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市場調查報告書

商品編碼

2068717

人工智慧驅動的工業自動化市場預測至2034年——按組件、技術、產業、應用、最終用戶和地區分類的全球分析

AI-Powered Industrial Automation Market Forecasts to 2034 - Global Analysis By Component (Hardware Platforms, AI Software Solutions, Industrial AI Services, Edge AI Devices and Other Components), Technology, Industry, Application, End User and Geography

出版日期: 2026年06月11日 | 出版商:

Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

簡介目錄圖表

根據 Stratistics MRC 預測，全球人工智慧驅動的工業自動化市場規模預計將在 2026 年達到 280 億美元，預測期內複合年成長率 (CAGR) 為 19.8%，到 2034 年將達到 1200 億美元。人工智慧驅動的工業自動化將人工智慧技術與自動化系統結合，以提升工業和農業領域的決策能力、效率和預測能力。人工智慧演算法分析來自感測器、機械和生產系統的大規模資料集，從而最佳化工作流程、預測設備故障並提高流程精度。在農業領域，它支持智慧農業、自主農業機械和預測性維護。這項技術減少了人為干預，提高了生產力並提升了營運效率。數位轉型的推進和工業 4.0 的廣泛應用正在推動人工智慧驅動的自動化系統在全球範圍內的快速發展。

人工智慧在製造業的應用日益普及

製造商正在部署智慧演算法，以提高生產效率、預測性維護和即時決策能力。人工智慧技術透過實現對複雜工業流程的自適應控制，提高了操作精度。對快速、零誤差生產系統日益成長的需求進一步推動了其應用。工業企業正在投資智慧自動化，以減少停機時間並最佳化資源利用。機器學習和工業分析的不斷進步正在加速其在生產設施中的部署。

數據品質問題

為了使人工智慧模型在整個製造環境中有效運行，準確、即時且結構化的資料輸入至關重要。不一致或不完整的數據會降低系統精度，並對營運結果產生負面影響。當整合來自多個工業資料來源的資料時，相容性挑戰常常出現。感測器故障和通訊延遲會進一步降低模型可靠性。許多組織都在努力維護跨舊有系統和現代系統的標準化資料管道。

擴大自主生產線

自主系統能夠以最小的人工干預實現完全運作的製造流程，從而提高生產效率和營運效率。這正推動著全球大規模生產環境中自主生產線的擴張，因為工業企業擴大採用基於人工智慧的機器人、機器視覺系統和預測控制平台來簡化流程並提高製造精度。對靈活且擴充性的製造系統的需求正在穩步成長。全球對智慧工廠基礎設施的投資正在加速。這些趨勢預計將進一步增強長期市場潛力。

對勞動替代的抵制

人工智慧驅動的機器人和自主機械的日益普及正在減少多個製造流程中對人工的需求。這種轉變可能引發產業工人對工作保障的擔憂。工會和工人組織可能會反對大規模自動化舉措。對技術轉型的抵制可能會減緩某些地區的普及速度。企業也可能面臨與就業影響相關的監管和社會壓力。這些因素對市場構成了重大挑戰。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了全球各工業領域自動化和人工智慧技術的應用。在人手不足和營運中斷的情況下，製造商擴大部署智慧系統以維持生產的連續性。疫情期間，對人工智慧驅動的監控和預測性維護解決方案的需求顯著成長。供應鏈中斷凸顯了彈性自動化製造系統的重要性。工業企業加快了數位轉型策略，以減少對人工的依賴。疫情後，對智慧工廠技術的投資穩定成長。

在預測期內，硬體平台細分市場預計將佔據最大的市場佔有率。

預計在預測期內，硬體平台細分市場將佔據最大的市場佔有率，這主要得益於邊緣設備的普及，這些設備支援全球製造環境中的即時人工智慧處理和營運執行。隨著自動化程度的提高，對高性能工業硬體的需求持續成長。先進機器人和控制系統的整合進一步鞏固了該細分市場的主導地位。智慧工廠基礎設施的擴展正在推動硬體的廣泛應用。工業運算能力的不斷提升也是推動硬體應用的重要因素。這些因素預計將確保公司在該細分市場保持領先地位。

