Generative AI in Manufacturing Market Anticipated to Reach USD 6,398.8 Mn by 2032 | Analysis by MarketResearch.biz

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The advancement of AI and machine-learning technologies is steadily enhancing the potential of generative AI in the manufacturing sector. As a result, we can expect to witness a broader implementation of this technology across various industries.

New York, June 08, 2023 (GLOBE NEWSWIRE) — According to MarketResearch.Biz, the Generative AI in Manufacturing Market size is projected to surpass around USD 6,398.8 Million by 2032, and it is poised to reach a registered CAGR of 41.06% from 2023 to 2032. In 2022, the global generative AI in Manufacturing Market was worth USD 223.4 Million.

Generative artificial intelligence can produce original and unique outcomes from given data. Generative AI can be applied in the manufacturing industry to enhance product designs, streamline production, and reduce expenses. Artificial intelligence is utilized in the industrial sector to lower costs, increase productivity, improve quality control, and enable predictive maintenance. Utilizing this, businesses may create innovative and distinctive product designs to draw in customers. Companies may reduce costs by minimizing waste, enhancing quality control, and streamlining the production process.

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Generative AI in Manufacturing Market

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Key Takeaway:

  • Based on application, in 2022, the generative AI in Manufacturing market was dominated by the product design segment.
  • Based on deployment, in 2022, the on-premises segment dominated the largest market share in the deployment segment.
  • Based on the industry vertical, in 2022, the automotive segment is the most lucrative in the industry vertical segment of generative AI in the manufacturing market.
  • In 2022, North America dominated the market with the highest revenue share of 47.6%.

Factors affecting the growth of Generative AI in Manufacturing industry?

There are several factors that can have an impact on the growth of Generative AI in Manufacturing industry including:

  • Advancements in AI and machine learning: As AI and machine-learning technologies continue to develop the capabilities of generative AI for manufacturing are increasing. This will lead to more widespread adoption in various industries.
  • Increasing demand for automation: The need for automation in manufacturing drives the adoption of generative AI. It can automate many processes such as design optimization and predictive maintenance.
  • Growth in the IoT and big data: The Internet of Things and big data are generating huge amounts of data for manufacturing processes. Generative AI helps make sense of the data by analyzing and improving processes.
  • Need for customization and personalization: Customers are increasingly demanding personalized and customized products. Manufacturers can create unique products that are tailored to the needs of individual customers using Generative AI.
  • Cost savings: Generative AI helps manufacturers reduce costs through the optimization of designs, the prediction of maintenance needs, and improvements to quality control processes.

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Top Trends in Generative AI in Manufacturing Market

Generative Design is the process whereby AI algorithms are used to create optimal solutions for design based on constraints specified by the user. As manufacturers strive to reduce downtime and increase the lifespan of equipment, they are increasingly using generative AI. Generative AI can be used to improve the quality and performance of manufactured products. It analyses data from sensors and sources to detect defects and makes recommendations for improvement. Cloud-based generative AI is becoming more popular as it offers manufacturers a more cost-effective and scalable way to access this technology. As the generative AI market matures expect to see more solutions tailored to specific industries such as aerospace and automobile. As manufacturers become more focused on sustainability generative AI is used to create more sustainable and waste-reducing designs.

Market Growth

The generative AI in manufacturing market is expected to grow steadily in the upcoming years driven by the increasing demand for advancements and automation in AI & Machine Learning technologies as well as the need for cost reductions and productivity improvements in manufacturing. The growth of this market can be attributed to a number of factors an advance in AI and machine-learning technologies, increasing demand for automation, and the growth in IoT & Big Data. The need for personalization and customization, cost savings, increased competitiveness, and regulatory & complying requirements.

Regional Analysis

North America is accounted as the most dominant market in the global generative AI in manufacturing market with a market share of 47.6%, during the forecasted period. North America is the largest market in North America for generative AI in Manufacturing, due to the high adoption of AI technologies. The US and Canada are major contributors to this region’s growth.

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Scope of Report

Report Attribute Details
Market Value (2022) US$ 223.4 Million
Market Size (2032) US$ 6,398.8 Million
CAGR (from 2023 to 2032) 41.06%
North America Revenue Share 47.6 %
Historic Period 2016 to 2022
Base Year 2022
Forecast Year 2023 to 2032

Market Drivers

Manufacturing has an increasing requirement for generative AI. The manufacturing sector is increasingly focusing on automation to cut costs, boost equipment efficiency, and boost production. A potent tool, generative AI can automate design, enhance quality control, and optimize production. The continuing development of artificial intelligence technologies, particularly deep learning, has made it easier to create complex generative AI models. These models can handle large, complicated data sets and generate more precise, realistic results. The application of generative AI in manufacturing is being driven by this. The newest industrial trend, known as “Industry 4.0,” involves integrating cutting-edge technology like IoT & big data.

