×
Request Free Sample ×

Kindly complete the form below to receive a free sample of this Report

Leading companies partner with us for data-driven Insights

clients tt-cursor
Hero Background

North America Artificial Industrial In Manufacturing Market

ID: MRFR/ICT/60827-HCR
200 Pages
Aarti Dhapte
October 2025

North America Artificial Intelligence in Manufacturing Market Research Report By Application (Predictive Maintenance, Quality Control, Supply Chain Management, Process Optimization), By Technology (Machine Learning, Natural Language Processing, Computer Vision), By End Use (Automotive, Electronics, Aerospace, Pharmaceuticals), By Deployment Mode (On-Premises, Cloud-Based), and By Regional (US, Canada)-Forecast to 2035

Share:
Download PDF ×

We do not share your information with anyone. However, we may send you emails based on your report interest from time to time. You may contact us at any time to opt-out.

North America Artificial Industrial In Manufacturing Market Infographic
Purchase Options

North America Artificial Industrial In Manufacturing Market Summary

As per MRFR analysis, the North America artificial industrial-in-manufacturing market size was estimated at 1050.0 USD Million in 2024. The North America artificial industrial-in-manufacturing market is projected to grow from 1243.51 USD Million in 2025 to 6749.45 USD Million by 2035, exhibiting a compound annual growth rate (CAGR) of 18.43% during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The North America artificial industrial-in-manufacturing market is experiencing robust growth driven by automation and technological advancements.

  • The US remains the largest market for artificial industrial-in-manufacturing, while Canada is emerging as the fastest-growing region.
  • There is a notable increase in automation adoption across manufacturing sectors, enhancing operational efficiency.
  • A strong focus on sustainability is shaping manufacturing practices, with companies seeking eco-friendly solutions.
  • Rising labor costs and government incentives for automation are key drivers propelling market expansion.

Market Size & Forecast

2024 Market Size 1050.0 (USD Million)
2035 Market Size 6749.45 (USD Million)

Major Players

Siemens (DE), General Electric (US), Rockwell Automation (US), ABB (CH), Honeywell (US), Schneider Electric (FR), Mitsubishi Electric (JP), Emerson Electric (US), Bosch (DE)

North America Artificial Industrial In Manufacturing Market Trends

The artificial industrial-in-manufacturing market in North America is currently experiencing a transformative phase, driven by advancements in technology and increasing demand for automation. Companies are increasingly adopting artificial intelligence and machine learning to enhance operational efficiency and reduce production costs. This shift towards automation is not merely a trend but appears to be a fundamental change in how manufacturing processes are approached. The integration of smart technologies is likely to lead to improved productivity and quality control, which are essential for maintaining competitiveness in a rapidly evolving market. Moreover, sustainability concerns are influencing the artificial industrial-in-manufacturing market. Manufacturers are exploring eco-friendly practices and technologies to minimize their environmental footprint. This focus on sustainability may lead to the development of innovative solutions that not only comply with regulations but also appeal to environmentally conscious consumers. As a result, companies that prioritize sustainable practices could gain a competitive edge, positioning themselves favorably in the market. The interplay between technological advancement and sustainability is shaping the future landscape of manufacturing in North America, suggesting a dynamic and responsive market environment.

Increased Automation Adoption

The trend towards automation in the artificial industrial-in-manufacturing market is becoming more pronounced. Companies are investing in robotic systems and AI-driven solutions to streamline operations and enhance productivity. This shift is likely to reduce labor costs and improve efficiency, allowing manufacturers to respond more swiftly to market demands.

Focus on Sustainability

Sustainability is emerging as a critical factor in the artificial industrial-in-manufacturing market. Manufacturers are increasingly adopting eco-friendly practices and technologies to reduce waste and energy consumption. This trend not only addresses regulatory requirements but also aligns with consumer preferences for environmentally responsible products.

