Market Outlook:

The anticipated global AI in computer vision market size is poised to reach USD 16.94 Billion by 2024, with a projected escalation to USD 118.56 Billion by 2032, reflecting a compound annual growth rate (CAGR) of 21.48% during the forecast period. 

The aim of computer vision, a rapidly increasing branch of artificial intelligence, is to allow machines to understand and extract valuable information from visual input, comprising pictures and movies. This involves generating algorithms that can identify objects, identify patterns, and understand the context of graphic features to mimic how humans notice and understand visual stimuli. The main goal is to give computers the ability to "see" and analyze visual information in ways that go beyond just storing or playing back images. An AI-powered vision system, for instance, can identify objects in a picture, categorize them according to their characteristics, and even forecast how they will move during a video clip. It is now possible to automate or improve operations that formerly required human interaction by teaching computers to emulate human visual perception. Combining machine learning, deep learning, and sophisticated computer vision algorithms, this capacity enables machines to carry out tasks like face recognition, text recognition in images, and even real-time interpretation of complicated visual situations.

Market Dynamics:

Driver:

The growing innovations in the healthcare sector boost the growth of the AI in computer vision market. Al has a lot of prospects in computer vision as the healthcare industry's rapid developments, particularly in the areas of medical imaging and diagnostics. Al-powered systems are now required for image analysis to detect medical disorders and make treatment decisions as a result of advancements in healthcare technology. Al-driven visual analysis tools are becoming progressively more necessary in the healthcare industry, particularly for early disease detection and individualized treatment regimens. The demand for sophisticated imaging solutions is rising as a result of these advancements, which are broadening the range of Al's computer vision applications. For instance, the World Health Organization (WHO) introduced S.A.R.A.H. in April 2024, a digital health assistant that analyzes medical photos and improves patient contact using Al in computer vision. 

Restraint:

The rising data privacy and security concerns hinder the growth of the AI in computer vision market. The development of artificial intelligence in computer vision is severely constrained by laws about data security and privacy. The majority of these technologies handle and analyze private information, including photos, videos, and biometric information, which can be abused or compromised. Such situations might lead to ethical dilemmas, legal complaints, and privacy rights violations, which makes it challenging for businesses to put such ideas into practice. Along with identity loss brought on by unethical behavior that stymies prospects for partners and clients, legal fees and compliance costs also add to the strain on the organization. Algorithmic bias and prejudice in computer vision can impact AI in several applications, including security and facial recognition. This results in slow market uptake and unequal market outcomes. 

Opportunity:

The increasing technological advancements create a lucrative opportunity for the growth of the AI in computer vision market. The improvement of Al-facilitated computer vision algorithms has been enhanced by improvements in hardware technology. With the advent of breakthrough technical advancements, GPUs, TPUs, and edge devices have developed to increase computing efficiency and speed. Deep neural network topologies and powerful machine learning algorithms for visual data analysis are made possible by these improvements in total AI technology. For instance, Intel Corporation unveiled the new Intel Arc B-Series GPUs, such as the Intel Arc B580 and B570, in December 2024. These are also founded on this approach, are emphasized to provide the highest performance value in the industry, and are intended to increase Al's workload. The availability of AI hardware, including cameras, sensors, frame grabbers, optics, and more, has primarily impacted computer vision computing by making it possible to process images and videos in real time, identify intricate patterns, and fine-tune deep neural network training. Enhanced memory bandwidth, energy-progressive architectures, and particular Al acceleration in supervised circuits further help in the market expansion.

Challenge:

The high expenses of data management and storage, which are necessary for large-scale projects with enormous datasets, must be addressed to improve the quick development of Al in computer vision. Terabytes of storage are needed for training Al models, particularly when high-resolution photos and videos are used. This leads to large financial outlays for cloud storage, data centers, and sophisticated data management systems, which may be quite costly, particularly for startups and smaller businesses. These exorbitant prices act as a barrier to entry, limiting market share and innovation in computer vision products powered by Al. For these firms, the best course of action is to innovate and optimize data management and storage. One technique for dispersing the data processing process away from central storage is edge inferencing technology. To reduce storage requirements without compromising speed, data compression techniques are employed, such as the machine learning-based image representation technique. 

Key Players:

• Microsoft Corporation (US) 
• Google LLC (US) 
• IBM Corporation (US) 
• Amazon Web Services, Inc. (US) 
• Intel Corporation (US) 
• NVIDIA Corporation (US) 
• Apple Inc. (US) 
• Facebook, Inc. (US) 
• Qualcomm Incorporated (US) 
• Baidu, Inc. (China) 
• Alibaba Group Holding Limited (China) 
• Tencent Holdings Limited (China) 
• Samsung Electronics Co., Ltd. (South Korea) 
• Sony Corporation (Japan) 
• Huawei Technologies Co., Ltd. (China) 
• Others

Recent Development:

• In March 2023, Microsoft Corporation stated that their Florence foundation model would usher in a new era in computer vision AI. Billions of text-image pairs are used to train Microsoft's Florence foundation model, which is then integrated into Azure Cognitive Service for Vision as an affordable, production-ready computer vision service. Developers can now produce innovative, commercially viable, and ethical computer vision applications for a range of sectors due to the enhanced Vision Services.

• In June 2024, Intel Corporation launched Intel® GetiTM 2.0.0, an updated version of its AI vision software that offers improved functionality for data labeling, model training, and inferencing to speed up the development of computer vision. Current clients can also upgrade to take advantage of the most recent developments in Vision AI software. 

• In November 2024, Intel Corporation launched Intel OpenVINO 2024.5, a new version that improves support for big language models and optimizes runtimes for Intel hardware, advancing AI in computer vision. It makes it possible to deploy AI for vision applications effectively in edge, cloud, and local contexts. 

