The Patrick J. McGovern Foundation Data Practice Accelerator supports nonprofits working with complex datasets and analytical approaches to drive social impact. Selected cohort members receive up to $125,000 in funding plus intensive technical support including access to advanced data tools, industry-standard guidance from data scientists, engineers, and program managers. The program's goal is to de-risk learning by creating a space for nonprofits to build capacity for advanced data management, analytics, AI tools, and governance approaches. Previous cohorts focused on themes like Data at the Nexus of Climate and Health. The program operates on a cohort-based model with curated peer-to-peer learning.

Patrick J. McGovern Foundation Data Practice Accelerator Program is a grant from the Patrick J. McGovern Foundation that funds nonprofits seeking to advance their data and AI capabilities. Awards reach up to $125,000 and are paired with hands-on technical partnerships: selected organizations work directly with PJMF data engineers and technologists to prepare data assets, develop infrastructure, and translate complex datasets into actionable strategy. Eligible applicants are nonprofits at any stage of data readiness with complex datasets. Alongside funding, grantees receive long-term technical assistance and access to data science expertise to help build and sustain high-impact, AI-driven programs. The application deadline is July 1, 2026.

CIFAR and the Canadian AI Safety Institute fund Catalyst Project proposals addressing sociotechnical considerations in AI safety. The program supports interdisciplinary research in machine learning applications to science and society, with recent funded projects spanning misinformation combat, trustworthy language models, democratic alignment of AI systems, Indigenous AI governance, and real-world safety in autonomous systems. Designed to catalyze new research areas and collaborations at the intersection of social sciences, humanities, and AI safety.

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 enables key partnerships that accelerate the research-to-deployment cycle, creating synergies between academic researchers, nonprofits, startups and other companies, and governmental or intergovernmental organizations. Funded by the Quadrature Climate Foundation, Schmidt Futures, and Google DeepMind, with Future Earth serving as fiscal sponsor, this is one of the few dedicated grant programs specifically targeting the intersection of AI/ML and climate change. Projects typically involve climate modeling, weather prediction, emissions monitoring, energy optimization, biodiversity monitoring, and other environmental applications of machine learning. The 2026 competition opens with a full proposal deadline of September 15, 2026. The program has grown steadily since its inception, funding 23 projects to date across diverse climate domains and geographies.

The Climate Change AI Innovation Grants 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. Projects must create publicly available datasets and tools as digital public goods, and release open-source code. The program builds partnerships between academic researchers, non-profits, startups, companies, and governmental organizations to accelerate the research-to-deployment cycle. Past funded projects span climate modeling, emissions monitoring, renewable energy optimization, and disaster prediction across all continents.