세계의 AI 엣지 컴퓨팅 시장 : 규모, 점유율, 동향 분석 - 컴포넌트별, 조직 규모별, 용도별, 업계별, 지역별 전망과 예측(2024-2031년)
Global AI Edge Computing Market Size, Share & Trends Analysis Report By Component (Hardware, Software, and Services), By Organization Size, By Application, By Industry Vertical, By Regional Outlook and Forecast, 2024 - 2031
상품코드:1529165
리서치사:KBV Research
발행일:2024년 08월
페이지 정보:영문 308 Pages
라이선스 & 가격 (부가세 별도)
한글목차
세계 AI 엣지 컴퓨팅 시장 규모는 예측 기간 동안 20.9%의 연평균 복합 성장률(CAGR)로 성장하여 2031년까지 648억 달러에 달할 것으로 예상됩니다.
KBV Cardinal matrix에서 제시된 분석을 바탕으로 Cisco Systems는 AI 엣지 컴퓨팅 시장의 선구자입니다. Amazon Web Services, Cisco Systems, IBM 등의 기업은 AI 엣지 컴퓨팅 시장의 주요 혁신자의 일부입니다. 2022년 9월 IBM은 인도 통신사인 Airtel과 제휴했습니다. 이 협업은 IBM Cloud Satellite와 Red Hat OpenShift를 활용하여 인도에서 Airtel의 엣지 컴퓨팅 플랫폼을 구축하는 것을 목표로 했습니다.
시장 성장 요인
한 예측에 따르면, 온라인으로 연결된 기기의 수는 2025년까지 300억을 초과한다고 합니다. IoT 분야는 이미 크고 빠르게 확대되고 있습니다. 유엔무역개발회의는 2030년까지 전 세계에서 2020년 1조 6,000억 달러에서 12조 6,000억 달러로 증가할 것으로 예측했습니다.
또한 하드웨어와 소프트웨어의 발전으로 엣지에서 AI 모델의 효율성이 크게 향상되었습니다. 엣지 디바이스에는 현재 AI 워크로드를 효율적으로 처리하도록 설계된 GPU 및 TPU와 같은 전용 프로세서가 탑재되어 있습니다. 따라서 AI와 머신러닝의 발전으로 엣지 컴퓨팅 기능이 크게 향상되었습니다.
시장 성장 억제요인
엣지 컴퓨팅 시스템의 도입에는 많은 양의 선행 투자가 필요하며 특히 소규모 조직의 경우 큰 장벽이 될 수 있습니다. 엣지 컴퓨팅의 하드웨어 구성 요소에는 복잡한 AI 작업을 처리할 수 있는 고급 엣지 장치 구매가 포함됩니다. 이 고성능 프로세서는 고액이며 전반적인 비용을 증가시킵니다. 따라서 필요한 인프라 구축과 관련된 초기 비용의 높이는 시장에 큰 과제가 됩니다.
시장의 주요 기업은 시장에서 경쟁력을 유지하기 위해 다양한 혁신적인 제품으로 경쟁하고 있습니다. 위의 그림은 시장의 주요 기업 중 일부가 공유하는 수익의 비율을 보여줍니다. 시장의 주요 기업은 다양한 산업 수요에 부응하기 위해 다양한 전략을 채택하고 있습니다. 시장의 주요 개발 전략은 파트너십과 협업입니다.
구성 요소 전망
구성 요소별로 시장은 하드웨어, 소프트웨어 및 서비스로 나뉩니다. 하드웨어 부문은 2023년 시장에서 73%의 수익 점유율을 획득했습니다. 센서, 프로세서, 게이트웨이와 같은 고급 엣지 디바이스에 대한 수요가 증가함에 따라 이러한 이점을 추진하는 주요 요인입니다.
조직 규모의 전망
조직 규모별로 시장은 대기업과 중소기업으로 분류됩니다. 중소기업 부문은 2023년 시장에서 36%의 수익 점유율을 기록했습니다. 중소기업은 비용 효율성, 확장성 및 성능 향상 측면에서 엣지 컴퓨팅의 장점을 점점 더 잘 알고 있습니다.
The Global AI Edge Computing Market size is expected to reach $64.8 billion by 2031, rising at a market growth of 20.9% CAGR during the forecast period.
Video analytics involves using AI to analyze video feeds in real-time, extracting valuable insights, and enabling automated responses. Edge computing enhances video analytics by processing data close to the source, reducing latency and bandwidth usage. This is particularly important for applications such as security and surveillance, where real-time analysis of video feeds is crucial for identifying potential threats and ensuring public safety. Retailers also use video analytics to understand customer behavior and optimize store layouts, while transportation systems leverage it for traffic management and incident detection. Thus, the Video analytics segment generates 12% revenue share in the market 2023.
