Source: iResearch Consulting | Release Time: 2025/7/2 17:40:35
Online Browse Link: https://report.iresearch.cn/report_pdf.aspx?id=4730
Research Report on China's AI Glasses Industry in 2025
High‑quality multi‑polar growth for China AI glasses amid AI and spatial tech integration wave
AI Glasses,China AI Eyewear,AR Glasses,AI Wearable,Optical Waveguide,End‑side Large Model,Consumer Smart Glasses
This iResearch report dissects China AI glasses industry chain,market forecast,key manufacturers and consumer insights,covering supply‑demand dynamics and industry development outlook.
Boosted by end‑side large models and optical waveguide yield improvement,consumer‑grade AI glasses cost decreases. Consumer demands shift toward diverse scenarios. Report covers industry chain,vendors,user behavior and future trends.
1. Industry Overview: Definition & classification, development history, PEST driving factors, investment‑financing market performance.
2. Industry Status: Global & China market scale forecast, full‑chain analysis for upstream‑midstream‑downstream.
3. Typical Manufacturers: RayNeo Innovation, Lawaken Li, Rokid, DreamSmart.
4. Consumer Insights: User profile, purchasing behavior, product concerns, experience evaluation, repurchase & purchase willingness gap between buyers and interested customers.
5. Industry Prospects: Production‑side, demand‑side, retail‑side and industrial‑level trends.
6. Expert Voices & mass charts‑tables covering price, weight, optical scheme, chip, survey statistics.
Industry: Other
Report type: Free report
Page: 62
Chart: 61
Price: ¥0
Function Entrance: Add to Favorites, Download Report, Online browsing

In 2025, under the wave of deep integration of artificial intelligence and space technology, China's AI eyewear industry will continue to break through the boundaries of innovation, presenting a high‑quality, multi‑polar development trend and high‑speed development in medical, industrial, and consumer scenarios.
On the supply side, with the improvement of inference efficiency of end‑to‑end large models and breakthroughs in the yield of optical waveguides, the cost of consumer grade AI glasses has decreased, stimulating the prosperity of the hardware ecosystem.
On the demand side, consumers' demand for AI glasses has shifted from basic functions to diverse application scenarios, driving the booming development of the AI glasses market.
In order to clarify the development trajectory and level of AI glasses in the Chinese market, as well as consumers' purchasing needs and preferences for AI glasses.
IResearch has launched the "2025 AI Glasses Industry Research Report" project, aiming to comprehensively analyze the economic value and development potential of AI glasses.
By sorting out the development context, industry chain map, and consumer preferences of AI glasses, it can gain insights into the market value of AI glasses, analyze consumer demand and payment motivations, and provide in‑depth industry insights for industry practitioners, investors, and related researchers, and help promote the healthy development of China's AI glasses industry.
Introduction to the Overview of China's AI Glasses Industry
1.1 Definition and classification of AI glasses
1.2 Development history of AI glasses
1.3 PEST analysis of driving factors
1.4 Performance of the Investment and Financing Market
Analysis of the Current Situation of China's AI Glasses Industry
2.1 Global and Chinese AI Glasses Market Size Forecast
2.2 Panoramic dismantling of AI glasses industry chain
2.3 Analysis of China's AI Glasses Industry Chain ‑ Upstream of the Industry Chain
2.4 Analysis of China's AI Glasses Industry Chain ‑ Midstream of the Industry Chain
2.5 Analysis of China's AI Glasses Industry Chain ‑ Downstream of the Industry Chain
3 Typical AI Glasses Manufacturers in China
3.1 AI Glasses Market Manufacturer Sorting
3.2 Typical Manufacturer Introduction: RayNeo Innovation
3.3 Typical Manufacturer Introduction: Lawaken Li
3.4 Typical Manufacturer Introduction: Rokid
3.5 Typical Manufacturer Introduction: DreamSmart
4 Consumer Insights into Chinese AI Glasses
4.1 Consumer Research Explanation
4.2 Research User Profile
4.3 Analysis of Consumer Purchasing Behavior
4.2.1 Respondents' AI Glasses Cognition Status
4.2.2 Respondent's purchase of smart glasses
4.2.3 Purchase of AI Glasses by Customers
4.2.4 Purchasing AI Glasses Core Focus for Customers
4.2.5 Customer AI Glasses User Experience
4.2.6 AI Glasses Repurchase and Recommendation for Buyers
4.2.7 AI Glasses Perception and Purchase Concerns of Interested Customers
4.2.7 Interest Customers AI Glasses Purchase Core Focus
4.2.8 Deep level interest customers' future purchasing preferences
4.2.9 Deep level interest driven future purchases by customers
4.2.10 Differences in Future Needs between Buyers and Interested Customers
5 Trends and Prospects of China's AI Glasses Industry
5.1 Production Trends
5.2 Demand Side Trends
5.3 Retail Trends
5.4 Industry Trends
6 expert voices
Figure 1‑1 Starting prices of various brands of AI audio glasses
Figure 1‑2 Weight of AI audio glasses without glasses for each brand
Figure 1‑3 Starting prices of various brands of AI captured glasses
Figure 1‑4 AI captured the weight of glasses from various brands without glasses
Figure 1‑5 AI displays the starting prices of various brands of glasses
Figure 1‑6 Weight of glasses taken by AI without glasses for each brand
Figure 1‑7 Consumer Confidence Index ‑ Consumption Intention
Figure 1‑8 Monthly Value of Total Retail Sales of Social Goods in China from October 2010 to September 2024
