Motion-triggered camera traps are revolutionizing wildlife monitoring, generating vast amounts of data challenging manual analysis. SpeciesNet, a Google-developed AI model, identifies nearly 2,500 animal species in camera trap images, trained on millions of labeled images. Released as open-source, SpeciesNet allows global research groups to analyze data, accelerating research and conservation efforts. This AI tool identifies species with high accuracy, assisting in population health assessment and migration studies. SpeciesNet is integrated with Google Earth AI, supporting deep planetary intelligence to address global conservation needs. The model can process large volumes of images daily, offering efficient data analysis for researchers. Various organizations worldwide are adapting SpeciesNet, including the Wildlife Observatory of Australia and the Idaho Department of Fish and Game. SpeciesNet is incorporated into platforms like Wildlife Insights and Animl, enabling widespread access and collaboration. This technology aids in identifying rare and endangered species monitoring and management decisions. The open-source model encourages collaborative refinement with the goal of protecting biodiversity.