PolicyBrief
H.R. 2101
119th CongressMar 14th 2025
Duplicative Grant Consolidation Act
IN COMMITTEE

This Act establishes a system to prohibit federal agencies from awarding grants for the same purpose to applicants who have already received or are applying for duplicative funding, while also requiring the creation of a tracking system and a report on using AI to prevent waste.

Stephanie Bice
R

Stephanie Bice

Representative

OK-5

LEGISLATION

Federal Grant Double-Dipping is Out: New Law Targets Duplicate Funding, Except for Colleges

The Duplicative Grant Consolidation Act is a straightforward attempt to save taxpayer money by stopping federal agencies from funding the exact same project twice. Essentially, if you get a grant from Agency A to do Project X, Agency B can’t give you another grant for the exact same Project X. This rule applies across the entire executive branch.

The New Rule: No Double-Dipping

The core of this bill is a new prohibition (Sec. 2) that prevents any federal agency head or their Inspector General (IG) from awarding a grant if the applicant has already received money from a different executive agency for the exact same reason or purpose. If two agencies realize they are about to fund the same thing, they have to coordinate and decide which one is the right fit. This is a common-sense move aimed at cutting down on waste, ensuring that limited federal dollars stretch further and fund more unique projects, rather than simply doubling up on existing ones.

This section also explicitly bans awarding grants based on fraudulent applications—a necessary, if obvious, safeguard.

The College Carve-Out: Who Gets a Pass?

Here’s where it gets interesting: the bill makes a huge exception. This anti-duplication rule does not apply to colleges and universities (Sec. 2). Institutions of higher education can still apply for and receive multiple federal grants for similar work from different agencies. If you’re a small business owner or a non-profit, you’re under the microscope for duplication. If you’re a massive research university, you’re essentially exempt from this specific check. This could mean that while the bill successfully stops, say, two different community groups from getting separate grants for the same local literacy program, it leaves the door open for large universities to pursue overlapping research across multiple agencies. It raises the question of whether the bill’s biggest potential savings are being left on the table.

The Digital Watchdog: A New Tracking System

To enforce this, the bill mandates the creation of a centralized, electronic tracking system (Sec. 3) managed by the Office of Management and Budget (OMB). Within one year, this system must be up and running, allowing agencies and IGs to check if an applicant is already funded or applying for the same project elsewhere. Think of it as a mandatory federal grant registry that everyone has to check before cutting a check.

This system will track key details like who got the money, the principal investigator (PI) running the project, the award duration, and a summary of the project. Critically, it will also be used to prevent double-dipping on research funding. If you submit the same research plan to the National Science Foundation and the Department of Energy, this system is designed to flag it, even if the proposals are submitted to the same agency.

For the agencies, this means a significant new administrative burden to feed data into the system and, more importantly, to coordinate with other agencies when a duplicate is found. For applicants, it means an extra layer of scrutiny and the need to be meticulous about clearly defining how their proposed project differs from any other federal funding they’ve received.

Looking Ahead: Will AI Be the Solution?

Finally, the bill requires the OMB to partner with agencies like the National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST) to study the feasibility of using Artificial Intelligence (AI) to identify duplicative applications (Sec. 4). This is the forward-looking part of the bill—using machine learning to quickly spot waste, fraud, and abuse in the mountains of grant paperwork. If successful, this could significantly streamline the process and make the duplication checks faster and more effective than relying solely on human review.