Ophthalmologists, Except Pediatric

AI is also getting good at reading eye scans. Deep-learning programs trained on retina photos or OCT scans can spot diseases (like diabetic retinopathy or glaucoma) at rates similar to human experts ^[3]. Some FDA-cleared AI tools now screen for diabetic eye disease on their own, flagging problems early ^[3].

In practice, these tools help doctors catch disease sooner, but a human doctor still reviews the results.

Major eye surgeries and teamwork are still led by doctors. AI in the operating room is mostly supportive: for instance, AI can suggest intraocular lens power before cataract surgery and can track the surgery on video ^[4]. Augmented-reality glasses or cameras let distant experts watch a surgery live and even point things out in real time ^[5].

But none of this means the computer replaces the surgeon – the doctor’s skills, decisions, and patient conversations remain essential.

Cost and staffing also affect adoption. High-tech AI gear can be expensive, and medical centers weigh that against benefits. On the other hand, ophthalmology has staff shortages (e.g., around 19,000 ophthalmologists versus 60,000 technicians nationwide ^[3]), so automation can help care for more patients.

Many eye doctors are optimistic: they like that AI scribes let them spend more face time with patients rather than typing ^[1]. Studies also show that clinics using AI tools see better patient follow-up and efficiency ^[3]. In the end, specialists say AI will augment (not replace) ophthalmologists – saving time on tests and paperwork so doctors can focus on the human side of care ^{[1] [3]}.