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Global AI in Manufacturing Market Outlook to 2028

Region:Global

Author(s):Shambhavi

Product Code:KROD2115

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Published On

December 2024

Total pages

98

About the Report

Global AI in Manufacturing Market Overview

  • The Global AI in Manufacturing Market was valued at USD 4.10 billion in 2023. The market is primarily driven by the increasing demand for automation in manufacturing processes, which enhances productivity and reduces operational costs. The integration of AI technologies, such as machine learning and computer vision, into manufacturing systems is significantly boosting efficiency and quality control, further propelling market growth.

market overviews

  • The key players dominating the Global AI in Manufacturing Market include IBM Corporation, Siemens AG, Microsoft Corporation, General Electric Company, and SAP SE. These companies are at the forefront of AI innovation in manufacturing, offering advanced solutions such as predictive maintenance, robotics automation, and quality control.
  • In 2023, the European Union launched the AI4EU initiative, which aims to foster the adoption of AI across various industries, including manufacturing. The initiative focuses on creating a collaborative platform for AI resources, including datasets, computing power, and expertise, to accelerate AI integration in manufacturing.
  • In 2023, major manufacturing hubs such as the United States, Germany, and China continue to dominate the Global AI in Manufacturing Market. US dominance is driven by the automotive industry's reliance on AI for robotics and automation, while Germany's robust engineering and manufacturing sector. Also, as China is a tech hub, is leading in AI adoption due to its advanced electronics and machinery manufacturing industries.

Global AI in Manufacturing Market Segmentation

  • By Component: The market is segmented by component into hardware, software, and services. In 2023, the software segment held the dominant market share, driven by the increasing need for AI algorithms and platforms that can optimize manufacturing processes. The software segment's dominance is attributed to its critical role in predictive maintenance, quality control, and supply chain optimization. Companies like IBM and Microsoft are leading providers of AI software solutions, contributing to the segment's growth.

market overviews

 

  • By Region: The Global AI in Manufacturing Market is segmented by region into North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa. North America, particularly the United States, dominates the market share in 2023 due to the early adoption of AI technologies and significant investments in research and development. The presence of leading AI companies and the strong manufacturing base in North America contribute to the region's leadership. Additionally, government support for AI initiatives further drives market growth in this region.

market overviews

  • By Technology: The market is segmented by technology into machine learning, computer vision, and natural language processing (NLP). Machine learning dominated the market in 2023 due to its widespread application in predictive maintenance and quality control. The technology's ability to analyze vast amounts of data and generate actionable insights makes it indispensable in manufacturing environments. The machine learning segment's growth is bolstered by advancements in data processing and the increasing adoption of AI across various industries.

Global AI in Manufacturing Market Competitive Landscape

Company Name

Establishment Year

Headquarters

IBM Corporation

1911

Armonk, New York, USA

Siemens AG

1847

Munich, Germany

Microsoft Corporation

1975

Redmond, Washington, USA

General Electric Company

1892

Boston, Massachusetts, USA

SAP SE

1972

Walldorf, Germany

  • Watson Works Platform Launch (2023): IBM launched the Watson Works platform specifically for the manufacturing industry. This platform integrates AI and IoT to optimize supply chain management, predictive maintenance, and worker safety, resulting in up to a 25% improvement in production efficiency for early adopters. IBM partnered with Samsung to develop AI-driven semiconductor manufacturing solutions. This collaboration aims to enhance the precision of chip manufacturing processes, potentially reducing defect rates by 30%.
  • Siemen Collaboration with NVIDIA (2023): Siemens collaborated with NVIDIA to integrate AI and simulation capabilities into its digital twin offerings. This partnership aims to enhance production efficiency by enabling more accurate and scalable digital models. Siemens acquired an edge AI start-up specializing in manufacturing automation for $300 million.

Global AI in Manufacturing Market Analysis

Global AI in Manufacturing Market Growth Drivers

  • Increasing Adoption of AI for Predictive Maintenance: The manufacturing sector is increasingly adopting AI for predictive maintenance, which significantly reduces equipment downtime and maintenance costs. AI-based predictive maintenance can cut maintenance expenses by 20% and unscheduled breakdowns by half. This is particularly evident in North America, where large manufacturing facilities are integrating AI systems to monitor equipment health in real-time, resulting in operational efficiency and cost savings.
  • Expansion of Smart Factories with AI Integration: Smart factories, where manufacturing processes are highly automated and optimized through AI, are rapidly expanding across the globe. By 2025, most of all factories worldwide are expected to be smart factories, driven by the integration of AI in robotics, quality control, and supply chain management. This trend is particularly strong in Europe, where the EUs Industry 4.0 initiative is pushing manufacturers to adopt AI technologies, enhancing productivity and reducing waste.
  • Government Support for AI in Manufacturing: Governments worldwide are supporting the adoption of AI in manufacturing through various initiatives and funding programs. In 2023, the U.S. government announced a $1.2 billion funding initiative to support AI-driven manufacturing projects aimed at enhancing competitiveness in the global market. Similar initiatives are being rolled out in Asia-Pacific, particularly in Japan and South Korea, where governments are incentivizing AI integration to maintain their leadership in advanced manufacturing.

