Read More《动辄几千大洋的“AI眼镜”，玩具还是工具？》
Positive Reviews: AI glasses are standing at the critical point of human – machine interaction innovation, driven by both market potential and technological breakthroughs
The “Battle of a Hundred Glasses” at the end of 2025 marked a crucial step for AI glasses to move from the concept verification stage to large – scale commercial use. This round of explosion is not only the collective entry of technology giants, automobile manufacturers, and traditional eyewear brands but also the result of the resonance between technological iteration and market demand. The potential of AI glasses as the “next – generation human – machine interaction entrance” has begun to emerge.
First of all, the rapid growth of the market scale verifies the commercial value of AI glasses. According to IDC data, in the first half of 2025, the global shipments of smart glasses increased by 64.2% year – on – year, and the single – quarter shipments in the Chinese market increased by 145.5% year – on – year. This growth rate far exceeds that of mature smart hardware categories such as smartphones and smartwatches in the same period. More notably, industry institutions predict that the scale of the AI glasses industry will exceed 100 billion yuan in three years. This expectation is not only based on the short – term demand of “early adopters” but also on the possibility of replacing traditional interaction methods with its core features of “freeing hands, enhancing perception, and connecting the real and virtual worlds”. For example, Quark AI glasses integrate high – frequency applications such as Alipay, Gaode Map, and Taobao into the user’s field of vision. Users can complete payment, navigation, and product price comparison through voice. The Livis AI glasses of Li Auto target the “in – car scenarios” and support functions such as remote vehicle control and music recognition. These scenario – based innovations precisely address the pain points of users who “find it inconvenient to operate their mobile phones” during commuting, driving, and outdoor activities, providing a practical path for the transformation of AI glasses from “toys” to “tools”.
Secondly, technological integration and ecological layout lay the foundation for the long – term development of AI glasses. Different from Google’s Project Glass in 2012, which was a “single – function attempt”, the current AI glasses have a more profound technological reserve. The maturity of large models (such as the Qianwen large model built into Quark) endows them with more natural voice interaction capabilities. The integration of multiple cameras and sensors (such as the dual – camera + pickup device of Li Auto’s Livis) expands the dimension of environmental perception. The cross – border entry of Internet giants (Alibaba, Xiaomi) and automobile manufacturers (Li Auto) accelerates the integration of ecological resources. For example, Alibaba integrates its core ecosystems such as e – commerce, payment, and mapping into AI glasses, constructing a closed – loop of “vision + voice + service”. Automobile manufacturers deeply integrate AI glasses with smart cockpits and vehicle control, forming a “super assistant in mobile scenarios”. This ecological collaboration not only improves user stickiness but also may reshape the interaction logic of the “human – vehicle – environment”, creating a differentiated competitive barrier for AI glasses.
In addition, the “instantaneity” advantage of AI glasses gives them the potential to surpass smartwatches. Smartwatches require users to raise their hands for operation, while AI glasses can present information “unobtrusively” through the feature of being “worn in front of the eyes”. Navigation arrows are directly projected into the field of vision, and product prices are instantly displayed on the micro – display. These experiences are closer to the human habit of “natural observation”. As mentioned in the news, “it is inconvenient to operate a mobile phone by hand during commuting, driving, and traveling”, and the “wear – and – use” feature of AI glasses precisely fills this gap. This “instant interaction” feature makes it有望成为继手机之后，最贴近用户日常的智能硬件。
Negative Reviews: Technological bottlenecks, user pain points, and the lack of an ecosystem mean that AI glasses are still far from being “tool – oriented”
Despite the high market enthusiasm and capital expectations, AI glasses currently face multiple real – world challenges. From the high return rates reported by users (about 30% on JD.com and Tmall, and 40% – 50% on Douyin) to the industry’s own technological shortcomings, the realization of its “tool attributes” still needs to cross several key thresholds.
