Artificial intelligence (AI) and machine learning are terms describing software approaches that can be trained to perform tasks. Pattern recognition is at the core of most AI tools, including the growing suite of approaches for identifying wildlife. We describe the AI Image Toolkit (AIT, https://ait.dudek.com), a web-based system using a series of tasks in an overall workflow: 1) processing of large image datasets to identify and isolate images containing animals, 2) management of image files as part of camera trap projects, and 3) provision of data useful in occupancy and other modeling. In the first case, raw data from camera traps are uploaded to a cloud location. The tool identifies images containing animals (>95% accuracy) and returns them to a user in a zip file, along with a count of number of individual animals. In the second case, images containing animals are transferred to a web-based system, where the user can tag images with species, number of animals, behavior, demographics, and other information. In (3), data and metadata are organized and can be queried and automatically packaged into formats used in GIS or statistical analysis; for example, occupancy models, diversity indices, effectiveness of crossing structures.