HR7696-119

In Committee

AI Cyber Grid Protection Resilient Development Act of 2026

119th Congress Introduced Feb 25, 2026

Summary

What This Bill Does

The AI Cyber Grid Protection Resilient Development Act of 2026 directs the Director of the Cybersecurity and Infrastructure Security Agency and the Secretary of Homeland Security to establish, within 180 days, a grant program for secure artificial-intelligence cyber-physical testbeds. The testbeds would simulate grid-scale cyberattacks and allow AI models to be trained safely.

Eligible recipients include institutions of higher education, public colleges and universities, community colleges, Hispanic-serving institutions, National Laboratories, and consortia made up of those entities. The bill authorizes $100 million for fiscal years 2026 through 2030. It also requires annual reports to Congress through 2031 on evolving threats, AI mitigation progress, and recommendations for additional legislative or regulatory action.

Who Benefits and How

Universities, community colleges, Hispanic-serving institutions, National Laboratories, and eligible consortia benefit from new grant funding to build AI grid-cybersecurity testbeds. Electric utilities and grid operators benefit if the testbeds improve detection, simulation, and mitigation of grid-scale cyberattacks. CISA and DHS cybersecurity planners benefit from annual reporting that documents evolving threats and regulatory gaps.

Who Bears the Burden and How

CISA and the Department of Homeland Security must design, award, oversee, and report on the grant program. Eligible entities must apply for grants, build secure testbeds, and manage research controls for AI cyberattack simulation. Federal cybersecurity appropriations bear the $100 million authorization for fiscal years 2026 through 2030. Congress must review annual threat and mitigation reports through 2031.

Key Provisions

  • Requires CISA and DHS to establish the AI grid-cyberattack testbed grant program within 180 days.
  • Funds eligible colleges, universities, Hispanic-serving institutions, National Laboratories, and consortia.
  • Focuses awards on secure cyber-physical testbeds that simulate grid-scale cyberattacks and safely train AI models.
  • Requires annual congressional reports through 2031 on threats, mitigation progress, and needed policy action.
  • Authorizes $100 million for fiscal years 2026 through 2030.
  • Defines artificial intelligence by reference to the fiscal year 2019 National Defense Authorization Act.

Evidence Chain:

This summary is generated from the full bill text using AI analysis. Expand "Detailed Analysis" below for identified beneficiaries/burden bearers with clause-level evidence links.

At a Glance

What This Bill Does

Creates a Department of Homeland Security grant program for secure artificial-intelligence cyber-physical testbeds that simulate grid-scale cyberattacks and train AI models safely.

Key Policy Areas

Cybersecurity, Artificial Intelligence, Electric Grid, Federal Grants

Primary Purpose

Creates a Department of Homeland Security grant program for secure artificial-intelligence cyber-physical testbeds that simulate grid-scale cyberattacks and train AI models safely.

Policy Domains

Cybersecurity Artificial Intelligence Electric Grid Federal Grants

Section 2 AI cyber-physical grid testbed grant program

Identified Gains
  • Institutions of higher education running AI grid testbeds
  • National Laboratories running AI grid testbeds
  • Electric utilities exposed to grid-scale cyberattacks
  • CISA grid cybersecurity planners
Model: codex-gpt-5 | Version: bill_summary_v2 | Source: ih
CISA grid cybersecurity planners:
National Laboratories running AI grid testbeds:
Electric utilities exposed to grid-scale cyberattacks:
Institutions of higher education running AI grid testbeds:
Identified Costs
  • CISA grant administrators
  • Department of Homeland Security grant administrators
  • Eligible testbed grant applicants
  • Federal cybersecurity appropriations accounts
Model: codex-gpt-5 | Version: bill_summary_v2 | Source: ih
CISA grant administrators:
Eligible testbed grant applicants:
Federal cybersecurity appropriations accounts:
Department of Homeland Security grant administrators:

Legislative Progress

In Committee
Introduced Committee Passed
Feb 26, 2026

Referred to the Subcommittee on Cybersecurity and Infrastructure Protection.

Feb 25, 2026

Referred to the House Committee on Homeland Security.

Feb 25, 2026

Introduced in House

Feb 25, 2026

Mr. Hernández (for himself, Mr. Liccardo, and Mrs. Grijalva) introduced …

Stakeholder Effects

cui bono?

How this legislation distributes effects. Mention counts reflect frequency, not effect magnitude.

Government
3 mentions across 1 clause
+1 positive -2 negative

CISA grant administrators, Federal cybersecurity appropriations accounts, National Laboratories running AI grid testbeds

Positive-direction: National Laboratories running AI grid testbeds

Negative-direction: CISA grant administrators, Federal cybersecurity appropriations accounts

Technology
1 mention across 1 clause
+1 positive

Institutions of higher education running AI grid testbeds

Utilities
1 mention across 1 clause
+1 positive

Electric utilities exposed to grid-scale cyberattacks

1/2
sections analyzed
Full impact breakdown

Bill Structure & Actor Mappings

Who is "The Secretary" in each section?

Domains
Cybersecurity Artificial Intelligence Electric Grid Federal Grants
Actor Mappings
"director"
→ Director of the Cybersecurity and Infrastructure Security Agency
"secretary"
→ Secretary of Homeland Security
"eligible_entity"
→ Institution of higher education, National Laboratory, or eligible consortium

Key Definitions

Terms defined in this bill

2 terms
"artificial intelligence" §2(d)(1)

Artificial intelligence as defined in section 238(g) of the John S. McCain National Defense Authorization Act for Fiscal Year 2019.

"eligible entity" §2(d)(2)

An institution of higher education, public college or university, community college, Hispanic-serving institution, National Laboratory, or consortium of such entities.

We use a combination of our own taxonomy and classification in addition to large language models to assess meaning and potential beneficiaries. High confidence means strong textual evidence. Always verify with the original bill text.

Learn more about our methodology