AI in Manufacturing Market Size By Component, By Deployment Model, By Technology, By Application, By End Use, Growth Forecast 2025 – 2034

AI in Manufacturing Market Size

The global AI in manufacturing market was valued at USD 4.2 billion in 2024 and is estimated to register a CAGR of 31.2% between 2025 and 2034. The growing need for easy outsourcing services within the manufacturing industry is one of the key factors conducive to the adoption of AI technologies. In order to improve the efficiency of production processes, reduce expenditure, and scale production volumes, manufacturers leverage AI with the goal of process automation involving production control, inspection, and stock management tasks.
 

As an example, in December 2023, Mitsubishi Electric India inaugurated a smart manufacturing facility for next-generation factory automation systems in India. This manufacturing facility is built using the best industry standards to ensure that the products are of the highest quality with maximum reliability. Also, the availability of AI-based solutions is increasing both among large and SME companies operating in the manufacturing sector due to the development of AI hardware and software.
 

Governments all over the world are making it their main concern to increase their AI R&D in a bid to improve the competitiveness of their manufacturing sectors. There is a clear shift in efforts being made by these governments towards providing funding schemes, tax relief mechanisms, and regulations for the deployment of manufacturing industry AI technologies. All these moves are geared to enhance the level and scale of innovation, productivity, and cost-cutting across all industrial verticals. For example, in October 2024, the Biden-Harris Administration committed USD 100 million to improve AI for green semiconductor materials. This type of assistance helps in removing some of the obstacles that slow down the adoption of Artificial Intelligence technologies: these impediments include cost factors and skilled labor shortages, and as such, AI solutions are made available to any size manufacturer.
 

AI in Manufacturing Market Trends

• The machine learning (ML) and artificial intelligence (AI) developments are among the factors that are said to fuel the growth of the market. AI systems are also equipped with deep learning algorithms, reinforcement learning, and neural networks that help to analyze massive data and make prompt decisions.
   
• There has been a recent change in the AI industry whereby AI applications do not require the use of fully automated cloud systems anymore. Instead, shop users now have the capability to use AI applications on the edge, thanks to Edge computing as well as AI-equipped chips. GMI has reported that the edge computing market was estimated to be worth USD 13.4 billion in the year 2023 and it is forecasted to have a CAGR exceeding 28% from the year 2024 to 2032.
   
• It is now possible to deploy AI technologies at a quicker pace, and with less latency, and while the system is functioning normally, decisions may in fact be rendered instantaneously. The tools and resources at a business owner's disposal make it possible for AI to be used in a more practical and effective manner in any industry.
   
• With access to proprietary and other sensitive information (such as corporate data, employee details, and even details about the production process), Artificial Intelligence systems become vulnerabilities to cyber threats. Statista claimed that approximately 80 percent of manufacturers in the US expected such cyber threats back in 2022, which increased from 64 percent in 2018.
   
• As previously mentioned, unethical use of AI, such as biases within algorithms and displacing human jobs, raises concerns among employees, customers, or even regulators; in addition, technical flaws in the AI system can incur huge business losses, theft, and harm a company’s reputation.
   
• To avoid such instances, however, manufacturers must develop AI systems that are clear, appropriate, and robust, as well as effectively deal with the issues of job cuts and renormalization to prevent adverse social outcomes from AIs in the first place.
   

AI in Manufacturing Market Analysis

• Based on component, the market is divided into hardware, software, and service. In 2024, the hardware segment held a market share of over 55% and is expected to cross USD 32 billion by 2034.
   
• The industrial demand for highly sophisticated computing hardware has propelled the hardware segment even further. The analytics-generated use cases within the domain of AI scatter in manufacturing, including industrial robotics, predictive maintenance, and quality control, necessitate exceptionally advanced hardware components that can handle great amounts of data in real-time.
   
• Machine and deep learning algorithms will invariably require advanced hardware components to run. The more the manufacturers try to incorporate AI, the higher the expectation for faster, more efficient, and reliable hardware solutions grows.
   
• Also, faster data processing hardware developments that make systems more efficient generally lead to improved automation, greater productivity, and better decision-making processes.
   
• For example, the Gaudi 3 AI accelerators have capabilities that are said to output up to twenty percent more throughput and two times the price-performance in coverage compared to the H100. With such accelerators, LLaMa 2 70B AI solutions are ready to hit the market. After all, in September 2023, Intel announced the launch of the Xeon 6 processor, where it also launched the Gaudi 3 AI solutions that were touted as the next-generation AI supplement.
   

