With the advent of cheaper and more capable sensors, ecologists are collecting data at a never before seen rate. With this influx of data comes a new challenge, analysing and drawing out insights. With this data boom, another development has come about: AI/ML systems capable of processing large amounts of data either on the edge or in post. As the challenges of biodiversity loss and climate change intensify, we not only need new solutions but more timely ones; a way of going through past and current data more efficiently.

We will highlight various applications of AI in ecology, including tools for ecoacoustics, which enable powerful biodiversity monitoring through soundscape analysis, providing insights into species presence and ecosystem health. Additionally, we will discuss advancements in both 2D and 3D AI-image systems which promise to revolutionise classification, tracking, and monitoring at scale. These include emerging technologies like Neural Radiance Fields (NeRFs), which facilitate the creation of real-time 3D models of environments directly from mobile devices., The role of Large Language Models (LLMs) in analyzing extensive ecological literature and generating actionable recommendations for conservation will also be examined.

These examples demonstrate how AI can not only democratize access to high-quality ecological data but enhance our understanding of spatial dynamics in ecosystems, ultimately supporting more effective conservation planning and resource management. In a world where scientists are able to collect data at an ever-faster pace, we provide ways to process and utilize this data using cutting-edge AI/ML systems. 

The symposium will bring together experts from diverse fields to foster interdisciplinary dialogue on these innovative applications. By sharing their insights, we hope to ignite discussions about future research opportunities and collaborations that leverage AI for ecological and conservation initiatives, ultimately benefiting the ATBC community at large.