Artificial Intelligence (AI) in manufacturing Market Analysis

AI in Manufacturing Market Overview

AI in Manufacturing Market Size was valued at USD 3,544.6 Million in 2023. The AI in Manufacturing market industry is projected to grow from USD 4,384.1 Million in 2024 to USD 28,343.6 Million by 2032, exhibiting a compound annual growth rate (CAGR) of 29.7% during the forecast period (2024– 2032).

AI in Manufacturing refers to the integration of artificial intelligence technologies into manufacturing processes to enhance productivity, efficiency, and quality. This involves the use of machine learning, computer vision, robotics, and data analytics to automate tasks, predict maintenance needs, optimize supply chains, ensure quality control, and improve decision-making. By leveraging AI, manufacturers can reduce costs, minimize downtime, and create more flexible and responsive production environments.

Analyst Comment” The increasing adoption of AI in Manufacturing is being driven by several factors. The realization by manufacturers that AI holds out immense promise to be an amplifier of human productivity—providing rapid insight and, in time, automation of decisions—holds sway as one of the major factors.”

FIGURE1: AI IN MANUFACTURING MARKET, 2019 - 2032 (USD MILLION)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

AI in Manufacturing Market Driver

The Increasing Adoption of AI Technologies In Manufacturing

The increasing adoption of AI in Manufacturing is being driven by several factors. The realization by manufacturers that AI holds out immense promise to be an amplifier of human productivity providing rapid insight and, in time, automation of decisions holds sway as one of the major factors. According to a study commissioned by Research cape, 70% of manufacturers have already implemented some form of AI in their operations, while 82% intend to increase their budgets for AI in 2024. Manufacturers are leveraging AI and predictive analytics to provide insights in near real-time based on the volatile market signals to continuously reassess demand and synchronize supply with production dynamic adjustments in place to deliver orders reliably. This granting of agility is critical in a fast-moving manufacturing environment.

Nevertheless, making AI work in manufacturing requires more than simply placing it like a "rooftop bar" on top of the existing IT infrastructure. In terms of the backdrop, sound data management, connectivity, and workforce capabilities base are ultimately what manufacturers need to account for. The Forbes study indicates that manufacturers are only 37% confident in the data underpinning their AI initiatives. This indicates the importance of data cleanliness, connectivity, and validation prior to any AI solution implementation.

Manufacturers must be sure that their data streams, the majority derived from ERP and CRM systems, are unified and integrated into a single version of truth for AI models. At the same time, around 49% of the responses viewed the next significant barrier as being related to a lack of internal AI expertise. Considering this, manufacturers are investing in AI upskilling programs and availing the expertise from solution providers, ironically termed AI centers of excellence, which will guide them through the implementation process and gradually increase their internal AI fluency.                             

AI in Manufacturing Market Type Segment Insights

AI in Manufacturing Type Insights

Based on the Type, the AI in Manufacturing market is bifurcated into Hardware, Software and Services. Among these Software accounted for the largest market share with a market share of 48.2% in 2023, which is projected to grow at a CAGR of 33.1% during the forecast period. Al software can perform intelligent functions.

There are two types of AI software, firstly AI platform and secondly AI Solutions. The development of intelligent software involves imitating several capabilities, including reasoning, learning, problem-solving, perception, and knowledge representation. The growing adoption of Al solutions and platforms in various industries and the widening application scope of Al in the manufacturing sector are the prime factors driving the growth of the artificial intelligence in manufacturing market for the software segment.

AI services are a collection of offerings, including generative AI, with prebuilt machine learning models that make it easier for developers to apply AI to applications and business operations. The models can be custom trained for more accurate business results. The highly changing development and deployment of artificial intelligence is creating huge opportunities for the Al services. The Al service providers are orchestrating and integrating diverse Al and cognitive solutions and tools for its services delivery. This is likely to boost the demand for the services in artificial intelligence in the manufacturing market.

FIGURE2: AI IN MANUFACTURING MARKET, BY TYPE, 2023 & 2032 (USD MILLION)

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

AI in Manufacturing Market Technology Insights

AI in Manufacturing Technology Insights

Based on Technology, the AI in Manufacturing Market has been segmented into Machine Learning (ML), Computer Vision, Natural Language Processing (NLP), Context-Aware Computing, Machine Reasoning and Deep Learning. By technology, Machine Learning (ML) accounted for the largest market share with a market value of USD 780.4 million in 2023, which is projected to grow at a CAGR of 26.3% during the forecast period.

