The problem
AI funding exists for almost every field. Finding it is the hard part.
You know your field. You don’t know the AI funding landscape.
You’re a cancer biologist, a climate modeler, a soil scientist, an education researcher. You want to use machine learning in your next project. But AI funding is scattered across NSF, NIH, DOE, USDA, DARPA, and dozens of foundations — none of them organized by "projects that use AI."
Every agency frames AI differently
NIH calls it "data science and artificial intelligence." NSF files it under "CISE" or "smart and connected communities." DOE says "advanced scientific computing." USDA calls it "data-driven decision systems." The same approach needs completely different language depending on who’s funding it.
Proposals need AI methodology you haven’t written before
Reviewers want to see your ML pipeline, your training data strategy, your validation approach, your compute requirements. If this is your first AI-integrated proposal, you’re writing sections you’ve never seen in your discipline’s grant templates.
Deadlines close before you find the program
An NSF Dear Colleague Letter opens a 6-week window. A DOE FOA drops with a 45-day deadline. By the time a colleague forwards you the link, you’re already behind.
Who this is for
AI grants for every field, not just computer science
The biggest growth in AI funding isn't in CS departments — it's in domain-specific applications. Whatever your field, there's funding for AI-integrated research.
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