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Artificial Intelligence (AI) in manufacturing Market Share

ID: MRFR//6276-HCR | 100 Pages | Author: Aarti Dhapte| May 2024

In the competitive landscape of the Artificial Intelligence (AI) in manufacturing market, market share positioning strategies are crucial for companies aiming to establish a strong presence and gain a competitive edge. One pivotal strategy involves differentiation, where companies strive to distinguish their AI solutions from competitors by offering unique features, specialized functionalities, and comprehensive integration capabilities. By emphasizing innovation, adaptability, and industry-specific expertise, companies seek to carve out a distinct niche and attract a discerning customer base, ultimately enhancing their market share.


Strategic partnerships and collaborations are integral components of market share positioning in the AI manufacturing sector. Companies often form alliances with technology partners, research institutions, or industry leaders to enhance their product offerings and capabilities. These collaborations lead to the development of integrated and interoperable AI solutions that address a broader spectrum of manufacturing needs. The collaborative approach not only expands the range of services but also positions companies as leaders in providing comprehensive, end-to-end AI solutions, thereby increasing their market share


Acquisitions and mergers are impactful strategies employed by companies to strengthen their market share in the AI manufacturing market. Through strategic acquisitions, companies can gain access to cutting-edge technologies, talent pools, or niche markets. Merging with or acquiring competitors allows companies to consolidate resources, eliminate redundancies, and strengthen their overall market position. This strategic move is particularly effective for companies seeking rapid expansion and market dominance in a highly competitive environment.


A customer-centric approach is pivotal for securing and expanding market share in the AI manufacturing sector. Companies that prioritize understanding and meeting the unique needs of their customers can build strong and lasting relationships. Offering personalized solutions, providing excellent customer support, and continuously enhancing products based on customer feedback contribute to customer satisfaction and loyalty. A satisfied customer base not only drives repeat business but also serves as a valuable asset in attracting new customers through positive testimonials and referrals, ultimately expanding market share.


Price positioning is a crucial strategy that companies employ to gain a competitive advantage in the AI manufacturing market. Some companies focus on offering cost-effective solutions to appeal to budget-conscious manufacturers, aiming to capture market share by providing value for money. Others position themselves as premium providers, emphasizing advanced features, superior performance, and dedicated support services. By strategically determining their price positioning, companies can cater to specific market segments and optimize their market share based on the perceived value of their offerings.


Continued investment in research and development is a strategic imperative for companies aiming to maintain or expand their market share in the rapidly evolving AI manufacturing market. The introduction of new AI algorithms, machine learning models, and innovative features keeps offerings competitive and aligned with the evolving needs of manufacturers. By staying at the forefront of technological advancements, companies can differentiate themselves, attract new customers, and solidify their market share.


Geographical expansion is a market share positioning strategy often employed by companies looking to tap into new markets and regions. By understanding the unique manufacturing requirements of different geographic areas, companies can tailor their AI solutions to meet specific local needs. This strategy allows companies to diversify their customer base, reduce dependency on specific markets, and position themselves as global leaders in the AI manufacturing space.

Covered Aspects:

Report Attribute/Metric Details
Base Year For Estimation   2022
Historical Data 2018-2022
Forecast Period   2023-2030
Growth Rate   47.1% (2023-2030

Artificial Intelligence (AI) in Manufacturing Market Synopsis:


The Artificial Intelligence (AI) in Manufacturing Market industry is projected to grow from USD 2.03 Billion in 2023 to USD 31.47 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 35.60% during the forecast period (2023 - 2032).


Figure 1: Artificial Intelligence (AI) in Manufacturing Market Size, 2023 - 2030 (USD Billion)


Artificial Intelligence (AI) in Manufacturing Market.


Developing market of industry 4.0 and smart factories, increasing adoption of automation by SMEs as well as large enterprises, and development in advanced technologies such as artificial intelligence, machine learning & deep learning are some of the prime factors driving the growth of the Artificial Intelligence (AI) in Manufacturing Market. However, data security & privacy concerns, and high integrating cost of AI-based solutions are some major factors hindering the market growth. The developing market of big data technology and increasing application of AI for business intelligence are some factors bringing fruitful opportunities for the market in the coming years. Whereas, the lack of skilled expertise is a major challenge in the Artificial Intelligence (AI) in Manufacturing Market.

Industry 4.0 or smart maintenance, predictive maintenance, testing, and quality optimization, supply chain communication, and yield enhancement are some of the use cases of artificial intelligence in manufacturing. Artificial intelligence and machine learning are benefitting industry 4.0 in automated production and monitoring process in smart factories, advanced digitized networks, automation of quality and inspection process, decentralized manufacturing system, and others.


AI in Manufacturing Market Segmentation


The global artificial intelligence (AI) in manufacturing market has been segmented into component, technology, application, vertical, and region.



  • By component, the market has been segmented into hardware, software, and services. By hardware the market has been segmented into processor, memory, and network. The processor segment covers microprocessor unit (MPU), graphical processing unit (GPU), field programmable gate array (FPGA), and application-specific integrated circuits (ASICs). Whereas, the services segment has been further breakdown into deployment & integration, and support & maintenance.