Machine Learning (ML) is the type of AI that crunches huge datasets to spot patterns and trends, then uses them to build models that predict what will come. ML allows Manufactures to forecast fluctuations in demand and supply, estimate the best intervals for maintenance scheduling, and spot early signs of anomalies. machine learning in manufacturing, process plants can improve production quality, predict fluctuations in market demand, reduce the number of serious incidents, raise their reputation for safety and environmental impact, and increase efficiency and productivity across the board. Implementing ML and AI in manufacturing is an ongoing process that continuously delivers value and boosts revenue across the long term.

The Use of NLP into manufacturing is a critical component of the broader digital transformation efforts within the industry. Digital transformation services offer the expertise and technological solutions necessary to implement NLP effectively, ensuring that manufacturers can leverage this technology to its full potential.

These services encompass the development of custom NLP applications, integration with existing IT infrastructure, and ongoing support and optimization. The integration of Natural Language Processing (NLP) within manufacturing unlocks a spectrum of applications that revolutionize traditional practices, enhancing efficiency, reducing costs, and fostering innovation. These use cases not only exemplify the practical benefits of NLP but also underscore the importance of natural language processing services in realizing the potential of this transformative technology.

AI in Manufacturing Deployment Insights

Based on Deployment, the AI in Manufacturing Market has been market based on Deployment is segmented into On-Cloud and On-Premises. By Deployment, Cloud-Based accounted for the largest market share with a market value of USD 2,599.1 million in 2023, which is projected to grow at a CAGR of 32.1% during the forecast period. Cloud manufacturing refers to running a manufacturing facility’s software systems and platforms on the cloud. The cloud refers to servers that are housed in a provider’s data center and allows other businesses and organizations to run and store their own software and databases on those servers. A company’s software and data are then accessible via the internet, and the company doesn’t have to have physical server equipment at its own physical facility.

An on-premises AI platform is a platform that runs AI services and applications within the organization’s physical environment, rather than being hosted on the cloud. As a result, it is maintained and operated by the organization’s employees, rather than by the external cloud provider. On-premises AI platforms often allow enhanced security and privacy, as well as more customization and control. Regulated industries are often required to ensure on-premises AI deployment to meet compliance regulations.

AI in Manufacturing Organization Size Insights

Based on the Organization Size, the AI in Manufacturing market is bifurcated into SMEs and Large Enterprises. Among these Large Enterprises accounted for the largest market share with a market share of 77.2% in 2023, which is projected to grow at a CAGR of 30.8% during the forecast period. An enterprise of large size refers to a body that usually consists of over 1,000 employees and generates considerable revenue. It is typically made up of numerous business units plus departments regardless of physical distance between them.

The organizations are characterized with complex information technology systems; nonetheless, they have IT professionals within their premises to oversee the system. Due to the large volume of financial resources, they can inject into technology as well as the infrastructure itself— which ensures a high return — big data solutions come easily for such firms. The primary aim would be to enhance operational efficiency through utilization of appropriate data at all levels, thus cutting down on operation cost and achieving scalability.

AI in Manufacturing Application Area Insights

Based on Application Area, the AI in Manufacturing Market has been segmented into Predictive Maintenance and Machinery Inspection, Quality Control and Inspection, Production Planning and Management, Inventory Management, Predictive Analytics, Robotics and Automation, Energy Management, Supply Chain Optimization and Others.

By Application Area, Predictive Maintenance and Machinery Inspection accounted for the largest market share with a market value of USD 592.4 million in 2023, which is projected to grow at a CAGR of 31.7% during the forecast period. Predictive maintenance exemplifies NLP's capability to foresee equipment failures before they occur, minimizing downtime and associated costs.

By analyzing maintenance logs, operational data, and even the unstructured text from technician notes, NLP algorithms can identify patterns or anomalies indicative of potential issues. This anticipatory approach to maintenance ensures that manufacturing operations run smoothly, with equipment serviced only, when necessary, thereby extending the life of machinery and reducing unnecessary expenses.

