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The National AI Research Institutes program, led by NSF in partnership with USDA-NIFA and other agencies, funds large-scale, multi-institution research institutes that advance foundational and use-inspired AI while training a diverse AI workforce. USDA-NIFA fully funds the agriculture- and environment-focused themes, including AI-Driven Innovation in Agriculture and the Food System and AI for Climate-Smart Agriculture and Forestry.
Funded institutes such as AgAID (Washington State University) and AIIRA (Iowa State University) integrate AI into prediction, decision support, robotics, and digital twins to address labor, water, weather, and climate-change challenges across crop and food production. Each institute is funded at roughly $20 million over five years.
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Or search similar grants →According to the current listing, eligibility includes: U.S. institutions of higher education and eligible nonprofit research organizations leading multi-institution, multi-disciplinary teams. Institutes must focus on one of the program's designated AI research themes; agriculture and climate-smart agriculture themes are funded by USDA-NIFA. Confirm the full requirements in the official notice before applying.
The current listing shows each institute receives approximately $20,000,000 over five years. Recent rounds have invested roughly $220 million across multiple institutes, with USDA-NIFA fully funding agriculture- and climate-focused themes such as AI-Driven Innovation in Agriculture and the Food System and AI for Climate-Smart Agriculture and Forestry. Verify award ceilings, matching requirements, and allowable costs in the official notice.
NSF and USDA-NIFA National Artificial Intelligence Research Institutes for Agriculture, Food Systems, and Climate-Smart Agriculture is funded by National Science Foundation (NSF) and USDA National Institute of Food and Agriculture (USDA-NIFA). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The NEH Humanities Research Centers on Artificial Intelligence program funds the creation of university-based humanities research centers focused on the ethical, legal, and societal implications of artificial intelligence. Funded centers undertake interdisciplinary humanities-led research that brings ethics, law, history, philosophy, anthropology, religious studies, literature, linguistics, and cultural studies to bear on questions raised by AI systems. Topics include responsible AI governance frameworks, AI and civil rights, AI and labor, cultural impact of generative AI, AI and creative authorship, philosophical foundations of machine reasoning, history of AI thought, and humanistic evaluation of AI safety and alignment. Centers are expected to convene researchers, train new humanities scholars in AI, host public-facing programming, and produce publications and translational tools that inform policy and public understanding. Strong fit for universities seeking to launch sustained interdisciplinary AI humanities research programs in partnership with computer science and other STEM departments.
SaTC 2.0 is NSF's flagship cybersecurity, privacy, and trust research program reorganized to address emerging threats including generative AI security, open-source software security, quantum computing security, and supply chain security. Funded scope covers the bidirectional role of AI as both a cybersecurity threat (adversarial attacks on AI systems, AI-enabled cyberattacks, data poisoning) and a defensive tool (AI for intrusion detection, automated vulnerability discovery, secure-by-design AI). The program supports interdisciplinary collaboration across computer science, mathematics, social and behavioral sciences, and STEM education to build trust in global cyber ecosystems.
NSF SaTC 2.0 (Security Privacy and Trust in Cyberspace) is the largest open solicitation for university-led cybersecurity research in the federal portfolio now expanded with AI security as an explicit priority area. The 2.0 reboot added generative AI security open-source software security quantum computing security and supply chain security as topics of interest addressing the bidirectional role of AI as both a cybersecurity threat and a defensive tool. Research awards support adversarial machine learning and attacks on AI systems AI weaponization against people information and systems privacy-preserving machine learning and responsible AI use for detecting and responding to cyber threats. The program funds three award types: Research awards up to $1.2M for four years Education awards up to $500K for three years and Seedling awards up to $300K for two years through Dear Colleague Letters. Proposals are accepted on a recurring annual basis with two windows per year. This is distinct from NSF CyberAICorps which focuses on scholarship and workforce development and from NSF AIMing which focuses on AI formal methods and mathematical reasoning.
USDA NIFA's Community Food Projects Competitive Grants Program offers $4.8M in FY2026 with a July 16 deadline — planning grants to $50K and project grants to $400K over four years. The catch is a 1:1 match that screens out most applicants. Here is how to build the match, choose your track, and write a self-reliance story that scores.
Read articleWhile headlines chase AI and defense money, USDA's National Institute of Food and Agriculture runs a tight summer competitive cycle — Equipment Grants (June 25), Agricultural Genome to Phenome (June 29), New Beginning for Tribal Students (July 2), and Crop Protection and Pest Management (July 6). Here is how the four programs fit together, who is eligible, and why the land-grant system has a structural edge.
Read articleSecretary Rollins and NIFA opened the FY26 Research Facilities Act Program on June 15 with a four-tier award structure scaling from $100K planning grants to $30M facility complexes. The dollar-for-dollar cash match, the one-project-per-institution rule, and the 32-day application window are reshaping how land-grants will prioritize their long-deferred capital backlog.
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