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市場調查報告書
商品編碼
2021746

工業自動化領域人工智慧市場預測—全球分析（按組件、技術、自動化類型、應用、最終用戶和地區分類）—2034年

AI in Industrial Automation Market Forecasts to 2034 - Global Analysis By Component (Hardware, Software, and Services), Technology, Automation Type, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

全球工業自動化人工智慧市場預計到 2026 年將達到 150 億美元，到 2034 年將達到 1,400 億美元，預測期內複合年成長率為 32.0%。

工業自動化領域的人工智慧利用先進的演算法、機器學習和數據驅動技術來最佳化和控制工業流程，同時最大限度地減少人為干預。這些系統能夠分析大量數據，做出智慧決策，並即時適應不斷變化的環境。透過簡化操作、減少停機時間、加強品管以及支援預測性維護，這提高了製造業及相關領域的效率、準確性和生產力。

對預測性維護和營運效率的需求日益成長

人工智慧驅動的預測維修系統來自工業設備的即時感測器數據，預測零件故障的發生，從而顯著減少意​​外停機時間和維護成本。傳統的例行維護往往導致不必要的零件更換和意外故障。相比之下，人工智慧演算法能夠學習機器的正常運作模式並偵測異常情況，從而實現及時維修。這種方法延長了設備壽命，提高了整體設備效率，並降低了營運成本。隨著製造商面臨著在最大限度提高產量的同時最大限度減少停機時間的巨大壓力，人工智慧在預測分析領域的應用正在汽車、電子和重型機械等​​行業加速發展。

前期投資龐大且熟練勞動力短缺

將人工智慧應用於工業自動化需要前期在感測器、邊緣運算硬體、軟體平台和系統整合方面進行大量投資。對於中小企業而言，這些成本可能構成障礙。此外，傳統工業環境往往缺乏必要的資料基礎設施和連接標準。除了硬體之外，同時精通工業流程和機器學習的資料科學家、人工智慧工程師和自動化專家也嚴重短缺。彌合這項技能差距需要大量的培訓投入和企業內部的文化轉型，這減緩了人工智慧的廣泛應用，尤其是在開發中國家和傳統製造業領域。

工業4.0和智慧工廠概念的進展

全球向工業4.0和智慧製造的轉型為人工智慧在工業自動化領域的應用創造了機會。各國政府和大型企業正大力投資數位轉型（DX）項目，將人工智慧與物聯網、雲端運算和數位雙胞胎技術結合。人工智慧能夠實現生產線的自我最佳化、即時品質調整和自主物料流。協作機器人和衍生設計等新興技術進一步拓展了人工智慧的應用範圍。隨著工廠網路化程度的提高和資料量的日益豐富，人工智慧解決方案可以分階段部署，從而帶來顯著的投資回報。這一趨勢在汽車、電子和製藥行業尤為明顯。

網路安全和資料隱私問題

隨著工業自動化系統日益主導人工智慧並相互連接，網路攻擊的範圍也不斷擴大。人工智慧模型依賴海量的運行數據，這些數據可能遭到竄改或竊取。對抗性攻擊可以操縱感測器輸入，從而可能導致人工智慧演算法做出危險的決策，例如禁用安全系統或將缺陷產品錯誤​​分類。此外，許多工業環境仍使用安全性較弱的傳統協定。一次成功的攻擊可能導致生產中斷、設備損壞或安全隱患。保護人工智慧管道、確保資料完整性以及遵守不斷演變的網路安全法規仍然是亟待解決的關鍵挑戰，需要持續的投入和警覺。

新冠疫情的影響：

新冠疫情加速了人工智慧在工業自動化領域的應用，因為製造商面臨人手不足、供應鏈中斷以及保持社交距離的必要性。封鎖措施迫使工廠減少現場工人數量，從而增加了對自主系統、遠端監控和人工智慧驅動的品質檢測的需求。儘管在疫情高峰期，最初的資本投資被推遲，但疫情凸顯了依賴勞動力運作的脆弱性。因此，各產業迅速轉型為具有彈性的、人工智慧驅動的自動化解決方案。在後疫情時代，人工智慧主導的自動化解決方案持續成長，企業優先考慮數位轉型，以減少未來可能出現的干擾並提高營運靈活性。

