The race for so-called “AI glasses” — devices combining microphones, cameras, speakers, and AI models to translate, transcribe, guide, or respond in real time — is focusing on a very specific location: China. Several industry analyses indicate that the country is not only acting as a major assembly hub but has transformed into the center of an integrated supply chain spanning optics, electronics, and large-scale industrialization.
Meanwhile, the market is preparing for a volume leap reminiscent of other consumer electronics waves: the analysis firm Omdia estimates that global shipments of AI glasses will grow strongly, reaching 5.1 million units in 2025 and surpassing 10 million in 2026. In the longer term, projections point to 35 million by 2030, driven by the entry (or return) of major brands and by the “ecosystem” effect: more devices on the streets, more applications, and more everyday use cases.
From Prototype to Mass Production: The China Factor
The idea of glasses that “understand” their environment isn’t new, but what’s different is the industrial phase this sector is undergoing. Unlike other wearables, these products combine demanding requirements that are difficult to fit into a lightweight format: battery life, connectivity, high-quality microphones, discreet cameras, heat dissipation, and often integration with a phone and cloud services.
This is where China holds an advantage. Some reports and specialized coverage suggest that the country accounts for around 80% of global AI glasses production, supported by a highly fragmented but coordinated supply chain: optical parts, camera modules, batteries, PCBs, final assembly, and outbound logistics. Beyond the exact percentage — difficult to verify externally due to the diversity of white-label and ODM brands — the pattern is clear: a significant part of the global supply, even that linked to Western brands, depends on suppliers and industrial capacity in Asia.
The case of mass-market smart glasses illustrates this well: big tech companies are making moves, but manufacturing — and part of the industrial know-how — still revolves around Asian suppliers. Additionally, Chinese players are also pushing strongly in the market, from hardware manufacturers to internet companies integrating their own AI models.
A Growing Market… and One That Is Starting to Clarify Its Numbers
Beyond promotional noise, quantifiable forecasts are beginning to emerge. Omdia ranks China as the second largest market by volume in 2026 (after the United States), with 1.2 million units and a 12% share of global shipments that year. The dual message is clear: China manufactures a lot for the world, but it’s also building internal demand with its own device catalog, apps, and assistants.
Table 1. Global AI Glasses Shipment Forecast (Omdia)
| Year | Estimated Global Shipments | Comment |
|---|---|---|
| 2025 | 5.1 million | 158% annual jump according to Omdia |
| 2026 | >10 million | Market commercialization threshold |
| 2030 | 35 million | Sustained growth (CAGR 47% 2025–2030) |
Table 2. China in 2026 (According to Omdia)
| Indicator | 2026 Estimate |
|---|---|
| AI glasses shipments in China | 1.2 million |
| Share of global shipments | 12% |
What Can You Do with “AI Glasses” Today?
The appeal for the general public isn’t in complex “augmented reality” but in very specific, easy-to-understand functions: live translation of signs or conversations, meeting transcription, contextual reminders, hands-free navigation for routes and tasks, or quick photo and video capture with voice commands.
In China, for example, several companies are launching products that rely on proprietary language models to act as personal assistants. Outside the country, major consumer brands are also boosting their efforts on devices that serve as “gateway” to AI services, with the idea that the next interface won’t be an app but a device always carried on the person.
The Other Side: Dependency, Standards, and Privacy
This industrial concentration has implications. The first is resilience: when a category depends on a handful of manufacturing clusters, any logistical or geopolitical tension can lead to delays, cost increases, or supply issues.
The second is technological: if the value chain consolidates around specific suppliers, the pace of innovation — and de facto standards — tend to be set there. Practically, this can influence key components, the final price, and the functions prioritized.
And the third, perhaps most sensitive, is privacy. Wearing a camera and microphones on your face changes the debate: it’s not only about what the user does but also how captured data is managed and what limits are built in by design. This will be a key factor affecting real adoption in public spaces, workplaces, and educational settings.
A Sector Playing Its “iPhone Moment”
The next 18 months will be decisive. Shipment forecasts point to a scale-up, but the history of technology shows many categories that grew rapidly and then stalled due to user fatigue, lack of use cases, or social rejection.
The difference now is that generative AI has simplified interaction: talking, asking, summarizing, or translating no longer requires complex menus. This ease could push AI glasses to become a daily accessory. If that happens, China starts with a dominant position: manufacturing, innovating, and increasingly, consuming.
Frequently Asked Questions
What’s the difference between AI glasses and augmented reality (AR) glasses?
AI glasses typically focus on audio, camera, and assistant functions (translation, transcription, queries), whereas AR glasses prioritize overlaying graphics or screens in the field of view. Some combine both approaches, but not always.
Why does China dominate manufacturing of smart glasses?
Because it brings together optical, electronic, assembly, and logistics suppliers within the same ecosystem, reducing costs, accelerating iterations, and making the transition from prototype to mass production easier.
What privacy risks do AI glasses with cameras and microphones pose?
The main risk is accidental capture of third parties and subsequent data handling (storage, training, cloud transfer). Strong policies, visible indicators of recording, and local processing are key to building trust.
What day-to-day uses provide the most value?
Real-time translation, subtitles, voice notes, hands-free navigation, and meeting summaries are the most cited use cases because they solve tangible tasks without needing a phone.