Global AI in Computer Vision Market Size is valued at USD 19.0 Bn in 2024 and is predicted to reach USD 172.6 Bn by the year 2034 at a 24.8% CAGR during the forecast period for 2025-2034.
Computer Vision (CV) empowers machines to interpret and analyze digital images and videos using computational techniques. By mimicking human vision, CV enables automated detection, recognition, and understanding of visual inputs from cameras or sensors. Unlike human vision, computer vision systems operate with exceptional accuracy and consistency, reducing errors and proving invaluable in critical applications—such as early cancer detection through medical image analysis.
Businesses across industries leverage CV and machine learning to derive actionable insights from vast visual datasets, automating repetitive tasks, boosting operational efficiency, detecting fraud, enhancing customer experiences, & accelerating the development of innovative products and services.
In autonomous vehicles, computer vision processes data from cameras, LiDAR, and radar to perceive and navigate the environment. It enables real-time decision-making through traffic sign recognition, object detection, and lane tracking. AI-powered vision also drives Advanced Driver Assistance Systems (ADAS), supporting features like adaptive cruise control, lane-keeping, parking assistance, and collision avoidance. These systems enhance driver safety by instantly identifying obstacles, vehicles, and pedestrians.
The AI in the computer vision market is segmented into application, function, technology, vertical, and offering. The application segmentation includes quality assurance & inspection, measurement, identification, predictive maintenance, positioning & guidance. As per the function, the market is divided into training and inference. Whareas the technology segment divided into machine learning and generative AI. Based on the Vertical, the market is divided into automotive, consumer electronics, healthcare, retail, security and surveillance, manufacturing, agriculture, transportation & logistics, and other verticals. According to the offering, the market is divided into cameras, frame grabbers, optics, LED lighting, processors, AI vision software, and AI platforms.
Computer vision technologies in the automotive industry offer unmatched accuracy when checking cars for flaws like scratches or misassembled parts. Businesses like Audi have reduced the number of defective parts produced by using AI vision to find tiny flaws in sheet metal components. By streamlining production procedures and enhancing quality assurance, this lowers expenses and boosts productivity. To improve vehicle functionality, the automobile industry uses computer vision in conjunction with machine learning, sensor fusion, and the Internet of Things. For instance, in complex driving situations, vision-based systems use data from vehicle-to-everything (V2X) communication to make decisions in real time. High-performance computing for autonomous features is further supported by the integration of LiDAR, GPUs, and AI chips. Intel published OpenVINO 2024.5 in November 2024, which optimized AI vision applications for use in automobiles. It facilitates effective deployment in local, cloud, and edge contexts, improving autonomous driving systems' problem detection and safety compliance.
AI vision software is essential to computer vision since it makes it possible for fundamental features, including segmentation, classification, object identification, facial recognition, and image recognition. It is a crucial part of contemporary AI ecosystems because of its scalability and adaptability, which enable smooth implementation across a variety of devices and sectors. Furthermore, real-time processing is supported, and its application area is expanded by the integration of AI software platforms with cloud and edge computing environments. As technology businesses concentrate on integrating cutting-edge deep learning models like Convolutional Neural Networks & Transformers to improve performance and capabilities, the segment continues to benefit from high levels of R&D expenditure. For instance, Amazon Web Services launched AWS Panorama, a software development kit enhancing computer vision capabilities in the Asia-Pacific region. It supports edge devices for tasks like quality control and real-time analytics, driving adoption in automotive and manufacturing.
The market for AI in computer vision is dominated by the Asia Pacific region. The rapid advancement of technology, the increasing adoption of AI solutions, and robust governmental support in key economies. Major industries such as retail, manufacturing, healthcare, and automotive are propelling the necessity for AI to augment operational efficiency via automation and boost consumer experience. Also the collaborations enhance AI vision software for autonomous vehicles, improving object detection and safety features in Japan and China.
