AI in Computer Vision Market Size By Component (Hardware, Software, Service), By Application (Predictive Maintenance, Quality Assurance & Inspection, Position & Guidance, Identification), End-Use, & Global Forecast, 2023

Description

List of Tables

Global AI in Computer Vision Market will register significant growth from 2023 to 2032. The advancements in artificial intelligence and deep learning algorithms have significantly improved the accuracy and performance of computer vision systems. For instance, the development of deep learning architectures, such as transformer architecture, is very effective for natural language processing tasks, and it is being increasingly adopted for computer vision tasks as well.

The increasing adoption of automation and robotics in manufacturing, healthcare, and automotive industries is driving the demand for AI-powered computer vision for tasks like quality control, object detection, and medical imaging. The growing popularity of smart devices, autonomous vehicles, and facial recognition technology further contributes to market expansion. Additionally, the availability of large datasets and the development of cloud-based AI solutions have democratized access to computer vision capabilities, enabling businesses of all sizes to integrate AI into their products and services.

The overall AI in Computer Vision Market is classified based on component, application, end-use, and region.

Based on the component, the software segment will contribute significantly to the market from 2023-2032. As computer vision technology advances, the need for sophisticated and efficient algorithms, machine learning models, and image processing software is increasing. Software components play a crucial role in enabling computer vision systems to recognize and interpret visual information accurately. Moreover, the availability of open-source and cloud-based AI software solutions has made it more accessible for businesses to integrate AI into their computer vision applications, further driving the demand for software components in the market.

Regarding application, the AI in computer vision industry from the positioning and guidance segment will depict a high growth rate over 2023-2032. Computer vision technology with AI-driven positioning and guidance capabilities is becoming crucial in autonomous vehicles, drones, and robotics industries. It enables precise navigation, object tracking, and spatial awareness, leading to safer and more efficient operations. Moreover, the demand for augmented reality (AR) and virtual reality (VR) experiences in sectors like gaming, retail, and education are also driving the need for AI-powered computer vision for accurate spatial mapping and real-time interaction.

With respect to end-use, the government segment will accumulate a significant share of the AI in computer vision market revenue by 2032. Governments are recognizing the potential of AI-driven computer vision technology to enhance public safety, security, and efficiency in various areas. Applications include surveillance and monitoring systems, traffic management, and border control. The growing interest in leveraging AI in government operations and services is driving the demand for AI-powered computer vision solutions in the market.

Regionally, the APAC AI in Computer Vision Market will gain traction during the forecast period as the region continues to witness rapid economic growth, technological improvements, and a growing interest in adopting AI-powered computer vision solutions. APAC countries are leveraging computer vision for applications, such as smart city development, industrial automation, and healthcare diagnostics. Moreover, the increasing investments in AI research and development, in line with government initiatives promoting AI adoption, are driving the market expansion in the Asia Pacific, making it a key growth region for AI in computer vision.

Product Code: 5667

Chapter 1 Methodology and Scope

1.1 Scope & definitions
1.2 Base estimates and calculations
1.3 Forecast calculations
1.4 Data Sources
- 1.4.1 Primary
- 1.4.2 Secondary
  - 1.4.2.1 Paid sources
  - 1.4.2.2 Public sources

Chapter 2 Executive Summary

2.1 AI in computer vision industry 360 degree synopsis, 2018-2032
2.2 Business trends
- 2.2.1 Total Addressable Market (TAM), 2023-2032
2.3 Regional trends
2.4 Component trends
2.5 Application trends
2.6 End-Use trends

