Austin, May 19, 2025 (GLOBE NEWSWIRE) -- AI in Computer Vision Market Size & Growth Insights:
According to the SNS Insider,“The AI in Computer Vision Market was valued at USD 24.26 billion in 2023 and expected to reach USD USD 173.82 billion by the end of 2032, with a CAGR of 24.68 % between 2024 and 2032.”
Accelerating Market Momentum with AI-Powered Vision Systems Transforming Key Industries
The increasing penetration of AI-Powered vision systems in healthcare and automotive among other major sectors are fuelling overall growth of the market for AI in Computer Vision. The US market was estimated to be USD 4.46 billion in 2023 and is expected to reach USD 35.49 billion by 2032, with a CAGR of 26.13%. In the field of healthcare, AI-powered imaging technologies offer the advantage of detecting disease early, making a precise diagnosis and individualized treatment. In automotive, computer vision is critical for ADAS and autonomous vehicles for safety and on-the-fly decision-making.
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Leading Market Players with their Product Listed in this Report are:
- NVIDIA Corporation ( Jetson AGX Orin, DeepStream SDK )
- Intel Corporation – ( OpenVINO Toolkit, Intel RealSense )
- Facebook –( DeepFace, DINOv2 )
- Microsoft Corporation –( Azure Computer Vision, Seeing AI )
- Qualcomm ( Snapdragon Neural Processing Engine, Vision Intelligence Platform)
- AWS – ( Amazon Rekognition, AWS Panorama )
- Xilinx –( Kria Vision AI Starter Kit, Zynq UltraScale+ MPSoC )
- BASLER AG – ( Basler ace 2 Cameras, Basler pylon SDK )
- IBM Corporation ( IBM Maximo Visual Inspection, IBM Watson Visual Recognition )
- Google – ( Google Cloud Vision API, MediaPipe )
AI in Computer Vision Market Report Scope:
| Report Attributes | Details |
| Market Size in 2023 | USD 24.26 Billion |
| Market Size by 2032 | USD 173.82 Billion |
| CAGR | CAGR of 24.68% From 2024 to 2032 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segmentation | • By Component-( Hardware , Software) • By Application- ( Industrial , Non-industrial ) • By Function- ( Training, Interference ) • By End-use- ( Automotive, Healthcare, Retail Security And Surveillance, Robotics And Machines, Consumer Electronics ) |
| Key Drivers | • Growing Integration of AI-Powered Vision Systems Across Healthcare and Automotive Industries Accelerates The AI in Computer Vision Market Growth. • Expanding Application of AI Vision Technologies in Smart Retail and Surveillance Offers Lucrative Opportunities for AI in the computer Vision Market. |
The growth is powered by a strong technology environment, research infrastructure and growing capital for artificial intelligence startups. The increasing demand for automation, facial recognition, and smart surveillance especially in technology-driven areas such as North America and Asia-Pacific will also propel adoption and establish computer vision as a keystone of future intelligent systems.
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AI in Computer Vision Market: Key Insights and Segment-Wise Growth Highlights
By End-use
Consumer electronics was the dominant segment in the AI in computer vision market for the year 2023 with a revenue share of 32.60% as AI-based vision technologies have found wide application in smartphones, laptops, and smart home systems. Firms like Meta Platforms helped drive that growth with inventions such as the I-JEPA AI model, released in June 2023 and which can analyze and complete images in a human-like fashion.
The automotive segment is expected to grow at a 28.05% CAGR, mainly dominated by the emergence of autonomous driving and driver assistance solutions associated with NVIDIA’s DRIVE Thor and Ambarella’s AI-imaging SoC.
By Function
In 2023, the training segment dominated the AI in computer vision market, accounting for 68.30% of the revenue as high computational power and large datasets are necessary to create accurate AI models. Microsoft made a significant contribution with its Florence foundation model, which it released in March 2023, was trained on billions of text-image pairs and is part of Azure Cognitive Services.
The inference segment is projected to grow at the highest CAGR of 26.75%, as there is a growing demand of AI applications in real time type. the recent introduction of Pratham (a no-code platform) in February, 2024 by Assert AI, is an effort to simplify inferencing deployment and a push into markets.
By Application
In 2023, the non-industrial sector led the AI in computer vision market with a 53.60% revenue share, ue to high adoption rate in the retail, healthcare and consumer electronics industry. An illustrative example is the release of OpenAI’s GPT-4o in May 2024, a multimodal AI designed to process real-time audio, vision and text, leading to improved virtual assistants and customer service applications.
The industrial sector is projected to grow at the highest CAGR of 26.15%, because of the higher adoption of AI based vision system for the manufacturers. Companies such as Zivid and Mech-Mind Robotics are advancing 3D vision technology to enhance automation and quality.
By Component
In 2023, the software segment led the AI in computer vision market with a 62.40% revenue share, due to the increasing need for complex algorithms for computers to interpret visual data. For example, even though the GPT model, a ruler at text generation, GPT-40, is released in May 2024, it is a multimodal AI that can reason in real time through vision, audio and language, and is a quick reminder at the driving force of software behind AI advancement.
The hardware segment is projected to register the highest CAGR of 26.36%, due to developments in AI-dedicated chips. The introduction of the Hailo-10 at Hailo Technologies in April 2024 is an example how edge AI processing capabilities are increasingly becoming of interest.
Asia Pacific Leads While North America Accelerates in AI Computer Vision Innovation
In 2023, Asia Pacific dominated the AI in computer vision market with a 38.40% revenue share, as a result of investments in technologies and AI major investments in countries such as China, Japan and South Korea. For example, Sense Time announced in December 2023 its new product SenseRobotGo, an AI playing robot, which is able to play with people for Chinese Go, indicating the progression of regional intelligent robot technology.
North America is projected to experience the highest CAGR of 26.84% from 2024 to 2032, period, owing to surge in demand for AI in the automotive, healthcare, and retail industries. April 2024 saw Cognex release the In-Sight L38 3D Vision System, the world’s first AI gadget to provide 3D vision for inspection – whereas companies such as Ocrolus are using computer vision to analyses financial data sign of strong momentum in the area and high innovation potential.
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Recent Developments:
- In Jan 2025, NVIDIA introduced foundation models for RTX AI PC Systems that utilizes GeForce RTX 50 Series GPUs to accelerate AI capabilities for content creation and development. NIM microservices and AI Blueprints streamline the process of creating AI agents and workflows, opening up AI to developers and hobbyists.
- In Jan 2025, Intel unveiled the new 11th Gen Intel® Core™ Ultra processors designed on the AI infused with performance focus for mobile computing. These processors, like the 200V, 200HX, and the 200U series, provide businesses, creators, and gamers the edge with the best-in-class efficiency, AI acceleration, and edge computing.
Table of Contents - Major Points
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
5.1 Salary & Compensation Insights, 2023
5.2 Recruitment Efficiency & Hiring Trends, 2023
5.3 Candidate Behavior & Preferences, 2023
5.4 Fraud & Security in Online Hiring
6. Competitive Landscape
7. AI in Computer Vision Market Segmentation, by End-use
8. AI in Computer Vision Market Segmentation, by Function
9. AI in Computer Vision Market Segmentation, by Application
9. AI in Computer Vision Market Segmentation, by Component
10. Regional Analysis
11. Company Profiles
12. Use Cases and Best Practices
13. Conclusion
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