The Industrial AI market is undergoing dynamic changes driven by the integration of artificial intelligence (AI) technologies into industrial processes to enhance efficiency, productivity, and overall operational performance. This market revolves around leveraging AI applications such as machine learning, computer vision, and predictive analytics to optimize manufacturing, maintenance, and supply chain operations. The dynamics of the Industrial AI market are influenced by factors such as the increasing focus on automation and Industry 4.0, advancements in AI technologies, the need for predictive maintenance, and the growing demand for data-driven decision-making in industrial settings.
A key driver of the Industrial AI market is the increasing focus on automation and Industry 4.0. Industries are embracing digital transformation to create smarter, more connected factories where machines, systems, and processes communicate and collaborate seamlessly. AI technologies play a crucial role in this evolution by enabling machines to analyze data, learn from it, and make intelligent decisions. The market dynamics are shaped by the recognition that Industrial AI is a key enabler of Industry 4.0, offering unprecedented opportunities to optimize operations, reduce costs, and enhance overall manufacturing efficiency.
Advancements in AI technologies contribute significantly to the dynamic nature of the Industrial AI market. As AI continues to evolve, industrial applications are becoming more sophisticated and capable of addressing complex challenges. Machine learning algorithms are employed for predictive maintenance, computer vision enhances quality control, and AI-driven analytics optimize supply chain management. The market is responsive to solutions that harness the latest advancements in AI, allowing industries to stay competitive by adopting cutting-edge technologies that provide tangible operational benefits.
The need for predictive maintenance is another significant factor shaping the dynamics of the Industrial AI market. Industries are increasingly adopting predictive maintenance strategies to minimize downtime, reduce equipment failures, and extend the lifespan of machinery. AI technologies analyze historical data, monitor equipment conditions in real-time, and predict potential issues before they occur. The market dynamics are influenced by the recognition that predictive maintenance can lead to significant cost savings and operational efficiency gains, driving industries to invest in AI solutions that offer predictive capabilities.
The growing demand for data-driven decision-making in industrial settings is a crucial factor influencing the dynamics of the Industrial AI market. As the volume of data generated in industrial processes increases, industries seek AI solutions that can derive meaningful insights from this data. AI-driven analytics provide actionable intelligence, enabling decision-makers to optimize production schedules, identify areas for improvement, and enhance overall operational efficiency. The market is characterized by a shift towards data-driven decision-making, where industries recognize the value of AI in extracting actionable insights from vast amounts of industrial data.
Moreover, the competitive landscape within the Industrial AI market is marked by a diverse range of players, including industrial automation companies, technology vendors, and specialized AI solution providers. This competition fosters innovation as providers strive to differentiate themselves by offering unique AI solutions tailored to specific industrial processes and needs. Solutions that can seamlessly integrate with existing industrial systems, demonstrate scalability, and provide measurable improvements in operational efficiency gain traction in the market, shaping the competitive dynamics and encouraging continuous advancements in AI for industrial applications.
Report Attribute/Metric | Details |
---|---|
Market Size Value In 2022 | USD 2.04 Billion |
Market Size Value In 2023 | USD 2.98 Billion |
Growth Rate | 46.0% (2023-2032) |
The Industrial AI Market Size was valued at USD 2.04 Billion in 2022. The Industrial AI Market industry is projected to grow from USD 2.98 billion in 2023 to USD 89.53 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 46% during the forecast period (2023 - 2032).
Industrial AI is the application of artificial intelligence (AI) in industrial use cases such as automation in process manufacturing, industrial robotics, supply chain management, self-optimizing infrastructure plants and inventory storage. Generally, artificial intelligence is focused on the developments of human like systems that could help the human lives make better, but industrial AI is focused on applications of AI in industrial use cases for the ease of processes in industrial manufacturing and increasing productivity in process plants. Process manufacturers use industrial AI for increasing operational efficiency, to automate its workflow activities, to reduce the downtime, for performance monitoring and improvement, and to gain a sustainable competitive advantage.
FIGURE 1: INDUSTRIAL AI MARKET SIZE 2023-2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
Industrial Internet of Things (IIoT) enabled machines capture and communicate real-time data more accurately and consistently than previously possible. IIoT allows enterprises to break open data silos (a collection of data) and gain access to information at every level. IIoT helps in machine utilization, in predicting defects in machinery using real time data and taking preventing measures against such issues before they occur. IIoT helps in tracking products throughout the supply chain and can notify the respective monitoring authorities about possible damage to goods. It is used in monitoring vibrations, temperature, and humidity in manufacturing facilities. Also, IIoT is being used in industries for “Just in Time Manufacturing”, in connecting remote assets, and to transfer of knowledge across the manufacturing plant. Thus, due to such numerous use cases of IIoT in industrial manufacturing, Industrial Ai is causing the growth of the market.
The Industrial AI Market, in this report, has been segmented based on offering into hardware and software. Software is further segmented into AI platform and AI solution.
The hardware segment of the offerings holds the largest market share of 74%. This are being used for computer vision, deep learning, natural language processing and are used to optimize business processes. Also, they make use of cloud services for storage of large amounts of data to effectively monitor, command, and automate the workflow in manufacturing plants in industries. AI platforms like Amazon Web Services (AWS) Machine Learning, Google Cloud AI Platform, Microsoft Azure Machine Learning, and SAP Leonardo are widely being used by industries to automate workflow, and has tools and feature for machine learning, predictive analytics, and robotic process automation.
