Edge AI in Automation Market Forecasts to 2034 – Global Analysis By Component (Edge AI Hardware, Edge AI Software, AI Accelerators, Edge AI Services and Other Components), Technology, Industry, Application, End User and Geography
According to Stratistics MRC, the Global Edge AI in Automation Market is accounted for $11.5 billion in 2026 and is expected to reach $52.0 billion by 2034 growing at a CAGR of 20.8% during the forecast period. Edge AI in automation refers to the deployment of artificial intelligence algorithms directly on devices or machines at the data source rather than relying on centralized cloud systems. In agriculture and industrial systems, edge AI enables real-time processing of sensor data for tasks such as crop monitoring, equipment control, and predictive maintenance. This reduces latency, improves response time, and enhances operational efficiency even in low-connectivity environments. Edge AI supports autonomous decision-making in smart farming equipment and robotics. Increasing demand for real-time analytics and decentralized computing is driving adoption of edge AI technologies.
Market Dynamics:
Driver:
Need for real-time processing
Traditional cloud-based systems often struggle with latency, making edge solutions more attractive. Manufacturers are deploying edge AI to improve decision-making in critical operations. Real-time analytics enhance productivity and reduce downtime in smart factories. Governments are supporting digital transformation initiatives that emphasize edge computing. Technology providers are investing heavily in hardware and software tailored for automation. This growing reliance on immediate insights is driving the market forward.
Restraint:
High deployment integration complexity
A major restraint is the complexity involved in integrating edge AI systems into existing infrastructure. Many factories operate with legacy equipment that is difficult to modernize. High costs of integration discourage smaller enterprises from adoption. Skilled workforce shortages further complicate deployment. Vendors must provide extensive training and support to ensure smooth implementation. Regulatory compliance adds another layer of complexity for industries.
Opportunity:
Reduced cloud dependency benefits
An important opportunity lies in the reduced dependency on cloud systems offered by edge AI. By processing data locally, companies minimize reliance on external servers. This improves security and reduces risks of data breaches. Localized processing also lowers bandwidth costs and enhances operational efficiency. Manufacturers benefit from faster response times in mission-critical environments. Governments are encouraging edge adoption to strengthen data sovereignty. These advantages are fostering rapid growth in the edge AI automation market.
Threat:
Rapid technology evolution risks
Frequent updates and innovations can make existing systems obsolete quickly. Companies may hesitate to invest due to uncertainty about long-term viability. High costs of upgrading equipment add financial pressure. Smaller firms struggle to keep pace with rapid advancements. Vendors face challenges in maintaining compatibility across diverse platforms. This constant evolution is constraining consistent expansion of edge AI in automation.
Covid-19 Impact:
Covid-19 had a mixed impact on the edge AI automation market. On one hand, demand rose as industries sought resilient systems during supply chain disruptions. Remote monitoring and predictive analytics became essential for continuity. On the other hand, economic uncertainty limited investments in advanced technologies. Supply chain delays slowed hardware availability. Preventive health awareness increased focus on automation and contactless operations.
The edge AI hardware segment is expected to be the largest during the forecast period
The edge AI hardware segment is expected to account for the largest market share during the forecast period as devices that enable localized processing. Hardware solutions provide the foundation for real-time analytics. Manufacturers are prioritizing robust and scalable hardware platforms. Governments are supporting hardware innovation through funding and pilot projects. Adoption is strong in sectors such as manufacturing, logistics, and energy. Vendors are focusing on durability and efficiency.
The smart factory operators segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the smart factory operators segment is predicted to witness the highest growth rate due to rising demand for automation solutions that enhance productivity and reduce operational risks. Edge AI enables predictive maintenance and real-time monitoring in factories. Operators benefit from improved efficiency and reduced downtime. Awareness campaigns highlight the role of smart factories in Industry 4.0. Governments are funding initiatives to accelerate digital transformation. Partnerships between technology providers and operators are expanding reach.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share owing to early adoption of edge AI technologies. The US and Canada host leading innovators in automation and AI hardware. Policy frameworks encourage digital transformation across industries. Commercial enterprises are increasingly deploying premium edge AI systems. Retail penetration of automation solutions is widespread across the region. Academic institutions are actively researching edge AI applications.
