Artificial Intelligence in Ophthalmic Surgery: Applications Across the Perioperative Pathway

Abstract

This narrative review examines how artificial intelligence is being applied across the ophthalmic surgical pathway, spanning preoperative planning, intraoperative guidance and training, and postoperative prediction, and it identifies the priorities required for responsible clinical adoption. Recent studies show that preoperative biometric planning in cataract surgery and surgical video analysis are currently the most mature applications, while image-based risk stratification in corneal and retinal surgery and prediction of postoperative visual or refractive outcomes are advancing steadily. By contrast, real-time intraoperative guidance and autonomous robotic support remain earlier in development and are still limited by data heterogeneity, workflow-integration challenges, and sparse prospective validation. Artificial intelligence is unlikely to replace ophthalmic surgeons in the near term, but it can augment clinical judgment, standardize workflows, and improve efficiency and safety across the perioperative pathway. Wider clinical adoption will depend on stronger external validation, better interpretability, integration into real-world surgical workflows, and prospective studies demonstrating meaningful patient benefit.