AI In Computer Vision Market Size, Share & Trends

Report Code SE 6211
Published in Dec, 2024, By MarketsandMarkets™
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AI in Computer Vision Market by Offering (Cameras, Frame Grabbers, Optics, LED Lighting, CPU, GPU, ASIC, FPGA, AI Vision Software, AI Platform), Technology (Machine Learning, GenAI), Function (Training, Inference), Application - Global Forecast to 2030

 

AI in Computer Vision Market Size, Share & Trends

The global AI in computer vision market is projected to reach USD 63.48 billion in 2030 from USD 23.42 billion in 2025; it is expected to grow at a CAGR of 22.1% from 2025 to 2030. Computer vision aided by artificial intelligence deals with leveraging AI to make it possible for machines to analyze and interpret what they see from the world, such as images and videos. The subfield of AI is used to transform computer science with machine learning and undertake activities such as object identification, image classification, and video analysis. This growth is attributed to the rising trend of using automation and data analytics in various industries, including healthcare, automotive, retail, and security. Its expansion can be attributed to the increasing need for applications like face recognition, traffic analytics, defects in manufacturing, etc. The market growth is driven by developments in AI hardware and AI platforms, the enhancement of ML algorithms, and rising edge computing investments.

AI in Computer Vision Market

Attractive Opportunities in the AI in Computer Vision Market

ASIA PACIFIC

The growth of the AI in computer vision market in Asia Pacific is driven by advancements in machine learning, increasing adoption across industries, and government support for AI initiatives.

The market growth can be attributed to growing adoption of edge computing and IoT-enabled vision systems.

The presence of established AI in computer vision solution providers, primarily in the US, known for their technological expertise, contributes to the growth of the market in North America.

Acquisitions and product launches & developments are expected to offer lucrative growth opportunities for the market players during the next five years.

Complexities and high costs associated with maintenance and system upgrades pose challenges to the players in the AI in computer vision market.

Global AI in Computer Vision Market Dynamics

DRIVER: Advancements in hardware, such as GPUs, TPUs, and edge devices

Enhancements in hardware technology have emerged as a significant factor that has boosted the development of Al-facilitated computer vision techniques. GPUs, TPUs, and edge devices have evolved with revolutionary technological change, boosting computational speed and efficacy. These enhancements in the overall AI hardware allow for profound architectures in neural networks and substantial machine learning algorithms to analyze visual data. For instance, in December 2024, Intel Corporation introduced the new Intel Arc B-Series GPUs like Intel Arc B580 and B570. These are also based on such a strategy and are highlighted to deliver the industry’s top performance value and are designed to speed up Al's workload.

The availability of AI hardware such as AI cameras, sensors, frame grabbers, optics, and others has mainly influenced computer vision computation by enabling live image and video processing, identification of detailed patterns, and refined training of deep neural networks. Supervising chips with specific Al acceleration, enhanced memory bandwidth, and energy-progressive structures also facilitate market growth. These technologies minimize computational hindrances, decrease processing delays, and make the Al and visual intelligence applicable and more viable for commercial and personal use. This enhanced interactivity between hardware and optimized algorithms further boosts the market growth. .

RESTRAINTS: Data privacy and security concerns

Due to data privacy and security legalities, the growth of AI in computer vision has considerable limitations. Most of these technologies involve managing and analyzing personal data such as images, videos, and biometric data, which are prone to misuse or breach. Such instances may violate privacy rights, legal grievances, and ethical issues, making it hard for organizations to implement such solutions. Legal address and compliance expenses also contribute to the business pressures, alongside identity loss due to improper practices that hinder potential clients and partner opportunities.

AI in computer vision can be affected by algorithmic bias and discrimination in various applications such as face recognition and security. This leads to unfair market outcomes and a slow market adoption process. Also, when making decisions based on sensitive information, the secrets surrounding AI algorithms lack credibility. Therefore, organizations should pay great attention to data management and incorporate technical solutions to enhance privacy. Achieving legal compliance is also imperative in the development of AI systems. Such measures are necessary to avoid various challenges across healthcare, retail, manufacturing, automotive, and security sectors.