在預測期內，硬體領域預計將佔據最大佔有率。

預計在預測期內，硬體領域將佔據最大的市場佔有率，因為用於收集和處理即時工業數據的實體基礎設施至關重要。該領域包括感測器、控制器和機器人系統，它們構成了人工智慧在工廠部署的基礎。生產線上智慧感測器的日益普及以及協作機器人的廣泛應用，都顯著推動了硬體需求的成長。

在預測期內，軟體領域預計將呈現最高的複合年成長率。

在預測期內，軟體領域預計將呈現最高的成長率，這主要得益於市場對人工智慧平台、分析軟體和機器視覺工具日益成長的需求，這些工具能夠將原始工業數據轉化為可執行的洞察。軟體支援預測演算法、數位雙胞胎和自適應過程控制。隨著工業環境的資料密集度不斷提高，可擴展且可升級的軟體解決方案能夠提供柔軟性和快速部署能力，因此極具吸引力。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於該地區聚集了眾多人工智慧軟體供應商和工業機器人製造商，以及工業4.0技術的早期應用。美國憑藉其強大的汽車和電子製造業基礎，以及政府支持智慧製造的各項舉措，在該地區處於領先地位。此外，成熟的創業投資Start-Ups創投生態系統也正在加速創新。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於快速的工業化進程、中國大陸、台灣和韓國電子及半導體製造業的擴張，以及政府主導的智慧工廠計畫。印度、越南和泰國等國正在吸引大量外資用於自動化生產線建設。該地區龐大的勞動力向高科技製造業轉型，也進一步加速了人工智慧的應用。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域分類
    • 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 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
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球工業自動化人工智慧市場：按組件分類

  • 硬體
    • 感應器
    • 控制器
    • 機器人系統
  • 軟體
    • 人工智慧平台
    • 分析軟體
    • 機器視覺軟體
  • 服務
    • 諮詢
    • 整合與部署
    • 支援與維護

第6章：全球工業自動化人工智慧市場：按技術分類

  • 機器學習
    • 監督式學習
    • 無監督學習
    • 強化學習
  • 深度學習
    • 卷積類神經網路
    • 循環神經網路
    • GAN
  • 自然語言處理（NLP）
    • 語音辨識
    • 自然語言處理
  • 電腦視覺
    • 影像識別
    • 目標偵測
    • 影像分析
  • 預測分析和處方分析

第7章：全球工業自動化人工智慧市場：按自動化類型分類

  • 固定式自動化
  • 可程式自動化
  • 靈活/整合自動化
  • 自主系統

第8章：全球工業自動化人工智慧市場：按應用領域分類

  • 預測性維護和機械檢查
  • 品管和檢驗
  • 生產計畫與最佳化
  • 物料輸送和輸送
  • 供應鏈和庫存管理
  • 工業機器人
  • 流程自動化
  • 安全保障
  • 現場服務

第9章：全球工業自動化人工智慧市場：按最終用戶分類

  • 製造業
  • 車
  • 能源公用事業
  • 電子和半導體
  • 石油和天然氣
  • 衛生保健
  • 航太/國防
  • 零售
  • 食品/飲料

第10章：全球工業自動化人工智慧市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • Siemens AG
  • Rockwell Automation, Inc.
  • ABB Ltd.
  • Schneider Electric SE
  • Honeywell International Inc.
  • Emerson Electric Co.
  • Mitsubishi Electric Corporation
  • Omron Corporation
  • Yokogawa Electric Corporation
  • Fanuc Corporation
  • KUKA AG
  • Bosch Rexroth AG
  • Beckhoff Automation GmbH & Co. KG
  • Yaskawa Electric Corporation
  • Keyence Corporation
Product Code: SMRC35016

According to Stratistics MRC, the Global AI in Industrial Automation Market is accounted for $15.0 billion in 2026 and is expected to reach $140.0 billion by 2034, growing at a CAGR of 32.0% during the forecast period. AI in industrial automation involves the use of advanced algorithms, machine learning, and data-driven technologies to optimize and control industrial processes with minimal human intervention. These systems analyze large volumes of data, make intelligent decisions, and adapt to changing conditions in real time. This improves efficiency, accuracy, and productivity by streamlining operations, reducing downtime, enhancing quality control, and supporting predictive maintenance across manufacturing and related sectors.

