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市场调查报告书
商品编码
1817992

2032 年人工智慧工业视觉市场预测：按组件、部署模式、技术、应用、最终用户和地区进行的全球分析

AI-powered Industrial Vision Market Forecasts to 2032 - Global Analysis By Component (Hardware, Software and Services), Deployment Mode (On-premise, Cloud-based and Edge-based), Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球人工智慧工业视觉市场预计在 2025 年达到 238.1 亿美元，到 2032 年将达到 957.9 亿美元，预测期内的复合年增长率为 22.0%。

人工智慧主导的工业视觉正透过结合先进的电脑视觉和人工智慧，彻底改变製造业。这些技术提供即时监控、精确的缺陷识别和预测性维护功能，从而最大限度地减少错误并降低成本。透过利用深度学习，人工智慧视觉系统可以检测整个复杂生产过程中的异常情况，从而提高可靠性和效率。自动化视觉检测能够分析大量数据，提供优化营运的洞察。汽车、电子和製药等行业越来越多地采用这些系统来确保产品品质、加速生产流程并保持竞争力。人工智慧驱动的视觉解决方案正在迅速重塑工业流程，实现更智慧、更快速、更具成本效益的製造方法。

根据《智慧製造杂誌》（Springer）对 1,200 多篇学术论文的全面审查表明，生成式人工智慧越来越多地用于工业机器视觉的数据增强、异常检测和分辨率增强。

自动化和效率

对效率和自动化日益增长的需求正在推动人工智慧工业视觉市场的成长。製造商正在采用人工智慧视觉解决方案来自动化重复性任务，增强生产流程，并减少对人工检测的依赖。这些技术提供准确的即时监控，确保更快的流程，最大限度地减少人为错误，并降低营运成本。自动化使组织能够在不增加劳动力的情况下扩大产量并提高生产力。透过保持一致的品质标准和优化资源利用率，人工智慧主导的视觉系统已成为汽车、电子和製药等产业不可或缺的一部分。提高营运效率的动力使这项技术成为至关重要的市场成长要素。

初期投资成本高

人工智慧工业视觉系统高昂的前期成本是市场发展的一大限制因素。部署该系统需要在设备、软体以及与现有製造流程的整合方面进行大量投资。对于中小型企业而言，初期资本需求可能成为其应用的限制与障碍。此外，培训人员使用和维护这些系统的相关费用也增加了整体成本。虽然人工智慧视觉技术能够带来长期的效率提升和营运成本节省，但其所需的高额前期资本投入阻碍了许多企业采用。这种经济障碍在新兴市场尤为明显，限制了基于人工智慧的工业视觉解决方案的市场成长和采用率。

开发先进的人工智慧和深度学习演算法

人工智慧和深度学习技术的不断发展，为人工智慧驱动的工业视觉市场创造了巨大的商机。先进的演算法提高了缺陷检测的准确性、模式识别和自主决策能力。这些增强功能使视觉系统能够管理复杂的製造流程、分析大量资料集并产生切实可行的洞察。随着人工智慧模型的不断进步和从营运数据中学习，企业可以提高效率并保持高品质标准。人工智慧软体和工业整合的持续创新正在推动其在汽车、电子和製药行业的应用。这些技术进步使人工智慧驱动的视觉系统更加智慧、适应性更强，并成为现代製造业的重要工具，为产业格局创造了巨大的成长潜力。

竞争激烈，市场饱和

人工智慧工业视觉市场竞争日益激烈，对新参与企业和现有企业都构成了重大威胁。众多供应商提供雷同的解决方案，使得产品差异化变得困难，进而导致定价压力和利润率下降。规模较小的公司可能难以与拥有强大技术专长和雄厚资金支持的知名品牌竞争。市场饱和，尤其是在成熟地区，进一步限制了成长潜力。为了保持竞争力，公司必须不断创新并丰富其产品线。未能适应变化将导致客户流失和市场份额损失，从而限制其在竞争激烈的工业视觉领域的扩张机会。

