AI Resilience Report forOrthoptists

If you're considering becoming an orthoptist, the good news is that today's AI tools mostly support these specialists rather than replace them. The College of Optometrists in the UK recently summed this up clearly in its interim position statement on AI in eye care ^[1], which says the optical sector welcomes AI but is "equally clear that AI is here to support our clinicians, not to replace them," with the right safeguards to free up time and reduce inequalities. Research is moving fastest in the diagnostic-test parts of the job.

For example, a 2026 study in Diagnostics showed an AI-assisted framework using eye-tracking and machine learning ^[2] that reached 97.56% accuracy interpreting the Alternate Cover Test for strabismus, and a Scientific Reports paper validated a smartphone-based pipeline that screens horizontal strabismus ^[3] from selfie photos with around 95% accuracy. AI is also writing first-draft notes, analyzing slit-lamp and OCT images, and handling administrative paperwork, according to Healio's 2026 reporting on AI in eye care ^[4]. But interpreting subtle results, counseling families, prescribing exercises, and deciding when to refer to a surgeon still rely on a trained human — exactly the higher-value tasks orthoptists do.

Adoption is likely to be steady but careful. On the "speed up" side, the U.S. faces a real eye-care workforce gap: an Ophthalmology Science paper argues that with a constrained ophthalmology workforce, reallocating tasks to technicians and AI tools ^[5]00051-5/fulltext) gives the best economic return, which favors hiring orthoptists who can work alongside AI. On the "slow down" side, eye-care AI products are regulated medical devices, and an Ophthalmology Management legal review warns practices that AI tools must navigate FDA rules, fraud-and-abuse laws, and liability ^[6] before they can be safely deployed.

Patients also expect a human in the room when a child is being fitted for patches or fusion exercises. So if you love this field, AI is most likely to become your assistant — handling reports, image analysis, and repetitive measurements — while your empathy, hands-on testing skills, and clinical judgment remain the parts of the job that machines can't easily copy.