The purpose of this review is to evaluate AI applications in the analysis of biopsies and imaging modalities for patients with SARDs, systemic autoimmune rheumatic diseases. The review includes studies that utilized diagnostic models, segmentation models, infrequently regression models, and supervised learning, with most AI models used in SARDs using supervised learning. Supervised learning labels all inputed data, including patients and images, which can be useful for image analysis. However there are challenges as the datasets used to train the models often greatly differ from actual cases, limiting the use of AI image analysis. The review also discussed the need for more prognostic models that would be able to predict treatment response. Overall, AI can be useful in the field of systemic autoimmunity as it can handle larger datasets and utilize more complex pattern recognition, however further research is needed to fully refine the applications of AI.