Quality control processes by automating the analysis of feedback and reports from the production line. It scrutinizes textual data from product reviews, quality inspection reports, and customer feedback to identify trends and recurring issues. This real-time analysis enables manufacturers to address quality concerns swiftly, ensuring products meet the highest standards. Enhanced quality control, driven by NLP, not only optimizes production processes but also bolsters customer satisfaction and loyalty.

AI in Manufacturing End Use Industry Insights

Based on End Use Industry, the AI in Manufacturing Market has been market based on end-use Industry is segmented into Automotive, Electronics and Semiconductors, Pharmaceuticals and Chemicals, Food and Beverages, Heavy Metals and Machinery, Energy and Utilities, Textiles and Apparel, Aerospace and Defense, Consumer Goods and Other.

By End-use Industry, Electronics and Semiconductors accounted for the largest market share with a market value of USD 616.2 million in 2023, which is projected to grow at a CAGR of 26.3% during the forecast period. The integration of AI in semiconductor manufacturing and design offers immense benefits, including the need for substantial data collection and the potential for increased complexity in system management. However, as AI technologies evolve and the industry adapts, the potential for AI to further enhance efficiency, innovation, and sustainability in semiconductor manufacturing is vast and largely untapped.

AI plays a crucial role in shaping the future of semiconductor manufacturing and electronic component design. Its influence is considerable, providing a mix of effectiveness, creativity, and environmental responsibility that will shape the upcoming era of electronic devices. As AI technologies advance further, their significance in semiconductor manufacturing and design is poised to expand, signaling a new phase of technological progress and changes within the industry.

AI in Manufacturing Regional Insights

By Region, the study provides market insights into North America, Europe, Asia-Pacific, Middle East & Africa, and South America.  Asia-Pacific is anticipated to dominate the AI in Manufacturing market in 2023 and exhibit the highest CAGR during the forecast period.

Among Region, Asia-Pacific holds the highest market share of 31.2% in 2023 in AI in Manufacturing market, the market for Asia-Pacific was valued at USD 1,327.0 Million in 2023 and is anticipated to reach USD 11,639.5 Million in 2032 growing at a CAGR of 31.2%.

North America accounted for a considerable market share in 2023. In the United States, artificial intelligence is being integrated into precision manufacturing, enabling predictive maintenance and intelligent automation. This technology is not only increasing the country's worldwide manufacturing competitiveness, but it is also driving substantial industry improvements. The AI in manufacturing market in the region is distinguished by a dynamic ecosystem that includes startups, research efforts, and strategic collaborations among industry players.

The region's dominance is the result of better technological growth and massive investment in AI research & development. The existence of several advanced industrial businesses and technology innovators, particularly in the United States, fosters a robust environment for AI development. This environment is further improved by significant government backing for industrial automation, which accelerates the adoption of AI technologies. These factors combine to foster significant growth and innovation in the region's AI manufacturing sector.

The Europe AI in Manufacturing market is sub segmented into France, Germany, Italy, the UK, Russia, and the Rest of Europe. The European market is predicted to grow at a steady pace over the forecast period, owing to the government's increased initiative to construct smart factories across Europe. The European Union's (EU) Al policy aims to position the EU as a leading Al center while also ensuring that Al is created and used in a way that respects human values and is trustworthy. To improve Al excellence, the commission and member states have pledged to work together on policies and investments.  This is likely to help the regional market's revenue growth.

Asia-Pacific consists of China, Japan, India, South Korea and rest of APAC. The Asia-Pacific area is predicted to grow significantly at the highest CAGR during the forecast period. The manufacturing market for artificial intelligence (AI) in this region is witnessing rapid expansion and transformation. This sector is undergoing a tremendous transformation as AI technologies gain rapid acceptance and integration throughout Asia's manufacturing industries. This technological transition, facilitated by AI, ushers in a new era marked by increased operational efficiency and innovative advances. This disruptive technology is driving improved productivity, more efficient operations, and promoting innovation across a broad spectrum of manufacturing sectors in Asia.

The Middle East & Africa have been witnessing significant growth in manufacturing industries. In middle east and Africa countries such as UAE, Egypt, and Saudi Arabia have been investing heavily in their economies. This is one of the primary factors which is strengthening the manufacturing sector in the region. The Gulf Cooperation Council's manufacturing industry has been making significant advances owing to the improved technology acquisition and integration of advanced technology in the manufacturing sector.