Integration of Advanced Technologies

The integration of advanced technologies such as IoT and big data analytics is reshaping the artificial industrial-in-manufacturing market. These technologies enable real-time monitoring and data-driven decision-making, which can enhance operational efficiency and product quality. As manufacturers leverage these tools, they may gain a competitive advantage in the marketplace.

North America Artificial Industrial In Manufacturing Market Drivers

Rising Labor Costs

The artificial industrial-in-manufacturing market is experiencing a notable shift due to rising labor costs in North America. As wages increase, manufacturers are compelled to seek automation solutions to maintain profitability. This trend is particularly evident in sectors such as automotive and electronics, where labor expenses can account for a significant portion of production costs. The integration of artificial intelligence and robotics is seen as a viable strategy to mitigate these costs. Reports indicate that companies investing in automation technologies can reduce labor costs by up to 30%. Consequently, the demand for artificial industrial-in-manufacturing solutions is likely to grow as businesses strive to optimize their operations and enhance productivity.

Focus on Supply Chain Resilience

The artificial industrial-in-manufacturing market is shaped by the need for supply chain resilience. Recent disruptions have highlighted vulnerabilities in traditional supply chains, prompting manufacturers to adopt more robust and flexible systems. This shift involves the integration of artificial intelligence and data analytics to enhance visibility and responsiveness across the supply chain. Companies are investing in artificial industrial-in-manufacturing solutions that facilitate real-time monitoring and decision-making. By improving supply chain resilience, manufacturers can better navigate uncertainties and maintain operational continuity. This trend is expected to drive significant growth in the artificial industrial-in-manufacturing market as businesses prioritize adaptability and efficiency.

Government Incentives for Automation

Government initiatives aimed at promoting automation in manufacturing are playing a crucial role in the artificial industrial-in-manufacturing market. Various federal and state programs offer financial incentives, tax breaks, and grants to encourage manufacturers to adopt advanced technologies. For instance, the Manufacturing Extension Partnership (MEP) program provides resources to small and medium-sized enterprises to enhance their competitiveness through automation. Such support is expected to drive investment in artificial industrial-in-manufacturing solutions, as companies seek to leverage these incentives. The potential for reduced operational costs and increased efficiency makes this an attractive proposition for manufacturers across North America.

Demand for Customization and Flexibility

The artificial industrial-in-manufacturing market is significantly influenced by the growing demand for customization and flexibility in production processes. Consumers increasingly prefer tailored products, prompting manufacturers to adopt more agile manufacturing systems. This shift necessitates the integration of artificial intelligence and machine learning technologies to enable rapid adjustments in production lines. As a result, companies are investing in artificial industrial-in-manufacturing solutions that allow for quick reconfiguration of machinery and processes. Market analysis suggests that businesses that can offer customized solutions are likely to capture a larger market share, thereby driving the growth of the artificial industrial-in-manufacturing market.

Technological Advancements in AI and Robotics

Technological advancements in artificial intelligence and robotics are propelling the artificial industrial-in-manufacturing market forward. Innovations in machine learning, computer vision, and automation technologies are enhancing the capabilities of manufacturing systems. These advancements enable manufacturers to improve efficiency, reduce errors, and increase production speed. For instance, AI-driven predictive maintenance can minimize downtime, leading to significant cost savings. The market for industrial robots is projected to grow at a CAGR of 10% over the next five years, indicating a robust demand for artificial industrial-in-manufacturing solutions. As technology continues to evolve, manufacturers are likely to invest heavily in these systems to remain competitive.

Market Segment Insights

By Application: Predictive Maintenance (Largest) vs. Robotics (Fastest-Growing)

In the North America artificial industrial-in-manufacturing market, Predictive Maintenance captures the largest share due to its critical role in minimizing downtime and optimizing maintenance schedules. Following closely is Quality Control, which ensures product excellence and compliance with regulatory standards. Other segments like Supply Chain Management, Robotics, and Production Planning, while essential, occupy smaller market shares but are increasingly relevant in today's automated industry landscape. Growth trends indicate a rapid shift towards advanced technologies such as IoT and AI, driving the adoption of Robotics and Supply Chain Management. Businesses are increasingly leveraging these technologies to boost efficiency and maintain competitiveness. Moreover, Predictive Maintenance remains a significant driver as industries focus on reducing operational costs through enhanced equipment reliability, leading to notable market expansion.

