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Artificial Intelligence (AI) in manufacturing Market

ID: MRFR/ICT/6276-CR
189 Pages
Aarti Dhapte
September 2024

Artificial Intelligence (AI) in Manufacturing Market Size, Share and Trends Analysis Report By Application (Predictive Maintenance, Quality Control, Supply Chain Management, Robotics, Production Planning), By Technology (Machine Learning, Natural Language Processing, Computer Vision, Robotic Process Automation, Deep Learning), By Deployment Type (On-Premise, Cloud, Hybrid), By End Use Industry (Automotive, Electronics, Aerospace, Food and Beverage, Pharmaceuticals) and By Regional (North America, Europe, South America, Asia Pacific, Middle E... read more

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Summary Table of Contents Segmentation Download PDF

Artificial Intelligence (AI) in manufacturing Market Summary

As per MRFR analysis, the Artificial Intelligence (AI) in manufacturing Market Size was estimated at 4384.1 USD Billion in 2024. The AI in manufacturing industry is projected to grow from 5687.07 USD Billion in 2025 to 76730.09 USD Billion by 2035, exhibiting a compound annual growth rate (CAGR) of 29.72 during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The Artificial Intelligence in manufacturing market is experiencing robust growth driven by automation and data analytics.

  • North America remains the largest market for AI in manufacturing, showcasing a strong demand for advanced automation solutions.
  • The Asia-Pacific region is emerging as the fastest-growing market, fueled by rapid technological advancements and increased investment in AI.
  • Predictive maintenance continues to dominate the market, while quality control is witnessing the fastest growth due to rising quality standards.
  • Enhanced operational efficiency and supply chain optimization are key drivers propelling the adoption of AI technologies in manufacturing.

Market Size & Forecast

2024 Market Size 4384.1 (USD Billion)
2035 Market Size 76730.09 (USD Billion)
CAGR (2025 - 2035) 29.72%

Major Players

Siemens (DE), General Electric (US), IBM (US), Rockwell Automation (US), Honeywell (US), ABB (CH), C3.ai (US), Microsoft (US), SAP (DE), Oracle (US)

Artificial Intelligence (AI) in manufacturing Market Trends

The Artificial Intelligence (AI) in manufacturing Market is currently experiencing a transformative phase, characterized by the integration of advanced technologies that enhance operational efficiency and productivity. Companies are increasingly adopting AI-driven solutions to streamline processes, reduce costs, and improve product quality. This shift appears to be driven by the need for manufacturers to remain competitive in a rapidly evolving landscape. As organizations embrace automation and data analytics, the role of AI becomes more pronounced, suggesting a future where intelligent systems play a pivotal role in decision-making and process optimization. Moreover, the current landscape indicates a growing emphasis on sustainability and resource efficiency within the Artificial Intelligence (AI) in manufacturing Market. Manufacturers are leveraging AI to minimize waste and optimize resource utilization, aligning with global sustainability goals. This trend not only addresses environmental concerns but also enhances the overall resilience of manufacturing operations. As the market evolves, it seems likely that the convergence of AI technologies with traditional manufacturing practices will continue to reshape the industry, fostering innovation and driving economic growth.

Increased Automation

The trend towards increased automation within the Artificial Intelligence (AI) in manufacturing Market is becoming more pronounced. Companies are implementing AI technologies to automate repetitive tasks, thereby enhancing productivity and reducing human error. This shift allows manufacturers to allocate human resources to more complex and strategic roles, potentially leading to improved operational efficiency.

Data-Driven Decision Making

Data-driven decision making is emerging as a critical trend in the Artificial Intelligence (AI) in manufacturing Market. Organizations are harnessing vast amounts of data generated from production processes to inform strategic choices. By utilizing AI algorithms, manufacturers can analyze data patterns, predict outcomes, and optimize processes, which may lead to enhanced performance and competitiveness.