預計在預測期內，電腦視覺技術領域將呈現最高的複合年成長率。

在預測期內，電腦視覺技術領域預計將呈現最高的成長率，這主要得益於全球先進製造環境中即時物體辨識能力的提升。電腦視覺系統能夠實現精準的缺陷檢測，並提高生產線的操作精度。隨著全球製造商不斷採用人工智慧影像處理系統、基於深度學習的視覺分析和自動化檢測平台來提升產品品質並減少製造誤差，電腦視覺技術領域的成長正在加速。此外，視覺系統與機器人的整合應用日益廣泛，也進一步推動了市場擴張。這些因素共同支撐了該領域以較高的複合年成長率成長。

市佔率最大的地區：

在預測期內，亞太地區預計將佔據最大的市場佔有率，這主要得益於中國、日本、印度、韓國和東南亞等國家自動化技術的日益普及。該地區擁有眾多大規模生產設施，這些設施正在積極部署基於人工智慧的自動化系統。政府支持工業現代化的措施進一步推動了自動化技術的應用。對具成本效益製造解決方案日益成長的需求也促進了市場成長。對智慧工廠的持續投資正在提升該地區的競爭力。

複合年成長率最高的地區：

在預測期內，北美預計將呈現最高的複合年成長率，這主要得益於美國和加拿大對工業4.0實踐的快速採納。該地區的製造商正加大對智慧自動化和機器人系統的投資。對最佳化生產力和營運效率的高度重視正在推動技術整合。人工智慧工業分析的日益普及進一步加速了這一進程。高投資能力使得先進自動化系統的快速擴展成為可能。這些因素共同推動了該地區最快的成長。

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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
- 對主要公司進行SWOT分析（最多3家公司）
區域細分
- 根據客戶要求，我們可以提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
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領先公司進行基準分析。

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
ABB Ltd.
Rockwell Automation Inc.
Schneider Electric SE
Honeywell International Inc.
Microsoft Corporation
IBM Corporation
General Electric Company
SAP SE
Emerson Electric Co.
NVIDIA Corporation
Intel Corporation
Oracle Corporation
FANUC Corporation
Mitsubishi Electric Corporation

簡介目錄圖表

Product Code: SMRC37020

According to Stratistics MRC, the Global AI-Powered Industrial Automation Market is accounted for $28.0 billion in 2026 and is expected to reach $120.0 billion by 2034 growing at a CAGR of 19.8% during the forecast period. AI-powered industrial automation involves the integration of artificial intelligence technologies with automated systems to enhance decision-making, efficiency, and predictive capabilities in industrial and agricultural operations. AI algorithms analyze large datasets from sensors, machines, and production systems to optimize workflows, predict equipment failures, and improve process accuracy. In agriculture, it supports smart farming, autonomous machinery, and predictive maintenance. This technology reduces human intervention, increases productivity, and improves operational efficiency. Growing digital transformation and Industry 4.0 adoption are driving rapid expansion of AI-enabled automation systems globally.

Market Dynamics:

Driver:

Rising AI adoption in manufacturing

Manufacturers are integrating intelligent algorithms to enhance production efficiency, predictive maintenance, and real-time decision-making capabilities. AI technologies are improving operational precision by enabling adaptive control of complex industrial processes. Rising demand for high-speed and error-free production systems is further supporting adoption. Industrial enterprises are investing in intelligent automation to reduce downtime and optimize resource utilization. Continuous advancements in machine learning and industrial analytics are strengthening deployment across production facilities.

