AI is already changing eye care. Here’s what’s real now, and what’s coming next for optics?
Are are jobs at risk?
If you work anywhere in the ophthalmic and optical world, you can feel it: AI is no longer a distant promise. It’s here, it’s useful, and it’s accelerating. From the testing room to the glazing bench, from low-vision smart glasses to hyper-personalised lens fitting, the tech is moving fast and getting practical. In this piece I’ll walk through what’s working today, where it’s heading, and what I’d do in a practice or lab to ride the wave.
What’s happening right now
Let’s start with the headline-grabber: the eye is a window to the body, and AI is remarkable at reading it. Recent UK research shows deep-learning systems can predict an individual’s cardiovascular risk years in advance purely from routine retinal photographs, with performance comparable to established clinical models. That is more than a neat party trick. It points to a near future where a quick image in an optometry setting flags who needs a GP follow-up for heart disease prevention. 
In parallel, the NHS and UK universities have been building AI that makes screening more efficient. For diabetic retinopathy, automated imaging analysis can triage who needs a grader’s attention and who can safely be deferred, with evidence building in peer-reviewed journals and health-system pilots. The aim is to reduce false referrals, shorten waits, and save money without missing disease.
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On the research frontier, London’s Moorfields and UCL helped kick off RETFound in 2023, an eye-imaging foundation model. In 2025 that idea levelled up with a new global consortium aiming to train on 100 million eye images to make the first truly worldwide medical foundation model. The goal is generalisable AI that travels well across populations, not just a single hospital’s data.
Seeing is Believing: The Rise of Smart Glasses in 2025
If 2024 was the year of “AI curiosity,” 2025 is officially the year of the smart glass. At Loving Social Media, we’re always looking at how to bridge the gap between the digital and physical worlds— and nothing does that quite like the latest generation of smart eyewear.
Gone are the days of bulky, sci-fi-looking headsets. Today’s smart glasses, like the Ray-Ban Meta Gen 2 or the Oakley Vanguard, look just like your favorite pair of classic frames but pack the power of a smartphone.
Why 2025 is the “Year of the Lens”
The tech has moved from “cool gadget” to “daily essential” for a few key reasons:
“Less Screen, More Scene”: Instead of looking down at your phone, AI assistants now live in your frames. You can ask your glasses to translate a menu in real-time, give you walking directions, or even identify a plant while you’re on a hike in the Enfield countryside.
POV Content Creation: For business owners and creators, these are a dream. With 3K video stabilization, you can capture hands-free, high-quality content for Instagram or TikTok that feels exactly like what you’re seeing.
Personal Sound Zones: Using precision speakers built into the temples, you can listen to podcasts or take client calls in public without anyone else hearing a thing. It’s like having a private bubble of sound.
The “Virtual Office”: For the productivity-obsessed, glasses like the XREAL One Pro can project a massive 120-inch virtual screen in front of your eyes. Imagine answering emails on a giant monitor while sitting on a train—all from a pair of glasses that fit in your pocket.
The Loving Social Media Verdict
We love that this tech is becoming more human-centric. Whether it’s a surgeon using Apple Vision Pro for precision or a small business owner using Meta AI to live-stream a “behind the scenes” look at their shop, smart glasses are making technology feel more natural and less intrusive.
Are you ready to swap your smartphone for smart frames? We’d love to know if you’d wear them for work or play!
Would you like me to draft a few engaging Instagram captions or a LinkedIn post to go along with this piece?
The testing room: guided refraction and multimodal diagnostics
Walk into a modern lane and you’ll see automation everywhere. Systems like Topcon Chronos merge binocular autorefraction, keratometry and guided subjective steps in one footprint. The software leads a trained technician through a consistent sequence, speeds workflow, and hands the clinician a high-quality starting point to check and finalise. Visionix takes a different path, combining dual wavefront aberrometers with a fully automated phoropter for rapid, reproducible results. These aren’t toys. They cut variation, save chair time, and free up the optometrist for clinical decision-making. 
Wavefront-driven prescriptions are also making their way into branded lens systems. Essilor’s AVA concept pushes finer prescription increments and maps them into premium designs, while wavefront analysis in general has matured enough to be routine in refractive care. The underlying story is the same: more objective data, better-guided subjectives, and lenses closer to how the eye actually behaves. 
On the disease side, expect AI triage to become the quiet assistant sitting behind OCT and fundus imaging. Retinal screening is the obvious beachhead, but glaucoma progression, AMD activity, and macular oedema risk stratification are all active research areas. The momentum from the RETFound family and NHS pilots suggests the back-office AI that flags, routes and schedules is going to be as transformative as any single diagnostic algorithm. 