Region with highest CAGR:
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by supportive government subsidies for automation initiatives. Countries such as China, India, and Japan are investing heavily in smart factory infrastructure. Affordable edge AI solutions are gaining traction among mid-sized enterprises. Rural digitization programs are expanding access to advanced technologies. E-commerce platforms are helping distribute automation tools to diverse industries. Younger demographics are embracing digital transformation rapidly.
Key players in the market
Some of the key players in Edge AI in Automation Market include NVIDIA Corporation, Intel Corporation, Qualcomm Incorporated, Advanced Micro Devices Inc., IBM Corporation, Microsoft Corporation, Siemens AG, ABB Ltd., Schneider Electric SE, Honeywell International Inc., Rockwell Automation Inc., Advantech Co. Ltd., Cisco Systems Inc., HPE Corporation and Oracle 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 October 2025, NVIDIA Corporation announced the commercial rollout of its Jetson Orin Nano 8 GB module, delivering up to 40 TOPS of AI processing capability within a sub-15-watt power envelope. This hardware deployment targets compact robotics and embedded machine vision systems, working in tandem with the brand's updated JetPack SDK to streamline decentralized model deployment and computer vision processing on the factory floor without cloud dependencies.
Components Covered:
- 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:
Market Dynamics:
Driver:
Need for real-time processing
Traditional cloud-based systems often struggle with latency, making edge solutions more attractive. Manufacturers are deploying edge AI to improve decision-making in critical operations. Real-time analytics enhance productivity and reduce downtime in smart factories. Governments are supporting digital transformation initiatives that emphasize edge computing. Technology providers are investing heavily in hardware and software tailored for automation. This growing reliance on immediate insights is driving the market forward.
Restraint:
High deployment integration complexity
A major restraint is the complexity involved in integrating edge AI systems into existing infrastructure. Many factories operate with legacy equipment that is difficult to modernize. High costs of integration discourage smaller enterprises from adoption. Skilled workforce shortages further complicate deployment. Vendors must provide extensive training and support to ensure smooth implementation. Regulatory compliance adds another layer of complexity for industries.
Opportunity:
Reduced cloud dependency benefits
An important opportunity lies in the reduced dependency on cloud systems offered by edge AI. By processing data locally, companies minimize reliance on external servers. This improves security and reduces risks of data breaches. Localized processing also lowers bandwidth costs and enhances operational efficiency. Manufacturers benefit from faster response times in mission-critical environments. Governments are encouraging edge adoption to strengthen data sovereignty. These advantages are fostering rapid growth in the edge AI automation market.
Threat:
Rapid technology evolution risks
Frequent updates and innovations can make existing systems obsolete quickly. Companies may hesitate to invest due to uncertainty about long-term viability. High costs of upgrading equipment add financial pressure. Smaller firms struggle to keep pace with rapid advancements. Vendors face challenges in maintaining compatibility across diverse platforms. This constant evolution is constraining consistent expansion of edge AI in automation.
Covid-19 Impact:
Covid-19 had a mixed impact on the edge AI automation market. On one hand, demand rose as industries sought resilient systems during supply chain disruptions. Remote monitoring and predictive analytics became essential for continuity. On the other hand, economic uncertainty limited investments in advanced technologies. Supply chain delays slowed hardware availability. Preventive health awareness increased focus on automation and contactless operations.
The edge AI hardware segment is expected to be the largest during the forecast period
The edge AI hardware segment is expected to account for the largest market share during the forecast period as devices that enable localized processing. Hardware solutions provide the foundation for real-time analytics. Manufacturers are prioritizing robust and scalable hardware platforms. Governments are supporting hardware innovation through funding and pilot projects. Adoption is strong in sectors such as manufacturing, logistics, and energy. Vendors are focusing on durability and efficiency.
The smart factory operators segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the smart factory operators segment is predicted to witness the highest growth rate due to rising demand for automation solutions that enhance productivity and reduce operational risks. Edge AI enables predictive maintenance and real-time monitoring in factories. Operators benefit from improved efficiency and reduced downtime. Awareness campaigns highlight the role of smart factories in Industry 4.0. Governments are funding initiatives to accelerate digital transformation. Partnerships between technology providers and operators are expanding reach.
