Edge AI Software Market - Industry Dynamics, Market Size, And Opportunity Forecast To 2031

Market Scenario 

Global edge AI software market is forecast to record a revenue of US$ 27,457.6 Mn by 2031, up from US$ 1,734.8 Mn in 2022, at a CAGR of 35.9% during the forecast period 2023-2031.

The advancements in edge AI have brought about a new era of opportunities in various industries, and the automotive industry is no exception. Edge AI software has the potential to transform the automotive industry by enabling faster and more efficient communication between the different subsystems of a vehicle, such as the sensors, applications, and end-user experiences. Moreover, with the emergence of new technologies, the autonomous vehicle segment is expected to grow significantly, and edge computing will play a vital role in this growth. According to industry experts, the use of edge AI computing in 5G networks will enable better data control, reduced costs, and faster insights as compared to 4G networks, thereby creating new opportunities for the industry.

In addition to the automotive industry, other industries such as healthcare, manufacturing, and retail are also expected to benefit from the advancements in edge AI software market. The use of edge AI software in healthcare, for instance, can enable real-time monitoring of patient health, while in the manufacturing industry, it can help optimize production processes and reduce downtime.

The report also highlights that edge AI software is expected to enable the development of new applications and services that were previously impossible, leading to new revenue streams and business models. This includes applications such as augmented and virtual reality, which are expected to revolutionize the way people interact with technology.

Market Dynamics 

Drivers 

Increasing Demand for Remote Work Accelerated the Adoption of Remote Work

The COVID-19 pandemic has changed the way businesses operate and has highlighted the importance of remote work options in the global edge AI software market. Many employees have found that they are more productive working from home, and businesses have realized that remote work can reduce costs associated with office space and infrastructure. As a result, the demand for remote work is expected to continue to grow, even after the pandemic has ended. Companies are investing in technologies that enable remote work, such as virtual meeting platforms, cloud-based file-sharing systems, and project management tools, to facilitate collaboration between remote teams. This increased adoption of remote work is also driving the need for cybersecurity measures to ensure that remote workers can securely access company networks and data.

Advancements in Artificial Intelligence is transforming the way businesses operate

Artificial intelligence is driving the development of new technologies and applications that are changing the way businesses operate in the global edge AI software market. For example, AI-powered chatbots and virtual assistants are becoming increasingly popular for customer service and support, reducing the need for human interaction. In the healthcare industry, AI-powered tools are being used to analyze medical images and assist with disease diagnosis. In manufacturing, AI is being used to optimize production processes and reduce downtime. AI is also driving the development of autonomous vehicles, which have the potential to transform the transportation industry. As the technology continues to evolve and become more accessible, businesses of all sizes and industries are expected to adopt AI-powered applications to improve efficiency, reduce costs, and gain a competitive edge. However, there are also concerns about the potential impact of AI on employment and the need for ethical and transparent use of AI technologies.

Trend 

Increased Adoption of Hybrid Cloud Solutions

Hybrid cloud solutions are becoming increasingly popular among businesses due to their ability to provide the benefits of both public and private cloud environments. Hybrid cloud solutions in the edge AI software market allow businesses to store critical and sensitive data on private cloud servers, while also utilizing the cost savings and scalability benefits of public cloud providers for less sensitive data and applications.  The trend towards hybrid cloud solutions is driven by the need for businesses to balance cost, security, and flexibility. By adopting a hybrid cloud approach, businesses can reduce their infrastructure costs by using public cloud providers for non-sensitive data and applications, while maintaining control over their critical data and applications through private cloud solutions.

Moreover, as the amount of data generated by businesses continues to grow, hybrid cloud solutions can help manage and analyze this data more efficiently in the edge AI software market. The ability to store and process data on private cloud servers while leveraging the computing power of public cloud providers allows businesses to manage their data more effectively and gain deeper insights into their operations.

The adoption of hybrid cloud solutions is expected to continue to grow as businesses seek to optimize their infrastructure and gain a competitive edge in the marketplace. As a result, cloud service providers are expected to continue investing in hybrid cloud solutions to meet the growing demand for this technology.

Segmental Analysis

By Data Source

By data source, sensor data is expected to capture more than 26% revenue share of the global Edge AI software market by 2027. Sensors are a key component of Edge AI technology, as they collect data from the physical world and send it to Edge AI devices for processing and analysis. The report cites factors such as the growing adoption of IoT devices, increasing investments in AI and machine learning, and the need for real-time data processing and analysis as key drivers of the market's growth.

