15/04/2026
It’s interesting to watch how quickly AI in healthcare is changing shape.
Not that long ago, tools like ChatGPT were something people experimented with on the side. Now we’re seeing versions built specifically for healthcare, like ChatGPT Health and Claude for Healthcare, designed to fit into clinical workflows rather than sit outside them.
You can already feel this in practice.
Patients show up having run their symptoms through AI. Sometimes it helps. Sometimes it creates confusion. Either way, it changes the starting point of the conversation.
At the same time, there’s real potential on the clinician side. Documentation, summaries, admin tasks. The kind of work that quietly takes time away from patients is where these tools may actually make a difference.
In eye care, it raises a familiar question.
Where does AI genuinely help, and where do we need to be careful?
Because no matter how these tools evolve, they don’t replace what happens when you’re looking at a retinal image, weighing subtle findings, and deciding what needs attention now and what can wait.
At RetinaLyze, we see this as part of a broader shift. In diagnostics, but also in how information moves between patients and clinicians. And we're just getting started!