COVID-19的影响

新冠疫情对人工智慧工业视觉市场既带来了挑战，也带来了鼓舞。最初，製造业放缓、供应链中断以及工厂暂时关闭阻碍了市场扩张。然而，疫情加速了人工智慧和自动化解决方案的部署，因为各企业都在努力减少人机交互，确保持续营运并提高生产力。在此期间，远端监控、预测性维护和即时品质检测等应用变得至关重要，彰显了人工智慧视觉技术的重要性。疫情过后，各企业纷纷优先投资人工智慧工业视觉系统，以增强营运韧性，减少对人工的依赖，并为未来的生产中断和技术进步做好准备。

预计预测期内云端基础市场规模最大

预计云端基础的细分市场将在预测期内占据最大的市场份额，这得益于其灵活性、扩充性和经济高效的部署。利用云端基础设施，製造商无需在本地伺服器和硬体上进行大量投资即可管理和分析大量视觉数据。这些解决方案提供即时监控、远端存取以及与物联网设备和智慧工厂计划的顺畅整合。云端平台还提供集中管理、自动更新和快速实施，使其成为各种规模组织的理想选择。预测性洞察和高级分析可从任何地方访问，从而改善决策和营运绩效。这些优势使云端基础的人工智慧视觉系统成为市场主导。

预计深度学习模型部分将在预测期内实现最高的复合年增长率

预计深度学习模型领域将在预测期内实现最高成长率，这得益于对智慧和自适应检测系统日益增长的需求。这些演算法有助于在复杂的製造环境中实现精确的模式识别、缺陷检测和预测性维护。随着製造商寻求提高自动化程度和严格的品管，深度学习解决方案提供了超越传统视觉技术的高阶决策能力。它们能够持续从营运数据中学习并随着时间的推移优化效能，使其极具价值。汽车、电子和製药等行业正在迅速采用这些模型，以提高准确性、效率和可操作的洞察力，从而推动基于深度学习的工业视觉技术的市场大幅扩张。

比最大的地区

在预测期内，北美预计将占据最大的市场份额，这得益于其先进的工业基础、工业 4.0 的广泛应用以及针对人工智慧的大规模投资。汽车、电子和製药等关键产业越来越多地采用人工智慧视觉系统来加强品质保证、优化流程和实现预测性维护。该地区的技术专长、熟练的劳动力和政府支援将进一步推动市场扩张。此外，主要企业的存在及其对自动化和智慧製造设施的关注也巩固了北美的领先地位。由于这些综合因素，该地区将继续主导全球人工智慧工业视觉市场，并保持其作为市场收益最大区域贡献者的地位。

复合年增长率最高的地区

预计亚太地区在预测期内将呈现最高的复合年增长率，这得益于工业化进程的加速、智慧製造实践的采用以及自动化投资的增加。中国、日本、韩国和印度等国家正在升级其製造业，并实施人工智慧视觉技术，以提高流程效率、品质保证和预测性维护。优惠的政府政策、不断增长的熟练劳动力以及充满活力的科技新创企业生态系统将进一步推动市场扩张。工业设施的扩张，加上对先进生产解决方案日益增长的需求，使亚太地区成为成长最快的地区，并使其成为全球人工智慧工业视觉成长最快的市场。

免费客製化服务

此报告的订阅者可以选择以下免费自订选项之一：

  • 公司简介
    • 全面分析其他市场参与者（最多 3 家公司）
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章 全球人工智慧工业视觉市场（按组件）