Market Dynamics:

Driver:

Rising need for predictive maintenance and operational efficiency

AI-powered predictive maintenance systems analyze real-time sensor data from industrial equipment to forecast component failures before they occur, drastically reducing unplanned downtime and maintenance costs. Traditional scheduled maintenance often leads to either unnecessary part replacements or unexpected breakdowns. By contrast, AI algorithms learn normal machine behavior and detect anomalies, enabling just-in-time repairs. This approach extends asset life, improves overall equipment effectiveness, and lowers operational expenditures. As manufacturers face intense pressure to maximize throughput while minimizing disruptions, the adoption of AI for predictive analytics is accelerating across automotive, electronics, and heavy machinery sectors.

Restraint:

High initial investment and shortage of skilled workforce

Deploying AI in industrial automation requires substantial upfront capital for sensors, edge computing hardware, software platforms, and system integration. For small and medium-sized enterprises, these costs can be prohibitive. Additionally, legacy industrial environments often lack the necessary data infrastructure and connectivity standards. Beyond hardware, there is a critical shortage of data scientists, AI engineers, and automation specialists who understand both industrial processes and machine learning. Bridging this skills gap demands significant training investments and cultural change within organizations, slowing down widespread adoption, particularly in developing economies and traditional manufacturing sectors.

Opportunity:

Growth of Industry 4.0 and smart factory initiatives

The global push toward Industry 4.0 and smart manufacturing creates a fertile ground for AI in industrial automation. Governments and large corporations are investing heavily in digital transformation projects that integrate AI with IoT, cloud computing, and digital twins. AI enables self-optimizing production lines, real-time quality adjustments, and autonomous material flow. Emerging technologies such as collaborative robots and generative design further expand AI's role. As factories become more connected and data-rich, AI solutions can be deployed incrementally, offering clear return on investment. This trend is especially strong in the automotive, electronics, and pharmaceutical industries.

Threat:

Cybersecurity and data privacy concerns

As industrial automation systems become more AI-driven and interconnected, they expand the cyberattack surface. AI models rely on vast amounts of operational data, which can be tampered with or stolen. Adversarial attacks can manipulate sensor inputs to cause AI algorithms to make dangerous decisions, such as disabling safety systems or misclassifying defective products. Furthermore, many industrial environments still use legacy protocols with weak security. A successful breach could lead to production shutdowns, equipment damage, or safety hazards. Protecting AI pipelines, ensuring data integrity, and complying with evolving cybersecurity regulations remain significant challenges that require continuous investment and vigilance.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of AI in industrial automation as manufacturers faced labor shortages, supply chain disruptions, and the need for social distancing. Lockdowns forced plants to reduce on-site workforce, driving demand for autonomous systems, remote monitoring, and AI-powered quality inspection. While initial capital investments were delayed during the peak of the crisis, the pandemic highlighted the vulnerability of labor-dependent operations. As a result, industries rapidly pivoted toward resilient, AI-driven automation solutions. The post-pandemic era has seen sustained growth, with companies prioritizing digital transformation to mitigate future disruptions and improve operational agility.

The hardware segment is expected to be the largest during the forecast period

The hardware segment is expected to account for the largest market share during the forecast period, driven by the essential need for physical infrastructure to collect and process real-time industrial data. This segment includes sensors, controllers, and robotic systems that form the backbone of AI deployment in factories. The increasing installation of smart sensors on production lines and the growing adoption of collaborative robots contribute significantly to hardware demand.

