The Impact of Artificial Intelligence on Facial Aesthetic Surgery: A Systematic Review

Artificial intelligence (AI) has transformed medical practice, with early adopters using custom models in imaging-heavy fields. Millions of cosmetic surgeries prompt surgeons to seek better tools amid pressure for ideal outcomes. Past reviews have covered AI in facial cosmetic surgery for both reconstructive and aesthetic purposes. There remains a need to cover AI applications in a wider range of specialties while assessing clinical relevance, readiness, and, when available, comparison with standard care. This research examines AI's impact on facial cosmetic surgery by reviewing patient care stages, surgery types, AI architectures, and model sourcing. Following PRISMA 2020 guidelines and PROSPERO registration, the authors searched PubMed and Web of Science on August 25, 2025, for English studies on facial aesthetic surgery. They included studies using AI across all care stages, with at least 4 patients. Two reviewers independently screened, assessed, and extracted data. Of 1832 records, 29 met criteria. The authors used the Cochrane ROBINS-I and RoB 2 tools for risk of bias assessment. Most studies, mainly in Asia or the United States, focus on AI tool validation, development, and applicability, with few interventional studies. Most AI models use convolutional neural networks and are commercially available. In facial aesthetic surgery, AI aids treatment planning and outcome assessment, especially in facelifts, rhinoplasty, and blepharoplasty. The results highlight AI's potential and emphasize the need for standardized reporting, updated regulations, and education programs that promote collaboration where surgeons co-design AI models. Level of Evidence: 4 (Therapeutic).