Focus on Sustainability

A notable trend in the Artificial Intelligence (AI) in manufacturing Market is the increasing focus on sustainability. Manufacturers are adopting AI solutions to optimize resource usage and minimize waste, aligning their operations with environmental standards. This commitment to sustainability not only addresses regulatory pressures but also appeals to a growing consumer base that values eco-friendly practices.

Artificial Intelligence (AI) in manufacturing Market Drivers

Enhanced Quality Control

Quality control is a critical aspect of manufacturing, and the Global Artificial Intelligence (AI) in Manufacturing Market Industry is increasingly leveraging AI to enhance this process. AI systems can analyze vast amounts of data in real-time, identifying defects and inconsistencies that human inspectors might overlook. For example, AI-powered visual inspection systems can detect anomalies in products with over 95% accuracy. This capability not only reduces waste but also ensures that products meet stringent quality standards. As manufacturers strive to maintain competitiveness, the integration of AI in quality control processes is likely to become a standard practice.

Market Growth Projections

The Global Artificial Intelligence (AI) in Manufacturing Market Industry is poised for substantial growth, with projections indicating a market size of 3.5 USD Billion in 2024 and an anticipated increase to 22.5 USD Billion by 2035. This growth represents a compound annual growth rate (CAGR) of 18.43% from 2025 to 2035. The increasing adoption of AI technologies across various manufacturing sectors underscores the industry's commitment to innovation and efficiency. As manufacturers continue to integrate AI into their operations, the market is expected to expand significantly, reflecting the transformative impact of AI on the manufacturing landscape.

Supply Chain Optimization

The Global Artificial Intelligence (AI) in Manufacturing Market Industry is also driven by the need for supply chain optimization. AI technologies facilitate better demand forecasting, inventory management, and logistics planning. By analyzing historical data and market trends, AI can predict fluctuations in demand, allowing manufacturers to adjust their production schedules accordingly. This adaptability can lead to a reduction in excess inventory and associated costs. As the market is expected to grow to 22.5 USD Billion by 2035, the role of AI in enhancing supply chain efficiency is becoming increasingly vital for manufacturers aiming to remain agile in a dynamic market.

Data-Driven Decision Making

The Global Artificial Intelligence (AI) in Manufacturing Market Industry is increasingly characterized by a shift towards data-driven decision making. AI systems can process and analyze large datasets, providing insights that inform strategic decisions. This capability allows manufacturers to identify trends, optimize processes, and enhance product development. For instance, companies utilizing AI analytics have reported improved decision-making speed by up to 50%. As the industry evolves, the ability to harness data effectively will likely become a key differentiator for manufacturers, driving further investment in AI technologies.

Labor Shortages and Skill Gaps

Labor shortages and skill gaps present significant challenges in the Global Artificial Intelligence (AI) in Manufacturing Market Industry. As the workforce ages and fewer skilled workers enter the field, manufacturers are turning to AI to fill these gaps. Automation and AI-driven systems can perform repetitive tasks, allowing human workers to focus on more complex responsibilities. This shift not only addresses labor shortages but also enhances overall productivity. The increasing reliance on AI solutions is indicative of a broader trend where manufacturers seek to leverage technology to mitigate workforce challenges and maintain operational continuity.

Increased Efficiency and Productivity

The Global Artificial Intelligence (AI) in Manufacturing Market Industry is witnessing a surge in demand for solutions that enhance efficiency and productivity. AI technologies, such as machine learning and predictive analytics, enable manufacturers to optimize operations by minimizing downtime and streamlining processes. For instance, companies employing AI-driven predictive maintenance have reported reductions in equipment failure rates by up to 30%. This efficiency translates into significant cost savings and improved output quality. As the market is projected to reach 3.5 USD Billion in 2024, the drive towards operational excellence remains a pivotal factor in the industry's growth.

