Climate change poses a major threat to biodiversity globally, and the ability to detect and respond to change within populations, species, and ecosystems is critical to mitigating the ongoing biodiversity crisis. As policymakers, land managers, and communities struggle to protect species and preserve or restore ecosystems, there has been an urgent need for data on how species abundances and distributions are changing and tools to assess the efficacy of policies and interventions. However, these data and tools remain very limited, due to the effort and expertise needed for effective data-gathering and tool development, the fast pace of ecological change, and imbalances in resources across geographies and taxonomic groups.Artificial Intelligence (AI) systems are well positioned to help fill the information gap, via massively scalable data streams such as satellite imagery, visual and audio sensors, environmental DNA, and participatory science data platforms. AI could enable a new paradigm of biodiversity change monitoring, making it possible to detect changes across taxonomic scales (from populations to ecosystems), spatial scales (from site to continental), and temporal scales (days to decades) that would be undetected with existing data streams and more traditional survey approaches.We propose a Global Climate Center on AI and Biodiversity Change (ABC) bringing together ecologists and AI researchers, together with stakeholders such as nonprofits, citizen scientists, and policymakers, to co-design and deploy AI-enabled solutions for biodiversity. Specifically, we will study cross-cutting research questions in biodiversity change, design innovative AI algorithms to match these challenges, publish open-source tools for community use, and co-design educational programs and resources to train AI and ecology stakeholders.