AI in Computer Vision Market Growth, Analysis, Latest Trends and Forecast till 2026

The AI in computer vision market is estimated to be valued at USD 15.9 billion in 2021 and reach USD 51.3 billion by 2026, at a CAGR of 26.3%. The growing need for quality inspection and automation, increasing demand for computer vision systems in non-traditional and emerging applications, and rising need for ASICs are the key factors driving the growth of the market. Likewise, government initiatives to support industrial automation and integration of AI into edge devices are expected to create lucrative opportunities for the players in the AI in computer vision market. However, rising security concerns related to cloud-based image processing and analytics are expected to restraint market growth.

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The AI in computer vision market, on the basis of component, has been segmented into hardware and software. The software segment is expected to register a higher CAGR between 2021 and 2026. Software tools, combined with a suite of computer vision software allow an individual to interface with a camera and a production line and automatically perform image improvement, location analysis, flaw detection, character verification, character recognition, symbol recognition, and several other functions.

The AI in computer vision market, on the basis of function, has been segmented into training and inference. In terms of value, the inference function segment is expected to account for a larger share of the market by 2026. The inference is sensitive to latency, and the trained model needs to analyze and provide analysis in near real-time. The requirement of the infrastructure for model deployment to be able to accelerate the data at the fastest rate is expected to drive the market for inference. The AI in computer vision market for training function is estimated to grow at a higher CAGR during the forecast period. In the context of AI, training is the process of developing an algorithm that can infer a result from data or processes. Training is computationally very expensive and is best accelerated with GPUs.

Machine learning enables systems to learn without being explicitly programmed. This technology can reliably and quickly scan, parse, and react to anomalies. The major sub-types of machine learning models are supervised learning, unsupervised learning, and reinforcement learning. The supervised machine learning model is expected to account for the largest share of nearly 84% of the AI computer vision market by 2026.

The AI in computer vision market, based on application, has been segmented into industrial and non-industrial. The industrial segment is expected to grow at a higher rate as modern technologies can help in several traffic situation systems, including toll collection, monitoring traffic flows, and identifying violations. 3D machine vision also has a huge potential for growth in non-industrial applications such as security and surveillance, postal and logistics, and intelligent transportation systems (ITS), where image quality, dimension, and orientation play a crucial role. Modern technologies can enhance several transportation systems, including toll collection systems and traffic monitoring systems.

In the non-industrial market, the growing demand for camera-enabled smartphones at both front and rear ends is driving the market for AI in computer vision, especially in the consumer segment. Rear-end cameras are driving enhancements in terms of higher pixel count, while front-end cameras are at a lower pixel count and are based on fixed-focus technology.
The AI in computer vision market, on the basis of end-use industry, has been segmented into automotive, consumer electronics, healthcare, retail, security & surveillance, manufacturing, agriculture, transportation & logistics, and others. The market for consumer electronics is expected to hold a major share of the market during the forecast period attributed to the increasing application of AI computer vision systems in consumer electronics such as smartphones, desktops, and laptops.

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North America is expected to hold the largest share of ~40% of the global AI in computer vision market in 2021. The presence of prominent AI technology providers, such as IBM (US), Google (US), Microsoft (US), NVIDIA (US), Intel (US), and Facebook (US) is complementing the growth of the regional market. The growing concern about the security of critical infrastructure and sensitive data has increased government intervention in recent years and resulted in the adoption of AI in computer vision in security applications. Europe is likely to hold a share of ~29% of the AI in computer vision market in 2021. Germany and the UK are the major contributors to the AI in computer vision market in this region. The automotive industry in the UK is contributing to the growth of the AI in computer vision market. APAC is expected to grow at the highest CAGR in the AI in computer vision market. Countries such China, Japan, and South Korea are expected to be the major contributors to the market in APAC. Increased manufacturing operations contribute mainly to the economic development in China, while the rising demand to incorporate Industry 4.0 and advanced manufacturing techniques for increasing automation across various applications in India is contributing to the tremendous growth of AI in computer vision in APAC.

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This release was published on openPR.