Emerging Artificial Intelligence: A New Digital Age Across The Aesthetic Landscape

Patients increasingly form expectations about plastic surgery from social media and other online sources, and artificial intelligence (AI) now functions both as a tool for analyzing that content and as a source of the content itself. This review maps original empirical studies that applied an AI or computational method beyond conventional statistical analysis to social media, online reviews, public digital images, surveys, or crowdsourced data in plastic surgery while reporting an outcome related to the perceptions, questions, experiences, or information exposure of patients or the public. Twenty-six studies published between 2019 and 2026 met inclusion criteria, 19 (73%) of them since 2024. Facial aesthetic surgery was the most represented domain (n = 9; 35%). RealSelf was the most common primary data source (n = 8; 31%), 18 studies (69%) analyzed a single platform, and 18 (69%) analyzed text alone. Sentiment or emotion analysis was the most common computational method (n = 13; 50%), and 16 studies (62%) applied pretrained models or lexicons as released, without training on study data. A human comparator was reported in 10 studies (38%) and external validation in 1 (4%). No study linked patient-generated digital data to a validated patient-reported outcome measure or evaluated these data for surgical education. Work at this intersection is expanding rapidly but remains descriptive, single-platform, and largely unvalidated.