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市場調查報告書
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1817992

2032 年人工智慧工業視覺市場預測：按組件、部署模式、技術、應用、最終用戶和地區進行的全球分析

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個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧工業視覺市場預計在 2025 年達到 238.1 億美元，到 2032 年將達到 957.9 億美元，預測期內的複合年成長率為 22.0%。

人工智慧主導的工業視覺正透過結合先進的電腦視覺和人工智慧，徹底改變製造業。這些技術提供即時監控、精確的缺陷識別和預測性維護功能，從而最大限度地減少錯誤並降低成本。透過利用深度學習，人工智慧視覺系統可以檢測整個複雜生產過程中的異常情況，從而提高可靠性和效率。自動化視覺檢測能夠分析大量數據，提供最佳化營運的洞察。汽車、電子和製藥等行業擴大採用這些系統來確保產品品質、加速生產流程並保持競爭力。人工智慧驅動的視覺解決方案正在迅速重塑工業流程，實現更智慧、更快速、更具成本效益的製造方法。

根據《智慧製造雜誌》（Springer）對 1,200 多篇學術論文的全面審查表明，生成式人工智慧擴大用於工業機器視覺的數據增強、異常檢測和解析度增強。

自動化和效率

對效率和自動化日益成長的需求正在推動人工智慧工業視覺市場的成長。製造商正在採用人工智慧視覺解決方案來自動化重複性任務，增強生產流程，並減少對人工檢測的依賴。這些技術提供準確的即時監控，確保更快的流程，最大限度地減少人為錯誤，並降低營運成本。自動化使組織能夠在不增加勞動力的情況下擴大產量並提高生產力。透過保持一致的品質標準和最佳化資源利用率，人工智慧主導的視覺系統已成為汽車、電子和製藥等產業不可或缺的一部分。提高營運效率的動力使這項技術成為至關重要的市場成長要素。

初期投資成本高

人工智慧工業視覺系統高昂的前期成本是市場發展的一大限制因素。部署該系統需要在設備、軟體以及與現有製造流程的整合方面進行大量投資。對於中小型企業而言，初期資本需求可能成為其應用的限制與障礙。此外，培訓人員使用和維護這些系統的相關費用也增加了整體成本。雖然人工智慧視覺技術能夠帶來長期的效率提升和營運成本節省，但其所需的高額前期資本投入阻礙了許多企業採用。這種經濟障礙在新興市場尤為明顯，限制了基於人工智慧的工業視覺解決方案的市場成長和採用率。

開發先進的人工智慧和深度學習演算法

人工智慧和深度學習技術的不斷發展，為人工智慧驅動的工業視覺市場創造了巨大的商機。先進的演算法提高了缺陷檢測的準確性、模式識別和自主決策能力。這些增強功能使視覺系統能夠管理複雜的製造流程、分析大量資料集並產生切實可行的洞察。隨著人工智慧模型的不斷進步和從營運數據中學習，企業可以提高效率並保持高品質標準。人工智慧軟體和工業整合的持續創新正在推動其在汽車、電子和製藥行業的應用。這些技術進步使人工智慧驅動的視覺系統更加智慧、適應性更強，並成為現代製造業的重要工具，為產業格局創造了巨大的成長潛力。

競爭激烈，市場飽和

人工智慧工業視覺市場競爭日益激烈，對新參與企業和現有企業都構成了重大威脅。眾多供應商提供雷同的解決方案，使得產品差異化變得困難，進而導致定價壓力和利潤率下降。規模較小的公司可能難以與擁有強大技術專長和雄厚資金支持的知名品牌競爭。市場飽和，尤其是在成熟地區，進一步限制了成長潛力。為了保持競爭力，公司必須不斷創新並豐富其產品線。未能適應變化將導致客戶流失和市場佔有率損失，從而限制其在競爭激烈的工業視覺領域的擴張機會。

COVID-19的影響

新冠疫情對人工智慧工業視覺市場既帶來了挑戰，也帶來了鼓舞。最初，製造業放緩、供應鏈中斷以及工廠暫時關閉阻礙了市場擴張。然而，疫情加速了人工智慧和自動化解決方案的部署，因為各企業都在努力減少人機交互，確保持續營運並提高生產力。在此期間，遠端監控、預測性維護和即時品質檢測等應用變得至關重要，彰顯了人工智慧視覺技術的重要性。疫情過後，各企業紛紛優先投資人工智慧工業視覺系統，以增強營運韌性，減少對人工的依賴，並為未來的生產中斷和技術進步做好準備。