Predictive Maintenance (Dominant) vs. Robotics (Emerging)

Predictive Maintenance stands as a dominant force within the application segment, leveraging analytics and IoT to predict equipment failures before they occur, thus enhancing operational efficiency in manufacturing. This segment is characterized by its ability to extend equipment life and reduce unexpected downtimes, making it a vital strategy for industries. Conversely, Robotics, categorized as an emerging application, is rapidly gaining traction due to advancements in automation and artificial intelligence. Robotics enhances productivity by performing repetitive tasks with greater precision and speed. As industries embrace automation, the demand for robotic applications in manufacturing, such as collaborative robots or 'cobots', is set to grow, indicating a shift in how manufacturing processes are approached.

By Technology: Machine Learning (Largest) vs. Robotic Process Automation (Fastest-Growing)

In the North America artificial industrial-in-manufacturing market, Machine Learning holds the largest market share, significantly outpacing its competitors such as Natural Language Processing and Computer Vision. These technologies have carved out substantial niches, but Machine Learning's adaptability and wide-ranging applications in automation and data analysis solidify its dominant position. Robotic Process Automation, while currently smaller in market share, is exhibiting rapid growth, attracting interest from industries looking to enhance efficiency and reduce errors. The growth of Machine Learning is driven by advancements in algorithms and increased availability of data, which enable businesses to leverage predictive analytics and automation. On the other hand, Robotic Process Automation is gaining momentum as companies strive for operational excellence and look for solutions to automate repetitive tasks efficiently. The ongoing digitization and the push towards Industry 4.0 are key trends that fuel the demand for both technologies, positioning them as essential components in the modernization of manufacturing processes.

Technology: Machine Learning (Dominant) vs. Robotic Process Automation (Emerging)

Machine Learning, as the dominant force in the segment, is characterized by its ability to analyze large datasets and draw actionable insights, making it invaluable for predictive maintenance and quality control in manufacturing. Its applications are vast and include everything from supply chain optimization to equipment malfunction predictions. Conversely, Robotic Process Automation represents an emerging trend focused on automating routine tasks and business processes. This technology is increasingly adopted by companies aiming for cost reduction and efficiency gains. While Machine Learning is deeply integrated into strategic decision-making, Robotic Process Automation is leveraged for tactical operational improvements. Both segments, therefore, complement each other, empowering businesses to become smarter and more adaptive.

By Deployment Type: Cloud (Largest) vs. Hybrid (Fastest-Growing)

The deployment type segment showcases a competitive landscape with cloud solutions leading the way in market share, attributed to their scalability and cost-effectiveness. On-premise solutions follow, while hybrid models are increasingly gaining traction due to their flexibility. The adoption rate of cloud-based solutions is primarily driven by the need for agility and access to advanced technologies, making it a preferred choice among manufacturers in North America. Growth in this segment is heavily influenced by the digital transformation initiatives undertaken by industries aiming to improve operational efficiency. Hybrid solutions are on the rise as companies seek to leverage both on-premise and cloud capabilities for optimized performance. This trend is bolstered by advancements in cybersecurity solutions, further assuring businesses of the reliability and security of their hybrid deployments.

Cloud (Dominant) vs. Hybrid (Emerging)

Cloud deployment is characterized by its ability to offer on-demand resources and services, making it the dominant choice for many manufacturers. It provides vast capabilities for data storage, processing, and analysis while reducing upfront infrastructure costs. Companies are increasingly adopting cloud solutions to enhance collaboration and innovation across teams. Conversely, hybrid deployment is emerging as a flexible alternative, combining the strengths of both on-premise and cloud systems. This approach allows businesses to maintain critical data on-site while utilizing cloud resources for less sensitive operations. Manufacturers favor hybrid solutions for their adaptability, facilitating a smoother transition to full cloud adoption while addressing specific regulatory and security concerns.

