Purpose: Artificial intelligence (AI) offers potential opportunities for novel methods of management of patients with vascular surgical conditions. This review aims to examine AI’s potential role in the management of patients undergoing endovascular repair of abdominal aortic aneurysms (EVAR). Methodology: A comprehensive literature review and online search was conducted to gather information on the current uses of AI in EVAR. Relevant journal articles, reports, and case studies were analyzed to identify AI’s current role and potential limitations in its use in patients undergoing EVAR. Results: Various AI-based models have been developed for EVAR. These include models assessing real-time identification of suitable landing zones during EVAR, prediction of post-EVAR complications, risk estimation during EVAR and stent graft segmentation. The strength of AI is in its ability to analyze vast quantities of clinical information and its ability to continuously improve its performance. Though promising, there are various limitations. The majority of these AI models were trained on small retrospective databases with less than 200 patients. Their performance was also limited when handling atypical images or clinical information that deviated from the dataset that it was trained on. To date, these AI models have not yet undergone external validation or been compared to surgeon judgement in a randomized and prospective fashion. Further research must focus on whether these AI models are superior to surgeon judgement and perception and whether AI can improve outcomes in patients undergoing EVAR. Conclusion: This review demonstrates the current applications of AI in the management of patients undergoing EVAR and its emerging potential. Future development of AI in EVAR must involve larger datasets that are externally validated with a focus on an improvement in patient outcomes.