• Based on deployment model, the AI in manufacturing market is categorized into on-premises and cloud. The cloud segment held a market share of around 43% in 2024.
   
• As the number of companies, including all sectors in modern society, increasingly embracing the need for being digitally competitive fully rushes, the cloud solutions demand is set to increase even further, which is fueling the manufacturing sector’s competitiveness. The combination of cloud solutions' benefits of flexibility and scalability that lowers costs by making operations easier is still improving in the industry.
   
• In addition, the remote implementation has better data storage and processing capabilities, which is essential for AI systems that utilize large datasets for learning algorithms. Cloud computing solutions enable real-time collaborations and sharing of information between manufacturers, suppliers, and customers, which enhances decision quality and decreases time to market.
   

Based on technology, the market is segmented into machine learning, computer vision, natural language processing, and context-aware computing. The machine learning segment dominated the market and is expected to hold around USD 19 billion revenue by 2034.
 

• The development of machine learning is rooted in providing intelligent automations and data driven strategies. As machine learning deeply develops, different areas of branch processes benefit from better defined insights generated from operational aggregated data.
   
• In addition, these algorithms can be useful in the sphere of quality management. Using robust machine learning frameworks, manufacturers can detect defects in products more accuracy thereby reducing production losses.
   
• Furthermore, the expected growth of the machine learning in manufacturing market is also driven by IoT-based technologies and other smart devices that assist in collecting, processing and analyzing data.
   
• Statista estimates that by 2030, there will be around 198.7 million IoT devices in the manufacturing industry, and the count is still expected to grow, which fully supports what the manufacturing sector.
   

Based on application, the AI in manufacturing market is divided into quality management, predictive maintenance, inventory management, energy management, industrial robotics, and others. The predictive maintenance segment dominated the market with around 25% market share in 2024.
 

• Predictive maintenance uses algorithms powered by AI and machine learning to assist in monitoring and evaluating the performance of the equipment in real-time. As a result, companies can avoid downtime and reduce maintenance costs by identifying equipment failures ahead of time, reducing total maintenance activities.
   
• Due to the increasing demands of industries for increased productivity, it is necessary to limit interference in the production process. The predictive maintenance systems can repair and aid in preventing needless maintenance downtime by fixing components that may have unexpectedly malfunctioned.
   
• Conversely, the car-making industry seems to be at the forefront of IoT and smart-sensor integration while the predictive maintenance driven by currently available approaches is becoming economical. The GMI reports asserts the global smart sensor market size is expected to surpass USD 45.4 billion in 2022, while during the period of 2023-2032, this market will grow at a CAGR of over 15.7%.
  
   
  
   
• U.S. dominated the North America AI in manufacturing market with a major share of around 75% in 2024. The U.S. market is expected to grow due to the strong government support for smart manufacturing initiatives.
   
• One of the sought objectives of the government of the USA is the enhancement of competitiveness of the manufacturing base of the country and to this end several government policy measures have been initiated among them the automation, the use of AI and other high-level technologies.
   
• More specifically, in September 2023, the U.S. government established a global AI inclusivity partnership together with eight companies.
   
• This alliance includes Amazon, Anthropic, Google, International Business Machines, Meta, Microsoft, Nvidia, OpenAI, and the U.S. State Department. They together brought more than US 100 million to the table to employ their pooled skills, assets, and networks to potentialize AI.
   
• Even a greater emphasis on putative production geography and supply chain resilience increases the market demand for AI in the industry. Technologies such as Predictive Maintenance and AI Machining are believed to be very considerable in increasing operational efficiency while keeping the costs low. 
   

The AI in manufacturing market in the UK is expected to experience significant and promising growth from 2025 to 2034.
 

• A key factor of market growth for the UK is the political determination to enhance the usage of industrialization version four technologies under the ‘Made Smarter’ banner. It concentrates on the application of digital tools such as AI in a manufacturing setting for upgrading work performance, decreasing the wastage, and enhancing the competitive position across the global markets.
   
• So too is the UK manufacturing grown, automotive and aerospace and pharmaceuticals, starting utilizing AI tools and solutions to improve supply chains, improve products, and ensure predictive maintenance.
   
• The combination of a rapid outburst in the quest for automation and digital transformation in the manufacturing industry as well as support from the government is propelling AI incorporation in manufacturing industries in the UK.
   

The AI in manufacturing market in China is anticipated to witness lucrative growth between 2025 to 2034.
 

