Artificial Intelligence in Manufacturing Market Size, Share & Industry Analysis, By Offering (Hardware, Software, and Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing), By Application (Process Control, Production Planning, Predictive Maintenance & Machinery Inspection), By Industry (Automotive, Medical Devices, Semiconductor &Electronics), and Regional Forecast, 2020-2032

The global AI in manufacturing market size was valued at USD 8.14 billion in 2019 and is projected to reach USD 695.16 billion by 2032, exhibiting a CAGR of 37.7% during the forecast period. The Asia Pacific dominated the ai in manufacturing market with a share of 8.48% in 2019. This significant growth indicates a rising adoption of AI technologies within the manufacturing sector. Advancements in AI technologies enhance efficiency, productivity, and decision-making in the industry.

The market is likely to show exponential growth during the forecast period. Rising demand from manufacturing industries such as automotive, semiconductors, and medical devices, among others will contribute significantly towards the growth of the artificial intelligence in manufacturing market.

AI helps to boost the production process and offer the best quality results to the manufacturer. Besides, with the rising adoption of industry 4.0 by manufacturers, the demand for AI is increasing for optimizing the factories. For instance, Airbus adopted Industry 4.0 for its new product development of aircraft. The company with the help of artificial intelligence technology checked and confirmed that no extra cost is required for the new aircraft.

Adoption of AI to Create Growth Opportunities Amid COVID-19 Crisis 

COVID-19 has not only affected our lives but our businesses too. During these unprecedented times, managing people and taking the right decision has become all the more critical. The pandemic is likely to create a huge financial impact on the business, especially to those that highly depend on the workforce to achieve results. Many manufacturing companies are temporarily closed, some are facing demand and supply shortage, whereas some have huge demand but are not able to work with full potential. Besides, the manufacturing industry process cannot be managed remotely as it requires an on-site presence.

Considering the situation, companies are shifting their focus on artificial intelligence to mitigate the COVID-19 impact on their businesses. Companies that are using this technology can apply predictive analytics to find any deviations or errors in real-time, thereby preventing failures before they even take place. AI-enabled platforms and tools will be able to offer a live-work environment along with creating an on-demand labor force. In many countries, governments are planning to further stop the economy decline by allowing companies to work with 20-30% of their total staff strength. This will encourage manufacturing companies to automate their operations, streamline supply chain management, and enhance their decision-making.

Therefore, on a short-term basis, the demand for AI in the manufacturing industry is steady. Also, in such uncertain financial conditions only large and established manufacturers will be able to invest. However, as the pandemic condition is under control to some extent, the demand for AI is likely to grow significantly. Large enterprises and SMEs are likely to invest in this technology to boost their production process.

MARKET TRENDS

Manufacturing Industry to Witness High Investment in AI-driven Collaborative Robots

The recent advancements in AI have enhanced the Cobots to run operations more smoothly in dynamically changing workplaces such as manufacturing. Innovations in robotics have made Cobots more compatible, safer, and cost-effective. Cobots use computer vision technology to quickly examine huge quantities of the flaws and avoid hazards using its predictive intelligence. Cobots integrated with AI are used in industries for repetitive and dangerous tasks, making it safer and efficient for human counterparts.

The manufacturing industry process involves continuous improvement, i.e. present work process can be upgraded by utilizing advanced technologies such as AI, IoT, and machine learning, among others. The Cobots can add a meaningful contribution to its implementation by detecting the changing condition on the floor and accordingly monitor and optimize its further operations. Additionally, Cobots can inspect the testing equipment, diagnose failure condition, read its result, and accordingly make changes in its decisions. This is likely to gain the attention of many manufacturers owing to the rising demand for customization.

For Instance, a Danish kitchen manufacturer, MVI Maskinfabrik, was receiving increasing demand for its product. Instead of acquiring labor, the manufacturer invested in a Cobot to boost flexibility and meet the growing demand. The manufacturer implemented the AI-driven Cobot in place of its old welding robot. According to the manufacturer, this investment has resulted in a 50% reduction in the time required for welding. Besides, the cost of a collaborative robot was less than the new welding machine. Moreover, adoption of the AI in manufacturing industry is witnessing the trend of the increasing number of Cobots.

Companies Investing in Artificial Intelligence to Revolutionize Their Supply Chain Management

A well-crafted supply chain management strategy helps manufacturers improve the overall customer experience. AI revolutionizes supply chain management through predictive analytics. With this integration, it accurately predicts future demand by critically analyzing data and enabling companies to enhance inventory levels, streamline supply chain channels, and reduce the risk of overstocking or stock outs. Thus, it becomes important for companies to invest in AI and leverage its benefits. The chart below highlights the AI adoption rate in the supply chain globally.