Market Segment Insights

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

In the Artificial Intelligence (AI) in manufacturing market, predictive maintenance holds the largest share due to its proven capability to reduce downtime and maintenance costs. This application leverages AI algorithms to predict equipment failures before they happen, thus allowing manufacturers to schedule maintenance effectively and minimize unplanned outages. As manufacturers increasingly look towards AI to enhance efficiency and reliability, predictive maintenance remains the cornerstone of AI applications in this sector. On the other hand, quality control emerges as the fastest-growing segment, driven by the rising demand for defect-free products in a highly competitive market. AI-enabled quality control solutions utilize machine learning algorithms to analyze production processes and identify defects in real-time, thus ensuring superior product quality and customer satisfaction.

Quality Control: Dominant vs. Supply Chain Optimization: Emerging

Quality control has established itself as a dominant force in the AI in manufacturing market, enabling firms to integrate AI technologies that enhance their inspection processes. This application benefits from computer vision and data analytics, allowing for real-time monitoring of production lines, detecting anomalies, and ensuring compliance with quality standards. As industries prioritize product reliability and performance, AI-driven quality control systems deliver substantial value through reduced wastage and increased customer trust. Conversely, supply chain optimization is considered an emerging segment, gaining traction as businesses aim to enhance their operational efficiency. AI technologies analyze vast amounts of data to forecast demand, optimize inventory levels, and streamline logistics. As manufacturers focus on building resilient and flexible supply chains, the role of AI in this domain is expected to grow significantly.

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

In the Artificial Intelligence (AI) in manufacturing market, the end use segment is significantly shaped by its diverse applications across various industries. The automotive sector holds the largest share, driven by the increasing adoption of automation and AI-driven technologies to enhance manufacturing efficiency and safety. Conversely, the electronics sector is witnessing the fastest growth due to the rapid advancement of AI technologies tailored for accelerated production processes and enhanced product quality. As manufacturers strive to meet consumer demands, these sectors are driving the overall market forward.

Automotive: Dominant vs. Electronics: Emerging

The automotive sector stands out as the dominant end use for AI in manufacturing, leveraging technology to optimize production lines, enhance quality control, and ensure compliance with safety standards. Companies in this domain are integrating AI solutions for predictive maintenance, supply chain optimization, and smart manufacturing practices. On the other hand, the electronics sector is an emerging powerhouse, harnessing AI to innovate product design and streamline production processes. As consumer electronics evolve, manufacturers are increasingly embedding AI for improved efficiency, leading to lower costs and enhanced user experiences. The interplay between these segments signifies a robust trajectory for AI technologies across manufacturing industries.

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

In the Artificial Intelligence (AI) in manufacturing market, Machine Learning has emerged as the largest segment, holding a significant share of the overall market. The implementation of machine learning algorithms in manufacturing processes enhances predictive maintenance, quality control, and supply chain optimization. Following closely, Robotic Process Automation has gained traction due to its ability to automate repetitive tasks, significantly increasing productivity and efficiency on the factory floor. This growth is indicative of the industry's shift towards digital transformation.

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

Machine Learning (ML) stands out as the dominant force in the AI in manufacturing sector due to its vast applications that span predictive analytics, real-time monitoring, and optimization of manufacturing operations. It facilitates improved decision-making and operational efficiency. In contrast, Robotic Process Automation (RPA) is rapidly emerging as a key player, driven by the increasing demand for automated workflows and enhanced operational efficiency. RPA solutions streamline business processes by enabling robots to complete tasks that traditionally required human intervention, thus reducing errors and operational costs and paving the way for significant advancements in manufacturing capabilities.

By Deployment Type: Cloud-Based (Largest) vs. On-Premises (Fastest-Growing)

The deployment type segment in the Artificial Intelligence (AI) in manufacturing market showcases a diverse landscape with Cloud-Based solutions leading in market share. This is primarily due to the increasing preference for scalable and flexible solutions that can handle large volumes of data, enhancing operational efficiency. On-Premises solutions, while more traditional, still hold a significant position, catering to manufacturers that require higher control and security over their data environments. Hybrid solutions are also gaining traction as they offer a balanced approach, combining the benefits of both Cloud and On-Premises deployments. Growth trends in this segment are driven by the rapid digital transformation within the manufacturing sector. Companies are adopting AI technologies to improve production efficiency, reduce costs, and enhance product quality. The Cloud-Based segment benefits from the increasing reliance on remote operations and access to advanced analytics tools. Meanwhile, On-Premises solutions are becoming faster-growing as more manufacturers recognize the need for robust security measures and data governance. This trend indicates a growing demand for customizable solutions that can address specific operational challenges.