Chapter 3 AI in Computer Vision Market Industry Insights

3.1 Impact of COVID-19
3.2 Russia- Ukraine war impact
3.3 Industry ecosystem
- 3.3.1 Hardware providers
- 3.3.2 Software providers
- 3.3.3 Service providers
- 3.3.4 Technology providers
- 3.3.5 End-user
- 3.3.6 Profit margin analysis
- 3.3.7 Vendor Matrix
3.4 Technology & innovation landscape
- 3.4.1 Robotic process automation
- 3.4.2 AI optimized hardware
- 3.4.3 Deep learning platform
3.5 Patent analysis
3.6 Key initiative and news
- 3.6.1 Partnership/Collaboration
- 3.6.2 Merger/Acquisition
- 3.6.3 New launch
- 3.6.4 Investment
3.7 Regulatory landscape
3.8 Industry impact forces
- 3.8.1 Growth drivers
  - 3.8.1.1 The growing penetration of AI in automotive industry
  - 3.8.1.2 The rapid integration of AI for security & surveillance purpose
  - 3.8.1.3 Rise in demand for predictive maintenance and quality assurance in manufacturing industry
  - 3.8.1.4 The increasing digitalization in retail industry
  - 3.8.1.5 The growing applications of AI in computer vision
- 3.8.2 Industry pitfalls & challenges
  - 3.8.2.1 Data safety and security related issues
3.9 Growth potential analysis
3.10 Porter's analysis
3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2022

4.1 Introduction
4.2 Company market share, 2022
4.3 Competitive analysis of major market players, 2022
- 4.3.1 Amazon Web Service, Inc.
- 4.3.2 Google LLC (Alphabet)
- 4.3.3 IBM Corporation
- 4.3.4 Intel Corporation
- 4.3.5 Microsoft Corporation
- 4.3.6 NVIDIA Corporation
- 4.3.7 Teledyne Technologies
4.4 Competitive positioning matrix
4.5 Strategic outlook matrix

Chapter 5 AI in Computer Vision Market, By Component

5.1 Key trends, by component
5.2 Hardware
- 5.2.1 Market estimates and forecast, 2018-2032
5.3 Software
- 5.3.1 Market estimates and forecast, 2018-2032
5.4 Services
- 5.4.1 Market estimates and forecast, 2018-2032

Chapter 6 AI in Computer Vision Market, By Application

6.1 Key trends, by application
6.2 Predictive maintenance
- 6.2.1 Market estimates and forecast, 2018-2032
6.3 Quality assurance & inspection
- 6.3.1 Market estimates and forecast, 2018-2032
6.4 Position & guidance
- 6.4.1 Market estimates and forecast, 2018-2032
6.5 Identification
- 6.5.1 Market estimates and forecast, 2018-2032

Chapter 7 AI in Computer Vision Market, By End-Use

7.1 Key trends, by end-use
7.2 Retail
- 7.2.1 Market estimates and forecast, 2018-2032
7.3 BFSI
- 7.3.1 Market estimates and forecast, 2018-2032
7.4 Government
- 7.4.1 Market estimates and forecast, 2018-2032
7.5 Healthcare
- 7.5.1 Market estimates and forecast, 2018-2032
7.6 Agriculture
- 7.6.1 Market estimates and forecast, 2018-2032
7.7 Manufacturing
- 7.7.1 Market estimates and forecast, 2018-2032
7.8 Automotive & Transportation
- 7.8.1 Market estimates and forecast, 2018-2032
7.9 Others
- 7.9.1 Market estimates and forecast, 2018-2032