 

OPPORTUNITY: Rapid innovations in healthcare

Rapid innovations in the healthcare domain open huge opportunities for Al in computer vision, especially regarding medical imaging and diagnostics. As healthcare technology advances, Al-powered systems have become necessary for analyzing images to identify health conditions and subsequently decide on treatment.

The need for Al-driven visual analysis tools in healthcare is increasing, especially for early disease detection and personalized treatment plans. These developments are expanding the scope of applications for Al in computer vision, leading to heightened demand for advanced imaging solutions. For instance, in April 2024, the World Health Organization (WHO) launched S.A.R.A.H., a digital health assistant that uses Al in computer vision to analyse medical images and enhance patient interaction. This innovation emphasizes the growing role of Al in healthcare, offering more avenues for growth in the computer vision market.

Increasing investment in the healthcare sector is another factor fuelling the market's growth. In June, the Merck Global Health Innovation Fund led a USD 45 million Series D funding round for Qure AI to extend the reach of its AI-enabled imaging solutions to US markets. Qure AI deployed around 2,700 imaging sites worldwide with AI-enhanced detection for diseases, including tuberculosis, lung cancer, and stroke. Such investments support the AI in computer vision market growth.

CHALLENGE: High data storage and management cost

The rapid growth of Al in computer vision needs to be improved by the high costs of storing and managing data, which are essentials for large-scale projects that use massive datasets. Training Al models requires much storage, with some datasets consuming terabytes, especially when it involves high-resolution images and videos. This results in significant financial investments in data centers, cloud storage, and advanced data management systems, which can be a big burden, especially for smaller organizations and startups. These high costs make an entry barrier, restricting market participation and innovation in Al-driven computer vision solutions.

The best solution is to innovate and optimize data storage and management for these organizations. The technology of edge inferencing has become one way of spreading the data processing process away from central storage. Techniques in compressing data, including the machine learning-based image representation technique, are used to minimize storage needs without sacrificing performance. Solutions on cloud storage can offer a pay-as-you-go model that accommodates any organization's size. In addition, federated learning, which allows model training on decentralized devices, minimizes data transfer and storage expenses. These methods not only alleviate financial burdens but also promote the efficiency and accessibility of AI in computer vision, opening advanced visual intelligence to greater participation in the market.m.

AI in Computer Vision Market Ecosystem

The AI in computer vision ecosystem comprises of raw data providers, data processors, cloud storage providers, software and platform developers, and end users. Companies such as NVIDIA Corporation (US), AMD (US), Intel Corporation (US), Qualcomm Technologies, Inc. (US), and others fall into the categories of data processors. Meanwhile, Microsoft Corporation (US), Alphabet Inc. (US), Amazon.com, Inc. (US), and others fall into the category of cloud storage providers. These products are used in applications such as quality assurance & inspection, measurement, identification, predictive maintenance, positioning, and guidance.

Top Companies in AI in Computer Vision Market
 

Based on application, the quality assurance and inspection segment is expected to record the highest CAGR during the forecast period.

AI in computer vision for quality assurance and inspection is becoming popular quickly as industries try to improve product quality. Hand inspection or rule-based vision systems are common practices; however, these methods are neither efficient nor very accurate or scalable. As a direct result of implementing these systems, defects' identification, classification, and localization are entirely automatic.

These systems are used in automobiles, electronics, especially medicine-producing organizations, manufacturing, and many other industries to guarantee quality with fewer mistakes and costs.

Key factors driving this growth include manufacturers’ focus on efficiency and cost reduction. AI tools like Google Cloud’s Visual Inspection AI enable faster, more accurate defect detection, decreasing reliance on manual labor. These scalable solutions enhance quality control across production lines and facilities. Additionally, increased investments are propelling market growth. For example, Eigen Innovations’ USD 2.6 million funding in October 2024 aims to develop AI-enabled thermal inspection solutions, enabling factories to conduct fully automated in-line inspections for consistent product quality and reliability.

AI Vision systems have also proved their versatility across many industries. They examine the quality of welding seams and paints in automotive manufacturing and the faults in the wafers and the chips in semiconductor fabrication. These factors lead to tremendous growth in the market.

Based on function, the training segment is expected to record the highest CAGR during the forecast period.

