Artificial intelligence (AI) in Manufacturing Market
- December, 2023
- Semiconductor And Electronics
Artificial Intelligence (AI) in Manufacturing Market By Offering (Hardware, Software, Services), Technology (Machine Learning, Natural Language Processing), By Application (Predictive Maintenance and Machinery Inspection, Cyber security), By End-use Industry (Semiconductor & Electronics, Energy & Power, Pharmaceuticals, Medical Devices, Automotive, Machine Manufacturing, Consumer Goods, Aerospace and Defense), and By Region; Growth Trends & Forecasts (2024 - 2030)
As per Intent Market Research, the Artificial intelligence (AI) in manufacturing market is projected to grow from USD 3.0 billion in 2023-e to USD 40.6 billion by 2030, registering a CAGR of 45.0% during the forecast period (2024-2030).
The report focuses on estimating the current market potential in terms of the total addressable market for all the segments, sub-segments, and regions. In the process, all the high-growth and upcoming technologies were identified and analyzed to measure their impact on the current and future market. The report also identifies the key stakeholders, their business gaps, and their purchasing behavior. This information is essential for developing effective marketing strategies and creating products or services that meet the needs of the target market. The report also covers a detailed analysis of the competitive landscape which includes major players, their recent developments, growth strategies, product benchmarking, and manufacturing operations among others. Also, brief insights on start-up ecosystem and emerging companies is also included as part of this report.
Report Objectives
The report will help you answer some of the most critical questions in the Artificial intelligence (AI) in manufacturing market. A few of them are as follows:
- What are the key drivers, restraints, opportunities, and challenges influencing the market growth?
- What are the prevailing technology trends in the Artificial intelligence (AI) in manufacturing market?
- What is the size of the Artificial intelligence (AI) in manufacturing market based on segments, sub-segments, and regions?
- What is the size of different market segments across key regions: North America, Europe, Asia Pacific, Middle East, and Rest of the World?
- What are the market opportunities for stakeholders after analyzing key market trends?
- Who are the leading market players and what are their market share and core competencies?
- What is the degree of competition in the market and what are the key growth strategies adopted by leading players?
- What is the competitive landscape of the market, including market share analysis, revenue analysis, and a ranking of key players?
Report Scope:
Report Features | Description |
Market Size (2023-e) | USD 3.0 billion |
Forecasted Value (2030) | USD 40.6 billion |
CAGR (2024-2030) | 45.0% |
Base Year for Estimation | 2023-e |
Historic Year | 2022 |
Forecast Period | 2024-2030 |
Report Coverage | Market Forecast, Market Dynamics, Competitive Landscape, Recent Developments |
Segments Covered | Artificial intelligence (AI) in manufacturing market By Offering (Hardware, Software, Services), Technology (Machine Learning, Natural Language Processing), By Application (Predictive Maintenance and Machinery Inspection, Cyber security), By End-use Industry (Semiconductor & Electronics, Energy & Power, Pharmaceuticals, Medical Devices, Automotive, Machine Manufacturing, Consumer Goods, Aerospace and Defense) |
Regional Analysis | North America (US, Canada), Europe (Germany, France, UK, Spain, Italy & Rest of Europe), Asia Pacific (China, Japan, South Korea, India, and rest of Asia Pacific), Latin America (Brazil, Mexico, Argentina, & Rest of Latin America), Middle East & Africa (Saudi Arabia, South Africa, Turkey, United Arab Emirates, & Rest of MEA) |
Customization Scope | Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements |
Research Methodology
A comprehensive market research approach was employed to gather and analyze data on the Artificial intelligence (AI) in manufacturing market. In the process, the analysis was also done to estimate the parent market and relevant adjacencies to major the impact of them on the Artificial intelligence (AI) in manufacturing market. The research methodology encompassed both secondary and primary research techniques, ensuring the accuracy and credibility of the findings.
Secondary Research
Secondary research involved a thorough review of pertinent industry reports, journals, articles, and publications. Additionally, annual reports, press releases, and investor presentations of industry players were scrutinized to gain insights into their market positioning and strategies.
Primary Research
Primary research involved conducting in-depth interviews with industry experts, stakeholders, and market participants across the AI in manufacturing ecosystem. The primary research objectives included:
- Validating findings and assumptions derived from secondary research
- Gathering qualitative and quantitative data on market trends, drivers, and challenges
- Understanding the demand-side dynamics, encompassing end-users, component manufacturers, facility providers, and service providers
- Assessing the supply-side landscape, including technological advancements and recent developments
Market Size Estimation
A combination of top-down and bottom-up approaches was utilized to estimate the overall size of the Artificial intelligence (AI) in manufacturing market. These methods were also employed to estimate the size of various subsegments within the market. The market size estimation methodology encompassed the following steps:
- Identification of key industry players and relevant revenues through extensive secondary research
- Determination of the industry’s supply chain and market size, in terms of value, through primary and secondary research processes
- Calculation of percentage shares, splits, and breakdowns using secondary sources and verification through primary sources
Data Triangulation
To ensure the accuracy and reliability of the market size estimates, data triangulation was implemented. This involved cross-referencing data from various sources, including demand and supply side factors, market trends, and expert opinions. Additionally, top-down and bottom-up approaches were employed to validate the market size estimates.
