The Industrial AI Market is shaped by a multitude of factors that collectively contribute to its growth and transformation of industrial processes. One of the primary drivers propelling this market is the increasing need for operational efficiency and productivity in industries. Industrial AI solutions, powered by machine learning algorithms and data analytics, enable organizations to optimize production processes, predict equipment failures, and enhance overall efficiency. The ability of AI to analyze vast amounts of data in real-time and provide actionable insights plays a pivotal role in modernizing industrial operations.
The Industry 4.0 revolution, marked by the integration of smart technologies and automation, significantly influences the Industrial AI Market. As industries embrace the concept of interconnected and intelligent manufacturing systems, AI becomes a key enabler in creating smart factories. Industrial AI applications, such as predictive maintenance, process optimization, and quality control, contribute to the realization of Industry 4.0 principles, driving the market forward.
Technological advancements, particularly in AI algorithms, edge computing, and Internet of Things (IoT) integration, contribute to the evolution of the Industrial AI Market. AI solutions are becoming more sophisticated, capable of handling complex tasks, and offering real-time insights. Edge computing allows AI algorithms to be deployed directly on industrial devices, reducing latency and enabling faster decision-making, while IoT integration facilitates the seamless connectivity of devices for data exchange and collaborative analysis.
The ongoing global emphasis on sustainability and environmental responsibility is another crucial factor influencing the Industrial AI Market. AI applications help industries optimize energy consumption, reduce waste, and minimize environmental impact. Predictive maintenance powered by AI contributes to the efficient use of resources, prolonging the lifespan of equipment and reducing the need for frequent replacements.
The COVID-19 pandemic has accelerated the adoption of Industrial AI as industries strive to build resilient and agile operations. The need for remote monitoring, predictive analytics, and automated processes became more apparent during the pandemic, prompting industries to invest in AI solutions that enhance their ability to adapt to unforeseen challenges. The pandemic underscored the importance of AI-driven technologies in maintaining business continuity and ensuring operational stability.
Security considerations are paramount in the adoption of Industrial AI, especially in critical industrial environments. Industrial systems often handle sensitive data, and ensuring the security of AI applications is crucial to protect against cyber threats and unauthorized access. The integration of robust cybersecurity measures and adherence to industry standards contribute to the safe deployment of AI in industrial settings.
The competitive landscape and collaborations within the industrial sector significantly influence the Industrial AI Market. Collaboration among technology providers, industrial equipment manufacturers, and AI developers fosters innovation and the development of tailored AI solutions for specific industrial use cases. Partnerships between technology companies and industrial firms contribute to the seamless integration of AI technologies into existing industrial infrastructure.
Government initiatives and regulatory frameworks play a pivotal role in shaping the Industrial AI Market. Governments around the world are recognizing the transformative potential of AI in industrial processes and are investing in initiatives that promote AI adoption. Regulatory guidelines that ensure the responsible and ethical use of AI contribute to creating a conducive environment for industrial AI deployments.
Economic factors, including cost-effectiveness and return on investment, influence the adoption of Industrial AI solutions. Industries often assess the economic viability of AI implementations by evaluating the potential cost savings, increased efficiency, and improved overall productivity. Demonstrating the tangible benefits of Industrial AI becomes essential for widespread adoption across diverse industrial sectors.
Report Attribute/Metric | Details |
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Segment Outlook | Offering, Technology, Application, Industry, and Region |
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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