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市場調查報告書
商品編碼
1666053
邊緣 AI 硬體市場規模、佔有率及成長分析(按設備、功耗、處理器、功能、垂直產業和地區)—2025-2032 年產業預測Edge AI Hardware Market Size, Share, and Growth Analysis, By Device (Smartphones, Surveillance), By Power Consumptions (Less Than 1 W, 1-3 W), By Processor, By Function, By Vertical, By Region - Industry Forecast 2025-2032 |
邊緣AI硬體市場規模預計到2023年將達到239.2億美元,從2024年的281.5億美元成長到2032年的1036.9億美元,預測期內(2025-2032年)的複合年成長率為17.7%。
由於需要即時資料處理的邊緣和連網型設備的快速普及,對邊緣 AI 硬體的需求預計將激增。隨著物聯網 (IoT) 設備變得越來越普及,邊緣 AI 硬體供應商的商業機會將會擴大。對能源效率和硬體技術改進的關注將進一步推動市場成長,而自主技術和先進的人工智慧演算法的使用將刺激銷售。此外,全球正在對人工智慧專用硬體開發進行大量投資,這可能會在 2032 年之前提升市場潛力。然而,整合複雜性、技術純熟勞工短缺、繁重工作導致的高能耗以及對資料安全和隱私的擔憂等挑戰可能會在研究期間及以後阻礙需求。
Edge AI Hardware Market size was valued at USD 23.92 billion in 2023 and is poised to grow from USD 28.15 billion in 2024 to USD 103.69 billion by 2032, growing at a CAGR of 17.7% during the forecast period (2025-2032).
The demand for edge AI hardware is expected to surge, driven by the rapid adoption of edge and connected devices, which necessitates real-time data processing. As Internet of Things (IoT) devices proliferate, opportunities for edge AI hardware providers will expand. Emphasis on energy efficiency and improvements in hardware technology will further enhance market growth, while the increasing use of autonomous technologies and advanced AI algorithms will stimulate sales. Furthermore, significant investments in AI-specific hardware development worldwide are likely to propel market potential through 2032. However, challenges such as integration complexity, a shortage of skilled workers, high energy consumption for demanding workloads, and concerns regarding data security and privacy may hinder demand throughout the study period and beyond.
Top-down and bottom-up approaches were used to estimate and validate the size of the Edge Ai Hardware market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Edge Ai Hardware Market Segments Analysis
Global Edge AI Hardware Market is segmented by Device, Power Consumptions, Processor, Function, Vertical and region. Based on Device, the market is segmented into Smartphones, Surveillance, Robots, Wearables, Edge Servers, Smart Speakers, Automobiles and Other Devices. Based on Power Consumptions, the market is segmented into Less Than 1 W, 1-3 W, 3-5 W, 5-10 W and More Than 10 W. Based on Processor, the market is segmented into Central Processing Units, Graphics Processing Units, Application Specific Integrated Circuits and Other Processors. Based on Function, the market is segmented into Training and Inference. Based on Vertical, the market is segmented into Consumer Electronics, Smart Homes, Automotive & Transportation, Government, Healthcare, Industrial, Aerospace & Defense, Construction and Other verticals. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Edge Ai Hardware Market
The increasing necessity for real-time data processing, which minimizes delays across various applications, is expected to significantly enhance the sales of edge AI hardware in the upcoming years. Key sectors such as autonomous vehicles, industrial automation, and smart city developments rely heavily on swift decision-making capabilities. As the demand for efficient and immediate data handling in these critical applications rises, it is likely to be a primary factor propelling the growth of the global edge AI hardware market in the foreseeable future. This trend highlights the essential nature of edge AI solutions in advancing technology across multiple industries.
Restraints in the Edge Ai Hardware Market
The Edge AI Hardware market is currently facing a significant challenge due to a shortage of skilled professionals needed to design and manage advanced edge AI hardware solutions. This lack of expertise is projected to hinder the long-term sales and growth of edge AI hardware products. Emerging markets are likely to be more adversely affected by this constraint than their developed counterparts within the global edge AI hardware industry, particularly as we move toward 2032. The scarcity of qualified personnel not only impacts product innovation and deployment but also raises concerns about the overall development of the sector in these regions.
Market Trends of the Edge Ai Hardware Market
The emergence of TinyML is significantly shaping the Edge AI Hardware market, as it facilitates the deployment of machine learning models on ultra-low-power devices, enabling intelligent processing directly at the source of data generation. This trend presents substantial growth opportunities for companies committed to advancing TinyML algorithms and models, driving innovation in edge computing capabilities. By investing in this technology, edge AI hardware manufacturers can enhance the functionality and efficiency of their products, ultimately leading to increased revenue generation and market competitiveness. As applications across industries-from smart homes to industrial IoT-require real-time insights with minimal power consumption, TinyML is poised to revolutionize the edge AI landscape.