By End Use Industry: Automotive (Largest) vs. Electronics (Fastest-Growing)

In the artificial industrial-in-manufacturing market, the Automotive sector holds the largest share, significantly outpacing other end-use industries such as Electronics, Aerospace, Food and Beverage, and Pharmaceuticals. The demand for advanced manufacturing solutions in Automotive is driven by relentless innovation and a shift towards electric vehicles, enhancing its dominant position. On the other hand, the Electronics sector is witnessing impressive growth rates, fueled by the increasing adoption of automation and smart technologies across various applications. This trend is expected to further cement its status as the fastest-growing segment in this market. The growth trends for these segments highlight a substantial shift in consumer preferences and technological advancements. The Automotive segment's growth is primarily influenced by the need for efficiency and sustainability, as manufacturers seek to reduce waste and enhance productivity. Meanwhile, the Electronics sector is benefiting from the rise of the Internet of Things (IoT) and Industry 4.0 initiatives, which are driving increased investments in automation and intelligent manufacturing solutions. Companies in these sectors are adapting to these trends by integrating innovative technologies, ensuring they remain competitive and responsive to market demands.

Automotive (Dominant) vs. Pharmaceuticals (Emerging)

The Automotive sector stands as the dominant force within the end-use industries for artificial industrial-in-manufacturing, characterized by a robust demand for automated production processes and a focus on sustainable practices. This segment leverages advanced technologies such as robotics, AI, and machine learning to enhance production efficiency and reduce operational costs. In contrast, the Pharmaceuticals sector is emerging as a vital player, driven by the increasing focus on healthcare and the necessity for precise, reliable manufacturing processes. This sector emphasizes compliance, requiring stringent quality control measures and advanced technologies to meet regulatory standards. As the demand for healthcare products continues to rise, the Pharmaceuticals sector is poised to innovate, expanding its footprint in the artificial industrial-in-manufacturing landscape.

Get more detailed insights about North America Artificial Industrial In Manufacturing Market

Regional Insights

US : Leading the Industrial Automation Charge

The US holds a commanding market share of approximately 80% in the North American artificial industrial-in-manufacturing sector, valued at $840.0 million. Key growth drivers include advancements in automation technologies, increased demand for smart manufacturing solutions, and supportive government initiatives aimed at enhancing industrial productivity. Regulatory policies, such as the Manufacturing USA program, foster innovation and collaboration among industry stakeholders, while robust infrastructure supports the expansion of manufacturing capabilities.

Canada : Strengthening Industrial Capabilities

Canada's artificial industrial-in-manufacturing market is valued at $210.0 million, representing about 20% of the North American market. Growth is fueled by increasing investments in automation and a focus on sustainability in manufacturing processes. The Canadian government promotes initiatives like the Industrial Strategy Lab to enhance innovation and competitiveness. Demand trends indicate a shift towards smart technologies and eco-friendly solutions, aligning with global sustainability goals.

North America Artificial Industrial In Manufacturing Market Regional Image

Key Players and Competitive Insights

The artificial industrial-in-manufacturing market in North America is characterized by a dynamic competitive landscape, driven by rapid technological advancements and increasing demand for automation solutions. Key players such as Siemens (DE), General Electric (US), and Rockwell Automation (US) are at the forefront, each adopting distinct strategies to enhance their market positioning. Siemens (DE) emphasizes innovation through its digital twin technology, which streamlines manufacturing processes, while General Electric (US) focuses on integrating AI into its industrial applications to optimize operational efficiency. Rockwell Automation (US) is leveraging partnerships with software firms to enhance its IoT capabilities, thereby creating a more interconnected manufacturing environment. Collectively, these strategies foster a competitive environment that prioritizes technological integration and operational excellence.

