Artificial intelligence (AI) is increasingly used in facial aesthetic surgery. This specialty is well-positioned to benefit from its ability to analyze large visual data sets and provide more objective outcome measurements. The authors’ review will focus on current AI applications across various aspects of facial aesthetic procedures. Primarily, the authors will focus on their impact on patient-centered care. A comprehensive review of peer-reviewed literature from 2021 to 2026 identified 44 studies on AI in patient education, preoperative planning, intraoperative guidance, and postoperative evaluation. AI proves most effective in structured, data-driven tasks. In patient education, these consist of improved access to information and standardized counseling, though issues such as readability, hallucinations, and model variability were observed. In preoperative planning, AI was beneficial for image analysis, classification, and postoperative simulation. However, it cannot yet support personalized decision-making. Intraoperative use of AI is limited but shows successful applications in augmented reality and ultrasound-assisted procedures. Postoperatively, AI shows promise in quantifying outcomes through facial measurements, age estimation, and analysis of emotional expression, providing more standardized evaluations than traditional subjective methods. However, many challenges remain. AI models are influenced by biased training data, raising concerns about fairness, generalizability, and reinforcement of narrow cultural aesthetic standards. Additional issues include the lack of standardized data sets, inconsistent methodologies, and safety concerns. While AI has the capacity to improve facial aesthetic care throughout the surgical process, successful integration will require rigorous validation, bias reduction, and careful alignment with the subjective, patient-centered goals of aesthetic surgery.
Smith et al. (2026) studied this question.