This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterised by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis and risk stratification, syncope poses significant healthcare challenges. AI has the potential to improve symptom differentiation, risk assessment, and patient management. Machine learning, specifically Artificial Neural Networks (ANNs), has shown promise in accurate risk stratification. Artificial intelligence-powered clinical decision support tools can improve patient evaluation and resource utilisation. While AI holds great promise for syncope management, challenges such as data quality, class imbalance, and defining risk categories remain. Ethical concerns about patient privacy, as well as the need for human empathy, complicate AI integration. Collaboration among data scientists, clinicians, and ethics experts is critical for the successful implementation of AI, which has the potential to improve patient outcomes and healthcare efficiency in syncope management.