預計預測期內雲端基礎市場規模最大

預計雲端基礎的細分市場將在預測期內佔據最大的市場佔有率，這得益於其靈活性、擴充性和經濟高效的部署。利用雲端基礎設施，製造商無需在本地伺服器和硬體上進行大量投資即可管理和分析大量視覺數據。這些解決方案提供即時監控、遠端存取以及與物聯網設備和智慧工廠計劃的順暢整合。雲端平台還提供集中管理、自動更新和快速實施，使其成為各種規模組織的理想選擇。預測性洞察和高級分析可從任何地方訪問，從而改善決策和營運績效。這些優勢使雲端基礎的人工智慧視覺系統成為市場主導。

預計深度學習模型部分將在預測期內實現最高的複合年成長率

預計深度學習模型領域將在預測期內實現最高成長率，這得益於對智慧和自適應檢測系統日益成長的需求。這些演算法有助於在複雜的製造環境中實現精確的模式識別、缺陷檢測和預測性維護。隨著製造商尋求提高自動化程度和嚴格的品管，深度學習解決方案提供了超越傳統視覺技術的高階決策能力。它們能夠持續從營運數據中學習並隨著時間的推移最佳化效能，使其極具價值。汽車、電子和製藥等行業正在迅速採用這些模型，以提高準確性、效率和可操作的洞察力，從而推動基於深度學習的工業視覺技術的市場大幅擴張。

比最大的地區

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其先進的工業基礎、工業 4.0 的廣泛應用以及針對人工智慧的大規模投資。汽車、電子和製藥等關鍵產業擴大採用人工智慧視覺系統來加強品質保證、最佳化流程和實現預測性維護。該地區的技術專長、熟練的勞動力和政府支援將進一步推動市場擴張。此外，主要企業的存在及其對自動化和智慧製造設施的關注也鞏固了北美的領先地位。由於這些綜合因素，該地區將繼續主導全球人工智慧工業視覺市場，並保持其作為市場收益最大區域貢獻者的地位。

複合年成長率最高的地區

預計亞太地區在預測期內將呈現最高的複合年成長率，這得益於工業化進程的加速、智慧製造實踐的採用以及自動化投資的增加。中國、日本、韓國和印度等國家正在升級其製造業，並實施人工智慧視覺技術，以提高流程效率、品質保證和預測性維護。優惠的政府政策、不斷成長的熟練勞動力以及充滿活力的科技新創企業生態系統將進一步推動市場擴張。工業設施的擴張，加上對先進生產解決方案日益成長的需求，使亞太地區成為成長最快的地區，並使其成為全球人工智慧工業視覺成長最快的市場。

免費客製化服務

此報告的訂閱者可以選擇以下免費自訂選項之一：

  • 公司簡介
    • 全面分析其他市場參與者（最多 3 家公司）
    • 主要企業的SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶興趣對主要國家進行的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章 全球人工智慧工業視覺市場（按組件）

  • 硬體
  • 軟體
  • 服務

6. 全球人工智慧工業視覺市場（按部署模式）

  • 本地部署
  • 雲端基礎
  • 基於邊緣

7. 全球人工智慧工業視覺市場（按技術）

  • 2D視覺系統
  • 3D視覺系統
  • 深度學習模型
  • 生成式人工智慧模組
  • 嵌入式AI晶片

第8章全球人工智慧工業視覺市場（按應用）

  • 缺陷檢測和品質保證
  • 機器人尋路與物體定位
  • 預測性資產監控
  • 職場安全與危害監測
  • 自動排序和分類

第9章全球人工智慧工業視覺市場（按最終用戶）

  • 汽車製造業
  • 半導體和電子設備製造
  • 食品加工/包裝
  • 藥品生產與合規
  • 倉庫自動化/物流
  • 重型設備/金屬加工

第 10 章全球人工智慧工業視覺市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第12章 公司概況

  • 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.