The future of smart glasses will not begin with virtual worlds. It will begin with making everyday life easier.

A real world example: Contextual Human Assistance

I think back to when we made the ORA-1 and ORA-2 smart glasses at Optinvent in the early days. We had no idea what they would be used for. We built them and put them out there to see what app developers would come up with. Sure, they weren’t as advanced as a HoloLens or a Magic Leap One, but they had pretty decent capability (display, android, GPS, wifi, Bluetooth, camera, microphone, audio, etc.).

Out of the many applications developers made, one theme repeatedly emerged: remote maintenance, remote assistance and training. A technician in the field would wear the glasses while an expert at a desk could see what the technician was seeing through the camera and would guide them through a repair or procedure. There were no elaborate AR overlays.

The value came from something much simpler: Giving the right person the right information at the right moment.

Now replace the remote assistant with AI and the implication becomes clear: Smart glasses become an always-available assistant that can see, understand, and guide the user in context.

As a veteran in the industry, I’ve seen this category evolve from personal screens to video glasses, to smart glasses, to AR glasses.

Now I think we need a rebrand: Wearable AI.

For more than a decade, the promise of smart glasses has been defined by augmented reality. The vision was compelling: digital information seamlessly overlaid onto the physical world. Immersive experiences with 3D virtual objects integrated and mapped to your surroundings.

The technology was revolutionary and ambitious. But other than a few niche applications, the consumer breakthrough never really happened. Smart glasses were a problem looking for a solution that remained constrained by a fundamental question:

What would compel people to actually start using them every day despite the constraints?

The answer may not be AR.

The emergence of powerful AI assistants has changed the equation. Instead of just adding digital content to the real world, smart glasses can now understand the world around you and help you interact with it.

The “killer app” for smart glasses may not be seeing more. It may be understanding more.

From Augmented Reality to Augmented Intelligence

The original vision for AR focused on augmenting the real world with additional digital information (hence augmented reality): blending the real and digital worlds. The next computing paradigm, sometimes referred to as “spatial computing”. Basically, a computer with a 3D display that you wear on your face.

Humans constantly process enormous amounts of visual information:

• Recognizing faces
• Reading signs
• Remembering where objects were placed
• Understanding conversations
• Navigating unfamiliar environments

Much like the human brain, modern multimodal AI systems can combine vision, language, reasoning and instant search to interpret the environment around us. A pair of glasses with cameras, microphones and AI can become a personal assistant that sees what you see. Add a display (since vision is our primary sense) and it becomes the visual interface through which AI delivers contextual assistance.

The User Interface Problem With Traditional AR

Traditional AR has always faced a fundamental challenge: how do you interact with digital information seamlessly while still engaging with the real world?

Early AR experiences often required users to learn new interaction methods: gestures, controllers, menus, and other specialized interfaces. The user had to actively manage the technology: wear a device, open an application, choose an experience, and interact with digital overlays. AI changes this paradigm.

Instead of forcing users to adapt to the computer, the computer can adapt to the user.

Natural conversation, vision, and context become the interface. You simply ask, point, or interact normally, and the AI understands what you need.

Most successful consumer technologies do the opposite. They reduce effort and make the technology as seamless as possible. In other words, they reduce friction. The smartphone succeeded because it replaced dozens of separate devices with one tool in your pocket that you can interact with intuitively through a touchscreen. The smartwatch succeeded because it delivered information instantly without requiring you to reach for your phone.

AI glasses have the opportunity to be the next paradigm

A device that is present when needed, but invisible when not: Always on and hands free.

The reason smartphones became indispensable was not one killer feature. It was hundreds of small useful things throughout the day (GPS, messaging, taking pictures, listening to music, getting reminders, etc.).

AI glasses can take this even further. Now imagine the following:

1. You meet someone at a conference and your glasses remind you where you met before. The context surfaces while you’re still shaking hands.
2. You walk through a foreign city and your glasses translate signs automatically. No need to walk around like a tourist with your phone in your hand pointing the camera.
3. You are cooking and your glasses guide you through a recipe without touching a screen. Your hands stay on the food, not on a phone.
4. You attend a meeting and your glasses summarize key points afterward. It happens in the background, without you ever breaking eye contact.
5. You see an object and simply ask what it is. No need to take out your phone to do a google search.

These are not traditional immersive AR scenarios. The value is not the display’s large field of view or immersive 3D binocular vision with objects floating in front of you.

