Artificial intelligence (AI) was featured prominently at the 2nd International Glaucoma Symposium on 31 January 2026 in Mainz, Germany, where Priv.-Doz. Dr. med. Jan H. Terheyden, FEBO, spoke on how AI is already supporting ophthalmologists in everyday clinical care. The Eye Care Network caught up with Terheyden to learn more about which applications are delivering the greatest impact today, the hurdles to broader adoption, and how AI may evolve over the next decade.

Note: Transcript edited for clarity and length.

From your perspective, which AI applications are currently having the greatest real-world impact in ophthalmology, and why?

Priv.-Doz. Dr. med. Jan H. Terheyden, FEBO:The greatest impact is coming from AI applied to retinal imaging, particularly for diabetic retinopathy and other retinal diseases, where algorithms are approaching or matching expert performance and can be deployed at scale. From a research standpoint, these applications succeed because they leverage large, standardised imaging datasets and address clear clinical bottlenecks in screening and triage. In parallel, AI tools that support medical workflows, such as ambient clinical scribes and automated documentation tools, are beginning to have a meaningful impact by reducing administrative burden and allowing ophthalmologists to focus more on patient care.

What are the main challenges ophthalmologists face when integrating AI tools into everyday clinical workflows?

Terheyden: A key challenge is translating strong algorithmic performance into real clinical value—integrating AI seamlessly into workflows without adding cognitive or time burden. From my perspective, issues around generalisability, explainability, and trust are central, especially when models are trained on curated datasets that may not reflect real-world populations or imaging variability.

How do you see AI improving diagnostic accuracy or efficiency in areas such as retinal imaging, glaucoma detection, or cataract evaluation?

Terheyden: AI can improve efficiency by automating repetitive tasks like image quality control, segmentation, and risk stratification, allowing clinicians to focus on complex decision-making. I see particular promise in combining longitudinal data and multimodal inputs—such as imaging with clinical or functional data—to improve early detection and disease progression assessment, especially in glaucoma and retinal disease.

Looking ahead, what developments in AI do you believe will most significantly shape the future of ophthalmic care in the next 5 to 10 years?

Terheyden: I believe the biggest advances will come from clinically integrated, multimodal, and prospective AI systems—including decision support tools—rather than standalone diagnostic tools. From a research perspective, progress in foundation models, real-world validation, and regulatory-ready evaluation frameworks designed to function at the speed at which AI tools are being developed, will be critical in moving AI from proof-of-concept to routine, equitable ophthalmic care.

Priv.-Doz. Dr. med. Jan H. Terheyden, FEBO
E: [email protected]
Facharzt für Augenheilkunde | Ophthalmologist
Universitäts-Augenklinik Bonn
Department of Ophthalmology, University of Bonn
Bonn, Germany

Disclosures:
Consultant for Bayer
Research funding by Bayer, Roche, Novartis
Honoraria by Bayer, Novartis, Okko

Reference

1. Terheyden JH. How artificial intelligence supports ophthalmologists today. Presented at: 2nd International Glaucoma Symposium; 31 January 2026; Mainz, Germany.