Global AI in Manufacturing Market Challenges

  • High Implementation Costs of AI Technologies: The high initial cost of implementing AI technologies remains a significant barrier for many manufacturers, especially small and medium-sized enterprises (SMEs). The cost of deploying AI-driven automation systems, including hardware, software, and employee training, can exceed $500,000 per production line, making it unaffordable for smaller players.
  • Data Privacy and Security Concerns: The integration of AI in manufacturing involves the collection and processing of vast amounts of data, raising concerns about data privacy and security. In 2024, manufacturing companies globally will face data security breaches, primarily due to inadequate cybersecurity measures. The need to protect sensitive operational data and ensure compliance with regulations, such as GDPR in Europe, adds complexity and cost to AI adoption in manufacturing.

Global AI in Manufacturing Market Government Initiatives

  • NIST Funding Opportunity: In 2024,the National Institute of Standards and Technology (NIST) announced a competition for a new Manufacturing USA institute focused on AI in manufacturing, with up to $70 million available over five years. This funding aims to bolster the resilience of U.S. manufacturers through AI integration and workforce development.The Biden Administration has directed a significant portion of its $1.1 trillion funding package toward manufacturing modernization, with 17% already allocated to various entities, including manufacturers and universities.
  • European AI Strategy for Industry 4.0: The European Unions AI Strategy for Industry 4.0, launched in 2024, focuses on promoting the integration of AI in manufacturing through financial incentives and regulatory support. The strategy includes a USD 1.64 billion fund to support AI innovation in manufacturing, targeting SMEs and large enterprises alike. The initiative also aims to establish AI standards and ensure that AI applications in manufacturing are aligned with ethical guidelines and data protection regulations.

Global AI in Manufacturing Market Future Outlook

The global AI in the manufacturing market is expected to grow significantly by 2028, driven by increased automation, demand for smart factories, and advancements in machine learning, with robust growth projected through 2028.

Future Trends

  • Expansion of AI in Predictive Analytics: By 2028, the Global AI in Manufacturing Market will be significantly driven by the expansion of AI in predictive analytics. AI systems will be increasingly used to predict equipment failures, optimize production schedules, and enhance quality control processes. It is anticipated that by 2028, manufacturers globally will rely on AI-driven predictive analytics, leading to a substantial reduction in operational costs and improved efficiency across the manufacturing sector.
  • Widespread Adoption of AI in Smart Manufacturing: The widespread adoption of AI in smart manufacturing will be a key trend driving the market forward over the next five years. By 2028, smart factories powered by AI will account for nearly half of all manufacturing facilities worldwide. These smart factories will leverage AI to automate complex production processes, reduce waste, and enhance product customization, making them more competitive in the global market.

Scope of the Report

By Component

Hardware

Software

Services

By Technology

Machine Learning

Computer Vision

Natural Language Processing (NLP)

By Application

Predictive Maintenance and Machinery Inspection

Production Planning

Quality Control

By End-User Industry

Automotive

Pharmaceuticals

Electronics

Heavy Metals and Machinery

By End User

North America

Europe

Asia-pacific

MEA

Latin America

Products

Key Target Audience Organizations and Entities Who Can Benefit by Subscribing This Report:

  • AI Technology Providers
  • Manufacturing Industry Associations
  • Automation and Robotics Companies
  • Government and Regulatory Bodies (e.g., European Commission, U.S. Department of Commerce)
  • Venture Capital and Investment Firms
  • Industrial IoT Solution Providers
  • Automotive and Electronics Manufacturers
  • Software Development Firms

Time Period Captured in the Report:

  • Historical Period: 2018-2023
  • Base Year: 2023
  • Forecast Period: 2023-2028

Companies

Players Mentioned in the Report:

  • IBM Corporation
  • Siemens AG
  • Microsoft Corporation
  • General Electric Company
  • SAP SE
  • NVIDIA Corporation
  • Rockwell Automation
  • Oracle Corporation
  • Intel Corporation
  • Google LLC
  • ABB Ltd.
  • Bosch GmbH
  • FANUC Corporation
  • Mitsubishi Electric Corporation
  • Honeywell International Inc.

