USD 2,579.2Million
Report ID:
SQMIG45D2099 |
Region:
Global |
Published Date: June, 2024
Pages:
197
|Tables:
94
|Figures:
70
Global Artificial Intelligence (AI) in Manufacturing Market size was valued at USD 2.58 Billion in 2022 and is poised to grow from USD 3.20 Billion in 2023 to USD 64.63 Billion by 2031, growing at a CAGR of 45.6% in the forecast period (2024-2031).
The rapid development of artificial intelligence (AI) in manufacturing is being fueled using cutting-edge technological innovations including analytics, augmented reality, virtual reality, smart packaging and additive manufacturing. The flexibility of the manufacturing organizations and their increasing demand for sustainable solutions remain important factors driving the rise of AI adoption in manufacturing.
Besides the advancement in automation in manufacturing and increasing demand for big data integration enabling the expansion of market. The increasing use of machine vision cameras in various business applications such as machine tracking, logistics, field service and quality control. For example, in April 2023 Databricks launched Databricks Lakehouse for manufacturers, with pre-developed AI solutions and applications adopted by DuPont.
Global Market Size
USD 2,579.2Million
Largest Segment
Hardware
Fastest Growth
Services
Growth Rate
45.6% CAGR
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The artificial intelligence (AI) in manufacturing market is segmented by component, technology, end-use and Regional. By component the market is segmented into hardware and software. By technology the market is segmented into machine learning and computer vision. By end-use, the market is segmented into medical devices and automobiles. By application the market is segmented into production planning, predictive maintenance & machinery inspection. Based on regional the market is segmented as North America, Asia Pacific, Latin America, and Middle East & Africa (MEA).
Analysis By Component
The hardware segment led the market and accounted for 42.1% of global revenue in 2023. The development of dedicated AI chips and processors played a key role in the industry. This hardware growth is shaped that can meet the specific mathematical needs of AI algorithms and deliver complex datasets that are quickly and efficiently processed. Companies are allocating resources for specialized hardware specially optimized for machine learning-related tasks, with consequences coming with improving efficiency.
Software solutions enable a wide range of applications across a variety of product lines due to their versatility and exceptional flexibility. The rapid development, testing, and deployment of the software enables rapid deployment a key advantage in product development. This flexibility proves important in an industry that requires quick responses to market changes to technological development. Furthermore, software integration into existing industrial devices and operating systems is particularly simple and easy.
Analysis By Technology
Machine learning technologies account for the largest market share in 2023. Machine learning algorithms have dramatically changed predictive maintenance in manufacturing. Through pre-equipment data analysis, these algorithms have shown the ability to predict potential machine failures before it has been revealed. This automated approach enabled manufacturers to efficiently plan maintenance activities, avoid unexpected downtime and maximize machine performance. Machine learning adopted for predictive maintenance represents a shift from manufacturing to operational processes, resulting in both cost efficiencies and operational reliability in manufacturing plants increases.
Computer Vision technology is expected to register the fastest CAGR during the forecast period. The combination of artificial intelligence with computer vision techniques increases operational efficiency. Because robots perceive their surroundings electronically, they gain an in-depth understanding of their surroundings in the workplace. In smart manufacturing facilities, AI-controlled computer vision helps identify flaws and deficiencies in the manufacturing process, subsequently streamlining factory operations.
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North America dominated the market and accounted for 33.9% in 2023. Revenues in the regional market are driven by top manufacturers of high-performance hardware components required to operate advanced AI graphics. The national strategy for advanced manufacturing serves as a strategic plan that outlines initiatives to revitalize manufacturing and strengthen domestic supply chains. This framework prioritizes research efforts, including machine learning, data privacy, encryption and risk assessment. It aims to facilitate the integration of AI within manufacturing processes.
Asia-Pacific is the fastest growing region in the market as industries in this region have made great strides in upgrading smart manufacturing to the 4.0 principles. With a heavy emphasis on integrating IoT devices, AI analytics and computational-physical systems, the aim was to achieve a state-of-the-art facility capable of adaptive manufacturing, predictive analytics and early data-driven decision-making.
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Artificial Intelligence (AI) in Manufacturing Market Drivers
Improved Operational Efficiency
Advanced Provisioning for Prediction
Restraints
Increased Start-up Costs
Data Privacy and Security Concerns
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Artificial Intelligence (AI) in the manufacturing market is characterized by fierce competition among major players looking to use AI technology to enhance manufacturing The leading companies in this market are invest heavily in R&D, make strategic deals and acquire small technologies to strengthen their AI capabilities Competitive landscape Tech giants, Marked by AI specialists and the presence of traditional manufacturing companies, they are integrating AI solutions to stay ahead of the industry. Siemens is a leading player in artificial intelligence (AI) in manufacturing market, offering complete AI solutions through its digital factory division. The company is focused on developing AI-powered software to improve forecasting, product quality and supply chain efficiency.