The training segment constitutes the largest market in the AI in computer vision market since training is a preliminary step for an AI system to understand and interpret visual data. Training of an AI model requires using large data sets in machine learning algorithms to make them learn to classify, detect objects and make decisions. This involves many steps, from selecting the most suitable algorithms, curating datasets, and tuning the models for the best performance. By dealing with variables, inconsistencies, and outliers, training makes AI systems always improve as time goes by, making them proficient and efficient in various tasks.

A significant aspect that is boosting the dominance of the training segment is the insatiable appetite for high-quality and varied datasets. The same AI models are deployed to critical tasks in industries like diagnostics in healthcare, defect detection in automotive, and customer purchase behavior monitoring in retail. Synthetic data has become more used for training purposes, especially where real-life datasets are limited due to privacy regulation concerns. This approach enables practical model training on a wider scale and even solves data scarcity issues. Thus, the training segment is driving growth in the AI in computer vision market.

Based on Region, Asia Pacific Will be the Fastest-Growing Market During the Forecasted Period

The Asia Pacific region dominates the market for AI in computer vision. This growth is driven by the rapid pace of technological advancement, increasing adoption of AI solutions, and solid government support in key economies like China, Japan, South Korea, and India. Major industries such as retail, manufacturing, healthcare, and automotive push the demand for AI to drive greater operational efficiency through automation and customer experience improvement. China has a very powerful AI ecosystem because of government support. Different industries, from manufacturing to transportation, rely on AI-powered computer vision for intelligent quality assurance and fully autonomous systems. Japan is increasing its capabilities in AI through technological innovation and improvement in AI infrastructure coupled with the initiative to strengthen the digital transformation of industries.

South Korea's focus on R&D in AI, complemented by AI integration of industry and logistics, is further driving growth. India also has a mission on AI for localized AI capability development in various areas like healthcare, agriculture, and manufacturing. Such driving factors include the setup of large datasets, developing machine-learning algorithms, and cloud penetration. Thus, all these factors collectively place this region as a leader of AI in the computer vision market while driving innovation for adoption across various other industries.

LARGEST MARKET SHARE IN 2029
CHINA FASTER-GROWING MARKET IN REGION
AI in Computer Vision Market Size and Share

Recent Developments of AI in Computer Vision Market

  • In November 2024, Intel Corporation released a new version, Intel OpenVINO 2024.5, that advances AI in computer vision with optimized runtimes for Intel hardware and enhanced support for large language models. It enables efficient AI deployment across edge, cloud, and local environments for vision applications.
  • In November 2024, Texas Instruments Incorporated introduced the TMS320F28P55x and F29H85x microcontroller series, integrating edge AI and advanced real-time control capabilities. These MCUs enhance fault detection accuracy, decision-making speed, and safety compliance for automotive and industrial applications, advancing system efficiency and sustainability.
  • In October 2024, Teledyne FLIR LLC launched Prism AIMMGen, an ITAR-free AI model generation service that automates the creation of AI and machine learning models using synthetically generated data. This innovative tool significantly reduces costs and development timelines by generating millions of annotated synthetic images, enabling rapid fine-tuning of models for commercial, defense, and first-response applications.
  • In September 2024, Basler AG introduced pylon AI, an innovative AI image analysis software designed for precise and efficient applications. With features like performance benchmarking and no programming requirements, pylon AI simplifies entry into advanced image analysis for diverse industries.
  • In June 2024, Intel Corporation released an updated version of its AI vision software—Intel® Geti™ 2.0.0, offering enhanced features for data labeling, model training, and inferencing to accelerate computer vision development. Existing customers can also upgrade to leverage the latest advancements in Vision AI software.

