Edge AI software enables aggregation, processing, computation, and analysis of data present near or on the edge devices by leveraging AI and IoT technologies. The software helps to process data on edge nodes even in remote and decentralized networks, without cloud connectivity.
Integrating AI with IoT in edge devices helps enterprises to minimize latency, reduce bandwidth, lessen threats, avoid duplication, improve reliability, and maintain compliance. Moreover, edge AI software solutions enable an organization to utilize the computing resources in an optimal manner, minimize the bandwidth required to execute the solution, and lower the latency in particular response time.
Scope of the Report:The amount of IoT devices deployed worldwide is exploding across all industries and cloud computing is overwhelmed with challenges that prevent IoT from scaling. For this reason, the center of data production and computing is transitioning from the cloud to the edge creating the need of IoT devices with a small but power efficient footprint.
The potential of AI at the edge is vast. A report from Tractica estimates that AI edge device shipments will increase from 161.4 million units in 2019 to 2.6 billion units worldwide annually by 2026. The top AI-enabled edge devices, in terms of unit volumes, will include mobile phones, smart speakers, PCs/tablets, head-mounted displays, automotive sensors, drones, consumer and enterprise robots, and security cameras. There will also be more AI incorporated into wearable health sensors, building or facility sensors, and networks of sensors planted around facilities or entire cities. Artificial intelligence (AI)_a rapidly emerging force, is taking computing at the edge to a whole new level, in which insights and analysis are provided on the spot, in real-time. With the IoT now front and center of business and technology strategies, the ability to analyze data streaming through edge computing devices and systems means a significant improvement in visibility and awareness of events across a network.
The global Edge AI Software market is valued at 364.5 million USD in 2020 and is expected to reach 1056.3 million USD by the end of 2026, growing at a CAGR of 23.7% between 2020 and 2026.
The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions.
North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Edge AI Software.
Europe also play important roles in global market, with market size of xx million USD in 2020 and will be xx million USD in 2026, with a CAGR of xx%.
This report studies the Edge AI Software market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Edge AI Software market by product type and applications/end industries.
Market Segment by Companies, this report covers IBM
Microsoft
Intel
Google
TIBCO
Cloudera
Nutanix
Foghorn Systems
SWIM.AI
Anagog
Tact.ai
Bragi
XNOR.AI
Octonion
Veea Inc
Imagimob
Market Segment by Regions, regional analysis covers North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia and Italy)
Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
South America (Brazil, Argentina, Colombia)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
Market Segment by Type, covers Software Tools
Platforms
Market Segment by Applications, can be divided into Autonomous Vehicles
Access Management
Video Surveillance
Remote Monitoring & Predictive Maintenance
Telemetry
Others
Frequently Asked Questions
The base year for the study has been considered 2019, historic year 2014 and 2018, the forecast period considered is from 2020 to 2027. The regions analyzed for the market include North America, Europe, South America, Asia Pacific, and Middle East and Africa. These regions are further analyzed at the country-level. The study also includes attractiveness analysis of type, application and regions which are benchmarked based on their market size, growth rate and attractiveness in terms of present and future opportunity for understanding the future growth of the market.
Market is segmented on the basis:
- By Type
- By Application
- By Region
- By Country
- By Manufacturer
The report offers in-depth analysis of driving factors, opportunities, restraints, and challenges for gaining the key insight of the market. The report emphasizes on all the key trends that play a vital role in the enlargement of the market from 2019 to 2026.
The report provides company profile of the key players operating in the market and a comparative analysis based on their business overviews industry offering, segment market share, regional presence, business strategies, innovations, mergers & acquisitions, recent developments, joint venture, collaborations, partnerships, SWOT analysis, and key financial information.