The software segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the software segment is predicted to witness the highest growth rate, owing to the rising need for AI platforms, analytics software, and machine vision tools that transform raw industrial data into actionable insights. Software enables predictive algorithms, digital twins, and adaptive process control. As industrial environments become more data-intensive, scalable and upgradable software solutions offer flexibility and faster deployment, making them highly attractive.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, driven by the presence of leading AI software vendors, industrial robot manufacturers, and early adoption of Industry 4.0 technologies. The United States, with its strong automotive and electronics manufacturing base, along with government initiatives supporting smart manufacturing, leads the region. A mature venture capital ecosystem for AI startups also accelerates innovation.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by rapid industrialization, expansion of electronics and semiconductor manufacturing in China, Taiwan, and South Korea, and government-backed smart factory programs. Countries like India, Vietnam, and Thailand are attracting significant foreign investment in automated production lines. The region's large workforce transition toward high-tech manufacturing further drives AI adoption.

Key players in the market

Some of the key players in AI in Industrial Automation Market include Siemens AG, Rockwell Automation, Inc., ABB Ltd., Schneider Electric SE, Honeywell International Inc., Emerson Electric Co., Mitsubishi Electric Corporation, Omron Corporation, Yokogawa Electric Corporation, Fanuc Corporation, KUKA AG, Bosch Rexroth AG, Beckhoff Automation GmbH & Co. KG, Yaskawa Electric Corporation, and Keyence Corporation.

Key Developments:

In March 2026, Siemens and Rittal have entered a strategic partnership to jointly develop future-proof, sustainable solutions for more efficient data center power distribution in the IEC market. The standardized infrastructure is intended to accelerate the construction of high-performance data centers, minimize time-to-compute, and address the rapidly increasing power densities of AI applications.

In March 2026, Honeywell announced it has signed a groundbreaking supplier framework agreement with the U.S. Department of War (DoW) to rapidly increase the production of critical defense technologies. This agreement includes a $500 million multi-year investment to upgrade the company's production capacity.

Components Covered:

  • Hardware
  • Software
  • Services

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Predictive & Prescriptive Analytics

Automation Types Covered:

  • Fixed Automation
  • Programmable Automation
  • Flexible/Integrated Automation
  • Autonomous Systems

Applications Covered:

  • Predictive Maintenance & Machinery Inspection
  • Quality Control & Inspection
  • Production Planning & Optimization
  • Material Handling & Movement
  • Supply Chain & Inventory Management
  • Industrial Robotics
  • Process Automation
  • Safety & Security
  • Field Services

End Users Covered:

  • Manufacturing
  • Automotive
  • Energy & Utilities
  • Electronics & Semiconductors
  • Oil & Gas
  • Healthcare
  • Aerospace & Defense
  • Retail
  • Food & Beverages

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 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2032 and 2034
  • 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI in Industrial Automation Market, By Component

  • 5.1 Hardware
    • 5.1.1 Sensors
    • 5.1.2 Controllers
    • 5.1.3 Robotics Systems
  • 5.2 Software
    • 5.2.1 AI Platforms
    • 5.2.2 Analytics Software
    • 5.2.3 Machine Vision Software
  • 5.3 Services
    • 5.3.1 Consulting
    • 5.3.2 Integration & Deployment
    • 5.3.3 Support & Maintenance

6 Global AI in Industrial Automation Market, By Technology

  • 6.1 Machine Learning
    • 6.1.1 Supervised Learning
    • 6.1.2 Unsupervised Learning
    • 6.1.3 Reinforcement Learning
  • 6.2 Deep Learning
    • 6.2.1 Convolutional Neural Networks
    • 6.2.2 Recurrent Neural Networks
    • 6.2.3 GANs
  • 6.3 Natural Language Processing (NLP)
    • 6.3.1 Speech Recognition
    • 6.3.2 Language Processing
  • 6.4 Computer Vision
    • 6.4.1 Image Recognition
    • 6.4.2 Object Detection
    • 6.4.3 Video Analytics
  • 6.5 Predictive & Prescriptive Analytics