Key Market Players

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Scope of the Report

Report Attribute Details
Market size available for years 2021–2030
Base year considered 2024
Forecast period 2025–2030
Forecast units Value (USD Million)
Segments Covered By Offering, By Technology, By Function, By Application, By End User, and By Region
Regions covered North America, Europe, Asia Pacific, and Rest of the World

Key Questions Addressed by the Report

Which are the major companies in the AI in computer vision market? What are their significant strategies to strengthen their market presence?
The major companies in the AI in computer vision market are NVIDIA Corporation (US), Microsoft Corporation (US), Intel Corporation (US), Alphabet Inc. (US), and Amazon.com, Inc. (US). These players adopt product launches, developments, and acquisitions as major strategies.
What is the potential market for AI in computer vision regarding the region?
The Asia Pacific region is expected to dominate the AI in computer vision market due to advancements in AI technology and increased adoption across various sectors, such as healthcare, manufacturing, and retail, in countries such as China, South Korea, Japan, and India.
What are the opportunities for new market entrants?
There are significant opportunities in the AI in computer vision market for startup companies. These companies provide innovative and diverse product portfolios.
What are the drivers and restraints for the AI in computer vision market?
Factors such as advancements in hardware such as GPUs, TPUs, and edge devices are fueling the growth. Data privacy and security concerns are some of the restraints.
What are the major AI in computer vision end users expected to drive the market's growth in the next five years?
The major end users for AI in computer vision are consumer electronics, security & surveillance, automotive, healthcare, and manufacturing.

 

