Washington, DC, 19 October 2026 — As countries work to accelerate delivery on the Kunming-Montreal Global Biodiversity Framework (KMGBF) 2030 targets, how can data, evidence and artificial intelligence (AI) create opportunities to integrate knowledge across cultures, formats and scales to improve decision-making, target interventions, track environmental change and strengthen adaptive management? The Scientific and Technical Advisory Panel (STAP), the Global Environment Facility (GEF) Secretariat and the GEF Independent Evaluation Office (IEO) will bring together a group of speakers to explore different pathways from data to policy and action, to evaluation of what works at a joint event during the seventeenth meeting of the Conference of the Parties to the Convention on Biological Diversity (CBD COP 17).
Titled “Data, Evidence and AI: Opportunities and Cautions for Accelerating Progress Towards the KMGBF Targets,” the event will take place on 22 October 2026, from 10:00 a.m. to 1:00 p.m., at the GEF Pavilion in Yerevan, Armenia, with a networking breakfast session from 9:00 a.m. to 10 a.m.
Advances in biodiversity data, monitoring technologies and AI offer new opportunities to improve decision-making. Yet these tools also bring risks, including data gaps, algorithmic bias, unequal access to technology and the environmental costs of AI infrastructure.
The challenge is to ensure that scientific knowledge and technological innovation translate into effective, equitable, and lasting outcomes for nature and people. This also means integrating Indigenous Peoples’ data with mainstream scientific data to inform intervention design and support effective adaptive learning, while respecting Indigenous Peoples’ knowledge, data sovereignty, and free, prior, and informed consent. By connecting scientific evidence, implementation experience, and evaluation findings, the event aims to identify transferable lessons and practical entry points to accelerate progress toward the KMGBF targets.
As the 2030 deadline approaches, the priority is not simply to generate more data or adopt new technologies, but to use evidence responsibly and direct knowledge and investment towards results that benefit biodiversity and people.