Market Restraints

When generative AI is used in the manufacturing process, costs may be significant. Its crucial investments are in infrastructure, software, hardware, and qualified staff to manage and maintain it. Mid-sized and small organizations may find it challenging to embrace this technology. AI models that generate data need a lot of high-quality data to provide accurate and relevant findings. But frequently, the information is either insufficient or of poor quality. Effective model training may be challenging and model capabilities may be constrained as a result. Additionally, generative AI applications in manufacturing may introduce new security vulnerabilities.

Market Opportunities

Manufacturing could undergo a revolution thanks to generative AI. Complex production procedures can be automated, production lines can be improved, and product quality can be raised. Businesses that want to improve operational efficiency or maintain their competitiveness can profit from generative AI. A significant growth area for generative AI is product design. Utilizing algorithms that generate and assess design options, generative AI assists businesses in developing new designs or optimizing existing ones. By using this strategy, businesses can produce more inventive products while using less time and resources. Another area where generative AI has a significant impact is predictive maintenance.

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Report Segmentation

Application Insight

The Product design holds a significant share in the application segment i.e., 27.1% in 2022. Product design is an important application segment of the generative AI market. Generative design software helps product designers and engineers to create better, more efficient products by using algorithms that generate and evaluate multiple options. Software for generative design can analyze parameters and constraints such as weight, material strength, and manufacturing limitations to create optimized designs that meet specific criteria.

Deployment Insight

Generative AI in manufacturing market share is dominated by the on-premises segment with a share of 56%. On-premises deployment is the installation of generative AI infrastructure and software within a company’s own data center, as opposed to using a cloud deployment model. Companies with strict security and compliance needs often prefer an on-premises deployment that allows them to retain complete control over their infrastructure & data. On-premises deployments can also offer better performance and lower latencies as data analysis & processing can be done locally without relying upon a cloud-based architecture.

Industry Vertical Insight

The automotive segment is the most lucrative in the industry vertical segment of the generative AI in manufacturing market with the largest share i.e., 33.5%. Generative AI is used in many applications within the automotive sector, including product design and predictive maintenance. In product design, generative artificial intelligence can help automotive companies optimize designs, improve performance, and reduce weight and material usage. Generative AI analyses data from simulations or experiments to create new design concepts. It can also identify the best design parameters based on a set of requirements.

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Market Segmentation

Based on Application

  • Product Design
  • Prototyping
  • Quality Control
  • Predictive Maintenance
  • Supply Chain Optimization
  • Other Applications

Based on Deployment

  • On-premises
  • On the Cloud

Based on Industry Vertical

  • Automotive
  • Aerospace
  • Electronics
  • Consumer Goods
  • Other Industry Verticals

By Geography

  • North America
    • The US
    • Canada
    • Mexico
  • Western Europe
    • Germany
    • France
    • The UK
    • Spain
    • Italy
    • Portugal
    • Ireland
    • Austria
    • Switzerland
    • Benelux
    • Nordic
    • Rest of Western Europe
  • Eastern Europe
    • Russia
    • Poland
    • The Czech Republic
    • Greece
    • Rest of Eastern Europe
  • APAC
    • China
    • Japan
    • South Korea
    • India
    • Australia & New Zealand
    • Indonesia
    • Malaysia
    • Philippines
    • Singapore
    • Thailand
    • Vietnam
    • Rest of APAC
  • Latin America
    • Brazil
    • Colombia
    • Chile
    • Argentina
    • Costa Rica
    • Rest of Latin America
  • Middle East & Africa
    • Algeria
    • Egypt
    • Israel
    • Kuwait
    • Nigeria
    • Saudi Arabia
    • South Africa
    • Turkey
    • United Arab Emirates
    • Rest of MEA

Competitive Landscape

Generative AI in manufacturing is fragmented. There are many market players like IBM Corporation, Microsoft Corporation, Oracle Corporation, etc. These companies invest heavily in research and development to improve their generative AI solution and maintain their position in the market. They also form partnerships and collaborate with other companies to expand their reach and provide more comprehensive solutions to customers.

Listed below are some of the most important Generative AI in Manufacturing industry players.

  • SAP SE
  • IBM Corporation
  • Microsoft Corporation
  • Alphabet Inc.
  • Siemens AG
  • General Electric Company
  • Autodesk Inc.
  • NVIDIA Corporation
  • Cisco Systems Inc.
  • Oracle Corporation
  • Other Key Players

Recent Developments of the Generative AI in Manufacturing Market

  • In 2021, Siemens announced a partnership with industrial robotics company Comau for the development of AI-powered manufacturing solutions. The partnership will focus primarily on developing software to optimize manufacturing processes and increase productivity.
  • In 2020, Autodesk launched its generative software for the construction sector, allowing architects and engineers to use AI to optimize their building designs. The company has also launched a cloud-based generative service that allows users access to the software from anywhere.

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  • Generative AI in Drug Discovery Market size is expected to be worth around USD 1129 Mn by 2032 from USD 109 Mn in 2022, growing at a CAGR of 27.1% during the forecast period from 2023 to 2032.
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  • Generative AI In Real Estate Market size is expected to be worth around USD 924.2 Mn by 2032 from USD 328.3 Mn in 2022, at a CAGR of 11.2%.

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