The AI in Computer Vision market is projected to grow from USD 23.01 Billion in 2024 to USD 268.36 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 35.94% during the forecast period (2024-2032). Additionally, AI in Computer Vision Market Size was valued at USD 16,91 Billion in 2023.
The market is substantially growing with advent of technology in application markets such as automotive, consumer electronics, healthcare, agriculture, robotics and more. The use of AI in computer vision is impeccable in terms of market development, ease of manufacturing, market positioning of products, supply efficiency, monitoring of inventory & product movement and more. The demand for AI in computer vision market is anticipated to be driven by rising demand for automation and quality inspection worldwide across end-use markets. Further, government across the globe are promoting businesses by supporting integration and automation of AI in computer vision to create opportunities for market participants in the ecosystem. However, the market reflects security concerns aligned to analytics and cloud-based image processing, which is anticipated to act as a restraining factor to market development over the foreseeable future.
FIGURE 1: AI IN COMPUTER VISION MARKET 2023 - 2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
Covid-19 Analysis
Covid-19 pandemic brought in saturation in terms of manufacturing unit and daily work of facilities. The use of AI in manufacturing sector has been undergoing turbulence during the pandemic. Government across the globe has been working on steering technological advancements in the field to cope up with thew rise in pandemic situation and sustain in the marketspace. The healthcare sector however reflected heavy growth in penetration of AI technology due to increased hospitalization and increased dependency of patients on healthcare facilities globally. Rest of the manufacturing sectors, however, reflected moderately lower penetration and application of AI in their operations during the pandemic.
Mobile Edge Computing is an emerging concept which is a paradigm that facilitates mobile devices which are resource-scarce to achieve high capabilities and therefore execute data-intensive applications while collaborating with network servers that are resource rich to enable ubiquitous computing. The use of edge computing in mobile devices are not particularly reliant on certain applications but are predominantly discussed under multiple cases. For instance, edge computing in mobile devices is utilized in connected vehicles in case of vehicles that are autonomous. The functionality is also prominent in case of virtual reality, augmented reality, and enterprise mixed reality applications, cloud gaming applications, real-time detection of drones, video analytics, and more.
The demand for computer vision is spread across an array of application markets wherein few of the non-traditional emerging applications include utilizing of the technology in traffic flow monitoring, road condition monitoring, CT scan & MRI scan in healthcare sector, and more. Increasing demand for computer vision in overcrowded roads is increasing across Asia Pacific region. In bigger cities across the region, computer vision plays a crucial role in diverting traffic and monitoring traffic flow on roads. The system includes few of the key steps including accepting video feedback from camera files and marking of vehicles counting number of vehicles on road in a particular time frame.
Traffic monitoring system includes two different approaches to computer vision technology utilization that includes the following; number-plate recognition system and generic road-traffic monitoring system. In the first system, the computer monitoring system utilizes the available number-plate recognition to identify and monitor vehicles. In the second technology, the computer system runs on identifying vehicles through make & model and monitoring vehicles through complex road scenes. Ease of road traffic monitoring is one of the key emerging application areas that is projected to drive demand for computer vision over the foreseeable future.
Machine vision is coming out to prove its ideal characteristics in shaping human task across industrial sector. With advent of computer vision in every aspect of manufacturing, there has been an ease in process and more profitability. This has led to increased demand in machine learning technology. However, lack of awareness among the end users is one of the challenges faced by industry participants worldwide. Ease of metrology, identification, and execution is a critical portion of the market development. However, industry participants are reluctant in understanding the core concepts of machine vision learning. These factors are poised to reflect substantial challenge in market development over the coming years globally.
The use of AI in computer vision is fragmented into hardware and software. Hardware was further split into processors, network and memory, whereas software was divided into AI platforms and AI solutions. The undivided attention to details for each of the components are highly fragmented based on technological advancements and use of AI across these components, thereby driving market demand and growth over the forecast period. Among components, Software segment expected to witness rapid growth over the forecast period.
FIGURE 2: AI IN COMPUTER VISION MARKET, BY COMPONENT, 2022 VS 2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
The AI in Computer Vision Market, in this report, has been segmented on the basis of machine learning process into Supervised Learning, Unsupervised Learning and Reinforcement Learning. Reinforcement Learning segment will be the fastest growing segment over the forecast period.
Machine learning, in a broader sense, in computer vision is a breakthrough that is increasingly in demand for startup founders, engineers, computer scientists and more. The implication of machine learning in computer vision is to perform tasks without instructions through AI. Machine learning is considered as an integral component of AI wherein computer vision is a direct subset of Artificial Intelligence.
Reinforcement learning is yet another key areas of machine learning which enables learning through process of trial and error, wherein the system utilizes its own feedback from experiences and actions to implement changes. The basic elements of reinforced learning model revolves around analysis through environment, current situation, reward, policy, and value. Few of the highly utilized reinforcement machine learning algorithms include Q-learning and State-Action-Reward-State-Action, and Deep Deterministic Policy Gradient. In simpler terms, reinforcement machine learning is about making sequential decisions wherein the current input decides the output and the subsequent input is based on the obtained output.