Moreover, according to a study in 2022, which focused on the use of ML in the manufacturing industry, technology-enabled forecasting tools enhance the accuracy of demand predictions and service-level operations by over 13%. In addition, AI-powered tools are capable of eliminating over half of all forecasting errors. 

In recent years, companies have also been investing in AI with the objective of using the technology to solve future supply chain issues. For instance,

• June 2023 - Jaguar Land Rover (JLR) and Everstream Analytics partnered with the intention of integrating AI capabilities into the company’s system to prevent future global supply chain issues. 

Thus, companies engaging in more and more investments relating to AI to transform their supply chain management have been flourishing in the market in recent years.

MARKET DRIVERS

Increasing Adoption of Production and Process Optimization to Boost the Demand for AI in Manufacturing Industries

Manufacturers are witnessing the need for production optimization in industries such as chemical, automotive, semiconductor & electronics, among others on a large scale. Artificial intelligence and machine learning are powerful tools to minimize the consumption of resources and energy in every industrial process. Manufacturing companies are using these technological models to optimize power consumption and resources. The advancements of artificial intelligence (AI) and machine learning (ML) have opened new horizons for production optimization. AI and ML support to build a statistical model using the available data from many sources such as a reading of many sensors, initial material used for manufacturing, and more. Based on this data it helps the manufacturer to predict accurate parameters of the final product. Furthermore, it prevents extra losses and gives the exact amount of materials/additives required for manufacturing a particular product reducing extra cost. Moreover, this enables the businesses to make the production cost-effective. 

For instance, AI technology has an important role in the BMW Group car manufacturing factories. The BMW Group has implemented artificial intelligence technology in its 31 sites across 15 countries. The AI provides insights from smart data analytics to improve and smoothen the production process. The adoption of AI was intended to reduce the rework and improve the process by accelerating the system. The AI offers the inspection and configuration of cars, i.e. it makes sure that correct rim, lighting, flooring, and the seats, among others are fitted in place. The object detection with the help of AI has optimized its production process. Further, AI evaluates all the components brought at the configuration floor and compares them with several other images of the same component within milliseconds. This AI-based image recognition system offers robust end product quality inspection. 

Thus, the rising demand and pressure of delivering quality products can be handled through AI technology via various methods. The AI helps to find simpler solutions for the complex process through its data drives approach. This is driving the demand for AI in manufacturing industries. Even small and medium manufacturers are adopting the AI to boost the product quality and process optimization. The rising need for an optimized process in the industries is likely to boost the artificial intelligence in manufacturing market.

The Impact of Industry 4.0 in Manufacturing Sector to Drive the Market

Industry 4.0 has a tremendous influence on the manufacturing sector. The industries are getting smarter with the high adoption of connected components, smart sensor, and robotic automation, among others. Industry 4.0 is highly automated and a huge amount of data is exchanged with the machines manufacturing technologies. Thus, industry 4.0 requires cognitive and autonomous solutions to manage the entire production processes. The technologies such as artificial intelligence, internet of things (IoT), machine learning, smart sensor, and advanced automation, these technologies will help the automated industries to grow and flourish in the years to come. Adoption of technologies have positively influenced the manufacturing sector leading to intelligent manufacturing. Intelligent manufacturing uses AI-based data-driven models for customized demands to take manufacturing decisions, predictions and real-time optimization in the manufacturing processes, while reshaping the manufacturing sector.

The AI in manufacturing industry offers reduced labor costs, reduced unplanned downtimes, product defects, and increased speed of production with accuracy. With the rising awareness of industry 4.0, the adoption of AI in manufacturing is likely to increase. According to the report of Microsoft Corporation in 2019, 15% of businesses are currently leveraging AI and 31% of businesses are planning to implement an intelligent system over next year. This remarkable technological advancement of industry 4.0 has created more demand for artificial intelligence in manufacturing market. Many industries are heavily investing in building smart factories to improve the production.

For instance, the automobile manufacturer Lamborghini has enhanced its manufacturing plant by transforming it into a smart factory by adopting Industry 4.0 strategy. The automobile manufacturer is managing the smart factory under the guidance of KPMG’s expertise. The strategy of industry 4.0 is to target customers with its new model. KPMG through its AI services will be providing the customer data and their preferences for Lamborghini’s new model. By adopting the industry 4.0 standard, the company is planning to integrate its skilled professional workers with the robotics and machine to machine collaboration. Lamborghini's project proved the critical importance of industry 4.0 in today’s world. Thus, the artificial intelligence in manufacturing market is witnessing increasing demand throughout the industries.

