Edge AI Market
完整報告名稱與涵蓋範圍
Edge AI Market Size, Share & Trends Analysis Report, By Component (Hardware, Software, Services), By Device Type (Smart Cameras and Vision Systems, Edge Servers and Gateways, Robots and Drones, Consumer and Wearable Devices, Vehicles), By Application, By End-Use Industry, By Region, and Segment Forecasts, 2026-2035
報告摘要
Edge AI executes machine learning inference directly on or near the device generating the data, on accelerator-equipped SoCs, edge servers, gateways, cameras, robots, and vehicles, rather than in remote clouds. The study covers dedicated AI silicon and modules, model optimisation and deployment software, MLOps platforms for distributed fleets, and integration services, across applications from factory visual inspection to autonomous navigation and on-device language processing.
The case for pushing inference to the edge rests on physics and economics that clouds cannot overcome: closed-loop control in robotics and driver assistance requires millisecond latency, video backhaul from thousands of cameras costs more than local processing, remote mines and farms lack dependable connectivity, and privacy statutes discourage exporting raw footage or health signals. Model compression techniques, including quantisation, pruning, and distillation of compact language and vision models, keep expanding what fits within edge power budgets, and NPUs are becoming standard in everything from microcontrollers to vehicle domain controllers. A notable trend is small language models running on-device, extending generative capabilities to handsets, PCs, and industrial HMIs without cloud round-trips.
Asia Pacific leads unit volumes through its electronics manufacturing and smart-city deployments, North America drives silicon innovation and industrial retrofits, and Europe anchors automotive and machine-vision applications. The competitive base is broad and layered, spanning semiconductor giants, low-power silicon startups, and software platforms for edge model lifecycle management, with no single vendor controlling the stack.
The InsightAce study delivers revenue forecasts in US$ across component, device type, application, industry, and regional segments for 2026-2035, along with segment trend analysis, competitive landscape mapping, and company profiles.
授權報價
| Single User | $4,500 USD |
| Enterprise / Global Site Licence | $9,500 USD |
目錄 Table of Contents
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Edge AI Market Snapshot
Chapter 4. Global Edge AI Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Market Drivers
4.3. Market Challenges
4.4. Emerging Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis - Porter's Five Forces Analysis
4.7. Competitive Landscape and Market Positioning
4.8. Market Opportunity Analysis
Chapter 5. Market Segmentation 1: By Component Estimates & Trend Analysis
5.1. Component & Market Share, 2026 & 2035
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analysis, 2026 to 2035, by Component:
5.2.1. Hardware
5.2.2. Software
5.2.3. Services
Chapter 6. Market Segmentation 2: By Device Type Estimates & Trend Analysis
6.1. Device Type & Market Share, 2026 & 2035
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analysis, 2026 to 2035, by Device Type:
6.2.1. Smart Cameras and Vision Systems
6.2.2. Edge Servers and Gateways
6.2.3. Robots and Drones
6.2.4. Consumer and Wearable Devices
6.2.5. Vehicles
Chapter 7. Market Segmentation 3: By Application Estimates & Trend Analysis
7.1. Application & Market Share, 2026 & 2035
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analysis, 2026 to 2035, by Application:
7.2.1. Visual Inspection and Quality Control
7.2.2. Autonomous Navigation
7.2.3. Predictive Maintenance
7.2.4. Voice and Language Processing
7.2.5. Real-Time Video Analytics
Chapter 8. Market Segmentation 4: By End-Use Industry Estimates & Trend Analysis
8.1. End-Use Industry & Market Share, 2026 & 2035
8.2. Market Size (Value US$ Mn) & Forecasts and Trend Analysis, 2026 to 2035, by End-Use Industry:
8.2.1. Manufacturing
8.2.2. Automotive
8.2.3. Retail
8.2.4. Healthcare
8.2.5. Agriculture
8.2.6. Smart Cities and Utilities
Chapter 9. Edge AI Market: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. United States
9.1.2. Canada
9.2. Europe
9.2.1. Germany
9.2.2. United Kingdom
9.2.3. France
9.2.4. Italy
9.2.5. Spain
9.2.6. Rest of Europe
9.3. Asia Pacific
9.3.1. China
9.3.2. Japan
9.3.3. India
9.3.4. South Korea
9.3.5. Australia
9.3.6. Southeast Asia
9.3.7. Rest of Asia Pacific
9.4. Latin America
9.4.1. Brazil
9.4.2. Mexico
9.4.3. Rest of Latin America
9.5. Middle East & Africa
9.5.1. GCC Countries
9.5.2. South Africa
9.5.3. Rest of Middle East & Africa
Chapter 10. Competitive Landscape
10.1. Company Market Positioning Analysis
10.2. Strategic Developments (Partnerships, Expansions, Product Launches, M&A)
Chapter 11. Company Profiles
11.1. NVIDIA Corporation
11.2. Qualcomm Technologies
11.3. Intel Corporation
11.4. Arm Holdings
11.5. MediaTek
11.6. NXP Semiconductors
11.7. Renesas Electronics
11.8. Texas Instruments
11.9. Hailo
11.10. Ambarella
11.11. Synaptics
11.12. STMicroelectronics
11.13. SiMa.ai
11.14. Axelera AI
11.15. Edge Impulse
11.16. Latent AI
圖表清單 List of Tables & Figures
Table 1. Global Edge AI Revenue Forecast by Component, 2026-2035 (US$ Mn)
Figure 1. Global Edge AI Market Snapshot, 2026 & 2035
Table 2. Global Edge AI Revenue Forecast by Device Type, 2026-2035 (US$ Mn)
Figure 2. Global Edge AI Share by Component, 2026 & 2035
Table 3. Global Edge AI Revenue Forecast by Application, 2026-2035 (US$ Mn)
Figure 3. On-Device Small Language Model Adoption Trend, 2026-2035
Table 4. Global Edge AI Revenue Forecast by End-Use Industry, 2026-2035 (US$ Mn)
Figure 4. Edge Inference versus Cloud Inference Cost and Latency Trade-Off Analysis
Table 5. North America Edge AI Revenue by Country, 2026-2035 (US$ Mn)
Figure 5. NPU Integration Trend Across Device Classes
Table 6. Europe Edge AI Revenue by Country, 2026-2035 (US$ Mn)
Figure 6. Asia Pacific Edge AI Growth Opportunity Analysis
Table 7. Asia Pacific Edge AI Revenue by Country, 2026-2035 (US$ Mn)
Figure 7. Competitive Positioning of Key Edge AI Vendors
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