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Table of Contents

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TITLE
PAGE NO
INTRODUCTION
15
RESEARCH METHODOLOGY
20
EXECUTIVE SUMMARY
25
PREMIUM INSIGHTS
30
MARKET OVERVIEW
35
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
  • 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER’S BUSINESS
  • 5.4 PRICING ANALYSIS
    AVERAGE SELLING PRICE TREND OF KEY PLAYERS,
    AVERAGE SELLING PRICE TREND, BY REGION
  • 5.5 VALUE CHAIN ANALYSIS
  • 5.6 ECOSYSTEM ANALYSIS
  • 5.7 TECHNOLOGY ANALYSIS
    KEY TECHNOLOGY
    - Deep Learning
    - Edge Computing
    COMPLEMENTARY TECHNOLOGY
    - Cloud Computing
    ADJACENT TECHNOLOGY
    - Natural language processing
  • 5.8 PATENT ANALYSIS
  • 5.9 TRADE ANALYSIS
    KEY CONFERENCES AND EVENTS (2024-2025)
    CASE STUDY ANALYSIS
    INVESTMENT AND FUNDING SCENARIO
    TARIFF AND REGULATORY LANDSCAPE
    - Tariff Data (HS code 8471 - Automatic data-processing machines and units thereof; magnetic or optical readers, machines for transcribing data onto data media in coded form and machines for processing such data, n.e.s.)
    - Regulatory Bodies, Government Agencies, and Other Organizations
    - Key Regulations
    PORTERS FIVE FORCE ANALYSIS
    - Threat from New Entrants
    - Threat of Substitutes
    - Bargaining Power of Suppliers
    - Bargaining Power of Buyers
    - Intensity of Competitive Rivalry
    KEY STAKEHOLDERS AND BUYING CRITERIA
    - Key Stakeholders in Buying Process
    - Buying Criteria
AI IN COMPUTER VISION MARKET, BY VARIOUS MACHINE LEARNING MODELS (Q)
70
  • 6.1 INTRODUCTION
  • 6.2 SUPERVISED LEARNING
  • 6.3 UNSUPERVISED LEARNING
  • 6.4 REINFORCEMENT LEARNING
AI IN COMPUTER VISION MARKET, BY USE CASE (Q)
80
  • 7.1 INTRODUCTION
  • 7.2 OBJECT DETECTION
  • 7.3 IMAGE RECOGNITION
  • 7.4 FACIAL RECOGNITION
  • 7.5 MOTION ANALYSIS
  • 7.6 MACHINE VISION
AI IN COMPUTER VISION MARKET, BY OFFERING
95
  • 8.1 INTRODUCTION
  • 8.2 CAMERAS
  • 8.3 FRAME GRABBERS
  • 8.4 OPTICS
  • 8.5 LED LIGHTING
  • 8.6 PROCESSORS
    CPU
    GPU
    ASIC
    FPGA
  • 8.7 AI VISION SOFTWARE
  • 8.8 AI PLATFORM
AI IN COMPUTER VISION MARKET, BY TECHNOLOGY
115
  • 9.1 INTRODUCTION
  • 9.2 MACHINE LEARNING
    DEEP LEARNING
    CONVOLUTIONAL NEURAL NETWORKS
  • 9.3 GENERATIVE AI
    AI IN COMPUTER VISION MARKET, BY FUNCTION
  • 9.4 INTRODUCTION
  • 9.5 TRAINING
  • 9.6 INFERENCE
AI IN COMPUTER VISION MARKET, BY APPLICATION
125
  • 10.1 INTRODUCTION
  • 10.2 QUALITY ASSURANCE & INSPECTION
    DEFECT DETECTION
    SURFACE INSPECTION
    CONTAINMENT DETECTION
    PACKAGING & LABELLING INSPECTION
  • 10.3 MEASUREMENT
    3D MEASUREMENT & PROFILING
    SITE MEASUREMENT & MONITORING
  • 10.4 IDENTIFICATION
    PERSON IDENTIFICATION
    PRODUCT RECOGNITION
  • 10.5 PREDICTIVE MAINTENANCE
    MACHINE HEALTH MONITORING
    WEAR & TEAR DETECTION
  • 10.6 POSITIONING & GUIDANCE
    ROBOTIC ARM GUIDANCE
    AUTOMATED GUIDED VEHICLES
AI IN COMPUTER VISION MARKET, BY END-USER
145
  • 11.1 INTRODUCTION
  • 11.2 AUTOMOTIVE
    ADAS
    IN-VEHICLE MONITORING SYSTEMS
    AUTONOMOUS VEHICLES
  • 11.3 CONSUMER ELECTRONICS
    SMARTPHONES AND TABLETS
    SMART HOME DEVICES
    AR/VR
  • 11.4 HEALTHCARE
    MEDICAL IMAGING
    PATIENT MONITORING
    SURGICAL ASSITANCE
  • 11.5 RETAIL
    CUSTOMER EXPERIENCE MANAGEMENT
    INVENTORY MANAGEMENT
  • 11.6 SECURITY & SURVEILLANCE
    CRIME DETECTION
    INTRUSION DETECTION
    LICENSE PLATE RECOGNITION
  • 11.7 MANUFACTURING
    QUALITY INSPECTION
    PREDICTIVE MAINTENANCE
  • 11.8 AGRICULTURE
    CROP MONITORING
    LIVESTOCK MANAGEMENT
    PRECISION AGRICULTURE
  • 11.9 TRANSPORTATION & LOGISTICS
    FLEET MANAGEMENT
    DRIVER BEHAVIOUR ANALYSIS
    ROUTE OPTIMIZATION
    INVETORY TRACKING
    OTHERS
AI IN COMPUTER VISION MARKET, BY REGION
185
  • 12.1 INTRODUCTION
  • 12.2 NORTH AMERICA
    MACROECONOMIC OUTLOOK
    US
    CANADA
    MEXICO
  • 12.3 EUROPE
    MACROECONOMIC OUTLOOK
    UK
    GERMANY
    FRANCE
    ITALY
    SPAIN
    REST OF EUROPE
  • 12.4 ASIA PACIFIC
    MACROECONOMIC OUTLOOK
    CHINA
    JAPAN
    SOUTH KOREA
    INDIA
    REST OF ASIA PACIFIC
  • 12.5 ROW
    MACROECONOMIC OUTLOOK
    MIDDLE EAST
    - GCC Countries
    - Rest of Middle East
    AFRICA
    SOUTH AMERICA
AI IN COMPUTER VISION MARKET, COMPETITIVE LANDSCAPE
210
  • 13.1 INTRODUCTION
  • 13.2 KEY PLAYER STRATEGIES/RIGHT-TO-WIN
  • 13.3 REVENUE ANALYSIS OF TOP 5 PLAYERS
  • 13.4 MARKET SHARE ANALYSIS
  • 13.5 COMPANY VALUATION AND FINANCIAL METRICS
  • 13.6 BRAND/PRODUCT COMPARISON
  • 13.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
    STARS
    EMERGING LEADERS
    PERVASIVE PLAYERS
    PARTICIPANTS
    COMPANY FOOTPRINT: KEY PLAYERS, 2024
    - Company Footprint
    - Region Footprint
    - Technology Footprint
    - Offering Footprint
    - Application Footprint
    - Function Footprint
    - End-user Footprint
  • 13.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
    PROGRESSIVE COMPANIES
    RESPONSIVE COMPANIES
    DYNAMIC COMPANIES
    STARTING BLOCKS
    COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    - Detailed List of Key Startups/SMEs
    - Competitive Benchmarking of Key Startups/SMEs
  • 13.9 COMPETITIVE SITUATION AND TRENDS
AI IN COMPUTER VISION MARKET, COMPANY PROFILES
240
  • 14.1 KEY PLAYERS
    NVIDIA CORPORATION
    MICROSOFT CORPORATION
    ALPHABET CORPORATION
    AWS
    BASLER AG
    COGNEX CORPORATION
    INTEL CORPORATION
    KEYENCE CORPORATION
    OMRON CORPORATION
  • 14.2 OTHER PLAYERS
    SIGHTHOUND
    NEURALA
    DATAGEN
    GRAPHCORE
    ROBOTIC VISION TECHNOLOGIES
    CUREMETRIX
    SNORKEL AI
    AMP
    VISO.AI
APPENDIX
270
  • 15.1 DISCUSSION GUIDE
  • 15.2 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
  • 15.3 AVAILABLE CUSTOMIZATIONS
  • 15.4 RELATED REPORTS
  • 15.5 AUTHOR DETAILS