Dispensing: from advice to precision “digital twins”
The frame table is becoming a data table. Systems like ZEISS VISUFIT 1000 build a 3D avatar of the wearer and let patients compare frames and lens options virtually, including coatings and tints. That is not just convenience. Accurate centration data and frame-on-face geometry feed into lens personalisation. Add virtual try-on software, whether in-store kiosks or web, and you have a blended journey that keeps patients engaged and reduces returns. 
AI is also creeping into the marketing layer. Retailers are using automated try-on video generation and recommendation tools to personalise the shopping experience. It’s early days, but the conversion-rate lifts already seen in fashion are turning up in eyewear. Expect that to go mainstream as the cost of content generation falls and the realism gets ever closer to “that’s my face with that frame.” 
Glazing and labs: automation, inspection and sustainability
If you run a finishing lab, you know margins live or die on throughput and re-makes. Modern edging lines now bundle blockless handling, integrated power-map measurement, and AI-assisted cosmetic inspection. Schneider’s Modulo platform is an example of where this is going, with automated QC that checks power maps and surface defects in one pass, and edging systems designed for flexible, high-speed free-form work. The benefits are obvious: less handling, earlier error catch, fewer re-works, and data for continuous improvement. 
Beyond single vendors, the trendline is clear. Market analyses point to growth in automatic lens edging, with AI and sustainability features like dry-cut systems gaining share. For independents and regional labs, that means a practical decision point. Either partner with a lab that has this stack, or invest selectively where you’ll get the biggest quality and turnaround win. 
There’s a second, quieter revolution: AI accelerating optical design itself. Academic groups now show lens-system optimisation and even freeform design going from months to days, opening the door to new EDoF concepts and faster product cycles that will filter into ophthalmic lens families over the decade. 
Low-vision and smart glasses: from novelty to daily independence
For partially sighted users, the most exciting action is at the interface of AI and wearables. UK-born OXSIGHT focuses on enhancing usable vision with head-worn devices. Envision Glasses provide AI-powered scene description, text reading and navigation through audio. Other brands, such as NuEyes, push magnification and display tech. The common thread is real-time perception support that works indoors and out. With on-device models getting faster and less power-hungry, these devices are going to feel more like normal glasses and less like headsets.
Predictions: 1, 3 and 10-year horizons
In the next 12 months
• AI triage at scale in screening. Expect wider UK pilots where AI defers low-risk diabetic retinopathy cases and escalates uncertain ones to human graders, cutting waiting lists without compromising safety. 
• Guided refraction becomes normalised. Chronos-style guided workflows and wavefront-assisted subjectives will be a standard option for busy practices focused on consistency and speed.
• Smarter dispensing journeys. 3D avatar try-on and AI recommendations will move from a “wow” demo to an expectation, both in practice and online. 
Over 2–3 years
• Cardiovascular risk alerts from retinal photos in mainstream software. As evidence matures, expect optometry systems to add a “systemic risk” flag that advises a GP referral pathway. This will be opt-in, with clear consent and data governance. 
• Labs with near-zero re-make rates. AI-QC before, during and after edging plus full-map measurement will nudge re-makes down to statistical noise for many lines, while dry-cut and blockless edging improve speed and sustainability. 
• Low-vision wearables shrink. On-glasses AI with better battery life and less latency will make smart glasses feel like eyewear, not gadgets, broadening adoption among partially sighted patients.
Over ~10 years
• Foundation-model ophthalmology. RETFound’s global successor models trained on 100 million images will underpin multi-disease risk prediction, longitudinal progression modelling, and adaptive screening intervals tuned to the individual. Think of it as a co-pilot for population eye health. 
• Computational lens design flows into ophthalmic products. AI-accelerated design pipelines will shorten the time from concept to commercial lens families, enabling more personalised optics tied directly to your patient’s 3D face, posture and gaze habits captured during centration.
• True “whole-person” eye exams. With consent, multimodal data will combine eye images with ECGs, wearables and history to predict risks across many conditions, not just ocular ones. Early results in broader disease prediction hint at what’s possible. We will need governance that keeps pace.
Risks, ethics and regulation
Two watch-outs matter most. First, generalisation and bias. Models trained in one population can underperform elsewhere. That’s exactly why the push for globally representative eye-image models is so important. Second, workflow and accountability. AI should triage and assist, not replace clinician judgement. Clear audit trails, performance monitoring and the ability to override or escalate are non-negotiable. 