Region with largest share:
During the forecast period, the North America region is expected to hold the largest market share owing to early adoption of edge AI technologies. The US and Canada host leading innovators in automation and AI hardware. Policy frameworks encourage digital transformation across industries. Commercial enterprises are increasingly deploying premium edge AI systems. Retail penetration of automation solutions is widespread across the region. Academic institutions are actively researching edge AI applications.
Region with highest CAGR:
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by supportive government subsidies for automation initiatives. Countries such as China, India, and Japan are investing heavily in smart factory infrastructure. Affordable edge AI solutions are gaining traction among mid-sized enterprises. Rural digitization programs are expanding access to advanced technologies. E-commerce platforms are helping distribute automation tools to diverse industries. Younger demographics are embracing digital transformation rapidly.
Key players in the market
Some of the key players in Edge AI in Automation Market include NVIDIA Corporation, Intel Corporation, Qualcomm Incorporated, Advanced Micro Devices Inc., IBM Corporation, Microsoft Corporation, Siemens AG, ABB Ltd., Schneider Electric SE, Honeywell International Inc., Rockwell Automation Inc., Advantech Co. Ltd., Cisco Systems Inc., HPE Corporation and Oracle 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 October 2025, NVIDIA Corporation announced the commercial rollout of its Jetson Orin Nano 8 GB module, delivering up to 40 TOPS of AI processing capability within a sub-15-watt power envelope. This hardware deployment targets compact robotics and embedded machine vision systems, working in tandem with the brand's updated JetPack SDK to streamline decentralized model deployment and computer vision processing on the factory floor without cloud dependencies.
Components Covered:
- Edge AI Hardware
- Edge AI Software
- AI Accelerators
- Edge AI Services
- Other Components
- Machine Learning Technology
- Deep Learning Technology
- Computer Vision Technology
- Real-Time Analytics Technology
- Other Technologies
- Manufacturing Industry
- Automotive Industry
- Healthcare Industry
- Logistics Industry
- Energy and Utilities Industry
- Other Industries
- Smart Manufacturing Applications
- Predictive Maintenance Applications
- Autonomous Robotics Applications
- Industrial Monitoring Applications
- Other Applications
- Industrial Enterprises
- Automation Solution Providers
- Smart Factory Operators
- Original Equipment Manufacturers
- Other End Users
- 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
- 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 EDGE AI IN AUTOMATION MARKET, BY COMPONENT
