What’s Next for Smart Glasses?

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By Eric Abbruzzese | 2Q 2024 | IN-7369

After many ups and downs over the last decade, questions surround the role of smart glasses in the broader technology market over the next few years. After some advancement in Virtual Reality (VR) with passthrough and spatial compute, smart glasses are waiting for their next big thing.

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The Next Big Thing, Eventually


The entire Extended Reality (XR) market has seen significant swings in interest and capability over the past decade, but smart glasses (by ABI Research’s definition, a device with optical passthrough display(s)), specifically have been most susceptible to those swings. The “first” smart glasses device is arguably Google Glass, which still is classified as a product failure, despite a successful run in the enterprise space for years—in consumers’ eyes, however, it was a failure. Other devices have come and gone, with no real mass market product making it to shelves. Successes in the enterprise sector continue, but even the most successful smart glasses deployments have not been large scale, dwarfed by any other device type: smartphone, tablet, watch, and other wearables. Enabling technologies have promised to propel glasses to new potential, but never gained purchase.

Today’s smart glasses market is more of the same, although the immediate potential is more clear than in the past. Tech giants are working on smart glasses projects, and after years of Research and Development (R&D) and experimentation in parallel segments (e.g., Virtual Reality (VR)), the potential, at least, for a mass market player is there. The latest partnership is Google and Magic Leap, with the companies joining for a strategic technology partnership. Details are scarce for now, though the announcement cited Magic Leap’s strengths in Augmented Reality (AR) and optics, along with Google’s broader technology platforms—likely the notably absent, so far, Android XR platform from Google is a significant piece of this. Meta, Samsung, and other major vendors are similarly looking into the space.

What these devices will look like is not yet clear, although there will with certainty be a shared marketing focus: Artificial Intelligence (AI) first.

AI First, for Now


AI has entirely dominated the news cycle over the past 6 to 12 months. XR was a victim of this, with excitement around spatial compute waning quickly in favor of AI. This is true from the top down, with companies previously XR-focused switching to AI first—namely Meta and Apple.

Some XR excitement has disappeared, as well as the excitement around how AI and XR can work together. A recently published ABI Insight, “How Do Artificial Intelligence and Industrial Extended Reality Work Together?” focused on this specifically through an industrial lens. As for a broader look at AI and XR, expect smart glasses and associated platforms to lean into AI as not only a value add for XR, but also as the primary application and use case: AI smart glasses will be a key product category over the next 2 years. This is true even if no notable advancements come in the way of hardware capabilities. There are continual improvements in processing efficiency and power and display capability (namely Field of View (FoV) and brightness), but these become less important as AI takes the go-to-market reins. As long as a device can enable AI in some form, that will be the selling point. There will also be some natural rebranding or renaming of existing XR use cases as AI use cases—virtual assistants, machine vision, tailored, content, and more will be labeled as AI applications, with varying levels of actual novel AI implementation involved.

This has a knock-on effect of naturally lowering device specification requirements; anything not directly suited to enabling or enhancing AI can be a secondary focus for these devices, leading to reduced costs. The do-it-all smart glasses device is simply not feasible today and will not be for some time, so focusing efforts on key applications is necessary.

New Device Categories Will Be Welcome


While this AI focus will present a new class of smart glasses device type, that is not to say that some devices will not focus on areas outside of AI. High-fidelity visualization is a cornerstone of VR, but applications where user vision is required are not currently well-served by AR glasses, so as hardware improves, there is still room for higher cost and higher visual/spatial capability devices. Enterprise data visualization is one market where such a device will still be valuable. Of course, there is nothing preventing these devices from also leveraging AI advances.

ABI Research’s definition of smart glasses necessitates the inclusion of a visual display; however, the market already has devices fitting this role of AI-first glasses, but without a display. Obviously, the content presented is limited, but we can glimpse the potential of these devices and their AI value-adds. For consumers, a device filling a role similar to smartwatches is most likely, with improved AI virtual assistants streamlining common use cases. With a front-facing camera, machine vision can be leveraged for environmental analysis and using that for content delivery as well. Adding a display creates a visual feedback system, as well as offering another way of presenting data outside of audio.

Whether these devices succeed will depend on the target audience and whether the go-to-market strategy is focused enough on high-value applications within that target audience—a US$500 basic pair of smart glasses has a vastly different audience than a US$1,500 high-end visualization device. Relatedly, the support software and service ecosystem must be mature and feature-complete for that target market and application. If streamlined AI use cases are the target, then that experience has to be seamless and near flawless; if visual content is a focus, then a selection of quality content needs to be easily accessible, which means robust developer tools and support, along with well-researched User Experience (UX). Every hangup or downside is amplified with high device costs and lack of user familiarity.

Ultimately, it is a mix of a defined target user base and applications, appropriate marketing, a realistic device price, and fleshed-out platform support that makes for the highest likelihood for success. AI simply offers another approach to these facets, and one that is currently the hottest tech topic in decades.


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