  • 硬体
  • 软体
  • 服务

6. 全球人工智慧工业视觉市场（按部署模式）

  • 本地部署
  • 云端基础
  • 基于边缘

7. 全球人工智慧工业视觉市场（按技术）

  • 2D视觉系统
  • 3D视觉系统
  • 深度学习模型
  • 生成式人工智慧模组
  • 嵌入式AI晶片

第八章全球人工智慧工业视觉市场（按应用）

  • 缺陷检测和品质保证
  • 机器人寻路与物体定位
  • 预测性资产监控
  • 职场安全与危害监测
  • 自动排序和分类

第九章全球人工智慧工业视觉市场（按最终用户）

  • 汽车製造业
  • 半导体和电子设备製造
  • 食品加工/包装
  • 药品生产与合规
  • 仓库自动化/物流
  • 重型设备/金属加工

第 10 章全球人工智慧工业视觉市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • Qualcomm Technologies, Inc.
  • Advanced Micro Devices, Inc.（AMD）
  • International Business Machines Corporation（IBM）
  • NVIDIA Corporation
  • Cognex Corporation
  • KEYENCE CORPORATION
  • Teledyne Technologies Inc.
  • FANUC Robotics
  • ABB Robotics
  • SenseTime
  • LandingAI
  • Mech-Mind Robotics
  • Averroes.ai
  • OMRON Group
  • Ripik.AI
Product Code: SMRC30955

According to Stratistics MRC, the Global AI-powered Industrial Vision Market is accounted for $23.81 billion in 2025 and is expected to reach $95.79 billion by 2032 growing at a CAGR of 22.0% during the forecast period. AI-driven Industrial Vision is revolutionizing the manufacturing sector by combining sophisticated computer vision with artificial intelligence. These technologies offer real-time monitoring, precise defect identification, and predictive maintenance capabilities, minimizing errors and saving costs. Utilizing deep learning, AI vision systems can detect irregularities across complex production processes, improving reliability and efficiency. Automation of visual inspections allows high-volume data analysis, generating insights to optimize operations. Sectors like automotive, electronics, and pharmaceuticals are increasingly implementing these systems to guarantee product quality, accelerate production workflows, and sustain a competitive edge. AI-powered vision solutions are rapidly reshaping industrial processes, enabling smarter, faster, and more cost-effective manufacturing practices.

According to the Journal of Intelligent Manufacturing (Springer), a comprehensive review of over 1,200 academic papers found that generative AI is increasingly used in industrial machine vision for data augmentation, anomaly detection, and resolution enhancement.

Market Dynamics:

Driver:

Automation and efficiency enhancement

Rising needs for efficiency and automation are fueling the growth of the AI-powered Industrial Vision market. Manufacturers implement AI vision solutions to automate repetitive operations, enhance production workflows, and reduce reliance on manual inspections. These technologies offer precise, real-time monitoring, ensuring faster processes and minimizing human error, while lowering operational costs. Automation enables organizations to expand output without proportionally increasing labor requirements, boosting productivity. By maintaining consistent quality standards and optimizing resource usage, AI-driven vision systems become indispensable in industries like automotive, electronics, and pharmaceuticals. The drive to improve operational efficiency makes this technology a pivotal market growth factor.

Restraint:

High initial investment costs

The high upfront costs associated with AI-powered Industrial Vision systems act as a major market restraint. Deployment requires significant investment in equipment, software, and integration with existing manufacturing processes. Small and mid-sized companies may find the initial financial requirements restrictive, hindering adoption. Additionally, expenses related to training personnel to use and maintain these systems add to the overall cost. While long-term efficiency gains and operational savings exist, the considerable capital investment needed initially prevents many organizations from implementing AI vision technologies. This financial barrier is especially pronounced in emerging markets, limiting the speed of market growth and adoption of AI-based industrial vision solutions.

Opportunity:

Development of advanced AI and deep learning algorithms

The ongoing evolution of AI and deep learning technologies creates substantial opportunities for the AI-powered Industrial Vision market. Advanced algorithms improve defect detection accuracy, pattern recognition, and autonomous decision-making. These enhancements allow vision systems to manage complex manufacturing processes, analyze extensive datasets, and generate actionable insights. As AI models advance and learn from operational data, companies can improve efficiency and maintain high-quality standards. Continuous innovation in AI software and industrial integration promotes adoption across automotive, electronics, and pharmaceutical sectors. These technological improvements enable AI-powered vision systems to become smarter, more adaptable, and essential tools in modern manufacturing, presenting significant growth potential in the industrial landscape.