Restraint:

Data quality dependency issues

AI models require accurate, real-time, and structured data inputs to function effectively across manufacturing environments. Inconsistent or incomplete data can reduce system accuracy and negatively impact operational outcomes. Integration of data from multiple industrial sources often creates compatibility challenges. Sensor malfunctions or communication delays may further affect model reliability. Many organizations face difficulties in maintaining standardized data pipelines across legacy and modern systems.

Opportunity:

Autonomous production line expansion

Autonomous systems enable fully self-operating manufacturing processes with minimal human intervention, improving productivity and operational efficiency. This is driving autonomous production line expansion as industrial enterprises increasingly deploy AI-based robotics, machine vision systems, and predictive control platforms to streamline manufacturing workflows and enhance precision in large-scale production environments globally. Demand for flexible and scalable manufacturing systems is rising steadily. Investments in smart factory infrastructure are accelerating worldwide. These developments are expected to strengthen long-term market potential.

Threat:

Workforce displacement resistance

Increasing deployment of AI-driven robotics and autonomous machines is reducing the need for manual labor in several manufacturing processes. This shift may lead to concerns regarding job security among industrial workers. Labor unions and workforce groups may oppose large-scale automation initiatives. Resistance to technological transition can slow down implementation in certain regions. Organizations may also face regulatory and social pressure related to employment impacts. These factors act as significant market challenges.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of automation and AI-driven technologies across industrial sectors worldwide. Manufacturers increasingly implemented intelligent systems to maintain production continuity amid labor shortages and operational disruptions. Demand for AI-powered monitoring and predictive maintenance solutions increased significantly during the pandemic period. Supply chain interruptions highlighted the importance of resilient and automated manufacturing systems. Industrial organizations accelerated digital transformation strategies to reduce dependency on manual operations. Investment in smart factory technologies increased steadily post-pandemic.

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

The hardware platforms segment is expected to account for the largest market share during the forecast period as edge devices to support real-time AI processing and operational execution across manufacturing environments globally. Demand for high-performance industrial hardware continues to grow with increasing automation adoption. Integration of advanced robotics and control systems further strengthens segment dominance. Expansion of smart factory infrastructure supports widespread hardware deployment. Continuous upgrades in industrial computing capabilities also drive adoption. These factors ensure strong segment leadership.

The computer vision technology segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the computer vision technology segment is predicted to witness the highest growth rate due to real-time object recognition capabilities within advanced manufacturing environments worldwide. Computer vision systems enable precise defect detection and enhanced operational accuracy in production lines. This is driving computer vision technology segment growth as manufacturers increasingly deploy AI-enabled imaging systems, deep learning-based visual analytics, and automated inspection platforms to improve product quality and reduce manufacturing errors across industrial operations globally. Rising adoption of robotics-integrated vision systems is further accelerating market expansion. These factors collectively support strong CAGR growth.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share owing to increasing adoption of automation technologies across countries such as China, Japan, India, South Korea, and Southeast Asia. The region hosts large-scale production facilities that are actively integrating AI-based automation systems. Government initiatives supporting industrial modernization further strengthen adoption. Rising demand for cost-efficient manufacturing solutions also contributes to growth. Continuous investment in smart factories enhances regional competitiveness.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR driven by rapid adoption of Industry 4.0 practices across the United States and Canada. Manufacturers in the region are increasingly investing in intelligent automation and robotics systems. Strong focus on productivity optimization and operational efficiency supports technology integration. Growing deployment of AI-based industrial analytics further accelerates adoption. High investment capacity enables rapid scaling of advanced automation systems. These factors drive the fastest regional growth.

Key players in the market

Some of the key players in AI-Powered Industrial Automation Market include Siemens AG, ABB Ltd., Rockwell Automation Inc., Schneider Electric SE, Honeywell International Inc., Microsoft Corporation, IBM Corporation, General Electric Company, SAP SE, Emerson Electric Co., NVIDIA Corporation, Intel Corporation, Oracle Corporation, FANUC Corporation and Mitsubishi Electric Corporation.

