세계의 엣지 AI 액셀러레이터 시장 규모, 점유율, 동향 분석 보고서 : 프로세서별, 디바이스별, 최종 용도별, 지역별, 전망 및 예측(2024-2031년)
Global Edge AI Accelerator Market Size, Share & Trends Analysis Report By Processor, By Device (Smartphones, IoT Devices, Robots, and Cameras), By End Use, By Regional Outlook and Forecast, 2024 - 2031
상품코드:1709844
리서치사:KBV Research
발행일:2025년 04월
페이지 정보:영문 294 Pages
라이선스 & 가격 (부가세 별도)
한글목차
세계의 엣지 AI 액셀러레이터 시장 규모는 예측 기간 동안 30.3%의 연평균 복합 성장률(CAGR)을 나타내 2031년까지 472억 5,000만 달러에 달할 것으로 전망됩니다.
그러나 엣지 디바이스에서 AI 모델을 관리하고 업데이트하는 과제는 복잡성을 높이고 있습니다. 따라서 엣지 AI 액셀러레이터는 실시간 처리 능력을 유지하면서 컴퓨팅 능력과 스토리지 한계를 극복하는 혁신적인 방법을 찾아야 합니다.
프로세서 전망
프로세서를 기반으로 시장은 중앙 처리 장치(CPU), 그래픽 처리 장치(GPU), 특정 용도용 집적 회로(ASIC), 필드 프로그래머블 게이트 어레이(FPGA)로 분류됩니다. 다양한 AI 대응 엣지 디바이스에 있어서의 CPU의 보급에 기인하고 있습니다. 또한, 멀티 코어 처리와 AI 최적화 CPU의 진보에 의해 계산 효율이 향상해, 엣지에서의 AI 워크로드 처리에 최적인 선택지가 되고 있습니다.
기기 전망
디바이스 기반으로 시장은 스마트폰, IoT 디바이스, 로봇, 카메라로 분류됩니다. IoT 디바이스 부문은 2023년 시장 점유율의 33%를 기록했습니다. 또한, IoT 에코시스템의 실시간 의사결정, 강화된 보안 및 저지연 처리의 요구에 따라 이 부문의 엣지 AI 액셀러레이터에 대한 수요가 높아지고 있습니다.
최종 용도 전망
최종 용도별로 보면, 시장은 헬스케어, 자동차, 소매, 제조, 보안·감시, 기타로 분류됩니다. 엔지니어링 엣지 AI 액셀러레이터 수요를 견인하고 있으며, 스마트 팩토리와 인더스트리 4.0의 도입 확대 및 실시간 운영 인사이트에 대한 요구 증가도 이 부문의 성장에 중요한 역할을 하고 있습니다.
지역 전망
지역별로 볼 때 엣지 AI 액셀러레이터 시장은 북미, 유럽, 아시아태평양, LAMEA의 4개 지역에 걸쳐 분석되고 있습니다. AI 기반 자동화, 예측 유지보수, 품질 관리 솔루션의 도입은 제조 분야에서 엣지 AI 가속기에 대한 수요를 촉진했습니다. 또한 스마트 팩토리 및 인더스트리 4.0 이니셔티브의 구현이 증가하고 실시간 운영 인사이트에 대한 필요성이 커지면서 이 부문의 성장에 중요한 역할을 했습니다.
The Global Edge AI Accelerator Market size is expected to reach $47.25 billion by 2031, rising at a market growth of 30.3% CAGR during the forecast period.
The rapid adoption of AI-driven technologies in autonomous vehicles, advanced driver assistance systems (ADAS), and in-vehicle infotainment significantly contributed to the segment's growth. Consequently, the automotive segment witnessed 24% revenue share in the market in 2023. Additionally, the increasing demand for real-time data processing to enhance vehicle safety, performance, and efficiency further boosted the adoption of edge AI accelerators in the automotive industry.
The convergence of 5G and edge AI is also transforming the automotive industry. Connected vehicles rely on AI-driven systems for navigation, object detection, and driver assistance. With 5G networks, vehicles can communicate with each other and infrastructure in real-time, improving road safety and efficiency. AI accelerators at the edge enable rapid data processing within vehicles, reducing dependence on cloud-based servers and ensuring uninterrupted performance even in low-connectivity areas. In addition, industries such as banking, retail, and transportation are adopting AI-driven surveillance systems to improve security measures. Financial institutions leverage AI-based fraud detection at the edge, while retailers use AI-powered cameras for theft prevention and customer behaviour analysis. AI accelerators enhance real-time decision-making in security applications, making them indispensable for businesses looking to mitigate risks and safeguard assets. Thus, the growing demand for AI-enabled security and surveillance solutions is propelling the market's growth.
However, the challenge of managing and updating AI models on edge devices adds to the complexity. Unlike cloud systems that can be updated centrally, updating AI algorithms on edge devices requires efficient model compression and deployment strategies. As AI models become more sophisticated, edge AI accelerators must find innovative ways to overcome computational and storage limitations while maintaining real-time processing capabilities. Thus, edge AI devices' limited computational power and storage constraints hamper the market's growth.
Processor Outlook
Based on processor, the market is characterized into central processing unit (CPU), graphics processing unit (GPU), application-specific integrated circuits (ASICs), and field-programmable gate array (FPGA). The central processing unit (CPU) segment garnered 33% revenue share in the market in 2023. This segment's dominance is attributed to the widespread use of CPUs in various AI-enabled edge devices, including smartphones, IoT devices, and industrial systems. Additionally, advancements in multi-core processing and AI-optimized CPUs have enhanced computational efficiency, making them a preferred choice for handling AI workloads at the edge. The growing integration of AI acceleration features in modern CPUs further strengthens their adoption in edge computing applications.
Device Outlook
On the basis of device, the market is classified into smartphones, IoT devices, robots, and cameras. The IoT devices segment recorded 33% revenue share in the market in 2023. The rapid expansion of smart home devices, industrial IoT applications, and connected healthcare solutions has contributed to the rising adoption of AI accelerators in IoT devices. Moreover, the need for real-time decision-making, enhanced security, and low-latency processing in IoT ecosystems has strengthened the demand for edge AI accelerators within this segment. As industries increasingly focus on automation and AI-driven analytics, the role of edge AI in IoT devices is expected to become even more prominent.
End Use Outlook
By end use, the market is divided into healthcare, automotive, retail, manufacturing, security and surveillance, and others. The manufacturing segment held 18% revenue share in the market in 2023. Adopting AI-driven automation, predictive maintenance, and quality control solutions has fuelled the demand for edge AI accelerators in manufacturing. Moreover, the increasing implementation of smart factories and Industry 4.0 initiatives and the need for real-time operational insights have played a significant role in the segment's growth.
Regional Outlook
Region-wise, the edge AI accelerator market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment recorded 38% revenue share in the market in 2023. The region's dominance can be attributed to the strong presence of technology giants, high investments in AI infrastructure, and widespread adoption of AI-driven applications across healthcare, automotive, and finance industries. Additionally, government initiatives supporting AI research and development further contributed to North America's market expansion. The growing demand for real-time data processing and intelligent edge devices has also fuelled market growth in the region.
