Part 2: Don't Let AI Sink Your Grant: How to Use It The Right Way, The Grantee Perspective

This article is Part 2 of a two-part series on AI and federal grants. Read Part 1, where we examined the use of AI from the federal perspective.

By: Jason Mistlebauer, Director of Grants and Policy 

April 23, 2026

 I wrote this series based on last month's REI Systems and National Grants Management Association (NGMA) 2026 Annual Grants Management Survey Results Webinar. What I heard there made one thing clear: the conversation around AI in federal grants has moved well beyond speculation. Representatives from several federal agencies spoke candidly about how AI is actively reshaping their grant management processes, from application review to compliance monitoring to post-award reporting. 

This is not a future trend. It is already happening at scale within the agencies your organization applies to. That reality is further validated by the Office of Management and Budget's (OMB) recent update to its government-wide AI use-case website. The numbers are striking: the latest inventory shows a 70% increase in reported AI use in 2025, with more than 3,600 documented AI use cases across the 56 federal agencies that submitted data.

For grant seekers, that figure is not just a data point; it is a signal. The agencies evaluating your applications are increasingly using the same technologies that many applicants are now using to write them. Understanding what that means for how you prepare and submit your applications has never been more important.

Start with the Notice of Funding Opportunity (NOFO).

The single biggest mistake AI-assisted grant writers make is treating the NOFO as an afterthought. AI tools are trained on vast amounts of general information. Still, they do not understand the specific program you are applying for, the agency's fiscal year priorities, or the nuances that distinguish one funding opportunity from another.

During the aforementioned webinar, a representative from the US Department of Agriculture (USDA) made this point regarding one of their research programs, which has 27 distinct components: an AI tool that is not explicitly anchored to the correct component will produce a grant application that sounds professional but misses the target entirely.

Before you write a single word, read the NOFO front to back. Then, when you use AI, feed it the actual NOFO text and instruct it to work only within that framework. If you skip this step, you are not saving time. You are setting yourself up for your application to be rejected for entirely avoidable reasons.

Give the AI your real program information.

This is where many applications fall apart. Federal grants, especially those awarded to state and local applicants, require applicants to ground their proposals in real data. Their own performance history. Their local needs assessment. The specific populations they serve. The measurable goals are tied to their actual geography and context.

An applicant representative on the webinar panel from the State of Kansas Department of Education described a US Department of Education (ED) application process so specifically that using AI is almost self-defeating. School districts must review their performance data over the past 3 years, identify their gaps, and propose strategies tailored to their local circumstances. No AI can do that without you first handing it the information. If you are using AI to draft narrative sections, give it your actual numbers and your actual program description. A polished narrative about “nobody's” program will not fool a human reviewer, let alone a federal AI system designed to detect exactly that kind of mismatch.

Use AI to pressure-test your draft, not to write it from scratch.

The most effective role for AI in grant writing is not generating the first draft. It is about improving the draft you have already built using real content. Once you have something on paper, use AI to sharpen the language, identify gaps, and check that you have responded to every evaluation criterion in the NOFO. Ask it directly: evaluate my application against the NOFO and identify strengths and weaknesses? What is missing? What would not hold up under scrutiny? That kind of analytical pass, using AI as a tough editor rather than a ghostwriter, plays to the technology's strengths while keeping you in control of the substance.

Check every fact before it goes out the door.

AI generates plausible-sounding content, which is different than reliably accurate content. Citations can get fabricated. Statistics have been invented. Research findings are attributed to studies that do not exist. In a federal grant application, that is not just an embarrassment; it is a potential integrity violation with real consequences for your organization's relationship with the agency.

Every factual claim in your application should be verified against a real source before you submit. Every citation should be checked. Treat anything the AI produces the way you would treat a first draft from a new hire: review it carefully, because the responsibility for what goes out under your name is yours.

Make sure your reports match your application.

A US Department of the Interior (DOI) representative on the webinar specifically called out the problem of progress reports that do not align with what the applicant originally promised. Federal AI systems are checking for that consistency. If your reporting drifts from your original project description, even if the work itself was solid, it raises flags. Build that consistency in from the beginning. The discipline required to write a strong application does not end with the award; it carries through implementation and reporting.

Find out what the agency actually allows.

There is no universal federal policy on the use of AI in grant applications. The USDA alone has 21 awarding agencies, and its webinar representative noted that some have explicit guidance (published policy) on the topic. In contrast, others have not addressed it at all yet. Before you submit anything AI-assisted, check whether the agency has issued guidance. If it has not, that does not mean you are in the clear; it means the standard of accountability still applies. You will be evaluated on the quality and integrity of your submission regardless of how it was produced.

The bigger picture.

Here is the thing that tends to get lost in the AI conversation: the federal officials who were most candid about all of this are not trying to catch applicants doing something wrong. They are trying to fund programs that work. The AI systems they described, tools that check budget narratives, audit compliance, and flag inconsistencies between applications and reports, are not traps. They are making efforts to manage an enormous, complex grants ecosystem more efficiently and ensure money goes where it is supposed to go.

For applicants, that is actually useful information. If you know what the agency's systems are looking for, you can write to meet that standard rather than hoping you have guessed right. Clear language. Specific data. Criteria addressed directly. Budget narratives that are honest and defensible. Reports that track with what you promised.

AI can help you get there. It can help you write more clearly, catch gaps in your narrative, and stress-test your draft before it goes out. What it cannot do is replace the knowledge of someone who genuinely understands the program and your project, has read the NOFO carefully, and knows the difference between a strong application and a well-formatted one.

That distinction is what gets applications funded. And no technology changes it. 

Managing grants efficiently, without compromising compliance and integrity, can be a challenging task. If your organization is navigating the complexities of grant management, we can help you enhance oversight, streamline processes, ensure outcomes and reduce the risks of waste, fraud, and abuse. Reach out today to learn how our expertise in grants management can ensure your programs meet their goals, stay compliant, and make the best use of taxpayer dollars. 

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