The study used four major activities to estimate the market size of the AI in computer vision. Exhaustive secondary research was conducted to gather information on the market and its peer and parent markets. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the total market size. Finally, market breakdown and data triangulation methods were utilized to estimate the market size for different segments and subsegments.

Secondary Research

The research methodology used to estimate and forecast the size of the AI in computer vision market began with the acquisition of data related to the revenues of key vendors in the market through secondary research. Various secondary sources have been referred to in the secondary research process to identify and collect information for this study. Secondary sources include annual reports, press releases, and investor presentations of companies; white papers, journals, certified publications, and articles by recognized authors; websites; directories; and databases. Secondary research has mainly been used to obtain key information about the value chain of the AI in computer vision market, key players, market classification, and segmentation according to the industry trends to the bottom-most level, geographic markets, and key developments from market and technology-oriented perspectives. Secondary data has been collected and analyzed to determine the overall market size, further validated through primary research. The secondary research referred to for this research study involves the viso.ai, Simplilearn Solutions, National Library of Medicine, Techopedia, and MDPI. Moreover, the study involved extensive secondary sources, directories, and databases, such as Hoovers, Bloomberg Businessweek, Factiva, and OneSource, to identify and collect valuable information for a technical, market-oriented, and commercial study of the AI in computer vision market. Vendor offerings have been taken into consideration to determine market segmentation.

Primary Research

In the primary research, various stakeholders from both the supply and demand sides have been interviewed to obtain the qualitative and quantitative information relevant to this report. Primary sources from the supply side include the key industry participants, subject-matter experts (SMEs), and C-level executives and consultants from various key companies and organizations in the AI in computer vision ecosystem. After the complete market engineering (including calculations for the market statistics, the market breakdown, the market size estimations, the market forecasting, and the data triangulation), extensive primary research has been conducted to verify and validate the critical market numbers obtained. Extensive qualitative and quantitative analyses have been performed during the market engineering process to list key information/insights throughout the report. Extensive primary research has been conducted after understanding the AI in computer vision market scenario through secondary research. Several primary interviews have been conducted with market experts from the demand and supply-side players across key regions: North America, Europe, Asia Pacific, and the Rest of the World (Middle East, Africa, and South America). Various primary sources from the supply and demand sides of the market have been interviewed to obtain qualitative and quantitative information. Following is the breakdown of the primary respondents.

Primary data has been collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, various departments within organizations, such as sales, operations, and administration, were covered to provide a holistic viewpoint in our report. After interacting with industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings from our primaries. This and the in-house subject matter experts’ opinions have led us to the findings described in the remainder of this report.

AI in Computer Vision Market Size, and Share

Note: The three tiers of the companies are defined based on their total revenue in 2023: Tier 1 - revenue greater than or equal to USD 1 billion; Tier 2 - revenue between USD 100 million and USD 1 billion; and Tier 3 revenue less than or equal to USD 100 million. Other designations include sales managers, marketing managers, and product managers.