FIGURE 2: INDUSTRIAL AI MARKET, BY OFFERING, 2022 VS 2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
The Industrial AI Market, in this report, has been segmented on the basis of technology into Computer vision, Deep learning, Natural Language Processing (NLP), and Context Awareness.
Deep learning is expected to hold the largest market share for the forecasted duration. Deep learning is a method that guides computers to process data just as a human brain processes the data in real life. Deep learning uses many complex models to recognize patterns in sounds, images, pictures, written text and produces accurate predictions and insights about the audiovisual data. It is being used in facial recognition, fraud detection, and digital assistants in industries. It is being used to detect if humas are at unsafe distances from hazardous machines and can inform people about the danger.
The Industrial AI Market, in this report, has been segmented on the basis of application into predictive maintenance and machinery inspection, material movement, production planning, field services, quality control, and others.
Predictive maintenance and machinery inspection is expected to hold the largest market share till 2032. Predictive maintenance is the condition-based monitoring of equipment and real time assessment of their health. Using real time data from sensors and analytics tools, it can identity the state of machines, detect and address issues, and predict future state of those machines and can reduce risk. It can Optimizing asset performance and uptime can reduce costs, increase productivity in industries.
The Industrial AI Market, in this report, has been segmented on the basis of industry into automobile, energy and power, pharmaceuticals, heavy metals and machine Manufacturing, semiconductor & electronics, food & beverages, and others.
The manufacturing industry is expected to hold the largest market share amongst the given industries. The manufacturing industry is one of the fastest to adopt industrial AI and it is being used in the manufacturing industry for a number of reasons. Industrial AI helps manufacturing in predictive maintenance to forecast remaining useful life of equipment, in robotic process automation, inspection of manufactured products, quality assurance, improvement of supply chain efficiency by forecasting demand, and warehouse automation.
Based on Region, the global Industrial AI is segmented into North America, Europe, Asia-Pacific, Middle East & Africa, and South America. Further, the major countries studied in the market report are the U.S., Canada, Germany, UK, Italy, Spain, China, Japan, India, Australia, UAE, and Brazil.
North America holds the largest share in the Industrial AI market. This is primarily due to the technological advancements happening in the region, strong research and development focused industries, presence of global players in IT, telecom, manufacturing, automobile, and healthcare in the north American region. Rise in adoption of AI in numerous industries, and positive government regulations for adoption of AI in the region are the major drivers for the growth of the industrial AI in the region.
Asia pacific Industrial AI market is the fastest growing region among regions. The Asia Pacific industrial AI market is focused on adoption of IIoT in industries and simplifying automaton processes for the manufacturing and automation industries. The Asia Pacific region includes countries such as China, Japan, India, South Korea, and several Southeast Asian nations, and is home to some of the world's largest automotive markets that makes use of AI to optimize its processes.
FIGURE 3: INDUSTRIAL AI MARKET SIZE BY REGION 2022 VS 2032, (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review
The Industrial AI market is a highly competitive industry, as numerous companies offer Industrial AI solutions such as AI platforms, AI software and solutions across the globe. The market is characterized by the presence of established and large information technological giants like Amazon, Microsoft and other companies applying these AI solutions in its processes. SiemensAI optimises tool placement within machine tools to successfully reduce production times by up to 10% – all without the need for new hardware. At GE, the development of Artificial Intelligence (AI) is primarily focused on integrating minds and industrial machines to enable intelligent and user-friendly products and services that move, cure, and power the globe.
IBM corporation
Microsoft Corporation
General Electric
Progress Software Corporation
Sight Machine
General Vision Inc
AIbrain
Rockwell Automation Inc
Cisco Systems Inc
Oracle Corporation
SAP SE
May 2023: ERP company- SAP inked an agreement with IBM to use its Watson AI technology. Its aim is to help users find apps on its solutions cloud. IBM Watson is expected to power the digital assistant in SAP Start, through which users enter its cloud solutions environment and search for, launch and "interactively engage” with apps. Residing in cloud solutions from SAP and S/4HANA, IBM Watson is intended to help users boost productivity with both natural language capabilities and predictive insights. Watson is a question-answering system developed by IBM in the Noughties. SAP said the Watson-powered system would help managers and employees find answers across various SAP business applications, having already been deployed in SAP Concur, the expense management application.
April 2023: Siemens and Microsoft are leveraging the collaborative power of generative artificial intelligence (AI) to assist industrial enterprises in driving innovation and efficiency throughout the product design, engineering, manufacturing, and operating lifecycle. The firms are integrating Siemens' Teamcenter software for product lifecycle management (PLM) with Microsoft's collaboration platform Teams and the language models in Azure OpenAI Service, as well as other Azure AI capabilities, to improve cross-functional communication.
December 2020: PepsiCo announced that they have started using Microsoft’s Project Bonsai solution to increase efficiency while maintaining consistency and quality. The solution uses data from a computer vision system to make recommendations or adjustments any time a product falls out of spec, has proven itself at a pilot plant and would be deployed in a production plant. PepsiCo, whose Frito-Lay division makes Cheetos -wanted a more efficient way to consistently manufacture Cheetos with the proper attributes while reducing waste. To meet this goal, PepsiCo developed an AI solution powered by Microsoft Project Bonsai that monitors and adjusts its extruders, the equipment that produces Cheetos.
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