Threat:

High competition and market saturation

Rising competition within the AI-powered Industrial Vision market represents a considerable threat to both new entrants and existing players. With numerous vendors providing similar solutions, distinguishing products becomes challenging, creating pricing pressures and narrowing profit margins. Smaller companies may struggle to compete with well-established brands that possess strong technical expertise and financial backing. Market saturation, particularly in mature regions, further constrains growth potential. To stay competitive, businesses need to continuously innovate and enhance their product offerings. Failure to adapt may lead to customer attrition and reduced market share, ultimately limiting expansion opportunities in the fast-paced and competitive industrial vision sector.

Covid-19 Impact:

The COVID-19 pandemic influenced the AI-powered Industrial Vision market in both challenging and encouraging ways. Initially, manufacturing slowdowns, disrupted supply chains, and temporary factory closures hindered market expansion. However, the pandemic also accelerated the deployment of AI and automation solutions, as organizations aimed to reduce human interactions, ensure continuous operations, and enhance productivity. Applications such as remote monitoring, predictive maintenance, and real-time quality inspection became crucial during this period, showcasing the importance of AI vision technologies. Following the pandemic, companies increasingly prioritize investments in AI-powered industrial vision systems to strengthen operational resilience, decrease reliance on manual labor, and prepare manufacturing processes for future disruptions and technological advancements.

The cloud-based segment is expected to be the largest during the forecast period

The cloud-based segment is expected to account for the largest market share during the forecast period due to its flexibility, scalability, and cost-effective deployment. By leveraging cloud infrastructure, manufacturers can manage and analyze extensive visual data without investing heavily in local servers or hardware. These solutions offer real-time monitoring, remote access, and smooth integration with IoT devices and smart factory initiatives. Cloud platforms also provide centralized control, automatic updates, and faster implementation, making them ideal for organizations of varying sizes. The ability to obtain predictive insights and advanced analytics from any location improves decision-making and operational performance. These benefits position cloud-based AI vision systems as the market's dominant segment.

The deep learning models segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the deep learning models segment is predicted to witness the highest growth rate due to increasing demand for smart and adaptable inspection systems. These algorithms facilitate precise pattern recognition, defect detection, and predictive maintenance in complex manufacturing environments. As manufacturers aim for enhanced automation and stringent quality control, deep learning solutions offer advanced decision-making capabilities beyond conventional vision technologies. Their capacity to learn continuously from operational data and optimize performance over time makes them highly valuable. Industries such as automotive, electronics, and pharmaceuticals are rapidly adopting these models for improved accuracy, efficiency, and actionable insights, driving significant market expansion for deep learning-based industrial vision technologies.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its advanced industrial base, widespread adoption of Industry 4.0, and significant AI-focused investments. Major sectors such as automotive, electronics, and pharmaceuticals are increasingly implementing AI vision systems to enhance quality assurance, optimize processes, and enable predictive maintenance. The region's technological expertise, skilled workforce, and government support further promote market expansion. Additionally, the presence of prominent companies and emphasis on automation and intelligent manufacturing facilities reinforces North America's leading status. These combined factors ensure that the region continues to dominate the global AI-powered industrial vision market, maintaining its position as the largest regional contributor to market revenue.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, supported by accelerating industrialization, adoption of smart manufacturing practices, and increased investment in automation. Nations such as China, Japan, South Korea, and India are upgrading their manufacturing sectors and deploying AI vision technologies to enhance process efficiency, quality assurance, and predictive maintenance. Favorable government policies, a growing skilled workforce, and a vibrant technology startup ecosystem further drive market expansion. The combination of expanding industrial facilities and increasing demand for advanced production solutions positions Asia-Pacific as the region with the highest growth rate, making it the fastest-growing market for AI-powered industrial vision globally.