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Both top-down and bottom-up approaches were utilized to estimate and validate the size of the AI in computer vision market and its submarkets. Secondary research was conducted to identify the key players in the market, and primary and secondary research was used to determine their market share in specific regions. The entire process involved studying top players' annual and financial reports and conducting extensive interviews with industry leaders such as CEOs, VPs, directors, and marketing executives. Secondary sources were used to determine all percentage shares and breakdowns, which were verified through primary sources. All parameters that could impact the markets covered in this research study were accounted for, analyzed in detail, verified through primary research, and consolidated to obtain the final quantitative and qualitative data.

AI in Computer Vision Market : Top-Down and Bottom-Up Approach

AI in Computer Vision Market Top Down and Bottom Up Approach

Data Triangulation

Once the overall size of the AI in computer vision market was determined using the methods described above, it was divided into multiple segments and subsegments. Market engineering was performed for each segment and subsegment using market breakdown and data triangulation methods, as applicable, to obtain accurate statistics. To triangulate the data, various factors and trends from the demand and supply sides were studied. The market was validated using both top-down and bottom-up approaches.

Market Definition

AI in computer vision refers to the application of artificial intelligence technologies to make machines interpret, process, and analyze visual data from the world, such as images or videos. This involves sophisticated techniques such as machine learning and deep learning in tasks such as object detection, facial recognition, image classification, and scene analysis. It is widely used across various ens users, such as automotive, consumer electronics, healthcare, retail, security & surveillance, manufacturing, agriculture, transportation & logistics, and others. By leveraging machine learning and deep learning technology, AI in computer vision systems can adapt and improve over time, providing greater efficiency and precision across these applications.

Key Stakeholders

  • Raw data providers
  • Cloud storage providers
  • AI in computer vision system providers
  • AI in computer vision software providers
  • Data processors providers
  • Professional services/solution providers
  • Research institutions and organizations

Report Objectives

  • To estimate and forecast the size of the AI in computer vision Market, in terms of value, based on offering, technology, function, application, end user, and region
  • To describe use cases of AI in computer vision technology
  • To describe and forecast the market size, in terms of value, for four major regions-North America, Europe, Asia Pacific, and Rest of the World (RoW)
  • To provide detailed information regarding major factors such as drivers, restraints, opportunities, and challenges influencing the market growth
  • To provide a detailed overview of the AI in computer vision value chain
  • To strategically analyze micromarkets regarding individual market trends, growth prospects, and contributions to the total market
  • To strategically profile key players and comprehensively analyze their market position in terms of ranking and core competencies, along with a detailed competitive landscape for the market leaders
  • To analyze major growth strategies such as product launches/developments and acquisitions adopted by the key market players to enhance their market position
  • To analyze the impact of the macroeconomic factors impacting the AI in computer vision market

Available Customizations

With the given market data, MarketsandMarkets offers customizations according to the specific requirements of companies. The following customization options are available for the report:

  • Detailed analysis and profiling of additional market players (up to 5)
  • Additional country-level analysis of the AI in computer vision market

Product Analysis

  • Product matrix, which provides a detailed comparison of the product portfolio of each company in the AI in computer vision market

Previous Versions of this Report

AI In Computer Vision Market by Component (Hardware, Software), Function (Training, Inference), Application (Industrial, Non-industrial), End-use Industry (Automotive, Consumer Electronics) and Region - Global Forecast to 2028

Report Code SE 6211
Published in Feb, 2023, By MarketsandMarkets™

AI in Computer Vision Market With Covid-19 Impact by Component, Machine Learning Models, Function, Application (Industrial, Non-Industrial), End-Use Industry (Security & Surveillance, Consumer Electronics) and Geography - Global Forecast to 2026

Report Code SE 6211
Published in Jun, 2021, By MarketsandMarkets™

AI in Computer Vision Market With Covid-19 Impact by Component, Machine Learning Models, Function, Application (Industrial, Non-Industrial), End-Use Industry (Security & Surveillance, Consumer Electronics) and Geography - Global Forecast to 2026

Report Code SE 6211
Published in Apr, 2018, By MarketsandMarkets™
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