Artificial Intelligence in Manufacturing Market by Technology, Application, End-User

Description

List of Tables

The Artificial Intelligence in Manufacturing Market was valued at USD 5.74 billion in 2023, expected to reach USD 7.90 billion in 2024, and is projected to grow at a CAGR of 39.04%, to USD 57.75 billion by 2030.

The scope of artificial intelligence (AI) in manufacturing revolves around optimizing production processes, enhancing efficiency, and reducing operational costs. It includes applications such as predictive maintenance, quality control, inventory management, and supply chain optimization. The necessity for AI in manufacturing is driven by the demand for higher productivity and the need for adaptive systems in a rapidly advancing technological environment. Primary end-use sectors include automotive, electronics, pharmaceuticals, and consumer goods, each leveraging AI to enhance product quality and streamline operations. Key factors influencing growth include increasing adoption of Industry 4.0 practices, advancements in sensor technologies, and the integration of IoT in manufacturing processes. A significant opportunity lies in the real-time data analytics offered by AI, providing enhanced visibility and decision-making capabilities across production lines. Manufacturers can also benefit from developing custom AI solutions tailored to niche challenges. However, challenges such as high implementation costs, lack of skilled workforce, and data privacy concerns present obstacles to market growth. Furthermore, ensuring cybersecurity and mitigating potential disruptions due to system failures are critical challenges. Innovative areas for growth include developing more sophisticated AI algorithms for improved predictive capabilities and enhancing human-machine collaboration through intuitive interfaces. Research focused on energy-efficient AI models and AI interoperability across varied manufacturing systems can drive sustainable growth. The market is projected to evolve dynamically, as manufacturers continue to adopt digital transformation initiatives to remain competitive. Companies can position themselves strategically by investing in AI-powered supply chain resilience and customizable automation solutions tailored to specific manufacturing verticals. Emphasizing strong partnerships with technology providers to speed up deployment and implementation can also help in overcoming barriers, enabling companies to capitalize on emerging AI opportunities effectively.

KEY MARKET STATISTICS
Base Year [2023]	USD 5.74 billion
Estimated Year [2024]	USD 7.90 billion
Forecast Year [2030]	USD 57.75 billion
CAGR (%)	39.04%

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Artificial Intelligence in Manufacturing Market

The Artificial Intelligence in Manufacturing Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

Market Drivers
- Growing need for automation and rapidly evolving industries
- Evolving IoT technology across manufacturing industries
- Increasing emphasis on operational efficiency and reducing cost
Market Restraints
- High initial investment for installation and implementation of technology
Market Opportunities
- Growing adoption of AI technology in machinery inspection and predictive maintenance
- Promising Government Initiatives & Investments in Developing Nations
Market Challenges
- Concerns regarding latency-sensitive applications and limited skilled workforce

Porter's Five Forces: A Strategic Tool for Navigating the Artificial Intelligence in Manufacturing Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Artificial Intelligence in Manufacturing Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Artificial Intelligence in Manufacturing Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Artificial Intelligence in Manufacturing Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Artificial Intelligence in Manufacturing Market

A detailed market share analysis in the Artificial Intelligence in Manufacturing Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Artificial Intelligence in Manufacturing Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Artificial Intelligence in Manufacturing Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the Artificial Intelligence in Manufacturing Market

A strategic analysis of the Artificial Intelligence in Manufacturing Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the Artificial Intelligence in Manufacturing Market, highlighting leading vendors and their innovative profiles. These include Advanced Micro Devices, Inc., AIBrain Inc., Bright Machines, Inc., Cisco Systems, Inc., ForwardX Technology Co., Ltd., General Electric Company, General Vision Inc., Google, LLC by Alphabet Inc., Graphcore Limited, Hewlett Packard Enterprise Company, Intel Corporation, International Business Machines Corporation, Landing AI, Medtronic PLC, Micron Technology Inc., Microsoft Corporation, Mitsubishi Electric Corporation, Novartis International AG, Nvidia Corporation, Oracle Corporation, Path Robotics, Progress Software Corporation, Rethink Robotics GmbH, Rockwell Automation Inc., SAP SE, Siemens AG, SparkCognition, Inc., UBTECH Robotics, Inc., and Uptake Technologies Inc..

