The latest report by IMARC Group, titled “Edge Computing Market Report by Component (Hardware, Software, Services), Organization Size (Small and Medium-sized Enterprises (SMEs), Large Enterprises), Vertical (Manufacturing, Energy and Utilities, Government and Defense, BFSI, Telecommunications, Media and Entertainment, Retail and Consumer Goods, Transportation and Logistics, Healthcare and Life Sciences, and Others), and Region 2024-2032“, The global edge computing market size reached US$ 14.7 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 90.3 Billion by 2032, exhibiting a growth rate (CAGR) of 24.35% during 2024-2032.

Factors Affecting the Growth of the Edge Computing Industry:

• Increasing Internet of Things (IoT) Adoption:

The widespread adoption of IoT devices across industries has led to a surge in data generation, creating a need for efficient data processing solutions. It is emerging as a vital strategy to address this challenge by allowing data to be processed and analyzed closer to its source, typically at the edge of the network. Moreover, edge computing reduces latency and minimizes bandwidth usage by eliminating the need to transmit large volumes of data to centralized cloud servers for analysis by decentralizing data processing. This proximity-based approach enhances real-time decision-making capabilities, enabling faster responses to events and optimizing network performance. Additionally, edge computing architectures are scalable and adaptable, making them well-suited for dynamic IoT environments where data volumes and processing requirements can vary significantly. As IoT adoption continues to grow, edge computing is essential in supporting the scalability and efficiency of IoT ecosystems across diverse industries.

• Growing Data Privacy and Security Concerns:

The proliferation of digital data and interconnected devices is increasing the concerns about data privacy and security. In addition, edge computing addresses these concerns by enabling data processing to occur locally, closer to the source of data generation. Edge computing reduces the need to transmit sensitive information over networks to centralized servers, by decentralizing data processing and storage, thereby minimizing the risk of data breaches and unauthorized access. This localized approach to data management enhances data privacy by giving organizations greater control over their data and reducing exposure to potential security vulnerabilities associated with transmitting data over long distances. As data privacy and security concerns continue to escalate, the adoption of edge computing offers a strategic solution to safeguard sensitive information and mitigate risks associated with centralized data processing architectures.

• Rise of 5G Networks:

The deployment of 5G networks represents a significant advancement in telecommunications technology, offering faster data transmission rates and lower latency compared to previous generations of mobile networks. This increased speed and responsiveness make 5G networks well-suited for supporting edge computing deployments, particularly for applications requiring high-speed data processing and real-time response capabilities. Additionally, edge computing platforms can deliver enhanced performance and reliability, enabling critical applications such as autonomous vehicles, augmented reality (AR), and industrial automation by leveraging the low-latency characteristics of 5G networks. Furthermore, 5G networks extend the reach of edge computing to a wider range of environments, including urban areas, remote locations, and industrial facilities, where high-speed connectivity is essential for supporting emerging IoT applications and services. As 5G networks continue to expand globally, their synergistic relationship with edge computing will drive innovation and enable the development of new transformative applications across various industries.

For an in-depth analysis, you can refer sample copy of the report: https://www.imarcgroup.com/edge-computing-market/requestsample

Competitive Landscape with Key Player:

• ABB Ltd.
• Amazon Web Services (AWS), Inc.
• Cisco Systems Inc.
• Digi International Inc.
• General Electric Company
• Hewlett Packard Enterprise Development LP
• Huawei Technologies Co. Ltd.
• IBM Corporation
• Intel Corporation
• Microsoft Corporation
• SAP SE
• Siemens AG

The report has segmented the market into the following categories:

Breakup by Component: 

• Hardware
• Software
• Services

Hardware represents the largest segment, due to the foundational role of physical infrastructure in facilitating data processing at the edge, encompassing devices, sensors, and servers essential for real-time computing.

Breakup by Organization Size:

• Small and Medium-sized Enterprises (SMEs)
• Large Enterprises

Large enterprises dominate the market growth, as they possess the resources and scale to invest significantly in edge computing infrastructure and capitalize on its potential for enhancing operational efficiency and innovation.

Breakup by Vertical:

• Manufacturing
• Energy and Utilities
• Government and Defense
• BFSI
• Telecommunications
• Media and Entertainment
• Retail and Consumer Goods
• Transportation and Logistics
• Healthcare and Life Sciences
• Others

Energy and utilities hold the largest market share, due to optimizing resource management, enhancing grid resilience, and integrating renewable energy sources, which necessitate robust edge computing capabilities.

Market Breakup by Region:

• North America (United States, Canada)
• Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, Others)
• Europe (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
• Latin America (Brazil, Mexico, Others)
• Middle East and Africa

North America’s dominance in the edge computing market is attributed to the early adoption, technological innovation, and a mature ecosystem fostering collaboration between industry players and favorable regulatory environments.

Global Edge Computing Market Trends:

At present, AI and machine learning (ML) are becoming more prevalent in various applications. There is a growing need to deploy AI models at the edge for real-time decision-making. Edge computing facilitates running AI algorithms locally on devices, enabling faster response times and preserving privacy by processing data locally. Moreover, the development of specialized hardware accelerators and edge AI chipsets is driving the efficiency and performance of edge computing devices. These chipsets are designed to handle AI workloads efficiently, enabling edge devices to process complex tasks locally without relying on cloud resources. Furthermore, edge computing solutions are being tailored to specific industries, such as manufacturing, healthcare, transportation, and retail. Each industry has unique requirements and use cases for edge computing, leading to the development of vertical-specific solutions and partnerships.

Note: If you need specific information that is not currently within the scope of the report, we will provide it to you as a part of the customization.

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