Purpose: The use of Artificial Intelligence (AI) as an informational resource has become a ubiquitous phenomenon in the last decade. AI shows exciting potential in medical research and vascular surgery is no exception to this. Recurrent neuronal networks have been used to predict bypass stenosis or identify abdominal aortic aneurysms, and algorithms have been developed for predicting ischaemic events following carotid intervention. While the ability of AI to process and distil big data into clinically useful insights is enticing, awareness needs to be spread about the limitations of AI to guide clinical practice. Methodology: A comprehensive literature review was conducted to identify studies that examine current and emerging applications of AI in vascular surgery. Articles evaluating the advantages of AI compared to traditional research methodologies were included, alongside studies highlighting the potential drawbacks, ethical concerns, and technical limitations of AI in this field. Results: Studies consistently report that AI enhances efficiency, reproducibility, and diagnostic accuracy, particularly in the interpretation of imaging, disease diagnosis, and image-guided vascular interventions. Key limitations in the application of AI include the ‘black box bias’ where the reasoning behind the algorithms output cannot be comprehended by the user, propagation of selection bias, variation in AI methodology, lack of standardised reporting, and threats to patient confidentiality. Conclusion: As AI becomes more prominent in healthcare, it is crucial that vascular surgeons are aware of its applications, potential diagnostic and prognostic capabilities, but also of the limitations and ethical considerations surrounding its use. Clinicians must be prepared to engage in informed discussions with patients about the use of AI in their care, ensuring that its implementation enhances, rather than compromises the integrity of medical decision making.