California Department of Fish and Wildlife biodiversity monitoring projects like the California Environmental Monitoring and Assessment Framework and Sentinel Sites for Nature, use trail cameras to collect data on small to large-sized mammals and reptiles at over 300 sites annually, resulting in millions of wildlife camera images each year. To process these data in a timely and consistent manner, we developed a data processing pipeline that uses artificial intelligence (AI), human validation, and sharing information through online platforms. We use Wildlife Insights to store and identify photos because the AI tool automatically identifies blank images and photographed animals to species, reducing our processing time by ~75%. To help people correct or confirm AI-generated species tags and ensure consistency, we created identification guides in ArcGIS Experiences. We provide example camera trap images and descriptions for all photographed animals, including small mammals and reptiles that can be challenging to identify. Our pipeline enables a small team of people, regardless of experience, to quickly process millions of images, making our methods scalable and open to collaboration. It also enables us to ask statewide questions that improve our understanding of how land use and climate-related changes are impacting our state’s natural resources.