In terms of business tactics, companies are increasingly localizing manufacturing to reduce lead times and enhance supply chain resilience. This trend is particularly evident in the moderately fragmented market structure, where the collective influence of key players shapes competitive dynamics. The emphasis on supply chain optimization is critical, as firms seek to mitigate risks associated with global disruptions while maintaining cost efficiency. As a result, the market is witnessing a shift towards more localized production models, which may alter traditional supply chain frameworks.

In October 2025, Siemens (DE) announced a strategic partnership with a leading AI firm to develop advanced predictive maintenance solutions for manufacturing equipment. This collaboration is poised to enhance Siemens' offerings in the industrial sector, allowing clients to minimize downtime and optimize maintenance schedules. The strategic importance of this move lies in Siemens' commitment to integrating cutting-edge technology into its product suite, thereby reinforcing its competitive edge in the market.

Similarly, in September 2025, General Electric (US) unveiled a new suite of digital tools aimed at enhancing energy efficiency in manufacturing processes. This initiative reflects GE's ongoing focus on sustainability and operational efficiency, aligning with broader industry trends towards greener manufacturing practices. The introduction of these tools is likely to position GE as a leader in sustainable industrial solutions, appealing to environmentally conscious clients.

In August 2025, Rockwell Automation (US) expanded its portfolio by acquiring a software company specializing in cloud-based manufacturing solutions. This acquisition is strategically significant as it enables Rockwell to offer comprehensive solutions that integrate cloud technology with traditional manufacturing processes. The move not only enhances Rockwell's technological capabilities but also positions the company to better serve the evolving needs of its clients in an increasingly digital landscape.

As of November 2025, the competitive trends in the artificial industrial-in-manufacturing market are heavily influenced by digitalization, sustainability, and AI integration. Strategic alliances are becoming increasingly vital, as companies recognize the need to collaborate to stay ahead in a rapidly evolving environment. The shift from price-based competition to a focus on innovation, technology, and supply chain reliability is evident, suggesting that future competitive differentiation will hinge on the ability to adapt to these emerging trends.

Key Companies in the North America Artificial Industrial In Manufacturing Market market include

Industry Developments

At CES in January 2025, NVIDIA unveiled generative AI models and blueprints to support Omniverse for industrial AI, paving the way for large-scale synthetic data production and robot-ready digital factories. In order to enable realistic digital twin visualization for production environments, Siemens introduced the Teamcenter Digital Reality Viewer, its first Xcelerator application powered by Omniverse.

Building on this, NVIDIA extended its physical AI platform in March 2025. Omniverse welcomed partners such as Omron, SAP, and Rockwell Automation, who started testing AI-powered automation and multi-robot fleet simulations through the Mega Omniverse Blueprint, which was a significant step forward for AI manufacturing capabilities in the United States and Canada.

NVIDIA introduced Omniverse Cloud Sensor RTX microservices in June 2024, allowing programmers to use physically realistic virtual environments to model sensor inputs for self-governing devices. Early in 2025, Microsoft said that it would integrate Omniverse APIs into Azure and simulation tools, allowing industrial clients to construct digital twins.

In June 2024, Rockwell Automation added to its industrial AI services by integrating NVIDIA's Omniverse Emulate3D APIs and Isaac robotics simulation. In the meantime, albeit without any events specifically related to after 2023, Oracle, PTC, and SAP continued to assist the development of AI in manufacturing through software and digital twin products.

North America Artificial Intelligence in

Future Outlook

North America Artificial Industrial In Manufacturing Market Future Outlook

The artificial industrial-in-manufacturing market is projected to grow at an 18.43% CAGR from 2024 to 2035, driven by automation advancements, increased efficiency demands, and sustainability initiatives.

New opportunities lie in:

  • Integration of AI-driven predictive maintenance solutions
  • Development of customized automation systems for niche industries
  • Expansion of smart factory technologies to enhance operational efficiency

By 2035, the market is expected to achieve substantial growth, positioning itself as a leader in manufacturing innovation.

