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AI in Manufacturing Market size exceeded over USD 1 billion in 2018 and is anticipated to grow at 40% CAGR from 2020 to 2025. Increasing venture capital investments in AI are fostering growth of artificial intelligence in manufacturing industry.
Investments in the technology led by tech giants and digital native companies including Google, Nvidia, and Intel. They are collectively investing billions of dollars in a wide variety of AI-based applications ranging from machine learning to robotics, virtual autonomous vehicles, assistance technology, and natural language to computer vision.
The exponential growth in digital data is driving growth of AI in the manufacturing market. It is estimated that by 2020, approximately 1.7 megabytes of new data will be created every second. It is further estimated to rise at an annual growth rate of 40% over the next 10 years. This growth is credited to the increasing adoption of big data technologies and IoT devices along with the rise in popularity of cloud platforms among enterprises. This is encouraging the adoption of the advance data analytics solutions among the manufacturers to process the data and extract actionable insights.
Report Attribute | Details |
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Base Year: | 2018 |
AI in Manufacturing Market Size in 2018: | 1 Billion (USD) |
Forecast Period: | 2019 to 2025 |
Forecast Period 2019 to 2025 CAGR: | 40% |
2025 Value Projection: | 16 Billion (USD) |
Historical Data for: | 2014 to 2018 |
No. of Pages: | 300 |
Tables, Charts & Figures: | 611 |
Segments covered: | Component, Technology, Application, End-use and Region |
Growth Drivers: |
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Pitfalls & Challenges: |
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However, the adoption of the technology in the manufacturing sector is still in the nascent stage due to the presence of several challenges in implementation of the AI technology in the industries. The complex nature of the industrial data and lack of skilled IT workforce in the industrial plants is hindering the adoption of the technology.
Hardware is leading the AI in manufacturing market with over 57% share in 2018 driven by the increasing demand for the AI processors among the industry sectors. GPUs account for more than 45% market share in 2018 and estimated to dominate the market through 2025. Its heavy compute capabilities are encouraging its demand among the organizations. Moreover, the increasing need for enhanced visual content and high memory graphic is augmenting the market.
Software segment is projected to expand at above 48% CAGR from 2019 to 2025 propelled by the increasing demand of the customized AI powered solutions among the manufactures. By deploying the right combination of the AI solutions, manufacturers can increase their operational efficiency, accelerate process, gain flexibility, and can optimize the operations. It has been estimated that the AI can reduce the operational cost by 20% with increasing the workforce productivity by more than 70%. It can also assist manufactures in increasing their sales by enabling manufacturers to develop customized products for the customers.
AI in manufacturing services segment is forecast to witness growth at around 54% during the next 7 years impelled by the increasing integration and deployment of AI solutions. The lack of skilled professional among the industry sector along with the growing demand for the third-party service providers is augmenting the market expansion. Moreover, the growing need among the manufactures to focus on the core business competencies is accelerating the services market.
Machine learning captured over 47% of the AI in manufacturing market share in 2018. The technology is used in the manufacturing industry due to rising needs to ensure quality management at every stage of the manufacturing process. ML predicts the quality of the product from the early stages of production with high degree of precision. This detects minuscule deviations from ideal product standards and its self-learning algorithms allow it to detect errors, which were previously unknown.
The context awareness technology segment is predicted to see around 41% CAGR through 2025. The need for highly flexible manufacturing processes is promoting the adoption of context awareness systems. The technology enhances the availability and efficiency of modern production systems simultaneously. It enables self-adaptation to support fluctuations in process parameters aimed at increasing flexibility and efficiency. It also allows effective knowledge acquisition & sharing to support maintenance, increasing the availability of production systems.
The quality management application is estimated to account for 20% stake in the AI in manufacturing market by 2025. Rising competition in the manufacturing landscape is promoting AI technology as a key differentiator to ensure quality control. The lack of quality poses major risks to the performance and competitive position of the company in the market, leading to high costs to the company. This is encouraging manufacturing companies to adopt deep learning & machine learning platforms to reinforce their existing infrastructure and proactivity identify mistakes & errors that can weaken the production chain and the quality of products.
The material movement segment is poised to observe at a CAGR of 43% during 2019 to 2025. As a skilled workforce is becoming increasingly difficult to recruit and retain, companies are shifting toward AI-based machine movement solutions to manage their labor challenges while ensuring productivity and profitability.
The energy & power end-use segment is likely to register gains at above 41.2% till 2025. Companies are investing in AI technology due to its ability to learn and adapt to changing environments. The technology will enable power generation companies to create predictions for the energy demand and its generation based on weather forecast. This will reduce the dependence on backup mechanisms for predicting & managing fluctuations in the production. The speed and the complex nature of the task are encouraging the use of advanced AI technologies in the manufacturing sector.
The heavy metal & machinery industry is set to achieve a CAGR of around 43% during the coming 7 years. The players operating in the heavy metal & machinery sector are using AI technology to optimize their raw material consumption, improve melt costs, and ensure quality finished products. It allows manufacturers to build accurate models based on previous raw material consumption. It reduces the quantity of raw materials consumed, enabling significant cost savings when raw materials used are precious metals such as gold, zinc, or copper.
Asia Pacific dominated the AI in manufacturing market with about 43% share in 2018 and is anticipated to resonate the trend through 2025. The highly developed manufacturing plants in the countries such as Japan, South Korea, and China will fuel the regional market demand. The rapid adoption of the industry 4.0 revolution in the region also promotes the adoption of AI solutions. Moreover, the increasing investment in the AI technology in the emerging economies such as India and China are driving the market revenue.
North America market is likely to witness similar growth trends as APAC and will grow at 43% CAGR during the forecast time period. The increasing investments by companies to modernize their manufacturing facilities are driving market growth. The early adoption of various advanced technology, such as IoT, is also fueling the penetration of AI-enabled manufacturing systems. Additionally, efforts by the government to bring back manufacturing operations to North America are supporting the use of AI technologies in the manufacturing sector.
Multinational players, such as
are investing heavily in developing new and high-performance enterprise AI solutions. The major players in the AI in manufacturing market are forming partnerships with various technology players to develop new product offerings. With the increasing adoption of industry 4.0 manufacturing technologies, the demand for AI chips has grown significantly driven by traditional chipmakers to invest in enterprise solutions. They are also acquiring new start-ups working on machine learning to solidify their position in the market.
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