Ophthalmology ManagementBringing AI Into Cataract Care

🎓 Expert Commentary / Peer Perspective

An AAO 2026 panel described real-world applications of conversational AI across the cataract pathway, from collecting preoperative histories and delivering individualized education to evaluating postoperative symptoms. One academic center is studying AI-assisted week-one follow-up against in-clinic assessment, while a private-practice surgeon described using AI before consultations. These experiences suggest potential workflow applications but largely reflect expert perspective and ongoing research rather than validated evidence of improved clinical outcomes.

Clinical Considerations

• Conversational AI can collect structured preoperative histories and provide patient education before the ophthalmologist enters the examination room.
• An ongoing trial is comparing AI-based week-one postoperative conversations with in-clinic evaluations after cataract surgery.
• Investigators reported encouraging agreement to date, but the article provides no sample size, performance estimates, or final trial results.
• Panelists emphasized maintaining physician oversight, particularly as AI assumes patient-facing roles involving symptom assessment and clinical information.
• Potential workflow benefits include reducing repetitive information gathering and identifying patients who may require additional postoperative evaluation.

Practice Applications

• Consider AI-supported intake and education as clinician-assistance workflows rather than replacements for ophthalmic assessment.
• Evaluate validation evidence before allowing conversational systems to influence postoperative triage or follow-up pathways.
• Recognize patient-facing AI requires attention to safety, reliability, privacy, and appropriate physician oversight.
• Monitor ongoing prospective evidence comparing AI assessments with conventional postoperative evaluation.