at least one high level category to help with navigating the information. These include: Funding Sources, Open Educational Resources, Educational Resources (paywall), Open Source Technologies, Institutional Infrastructures, Societal Infrastructures, Ethics and Accessibility Resources, Tools, and Books / Articles / Blogs. Institutional Infrastructures are meant to link to things individual universities may be doing in terms of AI major creation curricular pathways or centers for people at those institutions. Societal infrastructures are meant to relate to national and international resources that are accessible to people at a variety of institution types.

Get Involved

Partners

About CRA

About the Computing Research Association (CRA)

The Computing Research Association (CRA) unites industry, academia, and government to advance computing research and education. With nearly 300 member institutions across North America, CRA leads the computing research community, informs policymakers and the public, and promotes the development of an innovative and responsible computing research workforce.

CRA is proud to lead the NSF LEVEL UP AI initiative, bringing together organizations and experts from across the computing community to shape a shared vision for AI education. This initiative reflects CRA’s ongoing commitment to community-led collaboration and our mission to strengthen the future of computing.

Learn more about CRA’s mission and initiatives at cra.org.

Involved Leaders

This project is bringing together leaders from a wide range of backgrounds, including academia, industry, and key organizations.

Project Leaders

Tracy Camp
Computing Research Association
Website

Mary Lou Maher
Computing Research Association
Website

Enrico Pontelli
New Mexico State University
Website

Advisory Board Members

We are proud to be guided by an esteemed Advisory Board of thought leaders and experts:

Nate Derbinsky
Northeastern University
Website

Eric Eaton
University of Pennsylvania
AAAI
Website

Ashok Goel
Georgia Institute of Technology
Website

Mrinal Karvir
Intel
IEEE-CS
Website

Sneha Kumar Kasera
University of Utah
Website

James Lester
North Carolina State University
Website

Naja Mack
Morgan State University
Website

Jamie Payton
New Jersey Institute of Technology
Website

Tom Pearson
Chandler-Gilbert Community College
Website

Jane Prey
ACM Education Committee
Website

Jodi Reeves
National University
Website

Bart Selman
Cornell University
Website

Neelu Sinha
Fairleigh Dickinson University
Website

Ilias Tagkopoulos
University of California, Davis
Website

David Touretzky
Carnegie Mellon University
Website

Michael Wollowski
Rose-Hulman Institute of Technology
Website

Involved Leaders from Additional Partnering Organizations

AccessComputing

Maya Cakmak
University of Washington
Website

CAHSI

Ann Gates
University of Texas El Paso
Website

CIC

Carla Brodley
Northeastern University
Website

CRA-WP

Betsy DiSalvo
Georgia Institute of Technology
Website

NCWIT

Lucy Sanders
University of Colorado
Website

ECEP

Carol Fletcher
University of Texas at Austin
Website

iAAMCS

Kinnis Gosha
Morehouse College
Website

LEAP

Charles Isbell
University of Wisconsin-Madison
Website

SRC

Zoë Wood
Cal Poly, San Luis Obispo
Website

STARS

Tiffany Barnes
North Carolina State University
Website

CRA AI Education Fellow

Noah Cowit
Computing Research Association

NSF LEVEL UP AI is a collaborative effort involving ACM, CRA, IEEE-CS, AAAI, and other partnering organizations.

This material is based upon work supported by the U.S. National Science Foundation under Grant No. CNS-2434416. Any opinions, findings, conclusions, or recommendations expressed are those of the authors and do not necessarily reflect the views of the NSF.