The major strategies followed by the market participants are Partnership as the key developmental strategy to keep pace with the changing demands of end users. For instance, In June 2024, In April, 2023, Microsoft Corporation partnered with Epic, an AI services provider, to integrate Azure OpenAI with Epic's EHR software, enhancing productivity, patient care, and financial integrity in healthcare. This collaboration addresses healthcare's financial challenges and emphasizes responsible AI development. Additionally, HP, Inc. teamed up with NVIDIA, a global technology company, to launch NVIDIA AI Computing by HPE, featuring HPE Private Cloud AI, which integrates NVIDIA's AI computing stack with HPE's infrastructure. This solution would provide a scalable, energy-efficient path for generative AI deployment, supported by global system integrators and advanced infrastructure.
Based on the Analysis presented in the KBV Cardinal matrix; Cisco Systems, Inc. is the forerunner in the AI Edge Computing Market. Companies such as Amazon Web Services, Inc., Cisco Systems, Inc., IBM Corporation are some of the key innovators in AI Edge Computing Market. In September, 2022, IBM Corporation teamed up with Airtel, an Indian telecom company. The collaboration aimed to deploy Airtel's edge computing platform in India, utilizing IBM Cloud Satellite and Red Hat OpenShift.
Market Growth Factors
According to some projections, online-connected devices will surpass 30 billion by 2025. The IoT sector is already large and is expanding at a fast pace. The United Nations Conference on Trade and Development projects that by 2030, it will facilitate an increase from $1.6 trillion in 2020 to $12.6 trillion worldwide.
Additionally, the efficiency of AI models at the edge has improved significantly due to advancements in hardware and software. Edge devices are now equipped with specialized processors, such as GPUs and TPUs, designed to handle AI workloads efficiently. Thus, the advancements in AI and machine learning have significantly enhanced the capabilities of edge computing.
Market Restraining Factors
Deploying edge computing systems requires considerable upfront capital expenditure, which can be a significant barrier, especially for smaller organizations. The hardware component of edge computing involves purchasing advanced edge devices capable of handling complex AI tasks. These high-performance processors have a hefty price tag, adding to the overall cost. Hence, the high initial costs associated with deploying the necessary infrastructure pose a substantial challenge for the market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.
Component Outlook
Based on component, the market is divided into hardware, software, and services. The hardware segment garnered 73% revenue share in the market in 2023. The growing demand for sophisticated edge devices, including sensors, processors, and gateways, is the primary factor driving this dominance.
Organization Size Outlook
On the basis of organization size, the market is classified into large enterprises and small & medium enterprises. The small & medium enterprises segment recorded 36% revenue share in the market in 2023. SMEs increasingly recognize the benefits of edge computing in terms of cost efficiency, scalability, and enhanced performance.
Application Outlook
By application, the market is divided into IIoT, remote monitoring, content delivery, video analytics, AR & VR, and others. The AR & VR segment garnered 24% revenue share in the market in 2023. The integration of edge computing with AR and VR technologies enhances these applications' performance and user experience by providing low latency and high-speed data processing.
Vertical Outlook
Based on vertical, the market is segmented into automotive, healthcare, chemicals, oil & gas, manufacturing & robotics, public infrastructure, transportation & logistics, and others. The manufacturing & robotics segment acquired 24% revenue share in the market in 2023. One of the fundamental reasons for this is the widespread implementation of edge computing in manufacturing environments, which aims to enhance automation, predictive maintenance, quality control, and operational efficiency.
By Regional Analysis
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The Europe segment acquired 28% revenue share in the market in 2023. Europe has been at the forefront of adopting cutting-edge technologies to boost its industrial and economic growth.
Market Competition and Attributes
The AI Edge Computing market is highly competitive with key players focusing on innovation and scalability. Attributes defining this market include robust computing capabilities at the edge, real-time data processing, low latency, and enhanced privacy and security features. Companies are leveraging AI algorithms to optimize edge devices' performance across industries like healthcare, manufacturing, and automotive. The market's growth is driven by increasing demand for decentralized AI solutions that can handle data locally while reducing dependence on cloud resources.
Recent Strategies Deployed in the Market
In 2024, April, Vapor IO came into partnership with VAST Data, a technology company, to enhance AI deployments with Vapor IO's Zero Gap AI and the VAST Data Platform. This partnership provides an adaptable edge-to-core AI fabric, enabling enterprises to optimize their AI systems for various priorities, including cost, latency, accuracy, and resiliency.
In February, 2024, Nokia Corporation extended its partnership with Dell Technologies, an American technology company. The two companies aimed at providing private wireless connectivity solutions by integrating Nokia Digital Automation Cloud (NDAC) private wireless solution with Dell's private wireless platform.
In January, 2024, IBM Corporation partnered with American Tower, a wireless infrastructure services provider, to deploy a hybrid, multi-cloud computing platform at the edge. This partnership would enhance enterprise flexibility by leveraging American Tower's infrastructure with IBM's hybrid cloud capabilities.
In July, 2023, HP, Inc. teamed up with VMware, a global cybersecurity company, to introduce new AI inferencing solutions with HPE ProLiant Gen11 servers, optimized for AI workloads. the solutions feature VMware Private AI for secure, efficient AI model deployment. Key benefits of the solutions include privacy, enhanced AI performance, and comprehensive support for various AI use cases.
