Edge AI is a system which processes data generated at the local level by hardware devices using machine learning techniques. It refers to AI algorithms which are put forward locally on hardware devices and use data produced locally. They save the results locally on the devices before forwarding them to the cloud to be processed and stored. One of the major benefits of AI in edge computing is its speed. Integrating smart devices and functionality can detect faults and provide AI at the edge for insights. There is a wide range of AI in edge computing applications which majorly propels the market growth such as facial recognition and real-time traffic reports on smartphones and semi-autonomous vehicles or intelligent devices. Video games, security cameras, robots, smart speakers, drones and wearable health monitoring devices are among the other edge computing AI-enabled devices. The security camera detection procedure will benefit from edge computing AI. Conventional surveillance cameras take images for hours before storing and using them as required. With the edge AI, however, the algorithmic procedures will be performed in real-time in the system itself, enabling the cameras to identify and process suspicious activity in real-time, leading to more efficient and cost-effective services. The ability of autonomous vehicles to process data and images in real-time to detect traffic signs, pedestrians, other cars and roads will increase through Edge AI, improving transportation security. In respect of industrial IoT, Edge AI will decrease costs and increase safety (IIoT). Machine Learning will recompile data in real-time of the complete process, while AI will observe machinery for probable defects or faults in the production chain. However, the privacy and security issues associated to edge AI solutions to restrain the market.

Furthermore, the emergence of the 5G network is combing IT and telecommunications together and creating new possibilities for high-end applications to further minimize the network latency. The 5G network allow developing data centers at edge modules, as well as implementing industry-specific networks supported by virtualization and software-defined networking principles in a single environment. Vital AI applications, such as autonomous vehicles, surgery, industry automation and robotics, demand for ultra-low latency that is less than a round trip delay of 1 millisecond. These low latency rates can be attained by installing new hardware in air interfaces and adoption of edge nodes. The dawn of 5G networks among various applications is projected to increase the volume of data transferred to the data centers, thereby increasing the requirement for intermediary servers or edge networks.

The global AI in Edge Computing Market is segregated on the basis of Offering as Hardware, Solutions and Services. Based on End-User the global AI in Edge Computing Market is segmented in Manufacturing, Healthcare, Transportation, Government, Media and Entertainment, Energy and Utilities, Telecom and IT, Retail and Others.

The global AI in Edge Computing Market report provides geographic analysis covering regions, such as Europe, North America, Asia Pacific, and Rest of The World. The AI in Edge Computing Market for each region is further segmented for major countries including the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan, Brazil, South Africa, and others.

Competitive Analysis

Cisco Systems, Inc., ClearBlade, Inc., FogHorn Systems, Hewlett Packard Enterprise and others are among the major players in the global AI in Edge Computing Market. The companies studied in terms of product strategy and various n several growth and expansion strategies to gain a competitive edge in the market. The major players not only follow value chain integration with business operations in multiple stages of the value chain.

• In May 2020, IBM declared new services and solutions supported by a broad ecosystem of partners to assist enterprises and telecommunications companies propel their transition to edge computing in the 5G era.
• In October 2019, FogHorn Systems declared new features for the Lightning Edge AI platform. The features are tools and improvements for permitting operations technology (OT) professionals. The new drag-and-drop analytic programming abilities and high visualization dashboards allow operations technology staff to extract insights more quickly from real-time data without the requirement of assistance from data science teams.

The global AI in Edge Computing Market has been segmented as below:

AI in Edge Computing Market, By Offering

• Hardware
• Solutions
• Services

AI in Edge Computing Market, By End-User

• Manufacturing
• Healthcare
• Transportation
• Government
• Media and Entertainment
• Energy and Utilities
• Telecom and IT
• Retail
• Others
• AI in Edge Computing Market, By Region
• Europe
• North America
• Asia Pacific
• Rest of The World

AI in Edge Computing Market, By Company

• Cisco Systems, Inc.
• ClearBlade, Inc.
• FogHorn Systems
• Hewlett Packard Enterprise
• Huawei Technologies Co. Ltd.
• IBM Corporation
• Nokia Networks
• Rigado, LLC
• Saguna Networks Ltd.
• Vapor IO

The report covers the below scope:

• Global AI in Edge Computing Market sizes from 2020 to 2026, along with CAGR for 2020-2026
• Market size comparison for 2019 vs 2026, with actual data for 2019, estimates for 2019 and forecast from 2020 to 2026
• Global AI in Edge Computing Market trends, covering comprehensive range of consumer trends & manufacturer trends
• Value chain analysis covering participants from raw material suppliers to the downstream buyer in the global AI in Edge Computing Market
• Major market opportunities and challenges in forecast timeframe to be focused
• Competitive landscape with analysis on competition pattern, portfolio comparisons, development trends and strategic management
• Comprehensive company profiles of the key industry players

The years considered for the study are as follows:

• Base year - 2019
• Estimated year - 2019
• Projected year - 2020
• Forecast period - 2021 to 2026

Report Scope:

The global AI in Edge Computing Market report scope includes detailed study covering underlying factors influencing the industry trends. The report covers analysis on regional and country level market dynamics. The scope also covers competitive overview providing company market shares along with company profiles for major revenue contributing companies. The report scope includes detailed competitive outlook covering market shares and profiles key participants in the global AI in Edge Computing Market share. Major industry players with significant revenue share Cisco Systems, Inc., ClearBlade, Inc., FogHorn Systems, Hewlett Packard Enterprise and others.

Why to Buy this Report:

• Gain detailed insights on the AI in Edge Computing industry trends
• Find complete analysis on the market status
• Identify the AI in Edge Computing Market opportunities and growth segments
• Analyse competitive dynamics by evaluating business segments & product portfolios
• Facilitate strategy planning and industry dynamics to enhance decision making

Target Audience:

• The report targeted towards the existing players in the industry is as follows:
• Market Manufacturers/Service Providers
• Market Wholesale/Traders
• Investment and Financial Institutions

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