Chapter 8 AI in Computer Vision Market, By Region

8.1 Key trends, by region
8.2 North America
- 8.2.1 Market estimates and forecast, by component, 2018-2032
- 8.2.2 Market estimates and forecast, by Application, 2018-2032
- 8.2.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.2.4 U.S.
  - 8.2.4.1 Market estimates and forecast, by component, 2018-2032
  - 8.2.4.2 Market estimates and forecast, by Application, 2018-2032
  - 8.2.4.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.2.5 Canada
  - 8.2.5.1 Market estimates and forecast, by component, 2018-2032
  - 8.2.5.2 Market estimates and forecast, by Application, 2018-2032
  - 8.2.5.3 Market estimates and forecast, by End-Use, 2018-2032
8.3 Europe
- 8.3.1 Market estimates and forecast, by component, 2018-2032
- 8.3.2 Market estimates and forecast, by Application, 2018-2032
- 8.3.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.3.4 UK
  - 8.3.4.1 Market estimates and forecast, by component, 2018-2032
  - 8.3.4.2 Market estimates and forecast, by Application, 2018-2032
  - 8.3.4.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.3.5 Germany
  - 8.3.5.1 Market estimates and forecast, by component, 2018-2032
  - 8.3.5.2 Market estimates and forecast, by Application, 2018-2032
  - 8.3.5.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.3.6 France
  - 8.3.6.1 Market estimates and forecast, by component, 2018-2032
  - 8.3.6.2 Market estimates and forecast, by Application, 2018-2032
  - 8.3.6.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.3.7 Italy
  - 8.3.7.1 Market estimates and forecast, by component, 2018-2032
  - 8.3.7.2 Market estimates and forecast, by Application, 2018-2032
  - 8.3.7.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.3.8 Spain
  - 8.3.8.1 Market estimates and forecast, by component, 2018-2032
  - 8.3.8.2 Market estimates and forecast, by Application, 2018-2032
  - 8.3.8.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.3.9 Netherland
  - 8.3.9.1 Market estimates and forecast, by component, 2018-2032
  - 8.3.9.2 Market estimates and forecast, by Application, 2018-2032
  - 8.3.9.3 Market estimates and forecast, by End-Use, 2018-2032
8.4 Asia Pacific
- 8.4.1 Market estimates and forecast, by component, 2018-2032
- 8.4.2 Market estimates and forecast, by Application, 2018-2032
- 8.4.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.4.4 China
  - 8.4.4.1 Market estimates and forecast, by component, 2018-2032
  - 8.4.4.2 Market estimates and forecast, by Application, 2018-2032
  - 8.4.4.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.4.5 Japan
  - 8.4.5.1 Market estimates and forecast, by component, 2018-2032
  - 8.4.5.2 Market estimates and forecast, by Application, 2018-2032
  - 8.4.5.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.4.6 India
  - 8.4.6.1 Market estimates and forecast, by component, 2018-2032
  - 8.4.6.2 Market estimates and forecast, by Application, 2018-2032
  - 8.4.6.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.4.7 ANZ
  - 8.4.7.1 Market estimates and forecast, by component, 2018-2032
  - 8.4.7.2 Market estimates and forecast, by Application, 2018-2032
  - 8.4.7.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.4.8 South Korea
  - 8.4.8.1 Market estimates and forecast, by component, 2018-2032
  - 8.4.8.2 Market estimates and forecast, by Application, 2018-2032
  - 8.4.8.3 Market estimates and forecast, by End-Use, 2018-2032
8.5 Latin America
- 8.5.1 Market estimates and forecast, by component, 2018-2032
- 8.5.2 Market estimates and forecast, by Application, 2018-2032
- 8.5.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.5.4 Brazil
  - 8.5.4.1 Market estimates and forecast, by component, 2018-2032
  - 8.5.4.2 Market estimates and forecast, by Application, 2018-2032
  - 8.5.4.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.5.5 Mexico
  - 8.5.5.1 Market estimates and forecast, by component, 2018-2032
  - 8.5.5.2 Market estimates and forecast, by Application, 2018-2032
  - 8.5.5.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.5.6 Argentina
  - 8.5.6.1 Market estimates and forecast, by component, 2018-2032
  - 8.5.6.2 Market estimates and forecast, by Application, 2018-2032
  - 8.5.6.3 Market estimates and forecast, by End-Use, 2018-2032
8.6 MEA
- 8.6.1 Market estimates and forecast, by component, 2018-2032
- 8.6.2 Market estimates and forecast, by Application, 2018-2032
- 8.6.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.6.4 Saudi Arabia
  - 8.6.4.1 Market estimates and forecast, by component, 2018-2032
  - 8.6.4.2 Market estimates and forecast, by Application, 2018-2032
  - 8.6.4.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.6.5 UAE
  - 8.6.5.1 Market estimates and forecast, by component, 2018-2032
  - 8.6.5.2 Market estimates and forecast, by Application, 2018-2032
  - 8.6.5.3 Market estimates and forecast, by End-Use, 2018-2032
- 8.6.6 South Africa
  - 8.6.6.1 Market estimates and forecast, by component, 2018-2032
  - 8.6.6.2 Market estimates and forecast, by Application, 2018-2032
  - 8.6.6.3 Market estimates and forecast, by End-Use, 2018-2032