The most prominent issue is the “impossible triangle” of “performance – lightness – battery life”. The core contradiction of AI glasses lies in the fact that stronger computing power (to support large – model interaction and multi – sensor data processing) requires high – power – consumption chips, which shortens the battery life. Longer battery life requires a larger battery, which increases the weight. And lightness (a prerequisite for all – day wearing) limits the battery capacity and heat dissipation space. Currently, the industry’s solutions are mainly to “sacrifice aesthetics for battery life” (such as wide – leg and thick – frame designs) or use “removable batteries + portable charging” (such as Quark AI glasses). However, neither solution perfectly solves the user’s pain points. The former destroys the aesthetics of glasses as “daily accessories” (traditional glasses users are sensitive to appearance), and the latter increases the carrying burden (requiring an additional battery compartment). This technological compromise directly affects the user’s “willingness to wear”. If AI glasses are too bulky to be worn all day, their “instant interaction” advantage will be greatly reduced.
Secondly, “weak intelligent interaction” and “insufficient functional practicality” are the core reasons for user returns. Although AI glasses have significantly expanded their interaction functions compared to early smart glasses (such as Google Project Glass) (such as payment, navigation, and object recognition), according to evaluations and user feedback, their intelligence level still remains at the “auxiliary tool” stage and has not reached the expected level of a “super assistant”. For example, the accuracy of voice interaction is greatly affected by environmental noise, and the response speed to complex questions is slower than that of mobile phones. The monochromatic display of the micro – display (such as the basic model of Quark S1) limits the richness of information presentation. Although functions such as “price recognition” and “navigation projection” are practical, the coverage of scenarios is limited, making it difficult to support the user’s “high – frequency use” needs. More importantly, the current functions of AI glasses are essentially “extensions of mobile phone functions” rather than “the creation of a new ecosystem”. Users do not obtain unique values that mobile phones cannot provide by using AI glasses, resulting in a low – stickiness state of “putting them away after use” and making it difficult for them to become “must – have tools”.
Moreover, the “high price” directly hinders market penetration. Although the average price of smart glasses dropped from over 2,000 yuan to about 1,500 yuan in the first half of 2025, the starting price of “decent” AI glasses (with a micro – display and strong interaction functions) still needs to be 2,000 yuan, and high – end models (such as the monochromatic display model of Quark S1) are even close to 4,000 yuan. Compared with smartphones (thousand – yuan phones can meet basic needs) and smartwatches (the mainstream price range is 500 – 1,000 yuan), the pricing of AI glasses is significantly beyond the “trial cost” of the general public. For the myopic population, which accounts for 30% of the Chinese population (users with a rigid need to wear traditional glasses daily), if AI glasses cannot compete with traditional glasses (with an average price of several hundred yuan) or ordinary smart hardware in terms of price, the vision of “replacing traditional glasses” will be difficult to achieve.
Finally, the lack of a closed – loop ecosystem limits the long – term value of AI glasses. Currently, the functions of AI glasses mainly rely on the computing power support of mobile phones or the cloud (such as large – model calls), and they have not formed an independent application ecosystem. For example, the “price recognition” function of Quark AI glasses needs to be connected to Taobao, and navigation needs to call Gaode Map. These services are essentially “projections of mobile phone applications” rather than native applications designed specifically for AI glasses. The lack of an independent ecosystem means that AI glasses are difficult to build “irreplaceability”. Users may abandon paying additional costs for AI glasses because the functions of mobile phones are powerful enough, which is in sharp contrast to the “hardware + software” closed – loop formed by smartphones through the App Store.
Suggestions for Entrepreneurs: Focus on user pain points and break through the situation with “scenario – based” and “lightweight” strategies
Although the explosive trend of AI glasses is irresistible, entrepreneurs need to clearly recognize the current technological bottlenecks and user needs and look for opportunities in the following directions:
Prioritize solving the “impossible triangle” and improve the willingness to wear with lightweight design: In response to the contradiction of “performance – lightness – battery life”, entrepreneurs can explore technological paths such as “chip – level optimization” (such as using low – power – consumption AI chips) and “structural innovation” (such as flexible batteries and distributed computing power). For example, cooperate with chip manufacturers to customize low – power – consumption AI chips to reduce the dependence on large batteries. Or adopt a distributed computing power solution of “main device + glasses” (transfer part of the computing tasks to the mobile phone or the cloud) to reduce the hardware load of the glasses themselves. At the same time, the appearance design should be closer to that of traditional glasses. Users’ demand for the “accessory attributes” of AI glasses is no less than that for the “tool attributes”. Entrepreneurs can cooperate with fashion brands to launch lightweight and high – value co – branded models to attract myopic people who are sensitive to appearance.
