Players Include Google, Micron Technology, Siemens and General Electric

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Global artificial intelligence in the manufacturing market

Global artificial intelligence in the manufacturing market

Global artificial intelligence in the manufacturing market

Dublin, 22 November 2022 (GLOBE NEWSWIRE) – Report on “Global Artificial Intelligence in Manufacturing, Market Size, Sharing and Analysis of Industry Trends by Providing Industrial Technology Programs, Regional Perspectives and Yearly Forecasts” 2022-2028 “was added to Of Offer.

Global artificial intelligence in the manufacturing market is expected to reach $ 21.3 billion by 2028, up from a market growth of 42.2% CAGR during the forecast period.

In recent years, artificial intelligence has become one of the fastest growing technologies. AI is linked to human intelligence and shares similar characteristics such as language comprehension, thinking, learning, problem solving and so on. In the development and review of such technologies, manufacturers in the market face huge intellectual barriers. AI is at the heart of the market’s next-generation software technology.

The application of artificial intelligence in manufacturing is growing due to the increasing automation in the manufacturing industry and the increasing demand for big data integration. In addition, artificial intelligence in the manufacturing market is being driven by the increasing use of machine sight cameras in industrial applications such as machine control, motion equipment, field service and quality control.

In addition, leading marketers are using a variety of methods, such as product launches and product innovation, to enhance their current product portfolio and maintain competitiveness in the fast-growing AI industry. For example, Oracle released a new artificial intelligence-based software for supply chain, manufacturing and other professionals in October 2017. IBM has released Watson Assistant, an AI-enabled business assistant in 2018. This product is a smart enterprise powered by artificial intelligence assistants.

Artificial intelligence (AI) in the production supply chain can predict demand trends for goods over time, economically, socially and geographically. Leading corporations are incorporating AI into their systems to increase customer happiness. GE, for example, has launched the Brilliant Manufacturing Suite to get customers to design their Brilliant factory ideas.

In addition, the use of automation and big data in the manufacturing business reduces risks throughout the production process and allows customers to respond quickly, improving the customer experience. However, some people’s careers are projected to be replaced by AI-based technology in the near future.

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COVID-19 Impact Analysis

To stop the spread of the COVID-19 pandemic, unprecedented locks were adopted around the world and many factories were shut down. Epidemics wreaked havoc on the world’s population, and the virus killed millions around the world. It also has a very negative impact on the manufacturing sector.

Many people’s disposable income has fallen. This resulted in lower demand for industrial items and as a result slowed global economic activity. Many countries are in the process of recovering from the effects of an epidemic. Improving plant operational efficiency, increasing AI performance in smart business operations, and increasing the deployment of automation technologies to reduce the consequences of COVID-19 are hopes for AI in the manufacturing industry.

Market growth factors

Industrial IoT Technology Development and Automation

Industrial Internet of Things (IIoT) allows for an architecture that provides real-time information about operating systems and businesses that make industrial operations more efficient, productive and innovative. The data collected by the IoT device must be converted into instructions that tell the host how to perform certain tasks.

These guides are developed by AI systems that use in-depth learning, contextual understanding, and natural language processes to learn from human behavior (NLP). AI-based systems run faster and are less buggy. As a result, improved production efficiency contributes to business expansion.

The demand for AI in manufacturing is driven by the increasing volume of complex datasets.

Companies in the manufacturing industry have access to a wide range of data collection and tracking resources. Big data, known as sensor data, production data, IoT-driven systems, and production software, is too large and difficult for humans to understand.

Because large amounts of structured and unstructured data from different sources can be quickly examined, AI and big data analysis have emerged as viable solutions to critical production concerns.

Organizations can interpret data and detect anomalies using AI and machine learning algorithms, reduce maintenance costs, improve customer service, increase maintenance, forecasting and protection, and use raw data to support decisions.

Market barriers

Reluctance among manufacturers to adopt AI-based technology

Artificial Intelligence (AI) provides companies with tools to improve predictive maintenance and control processes. Instead, manufacturers are reluctant to incorporate new technologies, especially AI-based solutions, into their expensive machines and devices.

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Any management error can increase costs. In addition, many manufacturers are skeptical of the ability of AI-based systems to perform proper maintenance and monitoring work. Based on these considerations, convincing manufacturers and convincing them that AI-based solutions are cost-effective, efficient, and secure is a little more difficult. However, some manufacturers are increasingly embracing the potential benefits of AI-based solutions and the many applications they can support.

