JMIR Publications

ABSTRACT

Artificial intelligence as a medical device (AIaMD) is now progressively entering routine ophthalmic care, yet its impact is still mostly evaluated in terms of diagnostic performance rather than how it reshapes patient care pathways. This Viewpoint argues that careful pathway design is crucial to implementing AI in ophthalmology so that it translates into real, practical benefits for patients and services. We propose a framework that classifies AI- and telemedicine-enabled eye care pathways by the initial point of contact and the role of AI: from direct human assessment, to grader- or telemedicine-based use, to AI-first contact and fully autonomous AI gatekeeping. We apply this framework to two contrasting health systems, the United Kingdom and Germany, focusing on common retinal diseases and cardiovascular risk assessment from retinal images. In the UK, AI is being introduced mainly as a modular upgrade to standardised programmes layered onto a gatekeeper model centred on community optometrists and general practitioners. In Germany, direct access to office-based ophthalmologists, opportunistic screening and commercial retail offerings are producing more fragmented, clinician- and market-driven AI adoption. We conclude that the same AI tools can lead to very different patient journeys depending on how they are embedded into care pathways. AI has substantial potential when applied within explicitly designed pathways that include clear escalation rules, structured information transfer and appropriate task shifting from ophthalmologists to trained staff, while preserving safety, equity and professional accountability.