Key players in the market

Some of the key players in AI-powered Industrial Vision Market include Qualcomm Technologies, Inc., Advanced Micro Devices, Inc. (AMD), International Business Machines Corporation (IBM), NVIDIA Corporation, Cognex Corporation, KEYENCE CORPORATION, Teledyne Technologies Inc., FANUC Robotics, ABB Robotics, SenseTime, LandingAI, Mech-Mind Robotics, Averroes.ai, OMRON Group and Ripik.AI.

Key Developments:

In July 2025, Nvidia Corporation and YTL Power International have signed an agreement to develop $2.36 billion of AI infrastructure in Malaysia. The investment will see the development of an AI data center in the country, in addition to a cluster of Nvidia GPUs, all of which will be powered by green energy.

In May 2025, Qualcomm Technologies, Inc. and Xiaomi Corporation are celebrating 15 years of collaboration and have executed a multi-year agreement. The relationship between Qualcomm Technologies and Xiaomi has been pivotal in driving innovation across the technology industry and the companies are committed to delivering industry-leading products and solutions across various device categories globally.

In January 2025, IBM and Telefonica Tech have announced a collaboration agreement to develop security solutions addressing challenges posed by future quantum computers. The partnership involves integrating IBM's quantum-safe technology into Telefonica Tech's cybersecurity services. The collaboration aims to implement new quantum-safe cryptography standards defined by NIST, with IBM having co-developed two of the three published post-quantum cryptography standards.

Components Covered:

  • Hardware
  • Software
  • Services

Deployment Modes Covered:

  • On-premise
  • Cloud-based
  • Edge-based

Technologies Covered:

  • 2D Vision Systems
  • 3D Vision Systems
  • Deep Learning Models
  • Generative AI Modules
  • Embedded AI Chips

Applications Covered:

  • Defect Detection & Quality Assurance
  • Robotic Pathfinding & Object Localization
  • Predictive Equipment Monitoring
  • Workplace Safety & Hazard Surveillance
  • Automated Sorting & Classification

End Users Covered:

  • Automotive Manufacturing
  • Semiconductor & Electronics Fabrication
  • Food Processing & Packaging
  • Pharmaceutical Production & Compliance
  • Warehouse Automation & Logistics
  • Heavy Machinery & Metal Fabrication

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-powered Industrial Vision Market, By Component

  • 5.1 Introduction
  • 5.2 Hardware
  • 5.3 Software
  • 5.4 Services

6 Global AI-powered Industrial Vision Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 On-premise
  • 6.3 Cloud-based
  • 6.4 Edge-based

7 Global AI-powered Industrial Vision Market, By Technology

  • 7.1 Introduction
  • 7.2 2D Vision Systems
  • 7.3 3D Vision Systems
  • 7.4 Deep Learning Models
  • 7.5 Generative AI Modules
  • 7.6 Embedded AI Chips

8 Global AI-powered Industrial Vision Market, By Application

  • 8.1 Introduction
  • 8.2 Defect Detection & Quality Assurance
  • 8.3 Robotic Pathfinding & Object Localization
  • 8.4 Predictive Equipment Monitoring
  • 8.5 Workplace Safety & Hazard Surveillance
  • 8.6 Automated Sorting & Classification

9 Global AI-powered Industrial Vision Market, By End User

  • 9.1 Introduction
  • 9.2 Automotive Manufacturing
  • 9.3 Semiconductor & Electronics Fabrication
  • 9.4 Food Processing & Packaging
  • 9.5 Pharmaceutical Production & Compliance
  • 9.6 Warehouse Automation & Logistics
  • 9.7 Heavy Machinery & Metal Fabrication

