As innovation moves beyond devices, AI is reshaping how cataract care is planned, delivered, and managed

At ASCRS 2026, artificial intelligence (AI) emerged not as a distant concept, but as a central theme shaping discussions across cataract and refractive care. This was underscored by the keynote presentation by Dr Kerry Soloman, Artificial Intelligence in Ophthalmology: Where We Are, Where We Should Go, and How to Get There Responsibly, which set the tone for a broader conversation around both the opportunities and responsibilities associated with AI adoption.

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Beyond algorithms: AI, robotics, and simulation signal a broader transformation

While individual applications of artificial intelligence are already influencing cataract care, a symposium on Artificial Intelligence, Robotics, and Surgical Simulation highlighted a broader shift – one that extends beyond software tools to encompass how surgery is performed, taught, and scaled globally.

Presentations emphasized that AI is evolving alongside advances in robotics, imaging, and simulation, forming a more connected technological ecosystem. Updates in macular imaging demonstrated continued gains in diagnostic precision, while deep learning approaches to effective lens position (ELP) prediction point to further improvements in refractive accuracy.

At the same time, early experience with next-generation ophthalmic robotics, particularly from European centers, suggests steady progress toward more automated and precision-guided systems. While still emerging, these platforms are increasingly seen as a natural extension of technologies such as femtosecond lasers.

Simulation and virtual reality training also featured prominently, reflecting a shift away from traditional apprenticeship models. High-fidelity simulators are enabling skill development in controlled environments and supporting the scale-up of surgical training globally. As highlighted during the session, the “see one, do one, teach one” paradigm is being replaced by structured, competency-based training.

Finally, discussions addressed the responsible integration of AI, including its role in scientific publishing and the need to maintain ethical standards while improving efficiency. Together, these perspectives highlight a broader transformation across surgical practice, training, and knowledge delivery.

AI in surgical planning: improving accuracy in complex eyes

Accurate intraocular lens (IOL) power calculation remains one of the most critical and challenging steps in cataract surgery, particularly in eyes with prior refractive procedures. AI-based models are now being developed to address these complexities by integrating multiple data inputs and learning from large datasets, offering a more adaptive approach to prediction.

Abstract highlight: AI-driven IOL formulas deliver comparable accuracy in post-refractive eyes
AI-driven formulas such as PEARL-DGS and Kane demonstrated refractive accuracy comparable to Barrett True-K, with over 90% of eyes within ±1.00 D of target and no significant differences in mean absolute error between models. These findings suggest that AI-based approaches may serve as reliable alternatives in complex cases. Read the full abstract here

AI in postoperative care: scaling follow-up and patient communication

Postoperative follow-up represents a significant clinical burden, particularly in high-volume cataract settings. AI-driven tools, including large language models, are being explored as a means to scale patient communication while maintaining clinical oversight, with additional potential applications in documentation and workflow efficiency.

AI-powered assistant shows promise in automating postoperative cataract follow-up
A voice-based AI assistant achieved 92.2% agreement with clinicians in assessing symptom significance, with high patient acceptability and the ability to address the majority of patient queries. While promising, the findings indicate that such systems are best suited to supporting, rather than replacing, clinician-led care. Read the full abstract here

From automation to augmentation: defining the current role of AI

Across applications, a consistent theme emerges: AI is not replacing clinicians, but enhancing their ability to deliver efficient, consistent, and scalable care across clinical, operational, and patient-facing domains. The current generation of tools is best understood as augmenting clinical workflows, with future developments likely to build on this foundation.