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The AI edge computing market share is expected to increase to USD 14.28 billion from 2021 to 2026, and the market's growth momentum will accelerate at a CAGR of 20.27%.
The report extensively covers AI edge computing market segmentations by the following:
The AI edge computing market report offers information on several market vendors, including Adapdix, Alef Edge Inc., Amazon.com Inc., Azion Technologies Inc., Cisco Systems Inc., ClearBlade Inc., Hewlett Packard Enterprise Co., Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., Johnson Controls International Plc, Microsoft Corp., Nutanix Inc., Rigado Inc., SAGUNA Network LTD., SixSq SA, Synaptics Inc., Tact.ai Technologies Inc., Transcend Information Inc., and Vapor IO Inc. among others.
This AI edge computing market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches.
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The proliferation of edge AI devices is notably driving the AI edge computing market growth, although factors such as security concerns related to edge AI devices may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the AI edge computing industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.
Key AI Edge Computing Market Driver
The proliferation of edge AI devices is one of the key drivers fueling the artificial intelligence (AI) edge computing market growth. IoT and sensor technology generate large amounts of data that needs to be analyzed. For instance, Airbus A350 aircraft are embedded with more than 50,000 sensors that generate 2.5 terabytes of data per day. Real-time analysis of the data collected from these sensors can improve flight safety. Thus, as the volume of IoT devices grows, new techniques for data analysis and processing will be needed. Through edge AI computing, operational decisions can be automated as sensor data can be analyzed locally and in real-time. Thus, the proliferation of edge AI devices will augment the growth of the global AI edge computing market during the forecast period.
Key AI Edge Computing Market Trend
The growing use of AI edge computing to get real-time analytics is one of the key artificial intelligence (AI) edge computing trends supporting market growth. Self-driven cars are equipped with numerous sensors that continuously generate massive amounts of data regarding the operation of the car. These sensors measure the speed of tire rotation and the position of the vehicle. Autonomous vehicle manufacturers equip their models with these sensors so that necessary decisions regarding braking and steering can be made automatically based on the data collected from these sensors. For instance, Porsche Engineering, a subsidiary of Dr. Ing. h.c. F. Porsche AG has embedded its models with compact computers with graphics processing units (GPUs) manufactured by Nvidia Corp. The computing platform uses AI to calculate more precise positions from global positioning system (GPS) data. Such uses of AI may propel the AI edge computing market trends supporting market growth during the forecast period.
Key AI Edge Computing Market Challenge
Security concerns related to edge AI devices is one of the key factors challenging the AI edge computing market growth. Edge AI devices can be the source of a wide range of cybersecurity attacks such as distributed denial-of-service (DDoS) attacks, Man-in-the-Middle (MiTM) attacks, data breaches through hacking of devices, and others. These attacks deter the end-users from using IoT devices such as smart speakers, drones, and surveillance cameras. For instance, surveillance cameras could serve as a means for an attacker to hack into the IT infrastructure of end-users. Often surveillance cameras are mass-produced and identical, which allows the attacker to infiltrate them. Such threats may challenge the AI edge computing market growth during the forecast period.
This AI edge computing market analysis report also provides detailed information on other upcoming trends and challenges that will have a far-reaching effect on the market growth. The actionable insights on the trends and challenges will help companies evaluate and develop growth strategies for 2022-2026.
The report analyzes the market's competitive landscape and offers information on several market vendors, including:
This statistical study of the artificial intelligence (AI) edge computing market encompasses successful business strategies deployed by the key vendors. The AI edge computing market is fragmented and the vendors are deploying growth strategies such as integrating more optimized technology to compete in the market.
To make the most of the opportunities and recover from post COVID-19 impact, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.
The AI edge computing market forecast report offers in-depth insights into key vendor profiles. The profiles include information on the production, sustainability, and prospects of the leading companies.
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Five Forces Analysis
5 Market Segmentation by Type
6 Customer Landscape
7 Geographic Landscape
8 Drivers, Challenges, and Trends
9 Vendor Landscape
10 Vendor Analysis
11 Appendix
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