The real value is: reduced cognitive load.

This shift in software priorities also changes what matters in hardware. Traditional AR places enormous emphasis on:

• Wide fields of view
• Immersive 3D graphics
• High resolution
• 3D SLAM (Simultaneous Localization and Mapping)
• Sensor arrays
• Multiple cameras

Once you integrate all this technology into a frame, what you often end up with is not ordinary looking glasses, but something more akin to goggles. AI glasses prioritize different requirements. The perfect AI glasses will not look like a headset. They will look like normal eyewear because the feature set is completely different. The technology is already there.

The Importance of Social Acceptability

One of the biggest lessons from previous AR attempts is that technology adoption is not only about specs and capability. It is about behavior. People already know what glasses should look like. It’s been codified through hundreds of years (the first eyeglasses appeared in Europe in the late 13th century, eventually evolving into today’s prescription eyewear ecosystem). Fashion trends change but the idea of what “normal” eyeglasses look like is ingrained in our psyche.

The challenge is not teaching people how to wear a new computer on their face. The challenge is making that computer feel natural. AI helps because it changes the role of the device. Instead of saying: “Look at this new digital world overlaid on the real one” the glasses quietly say: “I can help you with the world you are already in.”

But social acceptability cuts both ways. A normal-looking pair of glasses with a camera and an active microphone creates friction in certain situations. Bystanders can’t tell whether they’re being recorded, and “there’s a small LED for that” hasn’t been a satisfying answer so far. The backlash to Google Glass is a prime example (e.g. Glassholes). AI raises the stakes further: an assistant that’s always listening for context needs to actually be doing that, at least in some passive way, which is a real product and policy problem.

The term “Pervert Glasses” is gaining traction on the internet. This isn’t a flaw in AI glasses as a general category, it’s a consequence of specific choices around consent, data handling, and oversight, all of which are solvable. The industry will need clear guidelines such as on-device processing where possible, and transparent norms about what’s captured, sent off device and stored. There’s no magic formula here and this is one of the main risks for this category.

As an industry, we need to collectively apply the hard-earned lessons from previous failures.

The Race Is No Longer About Building a Better Display

For years, the AR industry competed to create the most impressive optical experience: Immersive 3D experiences, light field optics, crisp 8K resolution. Fitting that into a lightweight eyeglass frame remains the unsolved problem.

Now the market is moving in another direction. The first mass-market smart glasses will not be the ones with the most immersive AR. They will be the ones that best combine: AI, comfortable hardware, natural interaction, everyday usefulness and affordability (yes, that’s the next big challenge for the industry).

Even with the shift from AR to AI glasses, the display (more specifically, the waveguide) remains the single most expensive component. I’ve written a separate article on this.

That’s why the Meta Rayban Display costs $800. Premium sunglasses without any electronics already sell in the $200-$400 range. That’s the target to truly go mainstream rather than continue to be an early adopter gadget.

The Next Computing Platform Will Be Contextual

Every major computing platform changed the relationship between humans and technology. The mainframe brought computing to the workplace.

The PC brought computing to the desk. The smartphone brought computing to the pocket. Smart glasses bring computing to your face (the brain implant is probably the next logical step, but hopefully not for a while).

The next computing paradigm will not be created by adding more graphics to reality. It will be created by making technology understand reality and help us act on it. AI is the key enabler that allows smart glasses to actually be a compelling solution to a real world problem. It transforms smart glasses from a device that shows information into a device that understands the world around us. That is why AI, not AR, is the real “killer app” for mainstream smart glass adoption.

This does not mean AR is dead. In fact, AR may become the most powerful interface for the next generation of smart glasses with AI assistance. The difference is that AI creates the reason people will want to wear the glasses regularly in the first place.

In conclusion: The future of smart glasses will not start with seeing immersive 3D overlays. It will start with helping us be better, smarter and faster in our everyday lives.

AR is at an inflection point. Smart glasses are starting to go mainstream: no longer a niche curiosity or a low volume vertical market solution looking for a problem. The killer app is here: AI. The shift from “immersive AR” to “wearable AI” is a wake-up call to the industry.

Consumer price points, scalability, and yield are now center stage. The optical engineering flex contest on immersive ultra-wide FOV, light field modulation, or 8K display resolution has given way to the harsh reality of cost economics.