Further, by the implementation of technologies in manufacturing industry, companies in the Middle East & Africa improve production, efficiency, cost savings, and quality of products to be competitive on the international market. This applies to a fair extent in industries such as electronics for the above-mentioned two industries. In conjunction with this, development enterprises in the Middle East and African regions are becoming gradually more conscious of the power of digital transformations. This change doesn't just improve effectiveness and output. It can enhance regional economic development efforts, establish the region as a strong competitor in manufacturing, and thereby create new job opportunities and reshape the region's economy.

FIGURE3: AI IN MANUFACTURING MARKET SIZE BY REGION 2023 & 2032

Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review

AI in Manufacturing Key Market Players & Competitive Insights

AI in manufacturing market, one can conclude about the focus on technological improvement, opportunities for a large-scale implementation of AI, and adherence to standards, as well as convenient interfaces. Manufacturing applications include but are not limited to predictive maintenance, quality assurance, supply chain management, and robotics. Such systems utilize big data, machine learning, and IoT to increase the efficiency of production and operational lines as well as minimize the amount of time that machines are out of order.

The leaders of the AI in manufacturing market are NVIDIA, Intel, Siemens, IBM, GE, Microsoft Corporation, Robert Bosch, Amazon Web Services, Cisco Systems Inc., and Rockwell Automation. These firms are leading the application of AI in manufacturing and have solutions that cover the entire range of possible uses.

Pertinent manufacturers and industries in the AI in manufacturing market focus on innovation, market scalability, and adherence to global standards. They focus on providing the methods and means that can be integrated into different types of manufacturing environments, effective networking of manufacturing systems and devices to provide efficient data exchange, friendly interfaces for human–machine interaction and monitoring of AI systems and compatibility with other systems in the manufacturing environment.

Key Companies in the AI in Manufacturing market include

• NVIDIA


• Intel


• Siemens


• IBM


• GE


• Microsoft Corporation


• Robert Bosch


• Amazon Web Services


• Cisco Systems Inc.


• Rockwell Automation


• Others

AI in Manufacturing Industry Developments

• December 2022, IBM is infusing robots with AI to monitor critical systems at the edge, Combining the power of AI, remote sensing, and edge computing, IBM is working with National Grid and Boston Dynamics to transform how facilities can be monitored for safety issues autonomously


• February 2024, GE Vernova announced the release of Proficy for Sustainability Insights, a new software solution designed to operationalize manufacturers’ goals toward sustainability, while helping maximize productivity and profitability.


• November 2023, Rockwell Automation completes acquisition of cybersecurity software and services company Verve Industrial Protection

AI in Manufacturing Market Segmentation

AI in Manufacturing, By Type Outlook

• Hardware


• Software


• Services

AI in Manufacturing, By Technology Outlook

• Machine Learning (ML)


• Computer Vision


• Natural Language Processing (NLP)


• Context-Aware Computing


• Machine Reasoning


• Deep Learning

AI in Manufacturing, By Deployment Outlook

• On-Cloud


• On-Premise

AI in Manufacturing, By Organization Size Outlook

• SMEs


• Large Enterprises

AI in Manufacturing, By Application Area Outlook

• Predictive Maintenance and Machinery Inspection


• Quality Control and Inspection


• Production Planning and Management


• Inventory Management


• Predictive Analytics


• Robotics and Automation


• Energy Management


• Supply Chain Optimization


• Others

AI in Manufacturing, By End User Outlook

• Automotive


• Electronics and Semiconductors


• Pharmaceuticals and Chemicals


• Food and Beverages


• Heavy Metals and Machinery


• Energy and Utilities


• Textiles and Apparel


• Aerospace and Defense


• Consumer Goods


• Others

AI in Manufacturing Regional Outlook

• North America


• US


• Canada


• Mexico


• Europe


• Germany


• France


• UK


• Italy


• Spain


• Rest Of Europe


• Asia-Pacific


• China


• Japan


• India


• South Korea


• Rest of Asia Pacific


• Middle East & Africa


• GCC Countries


• South Africa


• Rest Of Middle East & Africa


• South America


• Brazil


• Argentina


• Rest Of South America