Tuesday, 02 January 2024 12:17 GMT

Computer Vision Systems Market Expected To Reach USD 75.52 Billion By 2032, Fueled By Widespread AI And ML Adoption Worldwide SNS Insider


(MENAFN- GlobeNewsWire - Nasdaq) The market for computer vision systems is growing quickly, mostly due to the growing use of machine learning and artificial intelligence (AI) technologies across a range of industries.

Austin, Sept. 30, 2025 (GLOBE NEWSWIRE) -- The Computer Vision Systems Market Size was valued at USD 19.29 billion in 2024 and is expected to reach USD 75.52 billion by 2032 and grow at a CAGR of 18.63% over the forecast period 2025-2032.

Increasing use of computer vision due to the need for automation in the logistics, manufacturing, quality control, and medical diagnostics industries. Real-time processing made possible by developments in 3D vision, high-resolution imagery, and synchronized sensors to increase accuracy in areas like gesture tracking, facial identification, object detection, and automated optical inspection are some of the noteworthy results. Organizations may implement scalable and low-latency computer vision solutions thanks to the expanding trend of edge computing and cloud-based deployment models, which greatly boosts industry growth. Over 1,200 warehouses and logistics centers currently use real-time item detection, which enhances automated sorting and inventory tracking, according to the report.


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Key Players:

  • NVIDIA
  • Intel
  • AMD
  • Qualcomm
  • Ambarella
  • Teledyne Technologies
  • Omron Corporation
  • Keyence Corporation
  • Microsoft
  • Amazon Web Services (AWS)
  • Google Cloud
  • IBM
  • OpenCV
  • Roboflow
  • Matrox Imaging
  • Allied Vision Technologies
  • Mobileye (Intel)
  • Tesla
  • Aptiv
  • World Labs

Computer Vision Systems Market Report Scope:

Report Attributes Details
Market Size in 2024 USD 19.29 Billion
Market Size by 2032 USD 75.52 Billion
CAGR CAGR of 18.63% From 2025 to 2032
Base Year 2024
Forecast Period 2025-2032
Historical Data 2021-2023
Report Scope & Coverage Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments . By Component (Hardware, Software, Services)
. By Deployment Mode (Cloud-based, On-premises, Edge computing devices)
. By Application (Facial recognition, Image classification, Object detection, Object tracking, Optical Character Recognition (OCR), Image Segmentation, Automated optical inspection, 3D vision and depth sensing, Gesture recognition, Others)
. By Industry Vertical (Manufacturing, Healthcare, Retail, Automotive, Security and surveillance, Agriculture, Smart cities, Consumer electronics, Energy and utilities, Others)
Customization Scope Available upon request
Pricing Available upon request

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Segmentation Analysis:

By Component, in 2024, Hardware Segment Led the Market with a Share 58.40%, while Services are the Fastest-growing Segment with a CAGR of 20.38%

Hardware component segment occupies a majority share in the Computer Vision Systems Market, largely owing to the large-scale deployment of high-resolution cameras, sensors and GPUs across various industrial verticals. The Services segment is experiencing the highest growth, supported by the growing need for software integration, training and support with AI models, maintenance, consulting, and assistance with cloud-based deploy.

By Deployment Mode, in 2024, On-premises Dominated the Market with a Share of 65.10%, while Edge Computing Devices Fastest-growing Segment with a CAGR 19.96%

On-premises deployment is leading the Computer Vision Systems Market, as many organizations like to process their sensitive data locally in order to guarantee security and have control over their critical operations, especially in industries, such as healthcare, manufacturing, and automotive Edge computing devices are having the highest growth rate due to the demand for data processing at real time, low latency applications, and AI based decision making at-edge level.

By Application, in 2024, Facial Recognition Led the Market with a Share 25.07%, while Object Detection the Fastest-growing Segment with a CAGR 20.24%

Facial Recognition application segment dominated the Computer Vision Systems Market globally, in which computer vision technology is extensively adopted by the government, retail, and corporate sectors for security, surveillance, access control, and identity verification. Object Detection is growing fastest due to increasing need for real-time tracking, anomaly detection, and process optimization from autonomous vehicles, robotics, industrial automation, smart logistics, and others.

By Industry Vertical, in 2024, Manufacturing Dominated the Market with a Share of 32.03%, while Healthcare is the Fastest-growing Segment with a CAGR of 20.91%

Manufacturing tops the industry vertical in the Computer Vision Systems Market, as computer vision is increasingly used for factory deployment for quality inspection, defect detection, assembly verification, and automation globally. Healthcare is experiencing the quickest growth, which is attributed to the rise in uptake of diagnostic imaging, surgical assistance, patient monitoring, and medical image analysis powered by AI.

In 2024, North America Led the Market in 2024; Asia Pacific is Projected to be the Fastest Growing Region in the Market During 2025-2032

The computer vision systems market is propelled by the North America region as the market share 32.50%, owned by the early adopters of AI, machine learning, and advanced imaging technologies for various industries. Asia Pacific is a key and fast-growing market for Computer Vision System with a CAGR 19.74%, due to the rapid industrialization and urbanization along with the adoption of the latest technologies.

Recent Developments:

  • In May 2024 , Ambarella launched the CV75S AI SoC family built on 5nm technology, enabling power-efficient multi-modal vision-language models and AI inference for cameras and robotics.
  • In April 2024 , Intel announced the Gaudi 3 AI accelerator at Intel Vision 2024, enhancing inference throughput and efficiency for large AI models in data centers and edge devices.

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Exclusive Sections of the Report (The USPs):

  • Algorithm & Model Performance Metrics – helps you assess the efficiency and maturity of computer vision systems through accuracy and precision rates, real-time processing latency, and the frequency of model updates or optimizations.
  • Human-Machine Interaction Metrics – helps you understand the impact of CV adoption on workforce efficiency by tracking reductions in manual errors, improvements in operator productivity, and user engagement across retail, AR/VR, and industrial applications.
  • Security & Fraud Detection Metrics – helps you evaluate the reliability of CV systems in high-risk environments by analyzing false positive/negative rates, anomaly detection accuracy, and threat response time in surveillance and security applications.
  • Product Lifecycle & Reliability Index – helps you measure the operational resilience of CV hardware by monitoring metrics like mean time between failures (MTBF), lifecycle duration of sensors and cameras, and maintenance cost savings achieved through automation.
  • Real-Time Processing Efficiency – helps you benchmark system responsiveness by analyzing average milliseconds per frame in real-time CV applications, enabling performance comparisons across industrial and edge deployments.
  • Operational Cost Optimization – helps you quantify ROI and cost-effectiveness by assessing reductions in maintenance expenses and productivity gains from automation-driven CV integration.

About Us:

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