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, 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.
Additionally, In April 2024, 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.
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.
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.
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.
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, 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.
Additionally, In April 2024, 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.
Cardinal Matrix - Market Competition Analysis
Based on the Analysis presented in the Cardinal matrix; Cisco Systems, Inc. is the forerunner in the AI Edge Computing Market. Companies such as IBM Corporation, HP, Inc., Nokia Corporation are some of the key innovators in AI Edge Computing Market. In May, 2024, Cisco Systems, Inc. partnered with Lenovo, a technology company, to deliver integrated infrastructure and networking solutions to accelerate digital transformation. The collaboration combines Lenovo's AI-enabled portfolio with Cisco's networking ecosystem, providing turnkey solutions that enhance AI capabilities, streamline operations, and improve business outcomes with advanced security and performance from edge to cloud.
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.
Driving and Restraining Factors
Drivers- Rising adoption of IoT devices
- Advancements in AI and machine learning
- Rising demand for scalable and flexible deployment of AI applications
- significant initial investment in edge computing equipment
- Considerable security and privacy concerns
- Support for remote and rural areas
- Rapid deployment of 5G networks
- Lack of standardized protocols and frameworks
- Challenges associated with data management and storage
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.
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.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.
List of Key Companies Profiled
- Comsovereign Holding Corp.
- Nokia Corporation
- Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
- Johnson Controls International PLC
- Vapor IO, Inc.
- IBM Corporation
- Rigado Inc.
- Cisco Systems, Inc.
- ClearBlade Inc.
- HP, Inc.
Market Report Segmentation
By Organization Size- Large Enterprises
- Small & Medium Enterprises (SME)
- Hardware
- Software
- Services
- IIOT (Industrial Internet of Things)
- Remote Monitoring
- Content Delivery
- Video Analytics
- AR & VR (Augmented Reality and Virtual Reality)
- Manufacturing
- Healthcare
- Automotive
- Chemicals
- Oil & Gas
- Public Infrastructure and
- Transportation & Logistics
- Others
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Global AI Edge Computing Market by Organization Size
Chapter 6. Global AI Edge Computing Market by Component
Chapter 7. Global AI Edge Computing Market by Application
Chapter 8. Global AI Edge Computing Market by Vertical
Chapter 9. Global AI Edge Computing Market by Region
Chapter 10. Company Profiles
Companies Mentioned
- Comsovereign Holding Corp.
- Nokia Corporation
- Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
- Johnson Controls International PLC
- Vapor IO, Inc.
- IBM Corporation
- Rigado Inc.
- Cisco Systems, Inc.
- ClearBlade Inc.
- Hewlett Packard Enterprise Company
- Oracle Corporation
- Microsoft Corporation
- Amazon Web Services, Inc.
Methodology
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