Rosacea is a chronic inflammatory dermatological condition marked by subjective symptoms—such as facial flushing and burning—and objective manifestations like persistent erythema, papules, and pustules that often resemble acne. Recent advancements in deep learning, particularly in convolutional neural networks (CNNs), have revolutionized medical image analysis, including dermatological applications in rosacea. Models such as Inception-ResNet-v2, Ros-Net, FACES, MobileNet, VGG-16, InceptionV3, and Swin Transformers have demonstrated high performance in differentiating rosacea from its clinical mimickers or/and distinguishing among its various subtypes. Although studies specifically addressing AI-based assessment of rosacea severity remain limited, the integration of CNNs with high-resolution imaging systems like VISIA represents a promising future direction. Moreover, AI-powered tools, such as chatbots, could assist in personalized skincare and dietary guidance to help patients manage and mitigate disease flares post diagnosis.