Segment Insights:

By Component

AI in computer vision is a field of software that offers a variety of options, including platforms, frameworks, and algorithms, that give users the means to process, analyze, and interpret visual input. Deep learning frameworks, picture recognition software, video analytics tools, and AI-based algorithms all effectively cover the wide range of artificial intelligence. The software component serves as the foundation for most computer vision tasks, including object identification, image segmentation, face recognition, and AI model training. A multitude of factors contribute to the market dominance of the software category. First off, the accuracy and efficiency of deep vision systems have significantly improved due to the rapid advancement of deep learning algorithms and neural networks. As a result, there is now a greater need for sophisticated software programs that can analyze and handle images. 

By End-User

The largest segment of the global artificial intelligence (AI) computer vision market is the healthcare industry, which has a significant impact on diagnosis and care and is the most diverse application sector. These days, medical imaging, disease diagnosis, surgery planning, and patient health follow-up all use computer vision technology fueled by artificial intelligence (AI). Medical pictures such as X-rays, MRIs, and CT scans can be examined by computer vision procedures to recognize anomalies, make initial diagnoses, and give medical professionals valued information. The ambition for accurateness, efficiency, and affordability in medical imaging and diagnosis is the boosting the force behind the use of AI in healthcare. In contrast, the market for AI and computer vision is increasing at the greatest rate in the automotive sector. The addition of artificial intelligence (AI) into automobiles has changed the automotive industry through the use of computer vision technologies. ADAS and self-driving features are made conceivable by computer vision systems' technological expertise. Real-time visual data from cameras and sensors can be examined by these systems to identify pedestrians, locate objects, understand traffic signs, and guide tracks. 

Regional Insights:

The market for AI in computer vision is dominated by the Asia-Pacific region. The quick speed of technology development, the growing use of AI solutions, and strong government support in important economies like China, Japan, South Korea, and India are the main drivers of this rise. The need for AI to increase operational efficiency through automation and customer experience enhancement is being driven by major industries like retail, manufacturing, healthcare, and automotive. China has a robust government-supported AI ecosystem. AI-powered computer vision is vital for intelligent quality assurance and fully autonomous systems through a range of industries, comprising manufacturing and transportation. Japan is improving its AI capabilities through technological innovation, the expansion of AI infrastructure, and the purpose of supporting the digital transformation of industries. South Korea's attention on AI R&D and the integration of AI in logistics and industry is also boosting the growth of the market. Additionally, India has a mission on AI to create localized AI capabilities in a number of sectors, including manufacturing, healthcare, and agriculture. These motivating elements include cloud penetration, machine-learning algorithm development, and the establishment of big datasets. Together, these elements position this region as a leader in the market for artificial intelligence in computer vision while spurring innovation for adoption in a number of other industries.

Segmentation:

By Component

• Software
• Hardware

By Technology

• Machine Learning
• GenAI

By Function

• Training
• Inference

By Deployment

• On-Premises
• Cloud-Based

By Application

• Industrial
• Non-Industrial

By Application

• Automotive
• Consumer Electronics
• Healthcare
• Agriculture
• Transportation & Logistics
• Security & Surveillance
• Others

By Region

North America

• USA

• Canada

• Mexico

Europe

• France

• UK

• Spain

• Germany

• Italy

• Rest of Europe

Asia Pacific

• China

• Japan

• India

• South Korea

• Rest of Asia Pacific

Middle East & Africa

• GCC

• South Africa

• Rest of the Middle East & Africa

South America

• Brazil

• Argentina

• Rest of South America

What to Expect from Industry Profile?

1. Save time carrying out entry-level research by identifying the size, growth, major segments, and leading players in the AI in Computer Vision market in the world.

2. Use PORTER’s Five Forces analysis to determine the competitive intensity and therefore market attractiveness of the Global AI in Computer Vision market.

3. Leading company profiles reveal details of key AI in Computer Vision market players’ global operations, strategies, financial performance & recent developments.

4. Add weight to presentations and pitches by understanding the future growth prospects of the Global AI in Computer Vision market with forecast for the decade by both market share (%) & revenue (USD Million).

FAQ’s

1) What are the major factors driving the growth of the Global AI in Computer Vision Market?

• The growing innovations in the healthcare sector boost the growth of the AI in computer vision market. 

2) What would be the CAGR of the Global AI in Computer Vision Market over the forecast period?

• The Global AI in Computer Vision Market is poised to grow at a CAGR of 21.48% from 2024 to 2032.

3) Which region will provide more business opportunities for the growth of the Global AI in Computer Vision Market in the future?

• The Asia Pacific region is expected to create more opportunities in the market.

4) Who are the major players dominating the Global AI in Computer Vision Market?

• Microsoft Corporation (US), Google LLC (US), IBM Corporation (US), Amazon Web Services, Inc. (US), Intel Corporation (US), NVIDIA Corporation (US), Apple Inc. (US), Facebook, Inc. (US), Qualcomm Incorporated (US), Baidu, Inc. (China), Alibaba Group Holding Limited (China), Tencent Holdings Limited (China), Samsung Electronics Co., Ltd. (South Korea), Sony Corporation (Japan), Huawei Technologies Co., Ltd. (China), Others.

5) What are the segments in the Global AI in Computer Vision Market?

• By Component, By Technology, By Function, By Deployment, By Application, and By End-Use are the industry key segments considered for research study.

6) What is the estimated market revenue for the Global AI in Computer Vision Market in 2032?

The estimated revenue for the Global AI in Computer Vision Market in 2032 is USD 118.56 Billion.