By Tyler Morse
At Team Carey, we understand that securing federal grants can be a transformative opportunity for nonprofit organizations, providing the resources necessary to amplify your mission and make a lasting A recent federal controversy put a difficult question into the spotlight: if government staff can use AI to sift through grant portfolios, reports, and spending data to identify programs for review or even termination, how long will it be before that becomes standard practice across government grantmaking?
Boards and leadership teams should view this as a developing reality, not a remote possibility.
At the federal level, the policy environment has already shifted toward broader AI adoption in government. In April 2025, Office of Management and Budget (OMB) issued guidance aimed at accelerating federal use of AI and driving more efficient AI acquisition, signaling a much more active posture toward public-sector deployment. At the same time, reporting from Reuters and The Washington Post showed that AI was already being used inside parts of the federal government to analyze programs, spending, and internal data during cost-cutting efforts.
For nonprofits and other grant recipients, that matters.
Once AI is used to review grants at the federal level, it is reasonable to expect state and local grant providers to follow. In fact, they already are moving in that direction. The 2025 State CIO Survey found that 82% of state CIOs reported employees using generative AI in daily work and 90% said they were developing AI pilot projects. Separate reporting from Route Fifty and GovTech shows state and local governments using AI for document summarization, workflow simplification, and efficiency gains as budgets tighten and workloads rise.
That does not mean every state agency will suddenly hand grant decisions over to an algorithm. It does mean AI-assisted review of grant performance, compliance, and outcomes is becoming much more plausible within the next three to five years. That timing is an inference, but it is a grounded one: federal policy is encouraging use, states are already piloting AI, and government teams are being asked to do more with fewer resources.
Why AI use in grant oversight is likely to grow
Government Grantmakers face an uncomfortable math problem. Workloads are increasing, reporting expectations are rising, and staffing pressure is not going away. Route Fifty reported that states are doubling down on efficiency and tech modernization as budgets tighten, while GovTech has documented ongoing staffing shortages across parts of government alongside growing interest in AI and automation. The US Government Accountability Office (GAO) has also continued to flag the need for better data collection, information sharing, and reduced reporting burden in grant programs.
That combination makes AI attractive for a simple reason: it can help grant providers process more information faster.
Used well, AI can help agencies:
- summarize large narrative reports,
- flag missing documentation,
- compare budget-to-actual trends,
- identify outliers in spending patterns,
- group similar performance issues across grantees, and
- surface KPI trends that might otherwise stay buried in PDFs and spreadsheets.
Route Fifty recently reported that local governments are already using AI to simplify long federal funding documents and speed opportunity review. That same logic applies on the post-award side: if AI can help staff make sense of a 90-page funding notice, it can also help them digest dozens or hundreds of progress reports after the award is made.
Implications for Nonprofits
The most important takeaway is not fear. It is preparation.
If government grantors begin using AI to evaluate grantees, then nonprofits should assume their reports will be read in two ways: by humans and by machines.
That changes the test.
Historically, many organizations could survive with reporting that was technically complete but inconsistent, overly narrative, or difficult to compare period to period. In an AI-assisted review environment, those weaknesses become much more visible. If a grantor uses AI to scan for KPI movement, missed deliverables, budget variances, staffing ratios, or outcome trends, unclear reporting will not age well.
The nonprofits that perform best in that environment will not necessarily be the ones with the flashiest language. They will be the ones with the clearest data.
How to help clients “have the answers to the test”
This is where advisory firms can create real value. The goal is not to teach clients how to game AI models. The goal is to help them build cleaner, stronger grant reporting so that whether the reviewer is a program officer, an auditor, or an AI tool, the story is credible and easy to validate.
A few practical steps matter most.
1. Standardize KPI definitions
If one quarterly report defines “participants served” differently than the next, AI will surface inconsistency faster than a busy reviewer might. Help clients define each KPI clearly, keep formulas consistent, and document data sources.
2. Make narrative reports evidence-based
Narrative still matters, but it should connect directly to measurable outputs and outcomes. Instead of broad language about success, reports should tie claims to actual results, benchmarks, and explanations for variance.
3. Clean up report structure
AI works best on organized information. Encourage reporting packages that consistently separate financial performance, program activity, deliverables, and outcome measures. Good structure improves both human readability and machine interpretation.
4. Reconcile finance and program data
One of the biggest risks in grant reporting is mismatch between what the program team says happened and what the financial records show. Clients should be reconciling budget-to-actual results, labor allocations, unit metrics, and narrative explanations before submission.
5. Document exceptions before they become flags
If KPI performance dipped because of staffing turnover, procurement delays, or a timing issue outside the organization’s control, explain that clearly. AI tools are good at spotting outliers, but they are not automatically good at context unless that context is present.
6. Improve data hygiene now
Messy spreadsheets, inconsistent naming, duplicate files, and disconnected reporting workflows create risk. The more normalized and disciplined the data environment is, the stronger the organization will be when grantors increase automated review.
The opportunity for clients and advisors
There is an understandable tendency to frame AI oversight as a threat. But there is a more useful way to look at it.
If Grantmakers use AI to sort through reports and measure KPIs, organizations with strong reporting discipline may actually benefit. Clearer data can make strong performers easier to recognize. Consistent documentation can reduce avoidable questions. Better structured outcomes reporting can help credible nonprofits stand out in a crowded funding environment.
That is why this is not just a technology issue. It is a grant management, finance, and governance issue.
Advisors who can help clients improve KPI design, reporting quality, financial alignment, and operational discipline are not just preparing them for a future possibility. They are helping them get ready for a review environment that is already starting to take shape.
Final Thought
AI probably will not replace grant officers, finance reviewers, or program oversight teams. But it is increasingly likely to become the first layer of review.
And when that happens, the question for nonprofits will not be whether AI is fair, fast, or inevitable.
The practical question will be simpler:
When your client’s grant report is screened, summarized, compared, and scored, will the data tell a clear story?
That is the test worth preparing for now.
References:
White House Office of Management and Budget. M-25-21: Accelerating Federal Use of AI through Innovation, Governance, and Public Trust (April 3, 2025). (The White House)
White House Office of Management and Budget. M-25-22: Driving Efficient Acquisition of Artificial Intelligence in Government (April 3, 2025). (The White House)
National Association of State Chief Information Officers (NASCIO). The 2025 State CIO Survey: Leading Change Through Uncertain Times. (NASCIO)
Route Fifty. As budgets tighten, states double down on efficiency and tech innovation (January 22, 2026). (Route Fifty)
Route Fifty. How AI is helping local governments access federal grant funding (December 18, 2025). (Route Fifty)
Route Fifty. Generative AI’s state government use ticks up (October 22, 2025). (Route Fifty)
Smart Cities Dive. How state CIOs are using GenAI (October 28, 2025). (Smart Cities Dive)