Deeply cultivate scenario – based functions and shift from “mobile phone extension” to “creation of unique value”: Avoid piling up functions that mobile phones already have. Instead, focus on the core advantage of “freeing hands” and develop unique scenario – based applications for AI glasses. For example, for the commuting scenario, combine real – time bus/subway data with navigation and directly display the “arrival time of the next bus” and the “optimal transfer route” on the glasses through the micro – display. For the outdoor scenario, develop an “AR tour guide” function (identify scenery through the camera and provide real – time explanations). For the office scenario, support “voice shorthand + real – time translation” (convert meeting content into text and synchronize it to the cloud). These functions need to be designed based on users’ high – frequency scenarios and verified for “irreplaceability” through user research. Only when users feel that “they cannot efficiently complete a certain task without AI glasses” can the tool attributes of AI glasses be truly established.
Reduce the user threshold with “graded pricing” and gradually cultivate the market: Refer to the pricing strategy of smartwatches and launch graded products of “entry – level – mid – level – high – end”. The entry – level model can focus on “basic voice interaction + no display” and be priced at 500 – 1,000 yuan to attract “price – sensitive early adopters”. The mid – level model can add a monochromatic micro – display and common scenario functions (such as navigation and object recognition) and be priced at 1,500 – 2,500 yuan to cover “pragmatic users”. The high – end model can focus on “color micro – display + in – depth interaction with large models” and be priced above 3,000 yuan to meet the needs of “tech geeks”. At the same time, models such as “trade – in” (subsidies for exchanging traditional glasses for AI glasses) and “hardware + service subscription” (selling hardware at a low price and making a profit through value – added service fees) can be launched to reduce the initial purchase cost for users.
Build a “hardware + ecosystem” closed – loop to improve long – term stickiness: Entrepreneurs need to cooperate with software developers and content providers to create a native application ecosystem specifically designed for AI glasses. For example, open API interfaces to encourage developers to develop “voice – first” lightweight applications (such as “voice memo” and “AR shopping assistant”) for AI glasses. Cooperate with vertical fields such as education and medical care to develop scenario – based services such as “AI glasses + online courses” and “AI glasses + remote medical consultation”. Through the richness of the ecosystem, users will continue to use AI glasses due to “application dependence” rather than just for “trying something new”.
Pay attention to user feedback and quickly iterate and optimize: In response to the current problems of “weak intelligent interaction” and “insufficient functional practicality” reported by users, entrepreneurs need to establish a rapid response mechanism of “user feedback – technological iteration”. For example, collect users’ high – frequency use scenarios and pain points (such as “inaccurate voice interaction in noisy environments” and “insufficient brightness of the micro – display”) through communities and evaluation institutions, and optimize the algorithms (such as noise – reduction voice recognition) or hardware (such as high – brightness micro – displays) accordingly. At the same time, regularly launch software updates to continuously add new functions (such as developing “AI fitness action correction” and “pet recognition” according to user needs) to keep the product fresh and maintain user stickiness.
The “first year” of AI glasses may be in 2026, but the real explosion will have to wait for the breakthrough of technological bottlenecks and the in – depth matching of user needs. For entrepreneurs, instead of blindly chasing the heat of the “Battle of a Hundred Glasses”, they should focus on user pain points and establish differentiated advantages in niche markets with “lightweight design”, “scenario – based functions”, and “ecosystem closed – loop”. After all, when AI glasses transform from “toys” to “tools”, the enterprises that first capture users’ rigid needs will ultimately become the leaders in the industry.
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