Region:Global
Author(s):Shambhavi
Product Code:KROD2115
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 |
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.
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 |
1.1. Definition and Scope
1.2. Market Taxonomy
1.3. Market Growth Rate
1.4. Market Segmentation Overview
2.1. Historical Market Size
2.2. Year-on-Year Growth Analysis
2.3. Key Market Developments and Milestones
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
4.1. 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
5.1. 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)
6.1. 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
7.1. AI Regulation Standards
7.2. Compliance Requirements
7.3. Certification Processes
8.1. Future Market Size Projections
8.2. Key Factors Driving Future Market Growth
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 %)
10.1. TAM/SAM/SOM Analysis
10.2. Customer Cohort Analysis
10.3. Marketing Initiatives
10.4. White Space Opportunity Analysis
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.
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.
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.
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.
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.
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.
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.
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.
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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