Market Segmentation

North America Artificial Industrial In Manufacturing Market Technology Outlook

  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Robotic Process Automation
  • Deep Learning

North America Artificial Industrial In Manufacturing Market Application Outlook

  • Predictive Maintenance
  • Quality Control
  • Supply Chain Management
  • Robotics
  • Production Planning

North America Artificial Industrial In Manufacturing Market Deployment Type Outlook

  • On-Premise
  • Cloud
  • Hybrid

North America Artificial Industrial In Manufacturing Market End Use Industry Outlook

  • Automotive
  • Electronics
  • Aerospace
  • Food and Beverage
  • Pharmaceuticals

Report Scope

MARKET SIZE 20241050.0(USD Million)
MARKET SIZE 20251243.51(USD Million)
MARKET SIZE 20356749.45(USD Million)
COMPOUND ANNUAL GROWTH RATE (CAGR)18.43% (2024 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Million
Key Companies Profiled["Siemens (DE)", "General Electric (US)", "Rockwell Automation (US)", "ABB (CH)", "Honeywell (US)", "Schneider Electric (FR)", "Mitsubishi Electric (JP)", "Emerson Electric (US)", "Bosch (DE)"]
Segments CoveredApplication, Technology, Deployment Type, End Use Industry
Key Market OpportunitiesIntegration of advanced robotics and AI to enhance manufacturing efficiency and reduce operational costs.
Key Market DynamicsTechnological advancements drive automation adoption, reshaping competitive dynamics in the artificial industrial-in-manufacturing market.
Countries CoveredUS, Canada

Leave a Comment

FAQs

What is the expected size of the North America Artificial Intelligence in Manufacturing Market by the year 2024?

The North America Artificial Intelligence in Manufacturing Market is expected to be valued at 2.5 USD Billion in 2024.

What will be the market value of the North America Artificial Intelligence in Manufacturing Market in 2035?

The market is projected to reach a value of 10.5 USD Billion by the year 2035.

What is the expected compound annual growth rate (CAGR) of the market from 2025 to 2035?

The market is anticipated to grow at a CAGR of 13.935% during the period from 2025 to 2035.

Which region holds the largest market share in North America for Artificial Intelligence in Manufacturing?

The United States is expected to dominate the market, valued at 1.5 USD Billion in 2024 and projected to grow to 6.5 USD Billion by 2035.

What is the projected market value for Canada in the North America Artificial Intelligence in Manufacturing Market by 2035?

Canada's market share is expected to increase from 1.0 USD Billion in 2024 to 4.0 USD Billion by 2035.

What are the key applications driving the North America Artificial Intelligence in Manufacturing Market?

Key applications include Predictive Maintenance, Quality Control, Supply Chain Management, and Process Optimization.

What will be the market size for Predictive Maintenance in the North America Artificial Intelligence in Manufacturing Market by 2035?

The market size for Predictive Maintenance is expected to reach 3.4 USD Billion by the year 2035.

Which companies are the major players in the North America Artificial Intelligence in Manufacturing Market?

Key players include Oracle, PTC, NVIDIA, Siemens, Boeing, General Electric, ABB, Cisco, SAP, Rockwell Automation, C3.ai, IBM, Microsoft, Fanuc, and Honeywell.

What is the projected market value for Quality Control by 2035 in the North America Artificial Intelligence in Manufacturing Market?

The market for Quality Control is anticipated to reach 2.5 USD Billion by 2035.

What opportunities are driving growth in the North America Artificial Intelligence in Manufacturing Market?

Emerging trends include technological advancements and increasing demand for process optimization across industries, which are significant growth drivers.

Download Free Sample

Kindly complete the form below to receive a free sample of this Report

Compare Licence

×
Features License Type
Single User Multiuser License Enterprise User
Price $4,950 $5,950 $7,250
Maximum User Access Limit 1 User Upto 10 Users Unrestricted Access Throughout the Organization
Free Customization
Direct Access to Analyst
Deliverable Format
Platform Access
Discount on Next Purchase 10% 15% 15%
Printable Versions