This bridge addresses the grand challenge of developing AI systems that are ecologically grounded, culturally aware, and robustly generalizable across species, ecosystems, and deployment conditions. We aim to catalyze a sustained interdisciplinary community at the intersection of AI and wildlife conservation, recognizing that conservation is not solely a technical problem but also a cultural and societal one. By bringing together AI researchers, ecologists, Indigenous knowledge holders, and conservation practitioners, the bridge will explore open research questions, highlight successes and failures, and build shared infrastructure and research agendas. Through tutorials, case studies, and panel discussions, participants will gain a shared understanding of conservation realities and AI capabilities, while co-developing roadmaps for ethically grounded, field-ready, and scalable solutions to biodiversity loss and environmental change.

Topics
Core technical advances in AI for conservation; case studies in species re-identification, movement ecology, invasive species control, and habitat monitoring; cultural and ethical dimensions of deploying AI in conservation; benchmarks, datasets, and evaluation frameworks; vision-building toward a shared research roadmap; short discussion on research opportunities.

Attendance
The bridge will host 30–50 participants. Attendance is open to AI researchers, ecologists, conservation practitioners, early-career researchers, students, and policymakers. Space is limited to encourage active discussion and community-building.

Submission Requirements for Workshop Session
We invite submissions of 2–4-page extended abstracts (excluding references) describing relevant research, case studies, or ongoing work. Submissions should highlight both technical contributions and real-world conservation applications.