Chapter 9 Company Profiles

9.1 Advanced Micro Device, Inc.
- 9.1.1 Business Overview
- 9.1.2 Financial Data
- 9.1.3 Product Landscape
- 9.1.4 Strategic Outlook
- 9.1.5 SWOT Analysis
9.2 Amazon Web Service, Inc.,
- 9.2.1 Business Overview
- 9.2.2 Financial Data
- 9.2.3 Product Landscape
- 9.2.4 Strategic Outlook
- 9.2.5 SWOT Analysis
9.3 Basler AG
- 9.3.1 Business Overview
- 9.3.2 Financial Data
- 9.3.3 Product Landscape
- 9.3.4 Strategic Outlook
- 9.3.5 SWOT Analysis
9.4 Cognex Corporation
- 9.4.1 Business Overview
- 9.4.2 Financial Data
- 9.4.3 Product Landscape
- 9.4.4 Strategic Outlook
- 9.4.5 SWOT Analysis
9.5 Google LLC (Alphabet)
- 9.5.1 Business Overview
- 9.5.2 Financial Data
- 9.5.3 Product Landscape
- 9.5.4 Strategic Outlook
- 9.5.5 SWOT Analysis
9.6 Graphcore
- 9.6.1 Business Overview
- 9.6.2 Financial Data
- 9.6.3 Product Landscape
- 9.6.4 Strategic Outlook
- 9.6.5 SWOT Analysis
9.7 Hailo
- 9.7.1 Business Overview
- 9.7.2 Financial Data
- 9.7.3 Product Landscape
- 9.7.4 Strategic Outlook
- 9.7.5 SWOT Analysis
9.8 IBM Corporation
- 9.8.1 Business Overview
- 9.8.2 Financial Data
- 9.8.3 Product Landscape
- 9.8.4 Strategic Outlook
- 9.8.5 SWOT Analysis
9.9 Intel Corporation
- 9.9.1 Business Overview
- 9.9.2 Financial Data
- 9.9.3 Product Landscape
- 9.9.4 Strategic Outlook
- 9.9.5 SWOT Analysis
9.10 Keyence
- 9.10.1 Business Overview
- 9.10.2 Financial Data
- 9.10.3 Product Landscape
- 9.10.4 Strategic Outlook
- 9.10.5 SWOT Analysis
9.11 MediaTek Inc.
- 9.11.1 Business Overview
- 9.11.2 Financial Data
- 9.11.3 Product Landscape
- 9.11.4 Strategic Outlook
- 9.11.5 SWOT Analysis
9.12 Microsoft Corporation
- 9.12.1 Business Overview
- 9.12.2 Financial Data
- 9.12.3 Product Landscape
- 9.12.4 Strategic Outlook
- 9.12.5 SWOT Analysis
9.13 NVIDIA Corporation
- 9.13.1 Business Overview
- 9.13.2 Financial Data
- 9.13.3 Product Landscape
- 9.13.4 Strategic Outlook
- 9.13.5 SWOT Analysis
9.14 Qualcomm
- 9.14.1 Business Overview
- 9.14.2 Financial Data
- 9.14.3 Product Landscape
- 9.14.4 Strategic Outlook
- 9.14.5 SWOT Analysis
9.15 Teledyne Technologies
- 9.15.1 Business Overview
- 9.15.2 Financial Data
- 9.15.3 Product Landscape
- 9.15.4 Strategic Outlook
- 9.15.5 SWOT Analysis