AI Edge Computing Market
According to the report, the global AI edge computing industry generated $9.09 billion in 2020, and is anticipated to generate $59.63 billion by 2030, witnessing a CAGR of 21.2% from 2021 to 2030.
AI Edge Computing combines artificial intelligence (AI) with edge computing to process data locally on devices or near the data source rather than relying on centralized cloud servers. This approach enables real-time data processing, reduces latency, conserves bandwidth, and improves data privacy by keeping sensitive information closer to its origin. AI edge computing is essential for applications that require immediate insights, like autonomous vehicles, smart cities, and IoT devices, where quick response times are critical.
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The global AI edge computing market is influenced by several factors such as ability of the AI edge to overcome cloud computing challenges, rise in demand for real-time operations, and the proliferation of edge AI-enabled devices. In addition, several lucrative benefits offered by AI edge computing such as faster computing and insights and better data security fuel the growth of this market.
However, need for high investment and shortage of skilled IT professionals are projected to hamper growth of the market. On the other hand, advent of the 5G Network connectivity and emerging applications of AI edge computing are estimated to be opportunistic for the growth of the market.
Asia-Pacific is expected to observe highest growth rate during the forecast period, due to the proliferation of connected systems fueled by ongoing trend of smart offices and homes in the region coupled with the government-driven infrastructural projects. The data generated by edge devices in different industry verticals across the region and increased consumer spending on smart solutions across the countries such as China, Australia, Japan, and India, fuel the growth of the market. In addition to this, emerging adoption of innovative technologies as well as ongoing digital transformation initiatives in Asian countries, such as Australia, Japan, China, and India, to create the increased demand for improved customer experiences fueling the demand for AI edge computing.
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Covid-19 Scenario
1. The outbreak of the Covid-19 pandemic impacted the the global AI edge computing market positively.
2. The implementation of global lockdown has constrained organizations to move toward digitalization for the arrangement of work from home offices to their employee, which in turn, boosted the demand for AI edge computing.
3. In addition, edge computing is ending up to be a life-saving technology for the medical care industry, due to different IoT medical applications.
Based on application, the IIoT segment accounted for the largest share in 2020, contributing to nearly one-third of the global AI edge computing market, and is projected to maintain its lead position during the forecast period, owing to more data production by IIoT applications. However, the content delivery segment is expected to portray the largest CAGR of 22.2% from 2021 to 2030.
Based on component, the hardware segment held the highest market share in 2020, accounting for nearly three-fourths of the global AI edge computing market, and is estimated to maintain its leadership status throughout the forecast period. This is due to rise in applications of AI edge computing hardware or physical components such as processors, servers, switches, and routers. Moreover, the services segment is projected to manifest the highest CAGR of 25.7% from 2021 to 2030.
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Based on region, North America held the highest market share in terms of revenue in 2020, accounting for more than two-fifths of the global AI edge computing industry. This is attributed to several factors such as rise in need for faster processing devices coupled with the huge government funding on innovative technologies, increased number of IoT devices, and a strong technical base. However, the Asia-Pacific region is expected to witness the fastest CAGR of 24.6% from 2021 to 2030. This is due to the proliferation of connected systems fueled by ongoing trend of smart offices and homes in the region along with the government-driven infrastructural projects.
Some of the key AI edge computing industry players profiled in the report include Cisco Systems, Inc., International Business Machine Corporation, Clearblade, Inc., Foghorn Systems, Hewlett Packard Enterprise Development LP, Huawei Technologies Co. Ltd., Nokia, Rigado Llc, Saguna Networks Ltd., and Vapor IO. This study includes market trends, AI edge computing market analysis, and future estimations to determine the imminent investment pockets.
Key Industry Developments:
1. In August 2020, NVIDIA introduced its EGX platform in August 2020, designed to enable real-time AI at the edge. This platform allows organizations to deploy AI applications across various edge devices, enhancing data processing and analysis capabilities.
2. In February 2021, Microsoft announced new features for Azure IoT Edge, integrating AI capabilities that allow users to run machine learning models on edge devices. This development enhances the functionality of IoT devices, enabling faster decision-making processes.
3. In December 2020: AWS launched Wavelength in December 2020, allowing developers to build applications that deliver ultra-low latency by embedding AWS services at the edge of telecom networks. This solution targets industries like gaming, autonomous vehicles, and smart factories.
4. In April 2023, Intel unveiled new AI edge solutions aimed at optimizing performance for various applications, including smart cities and industrial IoT.
5. These solutions focus on providing advanced analytics and AI capabilities directly at the edge, reducing the need for data transmission to centralized data centers.
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