Key Developments:

In April 2026, Siemens AG announced a massive expansion of its Industrial Edge ecosystem at Hannover Messe, highlighted by the introduction of its all-inclusive Industrial AI Suite. This infrastructure rollout simplifies the lifecycle management of decentralized AI models, allowing plant engineers to scale predictive maintenance and automated visual quality inspection applications across multiple production plants while preserving air-gapped system security.

In March 2026, Intel Corporation rolled out its updated Intel AI Edge Systems and Edge AI Suites, integrating optimized software runtimes and pre-trained models explicitly designed for real-time inferencing. This product rollout leverages Intel's latest mobile-focused processors to power localized smart-factory automation and mobile-edge-compute nodes, enabling manufacturers to execute high-speed defect detection and predictive maintenance workflows directly at the device level.

In January 2026, Microsoft Corporation announced a deepening cloud infrastructure alliance with Rockwell Automation to embed Azure OpenAI service capabilities directly into edge-computing factory software. This technical integration allows operators to generate natural-language diagnostic queries from industrial digital twins, accelerating root-cause analysis on the factory floor by combining historical supervisory control data with live telemetry.

Components Covered:

Hardware Platforms
AI Software Solutions
Industrial AI Services
Edge AI Devices
Other Components

Technologies Covered:

Machine Learning Technology
Computer Vision Technology
Natural Language Processing Technology
Predictive Analytics Technology
Other Technologies

Industries Covered:

Automotive Industry
Manufacturing Industry
Energy and Utilities Industry
Food and Beverage Industry
Pharmaceutical Industry
Other Industries

Applications Covered:

Predictive Maintenance Applications
Quality Control Applications
Process Optimization Applications
Robotic Automation Applications
Other Applications

End Users Covered:

Large Industrial Enterprises
Small and Medium Enterprises
Automation Solution Providers
Industrial Facility Operators
Other End Users

Regions Covered:

North America
- United States
- Canada
- Mexico
Europe
- United Kingdom
- Germany
- France
- Italy
- Spain
- Netherlands
- Belgium
- Sweden
- Switzerland
- Poland
- Rest of Europe
Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Thailand
- Malaysia
- Singapore
- Vietnam
- Rest of Asia Pacific
South America
- Brazil
- Argentina
- Colombia
- Chile
- Peru
- Rest of South America
Rest of the World (RoW)
- Middle East
Saudi Arabia
United Arab Emirates
Qatar
Israel
Rest of Middle East
- Africa
South Africa
Egypt
Morocco
Rest of 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, 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

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-Powered Industrial Automation Market, By Component

5.1 Hardware Platforms
5.2 AI Software Solutions
5.3 Industrial AI Services
5.4 Edge AI Devices
5.5 Other Components

6 Global AI-Powered Industrial Automation Market, By Technology

6.1 Machine Learning Technology
6.2 Computer Vision Technology
6.3 Natural Language Processing Technology
6.4 Predictive Analytics Technology
6.5 Other Technologies

7 Global AI-Powered Industrial Automation Market, By Industry

7.1 Automotive Industry
7.2 Manufacturing Industry
7.3 Energy and Utilities Industry
7.4 Food and Beverage Industry
7.5 Pharmaceutical Industry
7.6 Other Industries

8 Global AI-Powered Industrial Automation Market, By Application

8.1 Predictive Maintenance Applications
8.2 Quality Control Applications
8.3 Process Optimization Applications
8.4 Robotic Automation Applications
8.5 Other Applications

9 Global AI-Powered Industrial Automation Market, By End User

9.1 Large Industrial Enterprises
9.2 Small and Medium Enterprises
9.3 Automation Solution Providers
9.4 Industrial Facility Operators
9.5 Other End Users