Report attributes


Page number


Forecast period

2021 – 2028

Estimated market value (USD) for 2021

$ 1812.2 million

Projected market value (USD) in 2028

$ 21342.3 million

Overall annual growth rate




Key topics covered:

Chapter 1. Scope of marketing and methods

Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview Marketing Components and Scenarios
2.2 Key factors affecting the market
2.2.1 Marketing drivers
2.2.2 Market Restrictions

Chapter 3. Competitive Analysis – Global
3.1 KBV Cardinal Matrix
3.2 Developing a comprehensive strategy for new industries
3.2.1 Partnerships, Cooperation and Agreements
3.2.2 Product launch and product expansion
3.2.3 Acquisitions and mergers
3.3 Market Share Analysis 2020
3.4 Top Win Strategy
3.4.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.4.2 Key Strategic Changes: (Partnerships, Collaboration and Agreements: 2018, August – 2022, Mar) Leading Players

Chapter 4. Global Artificial Intelligence in the Production Market by Offering
4.1 Global application market by region
4.2 Global Global Hardware Market
4.3 Global service market by region

Chapter 5. Global Artificial Intelligence in Programmatic Production Markets
5.1 Maintenance of global forecasts and regional machinery control markets
5.2 Regional Global Inventory Optimization Market
5.3 Global Global Quality Control Market
5.4 Global Global Security Market
5.5 Global Industrial Robot Market by Region
5.6 Global Global Field Service Market
5.7 Regional Global Production Plan Market
5.8 Other global markets by region

Chapter 6. Global Artificial Intelligence in Technology Marketing
6.1 Global Global Machine Learning Market
6.2 Global Global Computer Vision Market
6.3 Global Global Natural Language Processing Market
6.4 Markets calculated by global, regional context

Chapter 7. Global Artificial Intelligence in Industrial Markets
7.1 Global Global Car Market
7.2 Global Global Food and Beverage Market
7.3 Global Pharmaceutical Market by Region
7.4 Global market for heavy metals and machinery
7.5 Global regional electronics and electronics market
7.6 Other global markets by region

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Chapter 8. Global Artificial Intelligence in Regional Production Markets

Chapter 9. Company Profile
9.1 NVIDIA Corporation
9.1.1 Company Overview
9.1.5 Recent Strategies and Developments Partnerships, Cooperation and Agreements: Product Launch and Product Expansion:
9.2 Cisco Systems, Inc.
9.2.1 Company Overview
9.2.2 Financial analysis
9.2.3 Area Analysis
9.2.4 Research and Development Expenses
9.2.5 Recent Strategies and Developments Partnerships, Cooperation and Agreements:
9.3 Microsoft Corporation
9.3.1 Company Overview
9.3.2 Financial analysis
9.3.3 Sectional and regional analysis
9.3.4 Research and Development Expenses
9.3.5 Recent Strategies and Developments Partnerships, Cooperation and Agreements:
9.4 IBM Corporation
9.4.1 Company Overview
9.4.2 Financial Analysis
9.4.3 Regional and Segment Analysis
9.4.4 Research and Development Expenses
9.4.5 Recent Strategies and Developments Partnerships, Collaboration and Agreements: Purchases and Mergers:
9.5 Intel Corporation
9.5.1 Company Overview
9.5.2 Financial analysis
9.5.3 Sectional and regional analysis
9.5.4 Research and Development Expenses
9.5.5 Recent Strategies and Developments Partnerships, Cooperation and Agreements: Product Launch and Product Expansion:
9.6 Oracle Corporation
9.6.1 Company Overview
9.6.2 Financial analysis
9.6.3 Section and area analysis
9.6.4 Research and Development Expenses
9.6.5 Recent Strategies and Developments Product Launch and Product Expansion:
9.7 Google LLC
9.7.1 Company Overview
9.7.2 Financial analysis
9.7.3 Section and area analysis
9.7.4 Research and Development Expenses
9.7.5 Recent Strategies and Developments Partnerships, Cooperation and Agreements:
9.8 Micron Technology, Inc.
9.8.1 Company Overview
9.8.2 Financial Analysis
9.8.3 Section and Area Analysis
9.8.4 Research and Development Expenses
9.9 Siemens AG
9.9.1 Company Overview
9.9.2 Financial analysis
9.9.3 Sectional and regional analysis
9.9.4 Research and Development Expenses
9.9.5 Recent Strategies and Developments Partnerships, Collaboration and Agreements: Product Launch and Product Expansion:
9.10. General Electric (GE) Co.
9.10.1 Company Overview
9.10.2 Financial analysis
9.10.3 Sectional and regional analysis
9.10.4 Research and Development Expenses

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