  • By technology, the Artificial Intelligence (AI) in Manufacturing Market market has been segmented into machine learning & deep learning, natural language processing, context-aware computing, and computer vision.

  • By application, the Artificial Intelligence (AI) in Manufacturing Market has been sub-segmented into predictive maintenance, supply chain management, IT management, field services, quality control, robotics, and others

  • By vertical, the Artificial Intelligence (AI) in Manufacturing Market has been classified into automobile, aerospace & defense, energy & power, semiconductor & electronics, food & beverage, pharmaceuticals, and others.

  • By region, the Artificial Intelligence (AI) in Manufacturing Market has been segmented into North America, Europe, Asia-Pacific, and the rest of the world.


AI in Manufacturing Market Regional Analysis


Market Research Future (MRFR) study has covered the following countries in the regional analysis of artificial intelligence (AI) in the manufacturing market—the US, Canada, and Mexico in North America; Germany, the UK, France, Russia, Spain, the Netherlands, and Italy in Europe; China, Japan, India, Singapore, Australia, the Philippines, and South Korea in Asia-Pacific; and the Middle East & Africa and South America in the rest of the world.


Artificial intelligence in manufacturing market is currently dominated by Asia-Pacific region as the primary economic countries such as China, India, South Korea, and the Philippines are the major manufacturing centers of semiconductors, electronics, energy & power, and pharmaceuticals. Further, increasing adoption of robots in manufacturing processes is expected to aid the region in dominating the Artificial Intelligence (AI) in Manufacturing Market throughout the forecast period. 


North America is the second highest contributor in artificial intelligence market. The US is the early adopter of new technologies for application such as factory automation, process planning, engineering design, and production scheduling among others.


Artificial intelligence (AI) in the manufacturing market in Europe is projected to gain high momentum during the forecast period due to increasing adoption of industry 4.0 and robotics by automotive, and aerospace industry.


AI in manufacturing Market Key Players


Market Research Future has identified following key players in the market




  • Nvidia Corporation




  • Intel Inc.




  • IBM Corporation




  • Siemens AG




  • General Electric company




  • Google, Inc.




  • Microsoft Corporation




  • Amazon Web Services




  • Bosch




  • Rockwell Automation




  • Cisco Systems




  • SAP SE




  • Foxconn, and others.




Intended Audience



  • Investors and consultants

  • System Integrators

  • Government Organizations

  • Research/Consultancy firms

  • Technology solution providers

  • Software Developers

  • OEMs


Latest Industry News of AI in Manufacturing Market



Oden Technologies Ltd., a 2024 manufacturer of AI-driven solutions, said on Wednesday that it had raised $28.5 million in a new funding round headed by Nordstjernan Growth to address productivity issues in manufacturing through the use of AI and data analytics products. Oden client INX International Ink Co., Flat Capital, and Recurring Capital Partners are among the new investors participating in the Series B round. Participating in the round were almost all of the current investors, including Atomico and EQT Ventures. Oden raised a total of $58.7 million with the current fundraising round, which was led by Atomico in its $10 million Series A round in 2018. The world's first enterprise platform for AI governance, called AILM (AI Lifecycle Management Platform), will formally open in 2023, according to a statement made by Profet AI, an enterprise AI application supplier for the industrial sector. Manufacturers may control, manage, and disseminate their core domain know-how both internally and externally to support growth into new markets or nations thanks to AILM.


April 2023



Siemens and Microsoft collaborate to integrate AI into industrial processes, enhancing productivity and innovation. Through AI-powered apps and automation software engineering, they aim to streamline workflows and accelerate development in manufacturing. Industrial AI enables real-time quality inspection, defect detection, and prevention, fostering efficiency and cost-effectiveness in production.


May 2023


Leading electronics manufacturers like Foxconn, Innodisk, Pegatron, Quanta, and Wistron are utilizing NVIDIA Generative AI and Omniverse to digitalize their factories, enhancing production efficiency and lowering costs. Through a comprehensive reference workflow, these companies are leveraging NVIDIA technologies for generative AI, 3D collaboration, simulation, and autonomous machines to optimize factory operations. This collaboration aims to improve quality and safety while reducing costly surprises and delays in the manufacturing process. NVIDIA's ecosystem of partners, including Foxconn Industrial Internet, Innodisk, Pegatron, Quanta, and Wistron, is instrumental in advancing industrial digitalization efforts across the electronics manufacturing sector.


November 2023


AWS and Siemens collaborate to integrate OT and IT in manufacturing, leveraging AI to enhance efficiency and decision-making. The deployment of AWS IoT SiteWise Edge from Siemens Industrial Edge Marketplace streamlines data ingestion, enabling AI-driven insights from machine to cloud. This integration aims to break down data silos, facilitating seamless exchange of AI-driven insights for improved operational efficiency and decision-making in manufacturing. The offering enables scalable deployment of AI-driven edge-to-cloud applications, empowering manufacturers to optimize their operations effectively.

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