Under the guidance of the Artificial Intelligence Working Committee of the China Internet Association, Frost & Sullivan, LeadLeo, Junhe, and Jiayuan jointly prepared 'Blue Book on the Development and Application Practices of China's Edge AI Industry (2026)', and case collection is ongoing.

Regarding the Wuzhen Summit of the World Internet Conference

Influence of the Summit

Key Research Points

1. Research Background of China's Edge AI Industry

As the capabilities of large models continue to improve, artificial intelligence is gradually expanding from cloud-based training and inference to terminals such as mobile phones, computers, cars, robots, wearable devices, and smart homes. Edge AI can complete some or all data processing and model inference locally, offering significant benefits in reducing response latency, minimizing cloud costs, protecting data privacy, and enhancing personalized experiences. It is becoming an important direction for large-scale application of artificial intelligence.

At the same time, edge AI is not a single product or technology market but a composite industrial system composed of edge chips, storage, sensors, edge models, operating systems, development tools, terminal devices, and application services. With continuous improvement in chip computing power, accelerated development of smaller models, and gradual maturity of software and hardware collaboration capabilities, edge AI is moving from single-functional applications to system-level intelligence and multi-scenario applications.

Currently, the edge AI industry is still in a stage of rapid development. There are significant differences in penetration rates and commercialization paths of different terminals, and the industry has not yet reached a unified understanding of the market boundaries, industrial chain structure, and competitive landscape of edge AI. Some enterprises have already implemented products in AI phones, AI PCs, smart cars, robots, AI glasses, and other smart terminals, but they still face challenges such as balancing computing power and power consumption, model adaptation, software and hardware collaboration, cost control, data security, and large-scale production.

Based on the above industry development background, under the guidance of the Artificial Intelligence Working Committee of the China Internet Association, Frost & Sullivan, LeadLeo, JunHe, and JiaYuan have jointly compiled the "Blue Book on the Development and Application Practices of China's Edge AI Industry (2026)" with relevant research institutions, industrial chain enterprises, and experts. The blue book will systematically review the development foundation, industrial chain structure, key terminal markets, and competitive landscape of China's edge AI industry. Through representative enterprises and application cases, it will present the real path of edge AI from technical capabilities to product implementation and large-scale applications, providing references for enterprise strategic planning, industrial cooperation, and investment decisions.

2. Research Content

This blue book will take "whether technology is innovative, whether scenarios can be scaled, and whether enterprises can maintain sustainable competitiveness" as the main line, focusing on the following five aspects:

1. Definition and Development Overview of the Edge AI Market

Clarify the definition, scope of edge AI, and its relationship with cloud AI and edge AI. Review the technical architecture, development stages, and main driving factors of edge AI. Based on a unified market definition, analyze the current development status, market size, and future growth trends of China's edge AI market.

2. Edge AI Industrial Chain and Value Distribution

Systematically break down the edge AI industrial chain, covering components such as edge chips, storage and sensors, edge models, operating systems, development tools, terminal equipment, and application services. Analyze the core functions of each component, participating enterprises, and upstream and downstream relationships, and assess the main current development status of the industry.

3. Key Terminal Markets and Application Scenarios

Focusing on key terminals such as AI phones, AI PCs, smart cars, robots, AI glasses, wearable devices, smart homes, and IoT devices, analyze their market demand, product forms, AI functions, and commercialization prospects. Identify terminals and scenarios that are expected to achieve large-scale applications first.

4. Competitive Landscape and Industrial Ecosystem

Review the main participants and competitive relationships in the edge AI industry. Analyze the differentiated capabilities of chip manufacturers, model companies, operating system manufacturers, terminal brands, and application service providers. Focus on studying competitive elements such as computing power, power consumption, cost, model capabilities, software and hardware collaboration, and ecosystem adaptation, as well as possible changes in industry leadership and value distribution.

5. Benchmark Cases and Development Trends

Select representative edge AI enterprises and terminal application cases. Analyze their product positioning, core technologies, customer scenarios, business models, production progress, and ecosystem cooperation methods. Based on case studies, summarize the main problems and opportunities faced by the edge AI industry, assess development trends such as model miniaturization, edge-cloud collaboration, multi-modal interaction, and integration of smart agents and software and hardware, and provide suggestions for enterprise development.

The blue book will conduct research through public data analysis, enterprise interviews, expert interviews, and case studies, and cross-verify key data and market judgments, aiming to produce a research result with clear boundaries, reliable data, specific cases, and industrial reference value.

3. Value for Enterprises to Participate in this Blue Book

1. Participate in industry research and promote the formation of market consensus

Enterprises can combine their own business practices to provide professional opinions on the market definition, industrial boundaries, technical routes, application scenarios, and commercialization challenges of edge AI, helping to form a clearer, more objective, and executable research framework for the industry.

2. Incorporate benchmark cases to systematically display enterprise capabilities

The blue book will select representative industrial chain enterprises and application projects as cases to systematically display the business positioning, core technologies, product capabilities, customer scenarios, production progress, and ecosystem cooperation status of enterprises. Compared with single product promotion, case studies are more conducive to external institutions understanding the actual value and differentiated capabilities of enterprises in the edge AI industry.

3. Obtain professional expression and industry dissemination

Enterprise cases will be reviewed in third-party research language and disseminated through the blue book, release events, media coverage, and relevant industry channels, helping enterprises establish a clearer position in edge AI and enhance their professional recognition among customers, partners, investment institutions, and the industrial ecosystem.

4. Strengthen industrial chain connection and cooperation opportunities

The blue book will connect chips, models, software platforms, terminal brands, application enterprises, industrial parks, and investment institutions. Enterprises can use research interviews, case releases, and special discussions to establish connections with upstream and downstream enterprises and potential partners, expanding opportunities for joint research, product adaptation, customer verification, and ecosystem cooperation.

5. Obtain market insights to assist strategic decision-making

Enterprises can gain a deeper understanding of the structure of the edge AI industrial chain, the penetration rhythm of key terminals, the competitive landscape, and changes in customer needs, providing references for technical route selection, product planning, market entry, ecosystem cooperation, and resource investment.

6. Deposit enterprise case assets for sustainable use

Case content confirmed by enterprises can serve as important reference materials for enterprise external dissemination, customer communication, financing promotion, and industrial cooperation. Selected cases can also be used in industry forums, special seminars, and subsequent research results, forming long-term brand and research value.

Participation Process