7 Global AI in Industrial Automation Market, By Automation Type

  • 7.1 Fixed Automation
  • 7.2 Programmable Automation
  • 7.3 Flexible/Integrated Automation
  • 7.4 Autonomous Systems

8 Global AI in Industrial Automation Market, By Application

  • 8.1 Predictive Maintenance & Machinery Inspection
  • 8.2 Quality Control & Inspection
  • 8.3 Production Planning & Optimization
  • 8.4 Material Handling & Movement
  • 8.5 Supply Chain & Inventory Management
  • 8.6 Industrial Robotics
  • 8.7 Process Automation
  • 8.8 Safety & Security
  • 8.9 Field Services

9 Global AI in Industrial Automation Market, By End User

  • 9.1 Manufacturing
  • 9.2 Automotive
  • 9.3 Energy & Utilities
  • 9.4 Electronics & Semiconductors
  • 9.5 Oil & Gas
  • 9.6 Healthcare
  • 9.7 Aerospace & Defense
  • 9.8 Retail
  • 9.9 Food & Beverages

10 Global AI in Industrial Automation Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Siemens AG
  • 13.2 Rockwell Automation, Inc.
  • 13.3 ABB Ltd.
  • 13.4 Schneider Electric SE
  • 13.5 Honeywell International Inc.
  • 13.6 Emerson Electric Co.
  • 13.7 Mitsubishi Electric Corporation
  • 13.8 Omron Corporation
  • 13.9 Yokogawa Electric Corporation
  • 13.10 Fanuc Corporation
  • 13.11 KUKA AG
  • 13.12 Bosch Rexroth AG
  • 13.13 Beckhoff Automation GmbH & Co. KG
  • 13.14 Yaskawa Electric Corporation
  • 13.15 Keyence Corporation

