A two-day workshop jointly organized by the Food and Agriculture Organization of the United Nations (FAO) and Purdue University brought together global experts to explore the transformative potential of artificial intelligence (AI) in forest growth monitoring and climate mitigation efforts.

Forests play a critical role in capturing and storing carbon dioxide. However, recent studies reveal a troubling decline in the planet’s carbon sink capacity, posing risks to global climate targets.

In response, FAO’s AIM4Forests programme is launching For-Growth, a pioneering initiative that integrates AI with the Global Forest Biodiversity Initiative (GFBI), one of the largest in-situ forest databases. Together, they comprise the MATRIX forest growth model, designed to significantly enhance the accuracy of aboveground biomass (AGB) growth rate estimates, which can contribute to climate mitigation initiatives.

“The integration of AI and machine learning into forest monitoring can be a major step forward for forest-based climate action,” said Javier García Pérez, FAO’s Forestry Officer. “With tools like MATRIX, countries would gain unprecedented precision and automation in tracking biomass, enabling more reliable greenhouse gas inventories and improved carbon accounting.”

A diverse and influential group of changemakers convened for the workshop, including leading forest ecologists, AI developers, policy advisors, climate philanthropists, representatives from multilateral development agencies, and emerging leaders and researchers in forest science.

Tackling key challenges

The workshop focused on addressing three core challenges to scaling AI-based solutions in forest monitoring:

• bridging the gaps in global carbon budgets through AI tools tailored to country-specific needs for national greenhouse gas inventories and forest management;
• translating scientific innovation into practical support to national measurement, reporting and verification (MRV) systems; and
• fostering collaboration among participating – international organizations, academia and research centres to ensure operationalization of joint priorities.

Participants recognized the need to harmonize different approaches for estimating forest growth rates. The importance of applying the FAIR principles to promote high-quality data that is findable, accessible, interoperable and reusable was also highlighted. Furthermore, they emphasized the importance of an approach that is just and equitable towards those who manage forests – including producers, Indigenous Peoples, local communities and data owners – to ensure technical effectiveness along with respect for the fundamental rights of key stakeholders.

“Artificial intelligence is now part of our reality, and we must harness it to improve forest monitoring,” noted Maria Sanz, Scientific Director of the Basque Center for Climate Change. “This workshop was key in bringing together diverse research groups working on different aspects – from remote sensing to field data collection – and exploring how AI tools can connect these efforts to support more informed decisions for monitoring and managing forests.”

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