Edge Computing Market worth $111.3 billion by 2028, growing at a CAGR of 15.7%: Report by MarketsandMarkets™

Chicago, Aug. 10, 2023 (GLOBE NEWSWIRE) -- The global Edge Computing Market size is expected to grow from 53.6 billion in 2023 to USD 111.3 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 15.7% during the forecast period, according to a new report by MarketsandMarkets™. Edge computing solutions and services are gaining higher acceptance globally by large enterprises, mid-sized enterprises, and small enterprises owing to various benefits, such as growing adoption of automation, autonomous vehicles, connected car smart infrastructure, IoT benefits, and digitalization. The presence of several major edge computing providers along with multiple emerging startups/SMEs has made the market competitive, diversified, distinguished and catering to client customizations precisely. Numerous emerging players are providing niche, specific, and differentiated tailored offerings, catering to the target customers worldwide, those enterprises who demand customized solutions in order to carry out their operations.

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269 - Tables
58 - Figures
285 - Pages

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Scope of the Report

The IIoT (Industrial Internet of Things) application segment plays a crucial role in the edge computing market, as it represents a significant use case and driving force behind the adoption of edge computing technologies in industrial environments. IIoT refers to the integration of sensors, devices, and machinery within industrial settings to gather real-time data and enable smarter decision-making, automation, and optimization of industrial processes. Edge computing is particularly well-suited for IIoT applications due to its ability to process and analyze data locally, closer to the point of generation. This eliminates the need to transmit massive amounts of data to centralized cloud servers, reducing latency and improving response times for critical industrial operations.

By deploying edge computing in IIoT scenarios, industrial organizations can achieve faster insights and real-time analytics, enabling them to optimize production, enhance operational efficiency, and prevent costly downtime. Edge computing also offers the advantage of reliable connectivity in remote or harsh environments where maintaining continuous communication with centralized systems may be challenging. Furthermore, edge computing facilitates edge-based machine learning and AI algorithms, enabling intelligent decision-making at the edge. This capability empowers industrial systems to respond dynamically to changing conditions, perform predictive maintenance, and drive autonomous operations. Overall, the IIoT application segment is a key driver of the edge computing market, as it leverages edge technologies to transform industrial operations, enhance productivity, and unlock new possibilities for automation and optimization in various sectors, including manufacturing, energy, transportation, and agriculture. The combination of IIoT and edge computing offers tremendous potential for industrial organizations seeking to embrace digital transformation and achieve competitive advantages in today's interconnected world.    

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The software component of edge computing is gaining popularity in the marketing landscape of edge computing market during the forecast period, thereby recording the highest CAGR. The software segment plays a vital role in the edge computing market by providing the necessary tools, platforms, and applications to enable the efficient management, orchestration, and execution of edge computing environments. Software solutions tailored for edge computing offer a range of functionalities such as data ingestion, processing, analytics, security, and device management. These software offerings enable organizations to deploy, monitor, and control edge devices, as well as process and analyze data at the network edge. They also facilitate seamless integration with cloud services, enabling hybrid architectures that leverage both edge and centralized computing resources. Software solutions in the edge computing market empower businesses to harness the full potential of edge infrastructure, unlock actionable insights from real-time data, optimize performance, and drive intelligent decision-making at the edge of the network. 

Telecommunication vertical is predicted to showcase aggressive and upward growing curve during the forecast period. Edge computing streamlines the traffic flow and facilitates real-time localized data analysis by providing high-bandwidth networks. Since security is a big concern with many IoT devices, edge gateways ensure higher protection. The telecom industry has also responded with 5G technology, where edge computing has a huge application, as 5G technology is imperative to speed, security, and scale. Many companies are testing the benefits of edge computing in 5G networks. For instance, Ericsson and Telstra collaborated to explore the use cases of 5G edge computing in the financial sector. Edge computing can help telecom providers boost network reach, a major reason for its adoption. According to a survey, ~87% of Tier-1 operators in North America, Western Europe, and Asia Pacific are planning or have edge computing in the deployment phase. The benefits of edge computing are numerous, and with the growth of 5G, the demand for edge computing is expected to grow enormously.

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Top Trends in Global Edge Computing Market:

• The rising usage of Internet of Things (IoT) devices was fuelling demand for edge computing. Edge computing allows IoT devices to process and analyse huge volumes of data closer to the source, lowering latency and boosting real-time decision-making.
• The deployment of 5G networks was expected to drive the use of edge computing. Edge computing is a crucial component of the 5G ecosystem due to 5G's high bandwidth and low latency capabilities, which are well-suited for applications that demand real-time processing and analysis.
• Edge computing capabilities were being integrated with artificial intelligence (AI) and machine learning (ML), enabling more intelligent and autonomous edge devices. This trend was particularly relevant for applications such as driverless vehicles, industrial automation, and remote monitoring.
• Edge computing enables organisations to process data closer to its source, eliminating the need to transport all data to centralised cloud servers. This tendency contributes to the resolution of privacy problems, compliance issues, and bandwidth constraints.
• With data being processed and stored at the edge, security has become a top priority. A primary priority area was ensuring the security of edge devices, data, and device connectivity.
• Many organisations are implementing hybrid cloud-edge designs, in which data processing and storage take place both in the cloud and at the edge. This method provides flexibility, scalability, and efficient resource utilisation.
• Edge computing enables real-time data analytics at the source, allowing organisations to obtain insights and make choices without relying on centralised data centres.
• Edge computing was being investigated for specialised use cases in industries such as manufacturing, healthcare, transportation, and agriculture. The capacity of edge computing to provide real-time insights and decision-making proved especially helpful in these industries.

Key Industry Development:

• A variety of technological organizations, including cloud providers, hardware manufacturers, and software developers, were forging partnerships and collaborations to produce comprehensive edge computing solutions. These collaborations seek to pool expertise and resources in order to provide more integrated and seamless edge solutions.
• There was a surge in the development and use of specialized AI chipsets designed for edge computing applications. These chipsets were designed to handle AI tasks at the edge, allowing for faster and more efficient inference and decision-making.
• The number of open source projects and activities focusing on edge computing was increasing. These projects sought to offer standardized frameworks, tools, and platforms that developers and organizations could use to more quickly design and deploy edge applications.
• Businesses were concentrating on building data management solutions that were specifically designed for edge environments. These technologies attempted to address edge data storage, processing, and analytics concerns while maintaining data integrity and security.
• As data is processed and stored at the edge, the requirement for comprehensive edge security solutions has grown. Companies were establishing security standards and methods to protect edge devices, data, and communication channels.
• Platforms for managing and optimising edge computing resources were being created. These platforms sought to make it easier to install, monitor, and scale edge applications in distributed systems.
• Industries such as manufacturing, healthcare, energy, and retail were actively investigating and implementing edge computing for specialised use cases. Tailoring cutting-edge solutions to the specific needs of each industry enabled more efficient and productive operations.

• Advances in edge analytics allowed organizations to analyse data locally and extract real-time insights for fast decision-making. This trend was especially essential for applications that required low latency and quick feedback.

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