The AI in Computer Vision Market is segmented, based on component, into home security, home automation, home entertainment, home healthcare, and others healthcare segment will be the fastest growing segment over the forecast period.
Geographically, the AI in Computer Vision market has been categorized into North America, Europe, the Asia-Pacific, the Middle East & Africa, and South America.
North America is likely to be the dominant regional market. North America is considered a major hub for AI globally, with US capturing the maximum market share of 89.54% in North America in 2020. The country is hub to major AI reforming companies that have been increasingly investing in innovations and catering majority of end use markets across US and North America. Few of the leading AI suppliers in US as of 2021 includes AIBrain, AEye, Anki, AlphaSense, CaseText, Blue River Technology, ClarifAI, CognitiveScale, DataRobots, and CloudMinds, Abnormal Security, ASMP Robotics, Arize AI, Atomwise, Bearing, Canvas, and Cresta among others.
FIGURE 3: AI IN COMPUTER VISION MARKET SHARE BY REGION 2022 VS 2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
The AI in Computer Vision Market is distinguished by the presence of numerous global, regional, and local players catering to the growing demand for edge computing in mobile devices, growing impact of ai in machine vision and increasing demand for computer vision systems in non-traditional and emerging applications. However, high cost of implementation and lack of awareness and technical expertise may hamper the growth of the AI in Computer Vision Market. The major players have adopted a strategy of obtaining regulatory approval from government agencies for their products and signing contracts and agreements to broaden their reach and reduce operational costs. For instance, in November 2020, FLIR Systems, Inc. launched the FLIR VS290-32, an industry-first videoscope that combines thermal imaging and a visible camera specifically designed for safer and more efficient inspections of hard-to-reach underground utility vaults. The VS290-32 is the company's first industrial-grade, electrical safety-rated, flexible dual-sensor videoscope on a replaceable, two-meter-long camera probe. In August 2020, Omron Automation Americas launched a complete machine vision solutions package that can be easily installed on PC-based systems. The new FJ2 cameras feature state-of-the-art complementary metal-oxide-semiconductor (CMOS) sensors, frame rates as fast as 282 frames per second (FPS), and resolutions ranging from 0.4MP up to 5MP in both monochrome and color versions.
January 2022: Meta and Penguin Computing, Inc., a division of SGH and a leader in high-performance computing (HPC) focused on artificial intelligence and machine learning, partnered for providing AI-optimized architecture and managed services for the AI Research SuperCluster (RSC).
November 2021: Microsoft's low code application development advanced specialization was earned by UST, a California-based digital transformation solutions company.
The key vendors in the market are Ultraleap, Irida Labs S.A., Microsoft Corporation, Clarifai, Inc., General Electric, Xilinx, Inc., Omron Corporation, Nvidia Corporation, Qualcomm Technologies Inc., Meta Platforms Inc. Google, LLC, Apple Inc, Intel Corporation, Teledyne Technologies Inc, and Prisma AI
January 2025
A business combination between Getty Images and Shutterstock: Expecting to become a unified multinational company focused on visual content, Getty Images and Shutterstock announced a $3.7 billion merger. As a result, they will be able to enhance their still imagery, video, and music media services in response to the stiffer competition posed by AI-generated images.
Nvidia's AI Innovations: At CES 2025, Nvidia showcased 'Cosmos,' an assortment of AI models that can create images and 3D models for the training of humanoid robots, a range of industrial robots, and driverless cars, as well as the new GeForce RTX 50 Series of GPUs employing the cutting-edge Blackwell AI chip, which will drastically enhance graphical performance.
Razer's Approach Ava: As Razer introduced Project Ava, an AI co-gamer designed to assist players in honing their performance by monitoring activity and giving advice, a storm of controversy around the connection between AI and gaming was born.
March 2022
The New North American Market marked the beginning for Ermata, an AgTech company that offers computer vision and data science technology.
Building upon three years of integrated research, development, and testing, my company`s AI solution, Croptimus Pest and Disease, is ready to be introduced. This AI solution allows for pathogen detection via image analysis.
January 2022
Amazon Web Services, Inc. started AWS Panorama, an SDK that provides utilities for computer vision and related products to develop its business operations across the Asia-Pacific. In Sydney and Singapore, AWS Panorama will be available. This feature will enable businesses to automate processes, including the visual assessment of manufacturing bottlenecks, product quality, and worker safety.
March 2022
Intel Corporation USA extended its offerings to include cloud computing, IoT, and data center solutions. In their pronouncement, computer vision, machine learning, and predictive analytics technologies can enhance patient rooms and critical care areas in the healthcare sector.
© 2024 Market Research Future ® (Part of WantStats Reasearch And Media Pvt. Ltd.)