10 Global AI-Powered 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 ABB Ltd.
13.3 Rockwell Automation Inc.
13.4 Schneider Electric SE
13.5 Honeywell International Inc.
13.6 Microsoft Corporation
13.7 IBM Corporation
13.8 General Electric Company
13.9 SAP SE
13.10 Emerson Electric Co.
13.11 NVIDIA Corporation
13.12 Intel Corporation
13.13 Oracle Corporation
13.14 FANUC Corporation
13.15 Mitsubishi Electric Corporation

簡介目錄圖表

List of Tables

Table 1 Global AI-Powered Industrial Automation Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global AI-Powered Industrial Automation Market, By Component (2023-2034) ($MN)
Table 3 Global AI-Powered Industrial Automation Market, By Hardware Platforms (2023-2034) ($MN)
Table 4 Global AI-Powered Industrial Automation Market, By AI Software Solutions (2023-2034) ($MN)
Table 5 Global AI-Powered Industrial Automation Market, By Industrial AI Services (2023-2034) ($MN)
Table 6 Global AI-Powered Industrial Automation Market, By Edge AI Devices (2023-2034) ($MN)
Table 7 Global AI-Powered Industrial Automation Market, By Other Components (2023-2034) ($MN)
Table 8 Global AI-Powered Industrial Automation Market, By Technology (2023-2034) ($MN)
Table 9 Global AI-Powered Industrial Automation Market, By Machine Learning Technology (2023-2034) ($MN)
Table 10 Global AI-Powered Industrial Automation Market, By Computer Vision Technology (2023-2034) ($MN)
Table 11 Global AI-Powered Industrial Automation Market, By Natural Language Processing Technology (2023-2034) ($MN)
Table 12 Global AI-Powered Industrial Automation Market, By Predictive Analytics Technology (2023-2034) ($MN)
Table 13 Global AI-Powered Industrial Automation Market, By Other Technologies (2023-2034) ($MN)
Table 14 Global AI-Powered Industrial Automation Market, By Industry (2023-2034) ($MN)
Table 15 Global AI-Powered Industrial Automation Market, By Automotive Industry (2023-2034) ($MN)
Table 16 Global AI-Powered Industrial Automation Market, By Manufacturing Industry (2023-2034) ($MN)
Table 17 Global AI-Powered Industrial Automation Market, By Energy and Utilities Industry (2023-2034) ($MN)
Table 18 Global AI-Powered Industrial Automation Market, By Food and Beverage Industry (2023-2034) ($MN)
Table 19 Global AI-Powered Industrial Automation Market, By Pharmaceutical Industry (2023-2034) ($MN)
Table 20 Global AI-Powered Industrial Automation Market, By Other Industries (2023-2034) ($MN)
Table 21 Global AI-Powered Industrial Automation Market, By Application (2023-2034) ($MN)
Table 22 Global AI-Powered Industrial Automation Market, By Predictive Maintenance Applications (2023-2034) ($MN)
Table 23 Global AI-Powered Industrial Automation Market, By Quality Control Applications (2023-2034) ($MN)
Table 24 Global AI-Powered Industrial Automation Market, By Process Optimization Applications (2023-2034) ($MN)
Table 25 Global AI-Powered Industrial Automation Market, By Robotic Automation Applications (2023-2034) ($MN)
Table 26 Global AI-Powered Industrial Automation Market, By Other Applications (2023-2034) ($MN)
Table 27 Global AI-Powered Industrial Automation Market, By End User (2023-2034) ($MN)
Table 28 Global AI-Powered Industrial Automation Market, By Large Industrial Enterprises (2023-2034) ($MN)
Table 29 Global AI-Powered Industrial Automation Market, By Small and Medium Enterprises (2023-2034) ($MN)
Table 30 Global AI-Powered Industrial Automation Market, By Automation Solution Providers (2023-2034) ($MN)
Table 31 Global AI-Powered Industrial Automation Market, By Industrial Facility Operators (2023-2034) ($MN)
Table 32 Global AI-Powered Industrial Automation Market, By Other End Users (2023-2034) ($MN)