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Climate Change AI Innovation Grants for Machine Learning and Climate Action is sponsored by Climate Change AI (fiscally sponsored by Future Earth; supported by Quadrature Climate Foundation, Google DeepMind, Global Methane Hub). This program supports catalytic projects using AI and machine learning for climate action, funding research and deployment challenges in climate change mitigation, adaptation, and climate science.
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Climate Change AI Announces Innovation Grantees (April 29, 2026) | Climate Change AI Climate Change AI Innovation Grants Award $1. 7M to Projects Worldwide Interdisciplinary innovators using AI to fight climate change receive funding via the prestigious Climate Change AI Innovation Grants Program for catalytic projects and dataset creation.
Today, Climate Change AI announced awardees in its Innovation Grants program, which funds cross-sectoral teams tackling important climate challenges using AI algorithms. Climate Change AI is a nonprofit organization that has been critical in building the field of AI-for-climate.
Its Innovation Grants program has become exceptionally competitive, with 12 projects chosen this year out of over 400 submissions from institutions in 78 countries, with a total value of $1. 7M USD in grants awarded.
“We target especially catalytic projects using AI for climate action,” explained Dr. Maria João Sousa, Executive Director of Climate Change AI, “On top of direct impacts, teams are expected to build critical datasets as a digital public good supporting further innovation, and to release open-source code.
” Prof. Priya Donti of MIT, Co-Founder of Climate Change AI and one of TIME’s 100 Most Influential People in AI, said: “In a time where people often think AI means large language models from big tech, these projects show that on-the-ground impact often comes from completely different kinds of AI built by multi-stakeholder teams to match targeted societal needs.
” This round of the Climate Change AI Innovation Grants program was made possible thanks to the support of Quadrature Climate Foundation , Google DeepMind , and the Global Methane Hub . Climate Change AI is also grateful to the Canada Hub of Future Earth for serving as the fiscal sponsor for this program. Funding was awarded to the following projects, for which further information is available at www.
climatechange. ai/innovation_grants : CO-AI: Bridging Local Knowledge and AI through Coproduced Tools for Disaster Risk Reduction New York University (USA); ICLEI Africa (South Africa) Can AI technologies increase farmer’s resilience to climate change?
Impact evaluation of Croppie University of Göttingen (Germany); CGIAR (Colombia) DNA_DRV; the DNA biodiversity drive University of Auckland, Terra Pura Consulting, The NZ Institute for Public Health & Forensics Science, Te Tiaki Mahinga Kai, Bioeconomy Science Institute (New Zealand) Using Earth Observation and AI/ML technologies to support climate change adaptation for sustainable coral reef management and shoreline defence University of Queensland, University of New South Wales (Australia); Pele Island Environmental Livelihood Solutions Network, Live and Learn Vanuatu (Vanuatu) CLIMAI: Anticipating and reducing climate-driven mosquito-borne disease risks through data and collaboration University of Granada, Doñana Biological Station, Complutense University of Madrid, Andalusian School of Public Health (Spain); French National Research Institute for Sustainable Development (France); Universidad del Valle, Pontificia Universidad Javeriana, National University of Colombia (Colombia); McGill University (Canada); Ministry of Health (Costa Rica) FieldValAI: analysis ready AI training data for smallholder climate change adaptation strategies International Food Policy Research Institute (USA & Kenya); BlueGreen Labs (Belgium); ACRE Africa (Kenya); Dvara E-Registry (India) A Foundational Methane Detection Dataset: Transparent Access to Cloud-Optimized Spatio-Temporal Datasets (TACO) University of Valencia, Polytechnic University of Valencia (Spain); Leipzig University (Germany) Machine Learning and Decision Modeling for Climate-Smart Beef Production in South Africa Texas A&M University (USA); University of Pretoria, Agricultural Research Council (South Africa) Methane Emission Estimation from CAFOs with Machine Learning Stanford University (USA) Modeling and Learning Locational Emission Rates for Low-Carbon Power System Planning and Operation University of Alberta (Canada); University of California San Diego, ISO New England (USA) Madagascar energy insights: a multi-layered ground-truth and geospatial dataset for AI-powered solar forecasting and energy planning MAIDI, CNIA Madagascar, Solar Madagascar Power (Madagascar) SEER - Sustainable Electricity Expansion Roadmaps: Democratizing power systems planning for a robust and sustainable energy transition Rhiza Research, University of Washington (USA) Climate Change AI is a nonprofit that empowers a global community of innovators, practitioners, and decision-makers to accelerate responsible climate action through the use of AI, by addressing critical gaps in expertise, education, coordination, and research-to-deployment infrastructure.
Since 2019, Climate Change AI has inspired, informed, and connected thousands of stakeholders across the academic, private, and public sectors through networking and knowledge-sharing events, summer schools and other educational programs, international policy reports, and global grants programs.
Website , LinkedIn , BlueSky , Twitter The Climate Change AI Innovation Grants program supports projects that address research and deployment challenges in climate change mitigation, adaptation, and climate science by leveraging AI and machine learning, while also creating publicly available datasets and tools to catalyze further work. The program allocates grants typically of up to $150K for projects of one year in duration.
So far, Climate Change AI has allocated $4. 9 million USD in funding, including 34 projects over a broad range of application areas, with investigators from 97 institutions across 26 countries on 6 continents. Media contact: press@climatechange.
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According to the current listing, eligibility includes: Each application must have a Principal Investigator (PI) affiliated with an accredited university in an OECD Member country. Key partnerships with non-academic organizations are welcomed. Confirm the full requirements in the official notice before applying.
The current listing shows up to $150,000 USD per project for one year. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Climate Change AI Innovation Grants for Machine Learning and Climate Action is funded by Climate Change AI (fiscally sponsored by Future Earth; supported by Quadrature Climate Foundation, Google DeepMind, Global Methane Hub). 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.
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