Congress Wants to Train 1 Million Americans on AI by 2028

Senators Maria Cantwell (D-Wash.) and Jerry Moran (R-Kan.) introduced the NSF AI Education Act this month — a bipartisan bill that would use the National Science Foundation to fund scholarships, create community college AI centers, and set a grand challenge goal of training one million American workers on AI by 2028.

In a Congress that can’t agree on much, AI workforce training is one of the rare areas where both parties are saying the same thing: the skills gap is real, it’s expensive, and the federal government needs to help close it.

The $5.5 trillion problem

The bill didn’t emerge in a vacuum. IDC estimates that AI and IT skills shortages will cost the global economy $5.5 trillion by 2026 — in delayed products, missed revenue, quality issues, and impaired competitiveness. Over 90% of global enterprises are projected to face critical skills shortages this year.

The numbers on the ground are just as stark:

• Job postings requiring AI skills have increased 247% since 2023, according to Indeed. But the supply of workers with verified AI competencies has grown only 63% over the same period.
• 59% of enterprise leaders say their organization has an AI skills gap right now, even though most are already investing in some form of training.
• 94% of CEOs and CHROs identify AI as their top in-demand skill — yet only 35% feel they’ve prepared employees effectively.
• Perhaps most troubling: only 26% of organizations now offer formal AI upskilling programs, down from 35% a year ago. Employers are cutting training budgets even as the gap widens.

That last point is key. Companies know they need AI-skilled workers, but many are hoping the market will produce them rather than investing in training internally. The NSF AI Education Act is Congress’s way of saying: if the private sector won’t fill the gap fast enough, the public sector will help.

What the bill actually does

This isn’t a vague resolution about “supporting AI.” The bill has specific, funded mechanisms:

Scholarships and fellowships. NSF would award undergraduate and graduate scholarships in AI, with specific tracks for AI applied to agriculture, education, and advanced manufacturing. Professional development fellowships would help workers already in STEM and education careers add AI skills without starting over.

Community College Centers of AI Excellence. At least five community colleges and vocational schools would be designated as “Centers of AI Excellence,” developing best practices for teaching AI and disseminating them nationally. These centers would provide hands-on learning opportunities — research experiences, industry partnerships, and experiential training — specifically designed for students who aren’t on the four-year university track.

K–12 classroom support. NSF would research AI teaching tools and create publicly available guidance for integrating AI into classrooms, with a focus on K–12, low-income, rural, and tribal students.

Agricultural AI grants. The bill authorizes the Secretary of Agriculture, in collaboration with NSF, to fund AI research and training through land-grant universities and the Cooperative Extension Service — reaching rural communities that are often last to access new technology training.

The Grand Challenge. NSF would establish grand challenges to find strategies for educating one million or more U.S. workers on AI by 2028. Think of it as a moonshot for AI literacy — a public commitment with a measurable target and a deadline.

Why community colleges matter here

The community college focus is significant. Right now, most AI education happens at elite universities or through employer-sponsored programs at large tech companies. That leaves out the vast majority of the workforce.

Community colleges serve nearly 12 million students annually, and their students are disproportionately working adults, career changers, and people from communities underrepresented in tech. If AI skills remain locked behind four-year degrees and expensive bootcamps, the skills gap doesn’t close — it calcifies along existing lines of privilege.

The bill explicitly addresses this by requiring the Centers of AI Excellence to develop scalable programs that other community colleges can replicate, and to ensure AI education reaches women, rural residents, and underrepresented populations.

The bipartisan signal

Cantwell and Moran are the former chair and ranking member of the Senate Commerce Committee, which has jurisdiction over NSF. The bill also has a companion version in the House, introduced by Representatives Vince Fong (R-Calif.) and Andrea Salinas (D-Ore.). Bipartisan introduction in both chambers doesn’t guarantee passage, but it does signal that AI workforce development has crossed the partisan divide in a way that most tech policy hasn’t.

Senator Moran framed it directly:

“AI will impact nearly every aspect of our economy, and our workforce must be prepared. This legislation will help ensure Americans at every level — from K–12 students to mid-career professionals — have access to the training and education they need to thrive.”

What this means for you

If you’re considering an AI-focused education, here’s the takeaway: the federal government is now investing in the same thesis that the market data already supports. AI skills aren’t a niche specialization — they’re becoming baseline requirements across industries from agriculture to healthcare to manufacturing.

The bill also validates a model that isn’t the traditional four-year degree. Community college centers, vocational programs, professional development fellowships — Congress is explicitly building pathways for people who don’t have four years and $100,000 to spend on a traditional university education.

Whether this specific bill passes or not, the direction is clear. IDC projects that AI capabilities could trim $1 trillion from skills-gap losses by 2027 — but only if the workforce gets trained fast enough to use them. The race isn’t between AI and humans. It’s between people who learn AI skills and people who don’t.