List of Tables

  • Table 1 Global AI in Industrial Automation Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in Industrial Automation Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI in Industrial Automation Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI in Industrial Automation Market Outlook, By Sensors (2023-2034) ($MN)
  • Table 5 Global AI in Industrial Automation Market Outlook, By Controllers (2023-2034) ($MN)
  • Table 6 Global AI in Industrial Automation Market Outlook, By Robotics Systems (2023-2034) ($MN)
  • Table 7 Global AI in Industrial Automation Market Outlook, By Software (2023-2034) ($MN)
  • Table 8 Global AI in Industrial Automation Market Outlook, By AI Platforms (2023-2034) ($MN)
  • Table 9 Global AI in Industrial Automation Market Outlook, By Analytics Software (2023-2034) ($MN)
  • Table 10 Global AI in Industrial Automation Market Outlook, By Machine Vision Software (2023-2034) ($MN)
  • Table 11 Global AI in Industrial Automation Market Outlook, By Services (2023-2034) ($MN)
  • Table 12 Global AI in Industrial Automation Market Outlook, By Consulting (2023-2034) ($MN)
  • Table 13 Global AI in Industrial Automation Market Outlook, By Integration & Deployment (2023-2034) ($MN)
  • Table 14 Global AI in Industrial Automation Market Outlook, By Support & Maintenance (2023-2034) ($MN)
  • Table 15 Global AI in Industrial Automation Market Outlook, By Technology (2023-2034) ($MN)
  • Table 16 Global AI in Industrial Automation Market Outlook, By Machine Learning (2023-2034) ($MN)
  • Table 17 Global AI in Industrial Automation Market Outlook, By Supervised Learning (2023-2034) ($MN)
  • Table 18 Global AI in Industrial Automation Market Outlook, By Unsupervised Learning (2023-2034) ($MN)
  • Table 19 Global AI in Industrial Automation Market Outlook, By Reinforcement Learning (2023-2034) ($MN)
  • Table 20 Global AI in Industrial Automation Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 21 Global AI in Industrial Automation Market Outlook, By Convolutional Neural Networks (2023-2034) ($MN)
  • Table 22 Global AI in Industrial Automation Market Outlook, By Recurrent Neural Networks (2023-2034) ($MN)
  • Table 23 Global AI in Industrial Automation Market Outlook, By GANs (2023-2034) ($MN)
  • Table 24 Global AI in Industrial Automation Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 25 Global AI in Industrial Automation Market Outlook, By Speech Recognition (2023-2034) ($MN)
  • Table 26 Global AI in Industrial Automation Market Outlook, By Language Processing (2023-2034) ($MN)
  • Table 27 Global AI in Industrial Automation Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 28 Global AI in Industrial Automation Market Outlook, By Image Recognition (2023-2034) ($MN)
  • Table 29 Global AI in Industrial Automation Market Outlook, By Object Detection (2023-2034) ($MN)
  • Table 30 Global AI in Industrial Automation Market Outlook, By Video Analytics (2023-2034) ($MN)
  • Table 31 Global AI in Industrial Automation Market Outlook, By Predictive & Prescriptive Analytics (2023-2034) ($MN)
  • Table 32 Global AI in Industrial Automation Market Outlook, By Automation Type (2023-2034) ($MN)
  • Table 33 Global AI in Industrial Automation Market Outlook, By Fixed Automation (2023-2034) ($MN)
  • Table 34 Global AI in Industrial Automation Market Outlook, By Programmable Automation (2023-2034) ($MN)
  • Table 35 Global AI in Industrial Automation Market Outlook, By Flexible/Integrated Automation (2023-2034) ($MN)
  • Table 36 Global AI in Industrial Automation Market Outlook, By Autonomous Systems (2023-2034) ($MN)
  • Table 37 Global AI in Industrial Automation Market Outlook, By Application (2023-2034) ($MN)
  • Table 38 Global AI in Industrial Automation Market Outlook, By Predictive Maintenance & Machinery Inspection (2023-2034) ($MN)
  • Table 39 Global AI in Industrial Automation Market Outlook, By Quality Control & Inspection (2023-2034) ($MN)
  • Table 40 Global AI in Industrial Automation Market Outlook, By Production Planning & Optimization (2023-2034) ($MN)
  • Table 41 Global AI in Industrial Automation Market Outlook, By Material Handling & Movement (2023-2034) ($MN)
  • Table 42 Global AI in Industrial Automation Market Outlook, By Supply Chain & Inventory Management (2023-2034) ($MN)
  • Table 43 Global AI in Industrial Automation Market Outlook, By Industrial Robotics (2023-2034) ($MN)
  • Table 44 Global AI in Industrial Automation Market Outlook, By Process Automation (2023-2034) ($MN)
  • Table 45 Global AI in Industrial Automation Market Outlook, By Safety & Security (2023-2034) ($MN)
  • Table 46 Global AI in Industrial Automation Market Outlook, By Field Services (2023-2034) ($MN)
  • Table 47 Global AI in Industrial Automation Market Outlook, By End User (2023-2034) ($MN)
  • Table 48 Global AI in Industrial Automation Market Outlook, By Manufacturing (2023-2034) ($MN)
  • Table 49 Global AI in Industrial Automation Market Outlook, By Automotive (2023-2034) ($MN)
  • Table 50 Global AI in Industrial Automation Market Outlook, By Energy & Utilities (2023-2034) ($MN)
  • Table 51 Global AI in Industrial Automation Market Outlook, By Electronics & Semiconductors (2023-2034) ($MN)
  • Table 52 Global AI in Industrial Automation Market Outlook, By Oil & Gas (2023-2034) ($MN)
  • Table 53 Global AI in Industrial Automation Market Outlook, By Healthcare (2023-2034) ($MN)
  • Table 54 Global AI in Industrial Automation Market Outlook, By Aerospace & Defense (2023-2034) ($MN)
  • Table 55 Global AI in Industrial Automation Market Outlook, By Retail (2023-2034) ($MN)
  • Table 56 Global AI in Industrial Automation Market Outlook, By Food & Beverages (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.