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Report Attribute |
Specifications |
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Market Size Value In 2024 |
USD 19.0 Bn |
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Revenue Forecast In 2034 |
USD 172.6 Bn |
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Growth Rate CAGR |
CAGR of 24.8% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Mn and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Application, Function, Technology, Vertical, Offering |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South Korea; Southeast Asia; |
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Competitive Landscape |
NVIDIA Corporation, Microsoft Corporation, Intel Corporation, Alphabet Inc., Amazon.com, Inc., Cognex Corporation, Qualcomm Technologies, Inc., Sony Group Corporation, OMRON Corporation, KEYENCE CORPORATION, SICK AG, Teledyne Technologies, Texas Instruments Incorporated, Basler AG, Hailo Technologies Ltd. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing and Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI in Computer Vision Market Snapshot
Chapter 4. Global AI in Computer Vision Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Porter's Five Forces Analysis
4.7. Incremental Opportunity Analysis (US$ MN), 2024-2034
4.8. Competitive Landscape & Market Share Analysis, By Key Player (2023)
4.9. Use/impact of AI on AI in Computer Vision Market Industry Trends
4.10. Global AI in Computer Vision Market Penetration & Growth Prospect Mapping (US$ Mn), 2021-2034
Chapter 5. AI in Computer Vision Market Segmentation 1: By Function, Estimates & Trend Analysis
5.1. Market Share by Function, 2024 & 2034
5.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Function:
5.2.1. Training
5.2.2. Inference
Chapter 6. AI in Computer Vision Market Segmentation 2: By Application, Estimates & Trend Analysis
6.1. Market Share by Application, 2024 & 2034
6.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Application:
6.2.1. Quality Assurance & Inspection
6.2.2. Measurement
6.2.3. Identification
6.2.4. Predictive Maintenance
6.2.5. Positioning & Guidance
Chapter 7. AI in Computer Vision Market Segmentation 3: By Technology, Estimates & Trend Analysis
7.1. Market Share by Technology, 2024 & 2034
7.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Technology:
7.2.1. Machine Learning
7.2.2. Generative AI
Chapter 8. AI in Computer Vision Market Segmentation 4: By Vertical, Estimates & Trend Analysis
8.1. Market Share by Vertical, 2024 & 2034
8.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Vertical:
8.2.1. Automotive
8.2.2. Consumer Electronics
8.2.3. Healthcare
8.2.4. Retail
8.2.5. Security And Surveillance
8.2.6. Manufacturing
8.2.7. Agriculture
8.2.8. Transportation & Logistics
8.2.9. Other Verticals
Chapter 9. AI in Computer Vision Market Segmentation 5: By Offering, Estimates & Trend Analysis
9.1. Market Share by Offering, 2024 & 2034
9.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Offering:
9.2.1. Cameras
9.2.2. Frame Grabbers
9.2.3. Optics
9.2.4. Led Lighting
9.2.5. Processors
9.2.5.1. CPU
9.2.5.2. GPU
9.2.5.3. ASIC
9.2.5.4. FPGA
9.2.6. AI Vision Software
9.2.7. AI Platforms
Chapter 10. AI in Computer Vision Market Segmentation 6: Regional Estimates & Trend Analysis
10.1. Global AI in Computer Vision Market, Regional Snapshot 2024 & 2034
10.2. North America
10.2.1. North America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
10.2.1.1. US
10.2.1.2. Canada
10.2.2. North America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Function, 2021-2034
10.2.3. North America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.2.4. North America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
10.2.5. North America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Vertical, 2021-2034
10.2.6. North America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
10.3. Europe
10.3.1. Europe AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
10.3.1.1. Germany
10.3.1.2. U.K.
10.3.1.3. France
10.3.1.4. Italy
10.3.1.5. Spain
10.3.1.6. Rest of Europe
10.3.2. Europe AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Function, 2021-2034
10.3.3. Europe AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.3.4. Europe AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
10.3.5. Europe AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Vertical, 2021-2034
10.3.6. Europe AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
10.4. Asia Pacific
10.4.1. Asia Pacific AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
10.4.1.1. India
10.4.1.2. China
10.4.1.3. Japan
10.4.1.4. Australia
10.4.1.5. South Korea
10.4.1.6. Hong Kong
10.4.1.7. Southeast Asia
10.4.1.8. Rest of Asia Pacific
10.4.2. Asia Pacific AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Function, 2021-2034
10.4.3. Asia Pacific AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.4.4. Asia Pacific AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts Vertical, 2021-2034
10.4.5. Asia Pacific AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
10.5. Latin America
10.5.1. Latin America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
10.5.1.1. Brazil
10.5.1.2. Mexico
10.5.1.3. Rest of Latin America
10.5.2. Latin America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Function, 2021-2034
10.5.3. Latin America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.5.4. Latin America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
10.5.5. Latin America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Vertical, 2021-2034
10.5.6. Latin America AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
10.6. Middle East & Africa
10.6.1. Middle East & Africa Wind Turbine Rotor Blade Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
10.6.1.1. GCC Countries
10.6.1.2. Israel
10.6.1.3. South Africa
10.6.1.4. Rest of Middle East and Africa
10.6.2. Middle East & Africa AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Function, 2021-2034
10.6.3. Middle East & Africa AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
10.6.4. Middle East & Africa AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
10.6.5. Middle East & Africa AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Vertical, 2021-2034
10.6.6. Middle East & Africa AI in Computer Vision Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2021-2034
Chapter 11. Competitive Landscape
11.1. Major Mergers and Acquisitions/Strategic Alliances
11.2. Company Profiles
11.2.1. NVIDIA Corporation
11.2.1.1. Business Overview
11.2.1.2. Key Function/Service Overview
11.2.1.3. Financial Performance
11.2.1.4. Geographical Presence
11.2.1.5. Recent Developments with Business Strategy
11.2.2. Microsoft Corporation
11.2.3. Intel Corporation
11.2.4. Alphabet Inc.
11.2.5. Amazon.com, Inc.
11.2.6. Cognex Corporation
11.2.7. Qualcomm Technologies, Inc.
11.2.8. Sony Group Corporation
11.2.9. OMRON Corporation
11.2.10. KEYENCE CORPORATION
11.2.11. SICK AG
11.2.12. Teledyne Technologies
11.2.13. Texas Instruments Incorporated
11.2.14. Basler AG
11.2.15. Hailo Technologies Ltd.
Global AI in Computer Vision Market - By Application
Global AI in Computer Vision Market – By Function
Global AI in Computer Vision Market – By Technology
Global AI in Computer Vision Market- By Vertical
Global AI in Computer Vision Market – By Platform Access Model
Global AI in Computer Vision Market – By Offering
Global AI in Computer Vision Market – By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
Rest of the Middle East and Africa
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
