About $2.13M to send people who can do both cybersecurity and AI into federal service — awards under the same program starting the same day across ten states (Cal State San Bernardino)
Federal agencies increasingly need cybersecurity professionals able to use AI to detect, analyze and respond to threats, yet few graduates hold both skill sets. This award builds them through hands-on work on a cyber range and in a security operations center that defends three live campuses. It is part of a scheme granting scholarships in exchange for government service.
Grant overview (primary data)
- Award amount$2,132,180
- RecipientUniversity Enterprises Corporation at CSUSB (California)
- ProgramCyberAICorps SFS
- Period2026-08-01 〜 2030-07-31
- FunderU.S. National Science Foundation (NSF) / NSF
Key points
- The record states that federal agencies need professionals who can use AI to detect, analyze and respond to threats, yet few graduates hold both skill sets.
- Scholars take machine learning and applied AI alongside cybersecurity, with hands-on work on an AI-enabled cyber range and in a security operations center defending three campuses.
- The curriculum covers both detecting threats with AI and testing the security of AI systems themselves.
- Of the 120 NSF awards this site holds as of 2026-08-28, 11 belong to CyberAICorps SFS, and ten of those begin on the same date, 2026-08-01.
- Recipients span ten states, with amounts falling broadly between $1.7 million and $2.5 million.
- Ten of the 11 CyberAICorps SFS awards begin on 2026-08-01, with recipients spanning ten states.
1Few people hold both skill sets at once
What the record puts at the starting point is a situation: federal agencies need cybersecurity professionals who can use AI, and few graduates arrive with both. Security education and AI education have been built as separate courses of study, so whoever learned one lacks the other.
That this award goes beyond coursework to include work in an operations center defending live campus networks reads as a judgment that the gap does not close by stacking knowledge alone.
2Learning both to defend with it and to test it
Two directions appear in the record: detecting threats using AI, and testing the security of AI systems themselves. The first treats AI as a tool, the second treats it as something to be defended, and the required frame of mind differs. The further generative AI moves into ordinary work, the more AI joins the set of things to be protected.
That this project puts both in the curriculum rests on the premise that AI is simultaneously an instrument and an attack surface.
3The same program starting the same day in ten states
Of the 120 NSF awards this site holds as of 2026-08-28, 11 belong to CyberAICorps SFS. Ten of them begin on the same date, 2026-08-01, and the recipients span ten states: California, Texas (three), Florida, New Jersey, Michigan, Connecticut, Arizona, Tennessee and Virginia. Read alone, one looks like a single university education program; lined up, they appear as one national measure stood up simultaneously.
The amounts fall broadly between $1.7 million and $2.5 million, so the scale is aligned too.
Why it matters
Workforce measures look like individual university initiatives when read one at a time. Lining up awards under the same program shows what scale of people is being directed into which field, and when. For organizations that have hired cybersecurity and AI as separate roles, a cohort holding both arriving together in a few years changes the premise of hiring.
FAQ
What is CyberAICorps SFS?
Why learn to test AI itself?
Is the simultaneous start a coincidence?
Sources (primary)
Source: NSF Award Search (U.S. National Science Foundation, public domain). Amounts are the obligated amount. For privacy, we do not handle principal investigator names.
- NSF Award (original, official)
- NSF Award ID: 2623313