Artificial Intelligence (AI) in Computer Vision Market Size to Reach USD 130.57 Billion in 2030, Rising Demand for Computer Vision Systems in Automotive Applications

Reports and Data
Artificial Intelligence (AI) in Computer Vision Market Size – USD 15.87 Billion in 2021, Market Growth – at a CAGR of 26.3%, Market Trends – High demand for AI in the computer vision market

Rising demand for quality inspection and automation and government initiatives for development of AI-related technologies is driving AI in computer vision market revenue growth

The global Artificial Intelligence (AI) in computer vision market size is expected to reach USD 130.57 Billion in 2030 and register a revenue CAGR of 26.3% over the forecast period, according to the latest report by Reports and Data. Rising demand for computer vision systems in automotive applications and increasing demand for emotion AI are key factors driving revenue growth in the AI in computer vision market.

AI is the ability of a computer or a computer-enabled robotic system to manage data, produce output, and provide problem-solving outcomes that are similar to human thought processes. Computer vision is a branch of computer science that aims to simulate complexity of human vision system, allowing computers to recognize and process objects in images and videos in the same way that humans do. Major driving force behind development of computer vision is massive amount of data generated in everyday life and computer vision help to process them more efficiently and quickly. Accuracy of object detection has improved, as new hardware and algorithms in computer vision, have been introduced.

Emotion AI, also known as affective computing or artificial emotional intelligence, is a subset of AI (broad term for machines replicating way humans think) that measures understanding, simulates, and reacts to human emotions. . It’s commonly used in mobile applications, such as Snapchat and Instagram filters for entertainment and fun, which is boosting growth of Emotion AI, which is also used for face recognition in high-level security devices.

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Companies profiled in the global market report include NVIDIA Corporation, Intel Corporation, Microsoft., IBM, Qualcomm Technologies, Inc., Amazon Web Service, Inc., Advanced Micro Device, Inc. Google, AlphaTechsys, and Hailo.

Some Key Highlights From the Report

In April 2021, NVIDIA created a new type of NVIDIA-Certified System that delivers AI to businesses that run their applications on industry-standard corporate data center infrastructure. This new category includes high-volume enterprise servers from leading manufacturers that are certified for VMware vSphere 7, the world’s most widely used computer virtualization technology and can run NVIDIA AI Enterprise software suite.
The software segment accounted for largest revenue share in 2021 owing to technological advancements and due to its low cost and strong network infrastructure in developed countries, software system is registering increased demand. Manufacturing companies around the world are planning to shift to AI for reducing costs and eliminating need for human intervention in various processes, driving revenue growth of the segment.
The supervised learning segment accounted for largest revenue share in 2021. Supervised learning models can be a valuable solution for eliminating manual classification work and making future predictions based on labeled data. As a result, demand for supervised learning is growing day by day.
The non-Industrial segment accounted for largest revenue share in 2021. Advanced technologies are being used to make day-to-day life more comfortable and AI in computer vision is playing an important role to achieve it. Some applications of non-industrial AI in computer vision are driverless cars, autonomous farm equipment, drone applications, intelligent traffic systems, and guided surgery, among others. Demand for such applications is rapidly increasing driving revenue growth of this segment.
The automotive segment accounted for largest revenue share in 2021. During automotive production, computer vision is used to inspect every single detail. It detects flaws in every single product and rejects those that are defective. This helps to ensure that every product is of the highest quality and helps in reducing overall costs in the industry, which is driving revenue growth of this segment.
The North America market accounted for largest revenue share in 2021 mainly due to implementation of advanced technologies in manufacturing and automotive industries. Increasing use of IoT-enabled devices and rising demand for connected devices & wireless connectivity and government initiatives to encourage adoption of computer vision have propelled growth of the market in North America.

For the purpose of this report, Reports and Data has segmented the AI in computer vision market based on component, machine learning model, application, end-use, and region:

Component Outlook (Revenue, USD Billion; 2019–2030)


Machine Learning Model Outlook (Revenue, USD Billion; 2019–2030)

Supervised Learning
Unsupervised Learning
Reinforcement Learning

 Outlook (Revenue, USD Billion; 2019–2030)


End-use Outlook (Revenue, USD Billion; 2019–2030)

Consumer Electronics
Security & Surveillance

Regional Outlook (Revenue, USD Billion; 2019–2030)

North America
Latin America
Middle East & Africa

Key Advantages of Artificial Intelligence (AI) in Computer Vision Report:

Identification and analysis of the market size and competition
Qualitative and quantitative analysis of the market data
Data validated by industry experts after extensive primary and secondary research
Extensive regional analysis of the Artificial Intelligence (AI) in Computer Vision industry
Profiling of key players along with their business overview, business strategies, deals and partnerships, and product portfolio
SWOT and Porter’s Five Forces Analysis for in-depth understanding of the competitive landscape
Feasibility analysis and investment analysis to enable strategic investment decisions
Analysis of opportunities, drivers, restraints, challenges, risks, and limitations

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