5.1 Edge AI Hardware
5.2 Edge AI Software
5.3 AI Accelerators
5.4 Edge AI Services
5.5 Other Components
6 GLOBAL EDGE AI IN AUTOMATION MARKET, BY TECHNOLOGY
6.1 Machine Learning Technology
6.2 Deep Learning Technology
6.3 Computer Vision Technology
6.4 Real-Time Analytics Technology
6.5 Other Technologies
7 GLOBAL EDGE AI IN AUTOMATION MARKET, BY INDUSTRY
7.1 Manufacturing Industry
7.2 Automotive Industry
7.3 Healthcare Industry
7.4 Logistics Industry
7.5 Energy and Utilities Industry
7.6 Other Industries
8 GLOBAL EDGE AI IN AUTOMATION MARKET, BY APPLICATION
8.1 Smart Manufacturing Applications
8.2 Predictive Maintenance Applications
8.3 Autonomous Robotics Applications
8.4 Industrial Monitoring Applications
8.5 Other Applications
9 GLOBAL EDGE AI IN AUTOMATION MARKET, BY END USER
9.1 Industrial Enterprises
9.2 Automation Solution Providers
9.3 Smart Factory Operators
9.4 Original Equipment Manufacturers
9.5 Other End Users
10 GLOBAL EDGE AI IN 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 NVIDIA Corporation
13.2 Intel Corporation
13.3 Qualcomm Incorporated
13.4 Advanced Micro Devices Inc.
13.5 IBM Corporation
13.6 Microsoft Corporation
13.7 Siemens AG
13.8 ABB Ltd.
13.9 Schneider Electric SE
13.10 Honeywell International Inc.
13.11 Rockwell Automation Inc.
13.12 Advantech Co. Ltd.
13.13 Cisco Systems Inc.
13.14 HPE Corporation
13.15 Oracle Corporation
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 EDGE AI IN AUTOMATION MARKET, BY COMPONENT
5.1 Edge AI Hardware
5.2 Edge AI Software
5.3 AI Accelerators
5.4 Edge AI Services
5.5 Other Components
6 GLOBAL EDGE AI IN AUTOMATION MARKET, BY TECHNOLOGY
6.1 Machine Learning Technology
6.2 Deep Learning Technology
6.3 Computer Vision Technology
6.4 Real-Time Analytics Technology
6.5 Other Technologies
7 GLOBAL EDGE AI IN AUTOMATION MARKET, BY INDUSTRY
7.1 Manufacturing Industry
7.2 Automotive Industry
7.3 Healthcare Industry
7.4 Logistics Industry
7.5 Energy and Utilities Industry
7.6 Other Industries
8 GLOBAL EDGE AI IN AUTOMATION MARKET, BY APPLICATION
8.1 Smart Manufacturing Applications
8.2 Predictive Maintenance Applications
8.3 Autonomous Robotics Applications
8.4 Industrial Monitoring Applications
8.5 Other Applications
9 GLOBAL EDGE AI IN AUTOMATION MARKET, BY END USER
9.1 Industrial Enterprises
9.2 Automation Solution Providers
9.3 Smart Factory Operators
9.4 Original Equipment Manufacturers
9.5 Other End Users
10 GLOBAL EDGE AI IN 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 NVIDIA Corporation
13.2 Intel Corporation
13.3 Qualcomm Incorporated
13.4 Advanced Micro Devices Inc.
13.5 IBM Corporation
13.6 Microsoft Corporation
13.7 Siemens AG
13.8 ABB Ltd.
13.9 Schneider Electric SE
13.10 Honeywell International Inc.
13.11 Rockwell Automation Inc.
13.12 Advantech Co. Ltd.
13.13 Cisco Systems Inc.
13.14 HPE Corporation
13.15 Oracle Corporation
LIST OF TABLES
Table 1 Global Edge AI in Automation Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global Edge AI in Automation Market, By Component (2023–2034) ($MN)
Table 3 Global Edge AI in Automation Market, By Edge AI Hardware (2023–2034) ($MN)
Table 4 Global Edge AI in Automation Market, By Edge AI Software (2023–2034) ($MN)
Table 5 Global Edge AI in Automation Market, By AI Accelerators (2023–2034) ($MN)
Table 6 Global Edge AI in Automation Market, By Edge AI Services (2023–2034) ($MN)
Table 7 Global Edge AI in Automation Market, By Other Components (2023–2034) ($MN)
Table 8 Global Edge AI in Automation Market, By Technology (2023–2034) ($MN)
Table 9 Global Edge AI in Automation Market, By Machine Learning Technology (2023–2034) ($MN)
Table 10 Global Edge AI in Automation Market, By Deep Learning Technology (2023–2034) ($MN)
Table 11 Global Edge AI in Automation Market, By Computer Vision Technology (2023–2034) ($MN)
Table 12 Global Edge AI in Automation Market, By Real-Time Analytics Technology (2023–2034) ($MN)
Table 13 Global Edge AI in Automation Market, By Other Technologies (2023–2034) ($MN)
Table 14 Global Edge AI in Automation Market, By Industry (2023–2034) ($MN)
Table 15 Global Edge AI in Automation Market, By Manufacturing Industry (2023–2034) ($MN)
Table 16 Global Edge AI in Automation Market, By Automotive Industry (2023–2034) ($MN)
Table 17 Global Edge AI in Automation Market, By Healthcare Industry (2023–2034) ($MN)
Table 18 Global Edge AI in Automation Market, By Logistics Industry (2023–2034) ($MN)
Table 19 Global Edge AI in Automation Market, By Energy and Utilities Industry (2023–2034) ($MN)
Table 20 Global Edge AI in Automation Market, By Other Industries (2023–2034) ($MN)
Table 21 Global Edge AI in Automation Market, By Application (2023–2034) ($MN)
Table 22 Global Edge AI in Automation Market, By Smart Manufacturing Applications (2023–2034) ($MN)
Table 23 Global Edge AI in Automation Market, By Predictive Maintenance Applications (2023–2034) ($MN)
Table 24 Global Edge AI in Automation Market, By Autonomous Robotics Applications (2023–2034) ($MN)
Table 25 Global Edge AI in Automation Market, By Industrial Monitoring Applications (2023–2034) ($MN)
Table 26 Global Edge AI in Automation Market, By Other Applications (2023–2034) ($MN)
Table 27 Global Edge AI in Automation Market, By End User (2023–2034) ($MN)
Table 28 Global Edge AI in Automation Market, By Industrial Enterprises (2023–2034) ($MN)
Table 29 Global Edge AI in Automation Market, By Automation Solution Providers (2023–2034) ($MN)
Table 30 Global Edge AI in Automation Market, By Smart Factory Operators (2023–2034) ($MN)
Table 31 Global Edge AI in Automation Market, By Original Equipment Manufacturers (2023–2034) ($MN)
Table 32 Global Edge AI in Automation Market, By Other End Users (2023–2034) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.