Case in point: the Meta Ray-Ban Display has a modest 20° FOV in one eye (monocular). No light field, no 8K resolution, yet is still priced at $800. The non-display version, Ray-Ban Stories, sells for nearly half, and is consequently a runaway hit, with 7 million units sold in 2025. This disparity is not about marketing or price positioning, it reflects the cost reality of the optics, and in particular, one component most people have never heard of: the waveguide.

The waveguide is the major cost and supply bottleneck

$800: Selling price of Meta Rayban display AR glasses.  Too expensive for the mass market.

What a Waveguide Actually Does, and Why It Is So Expensive

A waveguide is the transparent lens-like element in AR glasses that takes an image from a tiny projector and redirects it into your eye while staying virtually invisible from the outside. Simple enough to design, but extremely complex to manufacture.

There are two dominant waveguide technologies in use today: diffractive and geometric (also called reflective)

Diffractive waveguides are the most common and used by Snap, Even Realities, TCL and a slew of others and are rumored to be used in the next gen. Meta Rayban Display. There are quite a few suppliers (including Applied Materials and several Asian companies). The architecture is based on nano-scale gratings that are either etched or nano-imprinted by lithography onto special high-refractive-index glass wafers.

Glass Geometric or reflective waveguides (used in the current Meta Ray-Ban Display and manufactured by SCHOTT) are built from a sandwich of approximately 30 individual glass pieces: cut from a high-index glass wafer, coated, glued, and polished to zero-defect tolerances.

Both technologies share the same foundation: specialty glass wafers processed in cleanrooms at nanometre levels of precision.

The waveguide currently represents roughly 30% of the factory cost of AI glasses.

The pain point: 30% of AR glasses factory cost comes from the glass waveguide

The Glass Wafer Problem: A Hard Cost Floor

The substrate for AR waveguides is not ordinary glass. SCHOTT’s RealView® wafers, the industry benchmark, require refractive indices of 1.7 to 1.9, tolerances an order of magnitude tighter than standard optical glass, and cleanroom processing throughout. Due to these constraints, industry estimates put them in the €1,500–€3,000+ range per 300mm wafer, yielding approximately 20-25 waveguide dies per wafer

The arithmetic is unforgiving:

• Glass wafer (300mm, high-RI): €1,500
• Dies per wafer: ~20–25
• Substrate cost per waveguide: €60–€75
• Total waveguide cost at volume (after processing): €100–€200+
• Consumer BOM target: sub-€20

The substrate alone, before any value-added processing, already exceeds the entire target BOM cost of the finished waveguide.

This is a structural problem. It cannot be solved by more volume or investment.

Silicon carbide wafers which have also been tried in the Meta Orion prototype are an order of magnitude more expensive since optical grade silicon carbide is an extremely rare commodity. In general, optical grade glass wafers with high purity are less readily available and much more expensive than the common silicon wafers used to make semiconductor integrated circuits.

Many people make the comparison to the semiconductor process. The argument is that waveguides are made in much the same way using wavers and semiconductor processes. This is a major fallacy. It’s true that the semiconductor industry has come a long way in reducing costs. Moore’s law, Xray lithography and incremental process improvements have allowed a single wafer to yield hundreds or even thousands of IC chips. However, the same economics don’t apply to waveguides. There’s no Moore’s law in optics and a large wafer yields only a few dozen waveguide components.

Semiconductor math doesn’t apply to waveguide manufacturing.

There’s no Moore’s law in optics and a large wafer yields only a few dozen waveguide components.

Three Showstoppers for Consumer AR

Strip away the technical debate on specs like MTF, color uniformity, eye-box, pupil swim, eye-glow and all the things optical engineers sweat over and three main issues block every glass-based waveguide from reaching consumer scale.

• Cost. The wafer substrate floor alone blocks glass waveguides from reaching sub-€20 target prices. Assembly and processing costs on top make it worse.
• Scalability. Cleanroom lithography and precision glass processing are optimized for low volumes and high margins. Consumer electronics demand millions of units per year at defect rates measured in parts per million. These two production philosophies are fundamentally incompatible.
• Ophthalmic incompatibility. Glass and optical polymer have thermal expansion coefficients that differ by a factor of 3–10×. Bond them directly and you get delamination, stress birefringence, and image degradation.