• The 2025 policy in regards to ‘Made in China’ focuses on digitizing and upgrading the industrial sector, the Chinese government is aiming to increase manufacturing in its region. This shift’s main component revolves around AI, as it is expected that manufacturing processes will be reformed with the implementation of automation, analytics and machine learning.
   
• Also, in March 2024, the country introduced a new digital economy initiative called “AI Plus.” This initiative focuses on improving AI’s transformation within industries to further improve industries right up to encouraging businesses to invest in AI-based research applications.
   
• The increasing industrialization, development of the electronics, automotive, and consumer goods sectors, and growth in disposable income are causing an escalation in the demand for AI solutions that increase production efficiency, product quality, and streamline supply chain management.
   
• In addition, AI’s role in the manufacturing industry in China is further advancing by the rapid development of green policies and – as it will be shown later – AI manufacturing tools.  China’s huge industrial base and manufacturing ecosystem are also slowly being premium with energy efficiency. 
   

AI in Manufacturing Market Share

IBM and Microsoft hold a market share of around 15% in the AI in manufacturing industry. IBM continues to promote its manufacturing-specific undertaking, Watson, as it invests heavily in further developing its AI-ready technology. The firm enhances its brand equity through its industry expertise by providing maintenance, optimization, and automation services. The company intends to strengthen its AI capabilities by various partnerships and acquisitions such as the econometric model of The Weather Company.
 

As a provider of cloud services, Microsoft encourages manufacturers to include AI tools into their processes as part of their other digital transformation efforts. This caused them to partner with leading companies and concentrate on the application of data analytics with AI in fueling their expansion. There is also a persistent interest from both companies in pouring money R&D on technological breakthroughs which will yield advanced AI products.
 

AI in Manufacturing Market Companies

Major players operating in the AI in Manufacturing industry include:

• AWS
• GE
• Google
• IBM
• Intel
• Microsoft
• Nvidia
• Rockwell
• SAP
• Siemens
   

The AI in manufacturing market is approached by both old and new firms that focus on revolutionizing industrial processes, this involves automation, real-time decision making and predictive analytics. There is a strong focus from well-known companies to develop unified AI platforms that enable integration with the current manufacturing network which allows for smart production lines, quality control and supply chain optimization. Companies such as these use state of the art technologies like machine learning, computer vision, natural language processing amongst others to aid in reducing downtimes, waste and inefficiencies.
 

AI in Manufacturing Industry News

• In November 2024, GFT Technologies announced a partnership with NVIDIA to deliver advanced AI solutions to the manufacturing industry. This collaboration leverages GFT’s expertise in digitizing manufacturing processes alongside NVIDIA’s AI software tools and accelerated computing platform for generative AI, aiming to foster greater innovation and efficiency in the sector.
   
• Aizon presented Aizon Execute, their state of the art Electronic Batch Record (eBR) software, in September of 2024. The software was developed in partnership with Euroapi, who are leaders in the API manufacturing of powdered formulations. The goal of their partnership is to facilitate the transition of their operations to more technology enabled processes.
   
• In October 2024, Lenovo launched a comprehensive new hybrid AI portfolio at Global Tech World Event. Lenovo showcased portfolio of AI solutions, services, and devices that delivers transformation and tangible return on investment to several industries.
   
• In April 2024, Microsoft unveiled new industrial AI innovations, extending from the cloud to the factory floor. These advancements offer manufacturers the opportunity to improve time-to-value, strengthen operational resilience, optimize factory and production costs, and achieve consistent, repeatable results.
   

The AI in manufacturing market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue ($Bn) and from 2021 to 2034, for the following segments:

Click here to Buy Section of this Report

Market, By Component

• Hardware     
  • Processors
    • Central Processing Units (CPU)
    • Graphics Processing Units (GPU)
    • Field Programmable Gate Arrays (FPGA)
    • Application Specific Integrated Circuits (ASIC)
    • Tensor Processing Units (TPU)
  • Memory & storage
  • Networking hardware
• Software      
• Services       
  • Professional service
  • Managed service

Market, By Deployment Model

• On-premise
• Cloud

Market, By Technology

• Machine learning
• Computer vision
• Natural language processing
• Context-aware computing

Market, By Application

• Quality management
• Predictive maintenance
• Inventory management
• Energy management
• Industrial robotics
• Others

Market, By End Use

• Automotive
• Electronics
• Pharmaceuticals
• Heavy machinery
• Food & beverage
• Aerospace & defense
• Others

The above information is provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Nordics
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • Southeast Asia 
• Latin America
  • Brazil
  • Mexico
  • Argentina 
• MEA
  • UAE
  • South Africa
  • Saudi Arabia