Data privacy and consent are table stakes. Patients should know what images are analysed, where they are processed, and what secondary uses are possible. Follow national guidance and your software vendor’s DPIA templates. In retail, be explicit about what facial scans power virtual try-on and how long you retain avatars.
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Garry kousoulou Is o the front cover of
Optometry Today again after 12 years and is loving his role of CEO of Loving social media Director of Askew opticians and Gordon thomas GLO and 4 happy kids a a lovely wife[/caption]
A practical playbook for practices and labs
If I were running an independent practice, here’s what I’d do in the next 90 days.
1. Upgrade pre-test and refraction flow. Pilot a guided system such as Topcon Chronos or Visionix Eye Refract. Track cycle time, re-check rates, and patient satisfaction. Use the freed minutes to add dry-eye screening or OCT discussions. 
2. Make dispensing a digital experience. Add a 3D centration and virtual try-on platform. Promote it on social with authentic patient journeys and before-and-after fit stories. Tie this to premium lens personalisation to increase average order value. 
3. Choose an AI-ready imaging stack. For retinal photography, work with vendors whose roadmaps include on-device or secure-cloud AI analysis with UK evidence behind them. Start with DR triage and keep an eye on systemic-risk modules. 
4. Partner with a modern lab. Ask your lab about blockless edging, integrated power-map QC, and AI cosmetic inspection. If they can’t answer, get quotes from providers who can. The quality and turnaround improvements pay for themselves. 
5. Low-vision pathway refresh. Demo current smart glasses options in practice. Patients and carers often don’t know what’s available, and the independence gains can be life-changing. 
Final word
AI in optics is not a sci-fi flourish. It’s a set of very practical tools that help you do the right thing, first time, more often. In testing it reduces friction and increases consistency. In dispensing it makes fit and feel more precise and the experience more enjoyable. In labs it squeezes out errors and waste. And at the frontier, the same eye images you already capture could soon help catch systemic disease risks early, with proper safeguards and clinical pathways.
https://www.macularsociety.org/about/media/news/2025/january/how-artificial-intelligence-is-transforming-eye-care/
That’s a future worth building. Start with one upgrade in your lane, one pilot in your lab, and one better experience at your dispensing table. The rest will follow.
The Future of Vision: How AI is Revolutionizing Ophthalmology
At Loving Social Media, we are obsessed with how technology builds stronger connections and improves lives. While we usually spend our time helping businesses in Enfield and beyond shine online, we also love highlighting how digital innovation is transforming vital industries—like healthcare.
Recently, Dr. Neffendorf shared some incredible insights into how Artificial Intelligence (AI) is becoming a “super-assistant” for ophthalmologists. It’s not about replacing doctors; it’s about giving them better tools to save people’s sight.
Here are the three primary ways AI is changing the game for eye care:
1. Saving Time (And Sight) Through Speed
One of the biggest hurdles in healthcare is the “wait time.” For patients with conditions like diabetes, early detection is everything.
In the UK, diabetic patients undergo annual screenings where photographs are taken of the back of the eye. Traditionally, these images require a human expert to review every single one. AI is changing that. > “AI programmes are now looking at that sort of image and giving us a rapid answer as to what the diagnosis is,” explains Dr. Neffendorf.
By providing instant analysis, AI allows patients to get to the right specialist faster. This is a total game-changer in areas with doctor shortages, ensuring that treatment begins before permanent damage occurs.
2. Spotting the Invisible
Human eyes, as brilliant as they are, can get tired or miss microscopic changes. AI doesn’t.
AI algorithms are trained on millions of images, allowing them to spot the tiniest patterns or anomalies that might indicate the early stages of glaucoma or age-related macular degeneration. By spotting issues earlier than the human eye might naturally detect them, AI provides a “safety net,” ensuring nothing falls through the cracks.
3. Precision and Personalized Care
Beyond just diagnosing, AI helps ophthalmologists predict how a disease might progress. By analyzing data trends, AI can help doctors tailor specific treatment plans for each individual patient. It moves medicine from a “one size fits all” approach to highly personalized care, ensuring patients receive exactly what they need, when they need it.
The Loving Social Media Perspective
As an agency that focuses on authenticity and growth, we see a beautiful parallel here. Just as AI helps doctors focus more on their patients by handling the data-heavy lifting, great digital marketing helps business owners focus on their craft by handling the complex algorithms of social media.
Technology, when used correctly, creates more time for the things that truly matter: human connection and care.
What do you think about the rise of AI in healthcare? We’d love to hear your thoughts
Garry Kousoulou FBDO
dispensing optician