Artificial Intelligence (AI) in Manufacturing Market Top Player’s Company Profiles
Recent Developments
Integration of AI and IoT for Smart Manufacturing: A key AI trend in the manufacturing market is the integration of AI into the Internet of Things (IoT). This convergence enables intelligent manufacturing with connected devices and sensors providing real-time information. AI algorithms analyze this data to optimize production processes, improve supply chain management, and improve production efficiency. The interaction between AI and IoT is driving the growth of Industry 4.0, making manufacturing processes smarter, more efficient and more scalable to changing market demands.
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Component types of teams that Collects, Collates, Correlates, and Analyzes the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
According to SkyQuest Analysis, artificial intelligence (AI) in the manufacturing market is growing exponentially, with the need to increase operational efficiencies and advanced predictive maintenance. AI systems are revolutionizing manufacturing processes by analyzing large amounts of data in real time, improving efficiency and reducing downtime. The predictive maintenance provided by AI helps manufacturers avoid costly unplanned downtime by anticipating equipment failures and creating proactive maintenance plans. However, there are notable limitations in this market. The high start-up costs are a significant barrier, especially for small and medium-sized enterprises (SMEs) that may struggle to allocate the resources needed for AI integration. Furthermore, data privacy and security concerns are of the utmost importance, as implementing AI requires processing large amounts of sensitive data and requires robust cybersecurity measures to protect them against breaches and cyberattacks. A key trend shaping the market is the integration of AI with the Internet of Things (IoT), enabling smarter manufacturing processes. This convergence enables connected devices and sensors to collect and analyze data over time, optimize production, improve supply chain management, and improve quality control. The interaction between AI and IoT is fueling Industry 4.0, making manufacturing smarter, efficient and adaptable to changing market requirements.
Report Metric | Details |
---|---|
Market size value in Manufacturing | USD 2.58 Billion |
Market size value in 2031 | USD 64.63 Billion |
Growth Rate | 45.6% |
Base year | 2023 |
Forecast period | 2024-2031 |
Forecast Unit (Value) | USD Billion |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the Artificial Intelligence (AI) in Manufacturing Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Artificial Intelligence (AI) in Manufacturing Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Artificial Intelligence (AI) in Manufacturing Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
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Artificial Intelligence (AI) in Manufacturing Market size was valued at USD 2.58 Billion in 2022 and is expected to grow from USD 3.20 Billion in 2023 to reach USD 64.63 Billion by 2031, at a CAGR of 45.6% during the forecast period (2024-2031).
The Artificial Intelligence (AI) in Manufacturing market exhibits fragmentation, with a notable market leader securing a significant market share. Key players in this landscape continually employ diverse growth strategies to maintain their competitive edge. These strategies encompass product launches, innovations, mergers, acquisitions, collaborations, and partnerships. Moreover, a relentless focus on research and development persists among these market leaders, aimed at delivering industries with the most efficient and cost-effective solutions. 'Amazon Web Services (Seattle) ', 'Cisco Systems Inc (San Jose) ', 'General Electric Company (Boston) ', 'Google LLC (Alphabet Inc.) (Mountain View) ', 'IBM Corporation (Armonk) ', 'Intel Corporation (Santa Clara) ', 'Microsoft Corporation (Redmond) ', 'Mitsubishi Electric Corporation (Tokyo) ', 'NVIDIA Corporation (Santa Clara) ', 'Oracle Corporation (Austin) ', 'Rethink Robotics (Boston) ', 'Rockwell Automation Inc (Milwaukee) ', 'SAP SE (Walldorf) ', 'Siemens AG (Munich)'
Automation enables tasks to be performed with greater precision, speed, and consistency, leading to higher productivity and reduced labor costs. AI-powered robotics and autonomous systems are revolutionizing traditional manufacturing methods by streamlining repetitive tasks, optimizing resource utilization, and enabling real-time decision-making.
Focused on Specialized AI Hardware: The increasing focus on specialized AI hardware is a significant supply-side trend shaping the AI market. Specialized hardware is commonly utilized to enhance the speed and energy efficiency of executing artificial intelligence (AI) programs. This encompasses technologies such as Lisp machines, neuromorphic engineering, event cameras, and physical neural networks. The semiconductor companies are adapting their approaches to meet market demands and enhance compatibility with other layers of the technology stack.
In the global Artificial Intelligence (AI) in manufacturing market, North America is in the lead concerning market share and revenue in the global market. The primary of its kind is due to the technological development of the region, the high rate of investment, and in the development of research studies regarding AI technological systems. The availability of advanced industrial players and tech gurus in the United States coupled with strong fundamentals of government support towards automation features of industries contribute to the subsequent growth of the market. The major areas for AI implementation among North American manufacturers remain the enhancement of production, prognostics, and maintenance, and supply chain management, which will allow companies to cement their market dominance.
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Report ID: SQMIG45D2099
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