Figure 1‑9 Per capita GDP and per capita disposable income of Chinese residents from 2013 to 2024
Figure 1‑10: The total number and proportion of myopic population in China from 2019 to 2023
Figure 1‑11 Number of Financing Events for AI Glasses Manufacturers from 2020 to 2024
Figure 1‑12 Scale of Financing Amount for AI Glasses Manufacturers in 2024
Figure 1‑13 Financing rounds of AI glasses manufacturers in 2024
Figure 1‑14 Comparison of Cumulative Changes in AI Glasses Index and Shanghai Composite Index (2024/8/16‑2024/12/11)
Figure 1‑15 Top 5 Industries of AI Glasses Index Component Stocks
Figure 1‑16 AI Glasses Index Component Stocks Main Business Word Cloud
Table 1‑1 AI Display Glasses Display Scheme
Table 1‑2: Use of Digital Technology by Domestic Listed Companies
Table 1‑3 Investment and Financing Events of Domestic AI Glasses Manufacturers in 2024
Figure 2‑1 AI Glasses Shipment Scale and Forecast from 2023 to 2028
Figure 2‑2 China AI Glasses Industry Chain Map
Figure 2‑3 Production Capacity of Domestic Micro OLED Wafer Enterprises (K/M)
Figure 2‑4 Screen Solutions for AR Glasses Products Released from 2022 to 2024
Figure 2‑5 Mass production level, yield, and cost of four types of optical solutions
Figure 2‑6: Optical Solutions for AR Glasses Released from 2022 to 2024
Figure 2‑7 General Capability Echelons of Large Models at Home and Abroad
Table 2‑1 Usage of AI Glasses SoC Chips (Partial)
Table 2‑2 Comparison of LCoS, Micro OLED, and Micro LED Screen Scheme Indicators
Table 2‑3 Comparison of Four Types of Optical Scheme Indicators
Table 2‑4 AI Layout of Domestic Mobile Phone Manufacturers (Part)
Table 2‑5 Data centers and intelligent computing centers of Internet enterprises (partial)
Table 3‑1 Representative Products of AI Audio Glasses Brands
Table 3‑2 Representative Products of AI Shooting Glasses Brands
Table 3‑3 AI displays representative products of certain eyewear brands
Figure 4‑1 Basic Characteristics and Profile of Survey Users
Figure 4‑2 Proportion of Information Acquisition Methods for Smart Glasses by Overall Respondents
Figure 4‑3 Types of smart glasses that the overall respondents have heard of
Figure 4‑4 Overall AI eyewear brands heard of by respondents (TOP10)
Figure 4‑5 Overall respondents' purchase of smart glasses
Figure 4‑6 Overall situation of respondents who have purchased or plan to purchase smart glasses
Figure 4‑7: The reasonable price range of smart glasses perceived by the overall respondents
Figure 4‑8: The number of AI glasses purchased by respondents and their actual expenses
Figure 4‑9: The main channels through which respondents purchase AI glasses
Figure 4‑10 Driving factors for respondents who have already purchased AI glasses
Figure 4‑11 Core concerns of respondents who have purchased AI glasses regarding functionality, design, and components
Figure 4‑12 Frequency and scenarios of respondents using AI glasses after purchasing
Figure 4‑13 Experience evaluation and evaluation content of the purchased AI glasses by the respondents who have already purchased them
Figure 4‑14: The likelihood of respondents who have already purchased AI glasses purchasing them again in the next year
Figure 4‑15: The willingness of respondents who have already purchased to recommend their current AI glasses to others
Figure 4‑16: The level of awareness and purchase concerns of interested respondents towards AI glasses
Figure 4‑17 Interest of respondents in AI glasses
Figure 4‑18: Conditions for Encouraging Interested Respondents to Purchase AI Glasses
Figure 4‑19 Interest respondents' attention to product iteration and preference for promotional activities when purchasing AI glasses
Figure 4‑20: Respondents with deep interests are most likely to place orders for AI glasses in the next year
Figure 4‑21: The deep interest respondents' preferred brands when purchasing AI glasses in the next year
Figure 4‑22: Driving factors for purchasing decisions of respondents with deep interests when purchasing AI glasses in the next year
Figure 4‑23 Deep interest respondents' expectations for battery life when purchasing AI glasses in the next year
Figure 4‑24: AI Glasses Appearance Style Expected by Respondents
Figure 4‑25: AI Glasses Lens Materials Expected by Respondents
Figure 4‑26 AI eyeglass frame material expected by respondents
Core Problems:
1. Hardware cost and weight remain high for display‑class AI glasses.
2. End‑side large‑model local operation power consumption is large, battery life is insufficient.
3. Mass consumers lack cognition, potential users hold purchase hesitation.
4. Application ecosystem is insufficient, practical scenarios are limited.
Solutions:
Optimize optical scheme yield; adopt low‑power SoC chip; carry out layered product positioning; enrich native AI application; strengthen popular‑science marketing.
Execution Mode:
Upstream: Cooperate with optical‑chip suppliers to iterate component performance and control cost.
Midstream: Launch multi‑grade product matrix covering entry‑level and high‑end versions; optimize hardware lightweight and power‑saving design.
Downstream: Complete scenario‑oriented software adaptation; build offline experience channels; conduct targeted user education for potential customers.
Acceptance Model:
1. Hardware indicator: Product weight, cost, battery life reach preset target value.
2. Market indicator: Brand awareness, real purchase conversion rate of interested users are improved.
3. User indicator: Survey feedback on wearing experience, function satisfaction, repurchase intention are promoted.
Comment Area