Research & Development

Extreme weather occurrences are increasing precipitation variability, narrowing planting windows and potentially impacting yields as early as 2030. This will affect our production of food, fiber, and fuel in the face of increasing demand due to population growth. At the same time, agriculture and forestry have unrealized potential to regenerate their soils, increasing their resilience to extremes and unrealized potential for economic gain which will help the rural economy and our country’s national security. While our forests and farms have significant untapped potential for carbon accrual realizing this potential requires addressing competition between land for biomass production and ecosystem services, scientific and technological challenges of actionable (e.g., less expensive and more accurate) sequestered carbon verification, computational integration of the incentive structures of land managers that implement agriculture and forest management practices, and innovations to encourage large-scale equitable adoption of regenerative agricultural practices.

AI-LEAF Institute’s mission is to revolutionize AI and enhance the sustainability and resiliency of agriculture and forestry, aiming to tackle previously insurmountable challenges and expedite adaptation and mitigation efforts, while informing policy and bolstering markets.

We aim to advance agriculture and forestry decision support by delivering AI-powered models, such as COMET emulators, digital twins, and Earth Economy models, that directly inform farm management, forest stewardship, and policy decisions, with success measured by tool adoption, user training, and policy impact. The initiative also seeks to build more resilient agricultural and forestry systems through predictive modeling of sustainability challenges, including geographic shifts, pest and disease risks, and carbon storage potential, as reflected in the production of resilience maps, agency use of risk assessments, and documented adaptation case studies. In parallel, AI-LEAF is committed to developing a highly qualified and diverse AI workforce by expanding interdisciplinary curricula, mentoring, and extension training that prepare students and professionals to lead at the intersection of AI, agriculture, and forestry, with outcomes tracked through participation, new educational offerings, and career trajectories. The program will further create and disseminate benchmark datasets and standards by releasing harmonized soil, crop, forest, and greenhouse gas datasets with transparent protocols that establish a gold standard for agricultural and forestry AI, measured through dataset releases, citations, and integration into decision systems. Finally, AI-LEAF will build and sustain a strong community of practice by deepening partnerships with USDA, industry, and non-governmental organizations and embedding stakeholder input throughout the research lifecycle, with success indicated by partnerships formed, resources leveraged, and stakeholder-informed tools and datasets.

Note: Research Themes have been expanded and can be found on the new AI-LEAF Research Themes web page.