Deployment Types: Cloud-Based (Dominant) vs. On-Premises (Emerging)

Cloud-Based deployment has emerged as the dominant choice in the Artificial Intelligence in manufacturing market, largely due to its unrivaled scalability and ease of integration with existing systems. Organizations benefit from reduced initial investments and can rapidly scale operations according to fluctuating demands. In contrast, On-Premises solutions are becoming increasingly regarded as emerging, driven by heightened concerns over data security and regulatory compliance. Manufacturers adopting On-Premises AI solutions appreciate the control over sensitive data and the ability to tailor systems to specific business needs. As these deployment types evolve, the adoption rates reflect a strategic shift toward hybrid models that leverage the benefits of both, allowing manufacturers to optimize their AI initiatives.

By Component: Software (Largest) vs. Services (Fastest-Growing)

In the Artificial Intelligence (AI) in manufacturing market, the component segment is primarily dominated by software solutions, which hold the largest market share. This dominance can be attributed to the increasing demand for data-driven insights and the rising complexity of manufacturing processes. Software technologies provide the necessary tools for automation, predictive maintenance, and real-time analytics, making them indispensable in modern manufacturing environments. On the other hand, services are emerging rapidly, fueled by the need for specialized support in deploying and optimizing AI applications. The integration of advanced AI technologies requires comprehensive support solutions, thus pushing the service component to become one of the fastest-growing segments.

Software (Dominant) vs. Services (Emerging)

Software solutions in the AI manufacturing market are characterized by their ability to enhance operational efficiency and decision-making processes. They encompass various applications, including machine learning algorithms, computer vision, and natural language processing, that drive innovation across industries. Companies leverage these software tools to optimize production lines, reduce downtime, and improve product quality. Meanwhile, services, which include consulting, implementation, and maintenance, are vital for companies that seek to adopt AI but lack the expertise. As manufacturing firms increasingly prioritize digital transformation, they are turning to service providers for tailored support and solutions, making services an emerging segment with significant growth potential in the AI landscape.

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Regional Insights

The Global Artificial Intelligence (AI) in Manufacturing Market is projected to experience substantial growth across various regions, significantly contributing to its overall valuation. By 2024, North America leads with a valuation of 1.4 USD Billion and is expected to reach 9.0 USD Billion by 2035, showcasing its majority holding and importance in the market due to advanced technology adoption and infrastructure. Europe follows closely, with a valuation of 1.0 USD Billion in 2024, reaching 7.0 USD Billion in 2035, reflecting a significant commitment to integrating AI in manufacturing processes.

The Asia-Pacific (APAC) region, although valued at 0.8 USD Billion in 2024 and projected to grow to 4.5 USD Billion by 2035, plays a crucial role in market dynamics due to rapid industrialization and technology initiatives. South America and the Middle East and Africa (MEA) represent the smaller segments with respective values of 0.2 USD Billion and 0.1 USD Billion in 2024, expected to grow to 1.5 USD Billion and 0.5 USD Billion by 2035. The variations in market size among these regions highlight the diversity in manufacturing capabilities and the strategic importance of regional investments.

The demand for automation, efficiency enhancement, and predictive maintenance is driving the Global Artificial Intelligence (AI) in Manufacturing Market segmentation forward.