Sensors are used in a wide range of applications, including smart homes, smart cities, and industrial automation. In the smart home segment, sensors are used to collect data on temperature, humidity, and air quality, allowing Edge AI devices to adjust environmental conditions automatically. In smart cities, sensors are used to collect data on traffic patterns, air quality, and energy usage, enabling city planners to optimize urban infrastructure and services. In industrial automation, sensors are used to collect data on production processes, allowing manufacturers to optimize operations and reduce downtime.

By Application 

Based on application, energy management is expected to generate more than 21% revenue share of the global Edge AI software market. The use of Edge AI technology in energy management applications allows for more efficient and cost-effective management of energy resources, leading to reduced energy consumption and lower costs. The report cites factors such as the increasing adoption of renewable energy sources and the need for real-time energy monitoring and control as key drivers of the market's growth.

Edge AI technology is used in a wide range of energy management applications, including smart grids, building automation, and industrial control systems. In smart grids, Edge AI devices are used to optimize energy distribution and consumption, reducing waste and improving efficiency. In building automation, Edge AI devices are used to monitor and control energy usage, adjusting lighting and temperature settings automatically to reduce energy consumption. In industrial control systems, Edge AI devices are used to optimize production processes, reducing energy usage and downtime.

Regional Analysis

The Asia Pacific region is the largest Edge AI software market, with a current market share of around 38%. The region's dominance in the market is driven by several factors, including the growing adoption of IoT devices, increasing investments in emerging technologies such as AI and machine learning, and the rising demand for cloud-based services. The report cites factors such as the increasing adoption of 5G networks and the growing need for real-time data processing and analysis as key drivers of the market's growth.

The Asia Pacific region's market dominance is further strengthened by several major players in the market, including Huawei, Alibaba, Baidu, and Samsung. These companies are investing heavily in Edge AI software development, with a focus on developing new applications and services that will help to drive the growth of the market in the coming years.

Additionally, several countries in the Asia Pacific edge AI software market including China, Japan, and South Korea, have made significant investments in AI research and development, which has helped to fuel the growth of the Edge AI software market. These investments have led to the development of new AI technologies and applications, creating new opportunities for businesses operating in the region.

As the market for Edge AI software continues to grow, businesses in the Asia Pacific region are expected to continue investing in the technology to gain a competitive advantage in their respective industries. However, businesses must also navigate the unique challenges of operating in the region, such as regulatory requirements, language barriers, and cultural differences, to be successful.

Competitive landscape of the Global Edge AI Software Market 

Top 4 players in the global edge AI software market are holding more than 25-30% share. Some of the key providers that are profiled in the report are:

• Alef Edge, Inc.
• Anagog Ltd.
• AWS
• Azion Technologies
• Bragi.Com
• Chaos Prime, Inc.
• Clearblade, Inc.
• Foghorn Systems, Inc.
• Google
• Gorilla Technology Group, Inc.
• IBM
• Imagimob
• Microsoft
• Nutanix
• Octonion
• Sixsq Sarl
• Synaptics
• TACT.AI
• TIBCO Software
• Veea Inc.
• Other Prominent Players

Market Segmentation

By Component

• Solution
• Software Tools
• Platform
• Services
• Training and Consulting Services
• System Integration Testing
• Support and Maintenance

By Data Source

• Biometric Data
• Mobile Data
• Sensor Data
• Speech Recognition
• Video and Image Recognition

By Application

• Access Control
• Autonomous Vehicles
• Energy Management
• Predictive Maintenance
• Remote Monitoring
• Telemetry
• Video Surveillance
• Others

By End Users

• Advance Industries
• Banking and Insurance
• Chemical Agriculture
• Consumers
• Cross Vertical
• Energy And Material
• Health Care Infrastructure
• Media and Entertainment
• Public Sector Utilities
• Retail
• Travel, Transport, and Logistics

By Region 

• North America
  • The U.S.
  • Canada
  • Mexico
• Europe
  • Western Europe
    • The UK
    • Germany
    • France
    • Italy
    • Spain
    • Rest of Western Europe
  • Eastern Europe
    • Poland
    • Russia
    • Rest of Eastern Europe
• Asia Pacific
  • China
  • India
  • Japan
  • Australia & New Zealand
  • ASEAN
  • Rest of Asia Pacific
• Middle East & Africa (MEA)
  • UAE
  • Saudi Arabia
  • South Africa
  • Rest of MEA
• South America
  • Brazil
  • Argentina
  • Rest of South America