Edge Computing Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

Market Overview

The edge computing market was valued at USD 5242.90 million in 2021, and it is expected to register a CAGR of 44.90% over the forecast period.

• The increasing adoption of IoT is augmented by 5G operations, primarily driving the growth of the market studied. A significant share of industrial IoT service providers and aggregators are offering 5G capable network offerings that are expected to adopt edge computing over the coming years for handling the sheer amount of data.
• As enterprises are embracing these new technologies, the need to analyze important data in near real-time has become more critical to benefit from the adopted technologies. The need became vital across many industries, including manufacturing, healthcare, telecommunications, and finance. Moreover, the explosion of data (according to SharesPost, more than 150 zettabytes (150 trillion gigabytes) of data is estimated to be generated by 2025) has been pushing the need further and making factors like network latency very critical.
• Furthermore, the development of processing-intensive applications involving artificial intelligence, IoT, and machine learning (ML), which work on larger data sets and perform massive algorithmic parallelism on models (to improve business operations), has promoted the demand for localized computing, data storage, and network resources. Therefore, along with IoT and IIoT, the adoption of AI and ML is also driving the growth of edge computing.
• Edge computing is being led by initiatives like OpenFog Consortium, an organization headed by vendors in the market studied, including Cisco, Intel, Microsoft, and Dell EMC, as well as academic institutions like Princeton University and Purdue University. The consortium aims at developing reference architectures for fog and edge computing deployments.
• Edge computing is expected to play a vital role in the widespread adoption and working of technologies, such as AR/VR, autonomous vehicles, IoT, next-gen CDNs, next-gen cloud, and streaming games. Edge computing is vital in operating an autonomous vehicle network in the future, influencing vendors to form a partnership to cater to the growing needs of these industries.
• The COVID-19 pandemic positively impacted global edge computing. According to the IBM Institute for Business Value, a study of 1,500 executives globally found that a growing number of leaders already see the value of edge computing, with 91% of respondents expecting their organization to implement edge computing within five years.

Scope of the Report

Edge computing refers to the distributed computing paradigm, mainly used to bring computing and data storage closer to the location to improve response time. The analysis tools used across industries are beginning to drive new levels of performance and productivity. Therefore, the distributed computing paradigm, edge computing, is gaining traction. The market studied is segmented into different components of edge computing, i.e., hardware, software, and services. It also covers the uses and applications of the technology across various end-user segments, such as the financial and banking industry, retail, healthcare, industrial, and energy and utilities across multiple geographies. Furthermore, the study also covers the impact of COVID-19 on the market.

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Key Market Trends

Industrial Sector to Account for the Largest Market Share

• One of the most prominent edge computing use cases is in the industrial manufacturing sector, where new technologies may potentially lead to massive productivity gains. Edge computing facilitates localized processing, which could help reduce latency issues and enables smart and intelligent manufacturing through predictive analytics. With the increase in IoT deployment, manufacturing companies have been rapidly adopting edge computing to enhance interoperability among IoT devices, reduce unforeseen downtime issues, and improve production efficiency.
• The edge computing framework significantly reduces the complexity of interconnected systems, making it easier to collect and analyze data in real time. It may also allow devices to gather critical information in remote sites where network connectivity is inconsistent or not cost-effective. Edge devices can be IoT-enabled machines, gateways, sensors, or single-board computers.
• Data may be gathered and analyzed locally, with only critical information being transmitted back to the central network when connections are possible. Combining edge computing and industrial IoT devices may make it easier to streamline industrial processes, optimize supply chains, and create the “smart” factory.
• Edge computing forms the framework of the machine learning (ML) network that makes automatic manufacturing driven by robotics possible. According to IFR, the operational stock of industrial robots was around 3 million units in 2020. Considering an increase in the use of artificial intelligence, automation software is expected to provide a way for companies to produce more products without increasing production costs or wages.
• Robots gathering and transmitting data through an edge network using IoT devices may identify irregularities and eliminate inefficiencies much more quickly than they could through the cloud-based architecture. The distributed nature of such a system also makes it much more robust, ensuring better levels of uptime productivity.
• Industrial manufacturing is witnessing a revolution, owing to the potential of edge computing. Combined with a new generation of smart IoT edge devices, edge computing applications would completely transform manufacturing in the coming decades to drive better efficiency and productivity while also controlling costs. This is expected to impact the market’s growth over the forecast period positively.

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