- Introduction
- Market Definition
- Scope of the Study
- Research Assumptions
- Study Limitations
- Research Methodology
- Research Approach
- Top-Down Method
- Bottom-Up Method
- Factor Impact Analysis
- Insights & Data Collection Process
- Secondary Research
- Primary Research
- Data Mining Process
- Data Analysis
- Data Validation and Revalidation
- Data Triangulation
- Research Approach
- Executive Summary
- Major Markets & Segments
- Highest Growing Regions and Respective Countries
- Impact of Growth Drivers & Inhibitors
- Regulatory Overview by Country
- Artificial Intelligence in Manufacturing Market, by Offering (Market Size in USD Million)
- Software
- Hardware
- Services
- Artificial Intelligence in Manufacturing Market, by Technology (Market Size in USD Million)
- Machine Learning
- Natural Language Processing
- Aware Computing
- Computer Vision
- Artificial Intelligence in Manufacturing Market, by Application (Market Size in USD Million)
- Predictive Maintenance and Machinery Inspection
- Inventory Optimization
- Production Planning
- Field Services
- Quality Control
- Cybersecurity
- Industrial Robots
- Reclamation
- Artificial Intelligence in Manufacturing Market, by Industry (Market Size in USD Million)
- Automotive
- Energy and Power
- Metals and Heavy Machinery
- Semiconductor & Electronics
- Food & Beverage
- Pharma
- Mining
- Others
- Regional Analysis
- Regional Overview
- North America
- Regional Trends & Growth Drivers
- Pressing Need to Handle Large and Complex Datasets Effectively
- Rising Adoption of IOT and Automation Technologies
- Thriving Semiconductor Chipset Industry Due to Increasing Adoption of AI Technology
- Barriers & Challenges
- Reluctance Among Manufacturers to Adopt AI-Based Technologies
- Concerns Regarding Data Privacy and Stringent Data Security Regulations
- Opportunities
- Utilization of AI-Powered Predictive Analytics and Production Planning Apps
- Execution of ML and NLP to Automate and Upgrade Business Processes
- Factor Impact Analysis
- Technology Trends
- Existing & Future Technologies Disrupting the Market
- Use Case Analysis
- Company Innovations
- Pricing Analysis
- Regulatory Landscape
- North America Artificial Intelligence in Manufacturing Market, by Offering (Market Size in USD Million)
- North America Artificial Intelligence in Manufacturing Market, by Technology (Market Size in USD Million)
- North America Artificial Intelligence in Manufacturing Market, by Application (Market Size in USD Million)
- North America Artificial Intelligence in Manufacturing Market, by Industry (Market Size in USD Million)
- Regional Trends & Growth Drivers
*Similar segmentation will be provided at each regional level
- By Country
- US
- US Artificial Intelligence in Manufacturing Market, by Offering (Market Size in USD Million)
- US Artificial Intelligence in Manufacturing Market, by Technology (Market Size in USD Million)
- US Artificial Intelligence in Manufacturing Market, by Application (Market Size in USD Million)
- US Artificial Intelligence in Manufacturing Market, by Industry (Market Size in USD Million)
- Canada
- US
*Similar segmentation will be provided at each regional and country level
- Europe
- APAC
- Middle East
- Latin America
- Africa
- Competitive Landscape
- Overview of the Key Players
- Competitive Ecosystem
- Platform Manufacturers
- Subsystem Manufacturers
- Service Providers
- Software Providers
- Company Share Analysis
- Company Benchmarking Matrix
- Strategic Overview
- Product Innovations
- Start-up Ecosystem
- Strategic Competitive Insights/ Customer Imperatives
- ESG Matrix/ Sustainability Matrix
- Manufacturing Network
- Locations
- Supply Chain and Logistics
- Product Flexibility/Customization
- Digital Transformation and Connectivity
- Environmental and Regulatory Compliance
- Technology Readiness Level Matrix
- Technology Maturity Curve
- Buying Criteria
- Company Profiles
- NVIDIA Corporation
- Company Overview
- Company Financials
- Product/Service Portfolio
- Recent Developments
- IMR Analysis
- NVIDIA Corporation
*Similar information will be provided for other companies
- Siemens
- Microsoft
- General Electric
- Appendix
Intent Market Research employs a rigorous methodology to minimize residual errors by carefully defining the scope, validating findings through primary research, and consistently updating our in-house database. This dynamic approach allows us to capture ongoing market fluctuations and adapt to evolving market uncertainties.
The research factors used in our methodology vary depending on the specific market being analyzed. To begin with, we incorporate both demand and supply side information into our model to identify and address market gaps. Additionally, we also employ approaches such as Macro-indicator Analysis, Factor Analysis, Value Chain-Based Sizing, and forecasting to further increase the accuracy of the numbers and validate the findings.
Research Approach
- Secondary Research Approach: During the initial phase of the research process, we acquire and accumulate extensive data continuously. This data is carefully filtered and validated through a variety of secondary sources.
- Primary Research Approach: Following the consolidation of data gathered through secondary research, we initiate a validation process to verify all the market numbers, assumptions, and findings by engaging with the subject matter experts.
Data Collection, Analysis and Interpretation:
Research Methodology
Our market research methodology utilizes both top-down and bottom-up approaches to segment and estimate quantitative aspects of the market. We also employ multi-perspective analysis, examining the market from distinct viewpoints.