Figure 3: Artificial Intelligence (AI) in Manufacturing Market Regional Insights

Artificial Intelligence (AI) in manufacturing Market Regional Image

Key Players and Competitive Insights

The Artificial Intelligence (AI) in manufacturing Market is currently characterized by a dynamic competitive landscape, driven by rapid technological advancements and increasing demand for automation. Key players such as Siemens (DE), General Electric (US), and IBM (US) are at the forefront, each adopting distinct strategies to enhance their market positioning. Siemens (DE) focuses on digital transformation and innovation, leveraging its expertise in automation to integrate AI solutions into manufacturing processes. General Electric (US) emphasizes partnerships and collaborations, particularly in the energy sector, to expand its AI capabilities. IBM (US) is heavily investing in research and development, aiming to enhance its AI offerings through advanced analytics and machine learning, thereby shaping a competitive environment that prioritizes technological superiority and operational efficiency.The market structure appears moderately fragmented, with a mix of established players and emerging startups. Key business tactics such as localizing manufacturing and optimizing supply chains are prevalent among major companies, allowing them to respond swiftly to market demands. The collective influence of these players fosters a competitive atmosphere where innovation and strategic partnerships are paramount, enabling firms to differentiate themselves in a crowded marketplace.In November 2025, Siemens (DE) announced a strategic partnership with a leading AI startup to develop next-generation predictive maintenance solutions. This collaboration is expected to enhance Siemens' existing portfolio, allowing manufacturers to reduce downtime and improve operational efficiency. The strategic importance of this move lies in Siemens' commitment to staying ahead in the AI landscape, as predictive maintenance is increasingly recognized as a critical component of smart manufacturing.In October 2025, General Electric (US) launched a new AI-driven platform aimed at optimizing supply chain operations for its industrial clients. This platform utilizes machine learning algorithms to analyze data in real-time, enabling companies to make informed decisions and streamline their processes. The significance of this initiative is underscored by the growing need for agility in supply chains, particularly in an era where disruptions can have far-reaching consequences.In September 2025, IBM (US) unveiled an advanced AI tool designed to enhance quality control in manufacturing environments. This tool employs deep learning techniques to identify defects in products during the production process. The strategic relevance of this development is evident, as quality assurance remains a critical focus for manufacturers seeking to maintain competitiveness and customer satisfaction.As of December 2025, current competitive trends in the AI in manufacturing market are heavily influenced by digitalization, sustainability, and the integration of AI technologies. Strategic alliances are increasingly shaping the landscape, as companies recognize the value of collaboration in driving innovation. Looking ahead, competitive differentiation is likely to evolve, with a shift from price-based competition to a focus on technological innovation and supply chain reliability. This transition suggests that companies that prioritize R&D and strategic partnerships will be better positioned to thrive in an increasingly complex market.

Key Companies in the Artificial Intelligence (AI) in manufacturing Market include

Industry Developments

Recent developments in the Global Artificial Intelligence (AI) in Manufacturing Market highlight a period of significant growth and innovation. In September 2023, Nvidia announced a collaboration with Siemens to enhance AI-powered manufacturing solutions, which is expected to drive efficiency and reduce downtime in factories globally. In August 2023, IBM launched new AI tools targeting predictive maintenance for manufacturing, reinforcing its position in the sector. Within the last few years, strategic mergers and acquisitions have also shaped the landscape, with Microsoft acquiring Nuance Communications in April 2021, focused on conversational AI to improve industrial processes.

Similarly, in March 2022, Rockwell Automation announced the acquisition of Fiix Software to bolster its AI capabilities in maintenance and asset management. Notably, SAP's continuous investment in AI applications has driven its market valuation higher, marking a significant trend towards integration of AI for operational excellence. The market's valuation has surged, propelled by enterprises' increasing reliance on advanced technologies to optimize production and enhance decision-making processes. These strategic advancements demonstrate a robust shift towards AI as a cornerstone of modern manufacturing practices globally.

Future Outlook

Artificial Intelligence (AI) in manufacturing Market Future Outlook

The Artificial Intelligence in manufacturing market is projected to grow at a 29.72% CAGR from 2024 to 2035, driven by automation, data analytics, and enhanced operational efficiency.

New opportunities lie in:

  • Predictive maintenance solutions for machinery optimization.
  • AI-driven quality control systems to reduce defects.
  • Robotic process automation for supply chain efficiency.

By 2035, the market is expected to be a cornerstone of manufacturing innovation and efficiency.

