The global edge computing market size is projected to reach USD 155.90 billion by 2030 and register a CAGR of 38.9% from 2022 to 2030. The integration of artificial intelligence (AI) into the edge environment is expected to propel market expansion. An edge AI system can assist businesses in making quick decisions in real-time.
Key industry insights & findings:
- The COVID-19 outbreak has bolstered the use of edge computing and data centers as more and more businesses are prioritizing the development of communications infrastructure.
- Based on component, the hardware segment captured a significant revenue share in 2021 due to the increasing number of IIoT and IoT devices. Edge cloud servers must have powerful routers that are flexible and able to handle a volume of incoming traffic while maintaining low latency.
- The Industrial Internet of Things (IIoT) applications segment dominated the global edge computing market in 2021 owing to the rampant digitization of services and the emergence of industry 4.0.
- Based on industry vertical, the energy and utility segment accounted for a revenue share of over 15% in 2021 as a result of the rising adoption of smart grids that mandates device edge infrastructure.
- Smart grids are being installed to aid alternative renewable power generation from sources such as wind and solar. Smart grids enhance operational efficiencies, including incorporation with smart appliances, real-time consumption control, and microgrids to support power generation from dispersed renewable sources.
- Geographically, Asia Pacific accounted for a significant market share due to the widespread development of connected device ecosystems in countries such as India and China.
Edge computing market growth & trends
Moreover, the necessity to reduce privacy breaches related to the transmission of massive volumes of data, as well as latency and bandwidth limitations that restrict an organization’s data transmission capabilities, is expected to drive market growth in the forthcoming years.
Precision monitoring and machinery control are a few use cases that employ AI on the edge. A fast-moving production line needs the minimum amount of latency possible, which can be achieved by using edge computing. It can be very beneficial to move data processing close to the manufacturing facility because it can be accomplished with AI. Many different endpoint devices, including sensors, cameras, smartphones, and other Internet of Things (IoT) devices, can make use of artificial intelligence-based edge devices.
Edge computing is currently in its early phases of development. Its operating and deployment models are still in their nascent stages; nonetheless, edge computing is anticipated to present considerable growth opportunities for new entrants in the coming years. As communications infrastructure continues to be developed, demand for edge computing will increase in the years following the COVID-19 pandemic. Working from home is gradually replacing traditional office work and the telecommunications industry is making strides in the development of video conferencing software.
Prominent platforms such as Zoom and Microsoft Teams are creating new solutions to cater to the growing demand. For example, in December 2020, Amazon Web Services and SK Telecom collaborated to launch 5G MEC-based edge cloud services. Energy & utility, healthcare, agriculture, transportation & logistics, retail, telecommunication, and real estate industries are rapidly adopting edge computing as it improves application performance and results, lowers operational costs, and eliminates centralized storage and redundant transmission expenditures.