Market Segmentation & Coverage

This research report categorizes the Artificial Intelligence in Manufacturing Market to forecast the revenues and analyze trends in each of the following sub-markets:

Based on Technology, market is studied across Deep Learning, Machine Learning Platforms, Machine Vision, Robotic Processes Automation, and Text Analytics & Natural Processing Language.
Based on Application, market is studied across Cybersecurity, Field Services, Industrial Robots, Material Movement, Predictive Maintenance & Machinery Inspection, Production Planning, Quality Control, and Reclamation.
Based on End-User, market is studied across Automobile, Energy & Power, Food & Beverages, Heavy Metals & Machine Manufacturing, Pharmaceuticals, and Semiconductor & Electronics.
Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Product Code: MRR-436901065773

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Growing need for automation and rapidly evolving industries
  - 5.1.1.2. Evolving IoT technology across manufacturing industries
  - 5.1.1.3. Increasing emphasis on operational efficiency and reducing cost
- 5.1.2. Restraints
  - 5.1.2.1. High initial investment for installation and implementation of technology
- 5.1.3. Opportunities
  - 5.1.3.1. Growing adoption of AI technology in machinery inspection and predictive maintenance
  - 5.1.3.2. Promising Government Initiatives & Investments in Developing Nations
- 5.1.4. Challenges
  - 5.1.4.1. Concerns regarding latency-sensitive applications and limited skilled workforce
5.2. Market Segmentation Analysis
- 5.2.1. Technology: Rising adoption of robotic process automation to increase productivity across manufacturing sector
- 5.2.2. Application: Increasing need for security and process automation in manufacturing sector
- 5.2.3. End-User: Growing demand for AI for propelling innovation and efficiency across energy & utility sector
5.3. Porter's Five Forces Analysis
- 5.3.1. Threat of New Entrants
- 5.3.2. Threat of Substitutes
- 5.3.3. Bargaining Power of Customers
- 5.3.4. Bargaining Power of Suppliers
- 5.3.5. Industry Rivalry
5.4. PESTLE Analysis
- 5.4.1. Political
- 5.4.2. Economic
- 5.4.3. Social
- 5.4.4. Technological
- 5.4.5. Legal
- 5.4.6. Environmental

6. Artificial Intelligence in Manufacturing Market, by Technology

6.1. Introduction
6.2. Deep Learning
6.3. Machine Learning Platforms
6.4. Machine Vision
6.5. Robotic Processes Automation
6.6. Text Analytics & Natural Processing Language

7. Artificial Intelligence in Manufacturing Market, by Application

7.1. Introduction
7.2. Cybersecurity
7.3. Field Services
7.4. Industrial Robots
7.5. Material Movement
7.6. Predictive Maintenance & Machinery Inspection
7.7. Production Planning
7.8. Quality Control
7.9. Reclamation

8. Artificial Intelligence in Manufacturing Market, by End-User

8.1. Introduction
8.2. Automobile
8.3. Energy & Power
8.4. Food & Beverages
8.5. Heavy Metals & Machine Manufacturing
8.6. Pharmaceuticals
8.7. Semiconductor & Electronics

9. Americas Artificial Intelligence in Manufacturing Market

9.1. Introduction
9.2. Argentina
9.3. Brazil
9.4. Canada
9.5. Mexico
9.6. United States

10. Asia-Pacific Artificial Intelligence in Manufacturing Market

10.1. Introduction
10.2. Australia
10.3. China
10.4. India
10.5. Indonesia
10.6. Japan
10.7. Malaysia
10.8. Philippines
10.9. Singapore
10.10. South Korea
10.11. Taiwan
10.12. Thailand
10.13. Vietnam

11. Europe, Middle East & Africa Artificial Intelligence in Manufacturing Market

11.1. Introduction
11.2. Denmark
11.3. Egypt
11.4. Finland
11.5. France
11.6. Germany
11.7. Israel
11.8. Italy
11.9. Netherlands
11.10. Nigeria
11.11. Norway
11.12. Poland
11.13. Qatar
11.14. Russia
11.15. Saudi Arabia
11.16. South Africa
11.17. Spain
11.18. Sweden
11.19. Switzerland
11.20. Turkey
11.21. United Arab Emirates
11.22. United Kingdom

12. Competitive Landscape

12.1. Market Share Analysis, 2023
12.2. FPNV Positioning Matrix, 2023
12.3. Competitive Scenario Analysis
- 12.3.1. IFS to acquire Falkonry AI
- 12.3.2. AI-driven biosimilar manufacturing partnership announced
- 12.3.3. AI-based startup helping India's manufacturing prowess raises USD 4.2 million
12.4. Strategy Analysis & Recommendation

Companies Mentioned

1. Advanced Micro Devices, Inc.
2. AIBrain Inc.
3. Bright Machines, Inc.
4. Cisco Systems, Inc.
5. ForwardX Technology Co., Ltd.
6. General Electric Company
7. General Vision Inc.
8. Google, LLC by Alphabet Inc.
9. Graphcore Limited
10. Hewlett Packard Enterprise Company
11. Intel Corporation
12. International Business Machines Corporation
13. Landing AI
14. Medtronic PLC
15. Micron Technology Inc.
16. Microsoft Corporation
17. Mitsubishi Electric Corporation
18. Novartis International AG
19. Nvidia Corporation
20. Oracle Corporation
21. Path Robotics
22. Progress Software Corporation
23. Rethink Robotics GmbH
24. Rockwell Automation Inc.
25. SAP SE
26. Siemens AG
27. SparkCognition, Inc.
28. UBTECH Robotics, Inc.
29. Uptake Technologies Inc.