The real KPI’s for consumer adoption of AR glasses

Focus on the Ophthalmic Dimension

This is the design problem most waveguide makers still treat as an afterthought. The ophthalmic industry has spent 40+ years building a polymer-first supply chain: CR-39, polycarbonate, Trivex, injection-molded polymer lenses at commodity prices, with 15,000+ labs worldwide for prescription customization. It is the distribution engine that consumer AR must eventually plug into.

Glass waveguides cannot do this. Their CTE (coefficient of thermal expansion), their material family, and their manufacturing processes are fundamentally incompatible with the polymer-native ophthalmic supply chain.

The problem is further compounded because most glass waveguides require a “push-pull” lens pair: one converging, one diverging, used to set the virtual image at a comfortable fixed focal distance rather than at optical infinity. That is two additional optical elements on top of the waveguide, adding weight and thickness. When prescription correction is also needed, the two lenses must be precisely matched to the individual’s prescription, adding further complexity and making it nearly impossible to plug into the existing ophthalmic supply chain.

With 2.7 billion people worldwide requiring vision correction, any waveguide that cannot integrate natively with prescription lenses will remain a niche product.

A Different Approach: Injection Molded Polymer Reflective Waveguides

The question is whether there is an architecture that sidesteps all three constraints simultaneously: not one that incrementally improves on glass, but one that starts from a different manufacturing and material paradigm entirely.

A “monolithic” molded polymer reflective waveguide replaces the glass substrate and multi-piece assembly with two injection-molded polymer parts.

There are several companies claiming “polymer” waveguides, but the devil is in the details.  The distinction is weather they are molded in one piece (monolithic) or if they rely on a polymer substrate on which a structure is applied.

Monolithic waveguides don’t rely on a substrate in polymer (essentially an expensive polymer based wafer) that is then treated with a diffractive nano-imprint layer, similar to how glass waveguides are made and therefore suffer the same yield and cost issues.

Monolithic means the whole waveguide including the reflective arrays are injection molded in one step. Pellets go into the machine and a two piece waveguide comes out, ready to be coated and bonded together.

This is compelling, compared to the yield limiting ~30-piece glass assembly where even a single defect at any stage of fabrication can condemn the entire unit. Furthermore, the precision cutting sequences and complex assembly processes that make glass reflective technology extremely difficult to scale all but disappear with injection molding.

30 glass pieces and highly complex process vs. 2 molded parts

The polymer used in this architecture is in the same material family as ophthalmic lenses: native CTE compatibility with prescription lenses, same coating and finishing technologies, and a manufacturing process (injection molding) that is geared for millions of units per year.

Furthermore, this architecture doesn’t require what’s called a “push-pull” lens (two optical elements in front and behind the waveguide) to focus the image at a finite distance which is the case today with the Meta Rayban Display.

Polymer injection molding produces parts for cents, not dollars. The waveguide cost per pair of glasses drops from ~€200 to ~€50 with a molded polymer approach, translating to an end-user price reduction from ~€800 to ~€450 for complete AI glasses.

And contrary to the glass approach, the volume equation does apply here: the process is inherently scalable, with costs that can reach as low as €10 at very high volume.

Nearly 2X cheaper AI glasses means more mainstream adoption

Where the Industry Stands

This approach is not purely theoretical. ORA-Lens®, developed by Optinvent (Rennes, France), is the only known molded polymer 2D reflective waveguide. It has proven 50° FOV, efficiency up to 5,000 Nits/lm, ~4g weight, and image focus at 1.5m without a push-pull lens, all from two molded polymer parts. The technology is protected by 40 international patents and a proprietary manufacturing process.

The broader implication should be a wake-up call for the entire segment :

the AR industry will not reach consumer scale by optimizing glass waveguide processes or waiting for volumes to fix the cost problem.

It has to start with an inherently scalable solution: a manufacturing paradigm that is intrinsically compatible with high-volume, low-cost production and fully compatible with the 2.7 billion people who need their smart glasses to also correct their vision.

Kayvan Mirza is Co-founder and President of Optinvent SAS and a member of the EuroXR Advisory Committee. www.optinvent.com

References

Optics.org: “SCHOTT ready to ramp higher-index glass for AR” — 25 waveguide dies per 300mm RealView® 1.9 wafer. optics.org
SCHOTT RealView® : “The larger the wafer’s diameter, the more eye pieces can be applied per wafer, reducing cost in the waveguide production process.” schott.com
Optinvent internal data: ORA-Lens® BOM and manufacturing cost
Electro Optics: “Waveguides seek to welcome consumer AR” electrooptics.com