Table 1 Global Edge AI in Automation Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global Edge AI in Automation Market, By Component (2023–2034) ($MN)
Table 3 Global Edge AI in Automation Market, By Edge AI Hardware (2023–2034) ($MN)
Table 4 Global Edge AI in Automation Market, By Edge AI Software (2023–2034) ($MN)
Table 5 Global Edge AI in Automation Market, By AI Accelerators (2023–2034) ($MN)
Table 6 Global Edge AI in Automation Market, By Edge AI Services (2023–2034) ($MN)
Table 7 Global Edge AI in Automation Market, By Other Components (2023–2034) ($MN)
Table 8 Global Edge AI in Automation Market, By Technology (2023–2034) ($MN)
Table 9 Global Edge AI in Automation Market, By Machine Learning Technology (2023–2034) ($MN)
Table 10 Global Edge AI in Automation Market, By Deep Learning Technology (2023–2034) ($MN)
Table 11 Global Edge AI in Automation Market, By Computer Vision Technology (2023–2034) ($MN)
Table 12 Global Edge AI in Automation Market, By Real-Time Analytics Technology (2023–2034) ($MN)
Table 13 Global Edge AI in Automation Market, By Other Technologies (2023–2034) ($MN)
Table 14 Global Edge AI in Automation Market, By Industry (2023–2034) ($MN)
Table 15 Global Edge AI in Automation Market, By Manufacturing Industry (2023–2034) ($MN)
Table 16 Global Edge AI in Automation Market, By Automotive Industry (2023–2034) ($MN)
Table 17 Global Edge AI in Automation Market, By Healthcare Industry (2023–2034) ($MN)
Table 18 Global Edge AI in Automation Market, By Logistics Industry (2023–2034) ($MN)
Table 19 Global Edge AI in Automation Market, By Energy and Utilities Industry (2023–2034) ($MN)
Table 20 Global Edge AI in Automation Market, By Other Industries (2023–2034) ($MN)
Table 21 Global Edge AI in Automation Market, By Application (2023–2034) ($MN)
Table 22 Global Edge AI in Automation Market, By Smart Manufacturing Applications (2023–2034) ($MN)
Table 23 Global Edge AI in Automation Market, By Predictive Maintenance Applications (2023–2034) ($MN)
Table 24 Global Edge AI in Automation Market, By Autonomous Robotics Applications (2023–2034) ($MN)
Table 25 Global Edge AI in Automation Market, By Industrial Monitoring Applications (2023–2034) ($MN)
Table 26 Global Edge AI in Automation Market, By Other Applications (2023–2034) ($MN)
Table 27 Global Edge AI in Automation Market, By End User (2023–2034) ($MN)
Table 28 Global Edge AI in Automation Market, By Industrial Enterprises (2023–2034) ($MN)
Table 29 Global Edge AI in Automation Market, By Automation Solution Providers (2023–2034) ($MN)
Table 30 Global Edge AI in Automation Market, By Smart Factory Operators (2023–2034) ($MN)
Table 31 Global Edge AI in Automation Market, By Original Equipment Manufacturers (2023–2034) ($MN)
Table 32 Global Edge AI in Automation Market, By Other End Users (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.