MARKET RESTRAINT

Lack of Technical Knowledge and Foundational Practices Hinder Market Growth.

The implementation of AI in manufacturing industries requires a skilled workforce who can handle the entire process right from product designing to the end product in the manufacturing industry. The skilled labor needs to have a deeper knowledge of AI technologies, its implementation, ideas for exploring all possible opportunities in the industry using AI, and its limitations too. Thus, the lack of in-house skills just to manage and implement AI is hampering the work. Besides, having less knowledge on whether AI can fully manage the work is holding the manufacturers back owing to less utilization of AI’s potential. Thus, addressing the features of AI and re-training the professionals is the need of the hour. This is holding the managers to fully adopt the technology and thereby hampering the adoption of AI in manufacturing.

SEGMENTATION

By Offering Analysis

 Hardware is Likely of Have Maximum Revenue Share of Market

The offering segment is categorized into hardware, software, and services.

The revenue share of hardware is likely to remain the maximum during the forecast period. The hardware consists of processors, and logic circuits, among others, which runs the AI software. The AI requires its unique processing units which are likely to boost the demand for hardware. Also, according to PWC, the AI hardware vendors are increasing and creating their market position.

The AI services are expected to witness exponential growth. The highly changing development and deployment of the artificial intelligence is creating huge opportunities for the AI services. The AI service providers are orchestrating and integrating diverse AI and cognitive solutions and tools for its services delivery. This is likely to boost the demand for the services in artificial intelligence in manufacturing market.

By Technology Analysis

Computer Vision to Gain Traction Owing to Rising Complexities in the Manufacturing Factories

The technology segment is categorized into computer vision, machine learning, natural language processing, and context awareness.

Computer vision technology is likely to gain high growth for the forecast period. The artificial intelligence coupled with computer vision techniques helps to complete tasks more efficiently. With the help of computer vision, the robots can understand better and navigate in the factory environment and around humans safely. In smart factories, the implementation of AI-based computer vision helps to detect faults and defects in the product result. The technology further optimizes the workflow of the factory. For instance, Micron Technology Inc. produces memory technology on silicon wafers. This process is highly precise and complex, with very high possibilities of defects that are invisible to the human eye. The company has installed an AI-based computer vision technique in its manufacturing factory to spot the defects that has improved the manufacturing effectiveness and efficiency.

Natural language processing is the next highly implemented technology in manufacturing. The factories use this intelligence to ensure process monitor, control, and predict planning, among others. Factories are progressing in utilizing natural language processing which acquires knowledge and solves the issues. With the help of NLP, the factory automation is self-aware about the details such as the amount of energy used, employees' daily work hours, number of implemented tools in the factory, and their efficiency, among others. NLP accumulates the entire data and offers the solution as per the requirement. Furthermore, with NLP implementation the manufacturers can observe query reports or other data to keep track of its supply chain with the vendors.

Thus, the rising complexities in the factories are boosting the adoption of various technologies offered by the artificial intelligence in manufacturing market. 

By Application Analysis

Rising Adoption of Artificial Intelligence in Manufacturing Industry

The Application segment is divided into process control, production planning, predictive maintenance & machinery inspection, logistics and inventory management, quality management, and others.

The predictive maintenance adoption is rising as it prevents untimely downfall of machines and equipment with the help of machine learning. This means it notifies the manufacturers when there is a need for machine maintenance with high accuracy. Because of a single faulty machine, the manufacturers might have to bear huge losses. Thus, preventive maintenance is gaining popularity among manufacturers as it helps to prevent losses. For instance, an iron ore plant in Australia was facing challenges of its asset’s health and untimely downfalls. The company adopted the predictive maintenance technology and kept the critical mining equipment under surveillance. The continuous monitoring helped the company to reduce the uncertain downfalls.

Increasing adoption of quality management in manufacturing industry to maintain quality of products during production. The rising competition in every market is also generating a need to produce better quality products. AI has a substantial impact on quality management, which detects the quality defects in the early production process. Manufacturers can use real-time generated data to ensure performance and quality issues. Thus, the implementation of quality management technology can improve product quality, customer services, and warranty management. 

By Industry Analysis

Medical Devices and Semiconductor & Electronics to Gain Traction Owing to High Demand for High-Quality Products

The industry segment is categorized into Automotive, Medical Devices, Semiconductor & Electronics, Energy & Power, Heavy Metal & Machine Manufacturing, and Others (Aerospace &Defense, Conglomerates, etc.)

