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The Industrial AI market is undergoing significant transformations, driven by the widespread adoption of artificial intelligence (AI) technologies to enhance efficiency, productivity, and decision-making in industrial processes. One prominent trend is the integration of AI-driven predictive maintenance solutions. Industries are leveraging machine learning algorithms to analyze equipment performance data, predict potential failures, and schedule maintenance proactively. This trend not only minimizes downtime and reduces operational costs but also extends the lifespan of industrial equipment, contributing to more sustainable and cost-effective operations.
The rise of AI-powered robotics and automation is another key driver of market trends in the Industrial AI sector. Manufacturers are deploying robotic systems equipped with AI capabilities to streamline production processes, improve precision, and increase throughput. AI-driven automation is particularly relevant in industries such as manufacturing, logistics, and warehousing, where the integration of robotic systems enhances operational efficiency and scalability. This trend reflects a broader shift towards smart factories and Industry 4.0 principles.
The development of AI-enhanced supply chain management is shaping market trends in the Industrial AI sector. Industries are utilizing AI algorithms to optimize supply chain processes, including demand forecasting, inventory management, and logistics planning. The ability of AI to analyze large datasets and predict market trends enables industries to make data-driven decisions, reduce supply chain disruptions, and enhance overall supply chain resilience. This trend contributes to more agile and responsive supply chain operations.
Edge computing is gaining prominence in the Industrial AI market trends. As industrial processes generate vast amounts of data, there is a growing need for real-time analysis and decision-making. Edge computing involves processing data closer to the source, reducing latency and enabling quicker responses. Industries are deploying AI algorithms at the edge to analyze data locally, improving operational efficiency and facilitating faster decision-making in critical industrial applications
The integration of AI in quality control and inspection processes is becoming a significant trend. AI-powered vision systems are capable of identifying defects, ensuring product quality, and minimizing errors in manufacturing. Industries such as automotive, electronics, and pharmaceuticals are leveraging AI-driven inspection systems to enhance product quality assurance, reduce waste, and maintain compliance with stringent quality standards. This trend contributes to more reliable and efficient manufacturing processes.
AI-enabled energy management is influencing market trends in the Industrial AI sector. Industries are deploying AI algorithms to optimize energy consumption, monitor equipment efficiency, and identify opportunities for energy savings. This trend aligns with sustainability goals, as industries seek to reduce their environmental footprint and improve energy efficiency in manufacturing and other industrial processes.
The focus on human-robot collaboration is shaping trends in the Industrial AI market. Rather than replacing human workers, industries are deploying AI-powered robotic systems that collaborate with human operators. This trend enhances workplace safety, improves productivity, and allows for more complex and precise tasks to be accomplished through the synergy of human and AI-driven automation.
The development of AI-enabled digital twins is gaining traction in the Industrial AI market. Digital twins involve creating virtual replicas of physical assets, systems, or processes. Industries are leveraging AI algorithms to analyze data from digital twins, enabling predictive modeling, simulation, and optimization of industrial processes. This trend facilitates better decision-making, reduces downtime, and enhances overall operational efficiency.
The incorporation of explainable AI (XAI) in industrial applications is becoming increasingly important. As AI algorithms make critical decisions in industrial processes, the ability to understand and interpret these decisions is crucial. XAI provides transparency by explaining the reasoning behind AI-driven decisions, facilitating trust and acceptance in industrial settings. This trend addresses concerns related to the black-box nature of some AI algorithms and promotes responsible and accountable AI implementation in industries.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Market Opportunities | · Significant growth opportunities for AI based technologies in emerging and developed countries. · Improving operational efficiency of manufacturing plants · Opportunity 3 |
Industrial AI Market Highlights:
Industrial AI Market Overview
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 AI Market Trend
Increasing use of Industrial IoT in manufacturing
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.
Industrial AI Market Segment Insights
Industrial AI Market- By Offering
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
Industrial AI Market- By Technology
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.
Industrial AI Market- By Application
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.
Industrial AI Market- By Industry
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.
Industrial AI Market- Regional Insights
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
Industrial AI Market- Key Market Players and Competitive Insights
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.
Industrial AI Market- Key Companies Include
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IBM corporation
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Microsoft Corporation
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General Electric
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Progress Software Corporation
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Sight Machine
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General Vision Inc
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AIbrain
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Rockwell Automation Inc
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Cisco Systems Inc
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Oracle Corporation
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SAP SE
Industrial AI Market- Industry Developments
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.
Industrial AI Market- Market Segmentation
Industrial AI Market- Offering Outlook
- Hardware
- Software
- AI platform
- AI solution
Industrial AI Market- Technology Outlook
- Computer vision
- Deep learning
- Natural Language Processing (NLP)
- Context Awareness
Industrial AI Market- Application Outlook
- Predictive maintenance and machinery inspection
- Material movement
- Production planning
- Field Services
- Quality Control
- Others
Industrial AI Market- Industry Outlook
- Automobile
- Energy and power
- Pharmaceuticals
- Heavy metals and machine Manufacturing
- Semiconductor & Electronics
- Food & beverages
- Manufacturing
- Others
Industrial AI Market- Regional Outlook
- North America
- US
- Canada
- Mexico
- Europe
- Germany
- France
- UK
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Australia
- Rest of Asia-Pacific
- Middle East & Africa
- Saudi Arabia
- UAE
- South Africa
- Rest of the Middle East & Africa
- South America
- Brazil
- Argentina
- Chile
- Rest of South America
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