Biodiversity is vital to sustainable development, public health, and ecosystem stability, and we are currently witnessing an unprecedented loss of biodiversity. To better understand and hopefully mitigate this loss, networks of ground-level sensors, satellites, drones, and community scientists are deployed to collect natural-world data at unprecedented scales. There is valuable scientific information stored in these raw data, the vast majority of which are as-yet inaccessible due to the time and resources needed to process the data by small groups of relevant human experts. AI is crucial to facilitate efficient extraction of scientific insights from quickly growing repositories of natural world imagery, and I will present several novel, application-driven innovations in AI which help realize the goal of global-scale, near-real-time biodiversity monitoring.