AI has a vast scope in the medical devices manufacturing industries owing to its technology such as quality control, yield optimization, and predictive maintenance, among others. Adopting machine learning and computing enhances the engineers’ job by learning from its mistakes and increases accuracy. Medical device manufacturers can utilize AI in many ways such as ensuring the quality of devices, and predictive maintenance from generated data, among others. For instance, the medical device is checked by AI predictive maintenance technology when there is a problem with the devices. The AI analyses the usability of the device, and if the algorithm shows some issues the device doesn't go to the engineering department. 

Many AI companies and medical device manufacturers are collaborating to offer a smart device. Many venture capitalists and corporate investors such as Andreessen Horowitz, Khosla Ventures, GE ventures, and IBM Watson, among others are highly investing in healthcare AI space.

Similarly, the semiconductor and electronics industries are highly adopting AI in their manufacturing industries. With AI technology, the manufacturers will be able to improve operations by optimizing the production process. Also, it will help to reduce the cost associated with the production and increase the production process. 

Quality assurance and rising investment are boosting the adoption of AI in the medical device industry.

REGIONAL ANALYSIS

Global AI in the manufacturing market scope is divided across five regions namely North America, Europe, Asia Pacific, Middle East, and Africa and Latin America.

North America is expected to grow steadily for the forecast period. The US is likely to witness the maximum revenue share of artificial intelligence (AI) in manufacturing. Government policies and regulations such as AI.gov (2019), and Modernizing Government Technology (MGT) Act (2017), among others in the US are making the AI presence strong in the country. For instance, the American AI initiative launched in February 2019 is majorly based on principles to promote and protect technological advancements in AI R&D with training workers to apply AI technologies in the work area. Multiple successful startups in AI have been witnessed in the US for connected cars, retail, and manufacturing, among others, owing to government initiatives and funding in the AI market.

Asia Pacific is expected to grow with the highest CAGR for the forecast period. The governments of China, Japan, Singapore and India are investing in artificial intelligence and also boosting the AI in manufacturing industry for smart factories and Industry 4.0. China has invested USD 150 billion on its Artificial Intelligence Development Plan for its national AI industries and with an aim to become AI super leader by 2030. AI in the China manufacturing industry is likely to have great opportunities owing to the rising adoption of smart factory technology. Overall, China's implementation of AI in manufacturing is very high. In India, the government initiatives of pushing the Make in India and Industry 4.0, is likely to incentivize the manufacturing sector and start-ups to integrate technologies such as AI, and IoT, among others. On the other hand, many companies are exploring the Singapore market for testing the AI technologies. The Singapore government is investing in partnerships by inviting firms to boost the AI capabilities of the country. Additionally, according to Thailand’s 4.0 economic models to reform its food manufacturing Industry, the country has invested in automation and robots to accelerate future growth.

Europe is growing next in line after Asia Pacific during the forecast period. UK is likely to grow significantly owing to its big investments of about USD 1.3 Billion in artificial intelligence technology. The country is also investing in sponsoring education programs for AI graduates, along with players such as Google’s Deepmind, BAE Systems and Cisco Systems. According to Capgemini’s report of 2019, European manufacturers are leading in implementing AI technology, Germany is at the top rank in adoption. The government of Italy also released guidelines for the public about the National Strategy on Artificial Intelligence. This is likely to witness huge demand and opportunity for the AI in the region. 

AI in the manufacturing industry has a huge scope in the Middle East and Africa. Dubai has adopted smart Dubai strategy and has set up smart labs to promote the implementation of AI in Dubai. Dubai has also adopted 3D printing strategy in the construction and manufacturing of consumer and medical products sector with a goal of having 25% of buildings in Dubai to be constructed using 3D printing. Such government initiatives have driven the AI market in United Arab Emirates (UAE). The government of UAE launched the UAE Strategy for Artificial Intelligence to boost its adoption by industries.

Latin America is expected to grow steadily in the market for the forecast period. Brazil government is investing in AI technology. The country is investing in building a network of research facilities that will be focusing on AI applications. Also, IBM is likely to launch Latin Americas' first AI network horizon by 2020. Mexico launched AI 2030 Coalition for promoting AI and its development across the industries. Also, Microsoft Corporation invested USD 1.1 billion for Mexico's Digital Revolution in 2020. This is likely to create various opportunities for industries, especially manufacturing operating in the market.