Market Segmentation

Artificial Intelligence (AI) in manufacturing Market End Use Outlook

  • Automotive
  • Electronics
  • Aerospace
  • Consumer Goods
  • Pharmaceuticals

Artificial Intelligence (AI) in manufacturing Market Component Outlook

  • Hardware
  • Software
  • Services

Artificial Intelligence (AI) in manufacturing Market Technology Outlook

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

Artificial Intelligence (AI) in manufacturing Market Application Outlook

  • Predictive Maintenance
  • Quality Control
  • Supply Chain Optimization
  • Robotics Automation
  • Process Automation

Artificial Intelligence (AI) in manufacturing Market Deployment Type Outlook

  • On-Premises
  • Cloud-Based
  • Hybrid

Report Scope

MARKET SIZE 20244384.1(USD Billion)
MARKET SIZE 20255687.07(USD Billion)
MARKET SIZE 203576730.09(USD Billion)
COMPOUND ANNUAL GROWTH RATE (CAGR)29.72% (2025 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Billion
Key Companies ProfiledSiemens (DE), General Electric (US), IBM (US), Rockwell Automation (US), Honeywell (US), ABB (CH), C3.ai (US), Microsoft (US), SAP (DE), Oracle (US)
Segments CoveredApplication, End Use, Technology, Deployment Type, Component
Key Market OpportunitiesIntegration of advanced predictive analytics enhances operational efficiency in the Artificial Intelligence (AI) in manufacturing Market.
Key Market DynamicsRising adoption of Artificial Intelligence in manufacturing enhances operational efficiency and drives competitive advantage across industries.
Countries CoveredNorth America, Europe, APAC, South America, MEA

Market Highlights

Author
Aarti Dhapte
Team Lead - Research

She holds an experience of about 6+ years in Market Research and Business Consulting, working under the spectrum of Information Communication Technology, Telecommunications and Semiconductor domains. Aarti conceptualizes and implements a scalable business strategy and provides strategic leadership to the clients. Her expertise lies in market estimation, competitive intelligence, pipeline analysis, customer assessment, etc.

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FAQs

What is the projected market size for the Global Artificial Intelligence (AI) in Manufacturing Market by 2035?

The Global Artificial Intelligence (AI) in Manufacturing Market is expected to reach a value of 22.5 USD Billion by 2035.

What is the expected CAGR for the Global Artificial Intelligence (AI) in Manufacturing Market from 2025 to 2035?

The market is anticipated to grow at a CAGR of 18.44% from 2025 to 2035.

Which region is expected to hold the largest market share for the Global Artificial Intelligence (AI) in Manufacturing Market by 2035?

North America is projected to dominate the market with a value of 9.0 USD Billion by 2035.

What are the forecasted market values for Predictive Maintenance in the Global Artificial Intelligence (AI) in Manufacturing Market by 2035?

Predictive Maintenance is expected to be valued at 6.5 USD Billion by 2035.

Who are some of the key players in the Global Artificial Intelligence (AI) in Manufacturing Market?

Major players include IBM, Rockwell Automation, SAP, Infosys, and NVIDIA.

What is the market value for Quality Control in the Global Artificial Intelligence (AI) in Manufacturing Market in 2024?

The market value for Quality Control is projected to be 0.8 USD Billion in 2024.

How much is the Artificial Intelligence (AI) in Manufacturing Market for Supply Chain Management expected to grow by 2035?

The market for Supply Chain Management is expected to reach 4.5 USD Billion by 2035.

What will be the market value for Robotics within the Global Artificial Intelligence (AI) in Manufacturing Market by 2035?

The market for Robotics is forecasted to grow to 5.5 USD Billion by 2035.

What is the expected market size for the Global Artificial Intelligence (AI) in Manufacturing Market in 2024?

The overall market is expected to be valued at 3.5 USD Billion in 2024.

What is the growth forecast for the APAC region in the Global Artificial Intelligence (AI) in Manufacturing Market by 2035?

The APAC region is anticipated to grow to 4.5 USD Billion by 2035.

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