PUBLISHER: KBV Research | PRODUCT CODE: 1529165
PUBLISHER: KBV Research | PRODUCT CODE: 1529165
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
List of Key Companies Profiled
Global AI Edge Computing Market Report Segmentation
By Organization Size
By Component
By Application
By Vertical
By Geography