KEY INDUSTRY PLAYERS

Google LLC is Continuously Acquiring AI Startups to Strengthen its AI Position in the Market

The company is focus on expanding the AI based product portfolio. Google LLC is acquiring companies from different countries such as China, India, the U.K., and the U.S. to name a few. Along with thirty AI startups of USD 4 billion, Google LLC tops the AI acquiring companies list. The company is also focusing on implementing AI in manufacturing industries. It is offering Cloud AI to boost and maximize the speed of process along with protecting the health and safety of workers. Also, it is investing in creating solutions and tools to ease the deployment and usage of AI in the manufacturing industries.

• Apr 2023 - Siemens and Microsoft collaborate to elevate industrial AI, revolutionizing product lifecycle management. Integrating Siemens’ Teamcenter software with Microsoft Teams and Azure OpenAI Service's language models enhances innovation and efficiency. This partnership fosters seamless cross-functional collaboration, driving advancements in design, engineering, manufacturing, and product operations, marking a significant leap in industrial technology integration.


• Oct 2023 - Google Cloud launches industry-focused Generative AI solutions for healthcare and manufacturing, aiming to enhance productivity and enable digital transformation. This move signifies a significant step in leveraging AI for industry-specific advancements.

List of Key Companies Profiled:

• Microsoft Corporation (United States)


• Google LLC (United States)


• IBM Corporation (United States)


• Amazon.com Inc. (United States)


•  NVIDIA Corporation (United States)


•  Siemens AG (Germany)


• GENERAL ELECTRIC (United States)


• SAP SE (Germany)


•  Rockwell Automation, Inc. (United States)


•  Mitsubishi Electric Corporation (Japan)

KEY INDUSTRY DEVELOPMENTS:

• November 2023 - Netweb confirmed that it is now a manufacturing partner for the NVIDIA GH200 Grace Hopper Superchip and Grace CPU Superchip MGX server designs. The company is expected to develop over ten server versions under its Tyrone range of AI systems that are capable of a wide range of high-performance computing/supercomputing and AI applications.


• October 2023 – Ai Build raised over USD 8.5 million in a Series A funding round to speed up the company’s product roadmap and enable more industrial 3D printing end users with enhanced automation and AI capabilities. Along with this, the company aims to widen its geographic presence with the development of a subsidiary based in the U.S. and strengthen its growth throughout Europe.


• March 2020 – Siemens collaborated with NEC Corporation to provide manufacturing industries analysis solutions and AI monitoring to accelerate digitization. This will offer manufacturing industries an easy to visualize and analyze the huge generated data sets. AI will help to model large and complex process to increase the productivity.


• July 2019 – Microsoft Corporation has partnered with and has invested $1 billion in a company named OpenAI to enhance the Azure platform and build next-generation application. Azure will be thus working/running on AI supercomputing technologies once ported with OpenAI services. In this collaboration Microsoft will be acting as a commercializing partner for OpenAI’s new AI technologies.

Several Companies are Focusing on Providing AI Solutions to Manufacturing Industries

Companies such as Rockwell Automation, Mitsubishi Electric Corporation, Siemens, Microsoft Corporation, etc. are entering collaboration and partnership with the different manufacturing industries to offer its AI solution. These companies are further collaborating with software companies to make the deployment process of AI more efficient via different tools and platforms. Moreover, the companies are focusing on Research and development of AI in manufacturing market.

REPORT COVERAGE

The market report highlights leading regions across the world to offer a better understanding of the user. Furthermore, the report provides insights into the latest industry trends and analyzes technologies that are being deployed at a rapid pace at the global level. It further highlights some of the growth-stimulating factors and restraints, helping the reader to gain in-depth knowledge about the market.

REPORT SCOPE & SEGMENTATION

ATTRIBUTE	DETAILS
Study Period	2016–2027
Base Year	2019
Forecast Period	2020–2027
Historical Period	2016– 2018
Unit	Value (USD billion)
Segmentation	By Offering Hardware Software Services
By Technology Computer Vision Machine Learning Natural Language Processing Context Awareness
By Application Process Control Production Planning Predictive Maintenance & Machinery Inspection Logistics and Inventory Management Quality Management Others
By Industry Automotive Medical Devices Semiconductor & Electronics Energy & Power Heavy Metal & Machine Manufacturing Others (Aerospace &Defense, Conglomerates, etc.,)
By Region North America (U.S. and Canada) Europe (U.K., Germany, France, Spain and Rest of Europe) Asia Pacific (Japan, China, India, Southeast Asia and Rest of Asia Pacific) Middle East & Africa (South Africa, GCC and Rest of Middle East & Africa) Latin America (Brazil, Mexico and Rest of Latin America)