Pulmonary hypertension (PH) is a severe and oftentimes fatal disease with a high degree of clinical variability. Its complexity necessitates a multifaceted approach, with clinical and prognostic results significantly improved with earlier identification and initiation of treatment. Developments in artificial intelligence (AI) and machine learning (ML) allow earlier diagnosis, individualized treatments, and new therapeutic options, which have already shown real potential to improve patient outcomes; such an intricate approach was not feasible before the AI innovations of the last decade. This article outlines the current applications of AI and ML for diagnostics, treatment optimization, surveillance, and drug discovery for PH.