Table of Contents

1. Global AI in Manufacturing Market Overview

1.1. Definition and Scope

1.2. Market Taxonomy

1.3. Market Growth Rate

1.4. Market Segmentation Overview

2. Global AI in Manufacturing Market Size (in USD Bn), 2018-2023

2.1. Historical Market Size

2.2. Year-on-Year Growth Analysis

2.3. Key Market Developments and Milestones

3. Global AI in Manufacturing Market Analysis

3.1. Growth Drivers

3.1.1. Increasing Adoption of Automation

3.1.2. Rise in Industrial IoT

3.1.3. Government Initiatives

3.1.4. Demand for Enhanced Productivity

3.2. Restraints

3.2.1. High Implementation Costs

3.2.2. Data Privacy and Security Concerns

3.2.3. Skill Gap in Workforce

3.3. Opportunities

3.3.1. Technological Advancements in AI

3.3.2. Expansion into Emerging Markets

3.3.3. Partnerships and Collaborations

3.4. Trends

3.4.1. Integration with Edge Computing

3.4.2. Adoption of Predictive Maintenance

3.4.3. AI in Supply Chain Optimization

3.5. Government Regulations

3.5.1. European AI Strategy for Industry 4.0

3.5.2. Data Protection Laws

3.5.3. NIST Funding Opportunity

3.6. SWOT Analysis

3.7. Stakeholder Ecosystem

3.8. Competitive Ecosystem

4. Global AI in Manufacturing Market Segmentation, 2023

4.1. By Component (in Value %)

4.1.1. Hardware

4.1.2. Software

4.1.3. Services

4.2. By Technology (in Value %)

4.2.1. Machine Learning

4.2.2. Computer Vision

4.2.3. Natural Language Processing (NLP)

4.3. By Application (in Value %)

4.3.1. Predictive Maintenance and Machinery Inspection

4.3.2. Production Planning

4.3.3. Quality Control

4.4. By End-User Industry (in Value %)

4.4.1. Automotive

4.4.2. Pharmaceuticals

4.4.3. Electronics

4.4.4. Heavy Metals and Machinery

4.5. By Region (in Value %)

4.5.1. North America

4.5.2. Europe

4.5.3. Asia-Pacific

4.5.4. Latin America

4.5.5. Middle East & Africa

5. Global AI in Manufacturing Market Cross Comparison

5.1. Detailed Profiles of Major Companies

5.1.1. IBM Corporation

5.1.2. Siemens AG

5.1.3. Microsoft Corporation

5.1.4. General Electric Company

5.1.5. SAP SE

5.1.6. Rockwell Automation

5.1.7. NVIDIA Corporation

5.1.8. Oracle Corporation

5.1.9. Intel Corporation

5.1.10. Google LLC

5.2. Cross Comparison Parameters (No. of Employees, Headquarters, Inception Year, Revenue)

6. Global AI in Manufacturing Market Competitive Landscape

6.1. Market Share Analysis

6.2. Strategic Initiatives

6.3. Mergers and Acquisitions

6.4. Investment Analysis

6.4.1. Venture Capital Funding

6.4.2. Government Grants

6.4.3. Private Equity Investments

7. Global AI in Manufacturing Market Regulatory Framework

7.1. AI Regulation Standards

7.2. Compliance Requirements

7.3. Certification Processes

8. Global AI in Manufacturing Future Market Size (in USD Bn), 2023-2028

8.1. Future Market Size Projections

8.2. Key Factors Driving Future Market Growth

9. Global AI in Manufacturing Future Market Segmentation, 2028

9.1. By Component (in Value %)

9.2. By Technology (in Value %)

9.3. By Application (in Value %)

9.4. By End-User Industry (in Value %)

9.5. By Region (in Value %)

10. Global AI in Manufacturing Market Analysts Recommendations

10.1. TAM/SAM/SOM Analysis

10.2. Customer Cohort Analysis

10.3. Marketing Initiatives

10.4. White Space Opportunity Analysis

Disclaimer

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Research Methodology

Step 01 Identifying Key Variables:

Ecosystem creation for all the major entities and referring to multiple secondary and proprietary databases to perform desk research around market to collate industry level information.

Step 02 Market Building:

Collating statistics on Global AI in Manufacturing Market over the years, penetration of marketplaces and service providers ratio to compute revenue generated in Global AI in Manufacturing Market. We will also review service quality statistics to understand revenue generated which can ensure accuracy behind the data points shared.

Step 03 Validating and Finalizing:

Building market hypothesis and conducting CATIs with industry experts belonging to different companies to validate statistics and seek operational and financial information from company representatives.

Step 04 Research Output:

Our team will approach multiple Global AI in Manufacturing Market companies and understand nature of product segments and sales, consumer preference and other parameters, which will support us validate statistics derived through bottom to top approach from AI in Manufacturing Market companies.

Frequently Asked Questions

01 How big is the Global AI in Manufacturing Market?

The Global AI in Manufacturing Market was valued at USD 4.10 billion in 2023, driven by the growing adoption of automation, advancements in AI technologies, and the integration of AI with industrial IoT.

02 What are the challenges in the Global AI in Manufacturing Market?

Challenges in Global AI in Manufacturing include high implementation costs, data privacy and security concerns, and a shortage of skilled workforce capable of developing and maintaining AI systems in manufacturing environments.

03 Who are the major players in the Global AI in Manufacturing Market?

Key players in the Global AI in Manufacturing market include IBM Corporation, Siemens AG, Microsoft Corporation, General Electric Company, and SAP SE, all of which lead due to their advanced AI solutions and strong global presence.

04 What are the growth drivers of the Global AI in Manufacturing Market?

The Global AI in Manufacturing market is driven by the increasing adoption of AI for predictive maintenance, the expansion of smart factories, and strong government support for AI integration in manufacturing processes.

05 What are the recent trends in the Global AI in Manufacturing Market?

Recent trends in Global AI in Manufacturing include the integration of AI with Industrial IoT, the rise of AI-driven collaborative robots (cobots), and the adoption of AI for supply chain optimization, enhancing efficiency and reducing costs.

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