10 Global AI-powered Industrial Vision Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Qualcomm Technologies, Inc.
  • 12.2 Advanced Micro Devices, Inc. (AMD)
  • 12.3 International Business Machines Corporation (IBM)
  • 12.4 NVIDIA Corporation
  • 12.5 Cognex Corporation
  • 12.6 KEYENCE CORPORATION
  • 12.7 Teledyne Technologies Inc.
  • 12.8 FANUC Robotics
  • 12.9 ABB Robotics
  • 12.10 SenseTime
  • 12.11 LandingAI
  • 12.12 Mech-Mind Robotics
  • 12.13 Averroes.ai
  • 12.14 OMRON Group
  • 12.15 Ripik.AI

List of Tables

  • Table 1 Global AI-powered Industrial Vision Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-powered Industrial Vision Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-powered Industrial Vision Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global AI-powered Industrial Vision Market Outlook, By Software (2024-2032) ($MN)
  • Table 5 Global AI-powered Industrial Vision Market Outlook, By Services (2024-2032) ($MN)
  • Table 6 Global AI-powered Industrial Vision Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 7 Global AI-powered Industrial Vision Market Outlook, By On-premise (2024-2032) ($MN)
  • Table 8 Global AI-powered Industrial Vision Market Outlook, By Cloud-based (2024-2032) ($MN)
  • Table 9 Global AI-powered Industrial Vision Market Outlook, By Edge-based (2024-2032) ($MN)
  • Table 10 Global AI-powered Industrial Vision Market Outlook, By Technology (2024-2032) ($MN)
  • Table 11 Global AI-powered Industrial Vision Market Outlook, By 2D Vision Systems (2024-2032) ($MN)
  • Table 12 Global AI-powered Industrial Vision Market Outlook, By 3D Vision Systems (2024-2032) ($MN)
  • Table 13 Global AI-powered Industrial Vision Market Outlook, By Deep Learning Models (2024-2032) ($MN)
  • Table 14 Global AI-powered Industrial Vision Market Outlook, By Generative AI Modules (2024-2032) ($MN)
  • Table 15 Global AI-powered Industrial Vision Market Outlook, By Embedded AI Chips (2024-2032) ($MN)
  • Table 16 Global AI-powered Industrial Vision Market Outlook, By Application (2024-2032) ($MN)
  • Table 17 Global AI-powered Industrial Vision Market Outlook, By Defect Detection & Quality Assurance (2024-2032) ($MN)
  • Table 18 Global AI-powered Industrial Vision Market Outlook, By Robotic Pathfinding & Object Localization (2024-2032) ($MN)
  • Table 19 Global AI-powered Industrial Vision Market Outlook, By Predictive Equipment Monitoring (2024-2032) ($MN)
  • Table 20 Global AI-powered Industrial Vision Market Outlook, By Workplace Safety & Hazard Surveillance (2024-2032) ($MN)
  • Table 21 Global AI-powered Industrial Vision Market Outlook, By Automated Sorting & Classification (2024-2032) ($MN)
  • Table 22 Global AI-powered Industrial Vision Market Outlook, By End User (2024-2032) ($MN)
  • Table 23 Global AI-powered Industrial Vision Market Outlook, By Automotive Manufacturing (2024-2032) ($MN)
  • Table 24 Global AI-powered Industrial Vision Market Outlook, By Semiconductor & Electronics Fabrication (2024-2032) ($MN)
  • Table 25 Global AI-powered Industrial Vision Market Outlook, By Food Processing & Packaging (2024-2032) ($MN)
  • Table 26 Global AI-powered Industrial Vision Market Outlook, By Pharmaceutical Production & Compliance (2024-2032) ($MN)
  • Table 27 Global AI-powered Industrial Vision Market Outlook, By Warehouse Automation & Logistics (2024-2032) ($MN)
  • Table 28 Global AI-powered Industrial Vision Market Outlook, By Heavy Machinery & Metal Fabrication (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.