Psoriasis is a chronic, immune-mediated skin disease characterized by recurrent inflammation and a significant burden on patient quality of life. Beyond its visible dermatological manifestations, psoriasis is increasingly recognized as a systemic condition linked to a range of comorbidities, including cardiovascular, metabolic, and psychiatric disorders. In recent years, the complexity of the disease has necessitated a shift toward precision medicine—an approach that tailors treatment based on individual clinical and biological profiles. In this evolving landscape, Artificial Intelligence (AI) has emerged as a promising tool for enhancing the diagnosis, monitoring, and management of psoriasis. Through machine learning, computer vision, and natural language processing, AI can analyze clinical images, patient-reported outcomes, and molecular data to support more accurate diagnostics, predict therapeutic responses, and guide personalized care. Despite the progress, challenges such as biased training datasets, lack of standardized imaging protocols, and limited clinical integration persist. Ethical and infrastructural barriers, including data privacy concerns and unequal access to technology, further complicate adoption. This chapter explores the current and future roles of AI in psoriasis care, discussing key innovations, limitations, and opportunities. A multidisciplinary, ethically grounded approach will be essential to realizing AI’s full potential in transforming dermatologic practice.