Since their first description in 1948, Spitz tumours remain one of the most challenging diagnostic entities in dermatopathology due to their complex histological features and ambiguous clinical behaviour. In recent years, artificial intelligence (AI) solutions have demonstrated significant potential across a wide range of medical applications, including computational pathology, for decision-making in diagnosis, along with promising advances in prognosis and tumour classification. However, the application of AI to Spitz tumours remains relatively underexplored, with few studies addressing this field. Yet in this evolving technological landscape, could AI provide the insights needed to help resolve the diagnostic uncertainties surrounding Spitz tumours? How could this technology be leveraged to bridge the gap between histopathological uncertainty and clinical accuracy? This review aims to provide an overview of the current state of AI applications in Spitz tumour analysis, identify existing research gaps, and propose future directions to optimize the use of AI in understanding and diagnosing these complex tumours.