Artificial Intelligence is revolutionizing optometry and ophthalmology across every aspect of care, from diagnostics to workflow and treatment. However, it is essential to cut through the hype and focus on what A.I. is delivering for eye care today and what it could bring in the near future.
Ultimately, the true value of A.I. lies in addressing these real-world challenges faced by clinicians:
- The imbalance between supply and demand, with too many patients and too few doctors.
- Rising costs combined with shrinking reimbursements.
- The explosion of data and the increasing burden of payer requirements
Where Are We on the A.I. Journey in Eye Care?
In my survey of ophthalmologists nationwide, fewer than 10% currently use A.I. in practice. However, nearly all anticipate incorporating A.I. into their work within the next three to five years. Below, I’ve categorized the current and upcoming A.I. advancements into three key areas — diagnostics, treatments, and efficiency — that are helping solve the problems outlined above.
A.I. in Diagnostics
Screening for eye diseases such as diabetic retinopathy is already being enhanced by autonomous A.I. technologies. Companies such as Digital Diagnostics, AEYE Health, and Eyenuk are leading the way in algorithm development, while Topcon, Canon, and Optomed provide the approved eye cameras.
A.I. is also poised to handle various imaging technologies, including fundus, OCT, visual fields, ultrasound, and ERG. It will offer clinical decision support for multiple conditions, including AMD, glaucoma, and cataract. There is a growing need for systems that integrate clinical workflows and assist multimodal imaging decision-making, such as EyeIntelligence from B+L or the glaucoma prediction tools from Eyelomics.
Another emerging field is Oculomics, which uses eye imaging for non-invasive screening of systemic diseases such as neurological and cardiovascular conditions. These tools even hold the potential to predict traditionally unrelated conditions such as Alzheimer’s, heart disease, and kidney disease. Companies such as Toku, Mediwhale, Retispec, and Verily are pioneering these groundbreaking technologies.
A.I. in Treatment
A.I. is transforming treatment by analyzing patient data to predict disease progression and tailor therapies, particularly in glaucoma management. Adjacent technologies, such as virtual reality and at-home OCTs, are being used to monitor and predict responses to treatment. Radius and Olleyes are advancing VR systems, while Notal Vision is leading in at-home OCT devices.
In surgical settings, A.I. is enhancing precision and outcomes by assisting in planning and executing procedures. Given the global demographic shifts, cataract surgery is becoming a prime candidate for both A.I.-assisted and eventually autonomous surgery. Companies such as Horizon Surgical Systems and ForSight are at the forefront of developing this robotic future.
A.I. in Efficiency
A.I. is significantly improving efficiency through automation and teleophthalmology. By automating routine tasks —such as scheduling, record management, and insurance processing — A.I. allows clinicians to focus more on patient care. Remote diagnosis and monitoring through teleophthalmology are also becoming crucial for providing care in underserved areas.
Challenges and Future Directions
Despite its potential, challenges remain in implementing A.I. Acceptance from patients, physicians, and payers, regulatory clarity to encourage safe development, and sustainable business models are essential factors. All stakeholders must collaborate to overcome these challenges and ensure A.I.’s successful integration into clinical care.