Global AI-based Raw Material Sourcing Optimization Market Growth (Status and Outlook) 2025-2031
Description
According to this study, the global AI-based Raw Material Sourcing Optimization market size will reach US$ 3344 million by 2031.
Artificial intelligence (AI)-based raw material procurement optimization is defined as the use of AI technology and algorithms to achieve intelligent decision-making and optimization in the raw material procurement process by analyzing historical data, market demand, supplier information, inventory levels and other multi-dimensional factors. This optimization aims to improve procurement efficiency, reduce costs, reduce inventory risks, and enhance the transparency and collaboration of the supply chain.
United States market for AI-based Raw Material Sourcing Optimization is estimated to increase from US$ million in 2024 to US$ million by 2031, at a CAGR of % from 2025 through 2031.
China market for AI-based Raw Material Sourcing Optimization is estimated to increase from US$ million in 2024 to US$ million by 2031, at a CAGR of % from 2025 through 2031.
Europe market for AI-based Raw Material Sourcing Optimization is estimated to increase from US$ million in 2024 to US$ million by 2031, at a CAGR of % from 2025 through 2031.
Global key AI-based Raw Material Sourcing Optimization players cover Amazon, IBM, FedEx, American Software, Inc., Kinaxis, etc. In terms of revenue, the global two largest companies occupied for a share nearly % in 2024.
LPI (LP Information)' newest research report, the “AI-based Raw Material Sourcing Optimization Industry Forecast” looks at past sales and reviews total world AI-based Raw Material Sourcing Optimization sales in 2024, providing a comprehensive analysis by region and market sector of projected AI-based Raw Material Sourcing Optimization sales for 2025 through 2031. With AI-based Raw Material Sourcing Optimization sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI-based Raw Material Sourcing Optimization industry.
This Insight Report provides a comprehensive analysis of the global AI-based Raw Material Sourcing Optimization landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on AI-based Raw Material Sourcing Optimization portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global AI-based Raw Material Sourcing Optimization market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI-based Raw Material Sourcing Optimization and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global AI-based Raw Material Sourcing Optimization.
This report presents a comprehensive overview, market shares, and growth opportunities of AI-based Raw Material Sourcing Optimization market by product type, application, key players and key regions and countries.
Segmentation by Type:
Demand Forecasting and Inventory Management
Supplier Selection and Evaluation
Logistics and Transportation Optimization
Resource Allocation and Quality Control
Automated Procurement Process
Others
Segmentation by Application:
Metals and Mining
Manufacturing
Agriculture
Food Processing
Textiles and Clothing
Pharmaceuticals
Other
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Amazon
IBM
FedEx
American Software, Inc.
Kinaxis
Blue Yonder
SAP
Intellinum
Alpha Augmented Services AG
ToolsGroup
RightChain Healthcare
QAD
Inspur Information
Neo Tangent
Please note: The report will take approximately 2 business days to prepare and deliver.
Artificial intelligence (AI)-based raw material procurement optimization is defined as the use of AI technology and algorithms to achieve intelligent decision-making and optimization in the raw material procurement process by analyzing historical data, market demand, supplier information, inventory levels and other multi-dimensional factors. This optimization aims to improve procurement efficiency, reduce costs, reduce inventory risks, and enhance the transparency and collaboration of the supply chain.
United States market for AI-based Raw Material Sourcing Optimization is estimated to increase from US$ million in 2024 to US$ million by 2031, at a CAGR of % from 2025 through 2031.
China market for AI-based Raw Material Sourcing Optimization is estimated to increase from US$ million in 2024 to US$ million by 2031, at a CAGR of % from 2025 through 2031.
Europe market for AI-based Raw Material Sourcing Optimization is estimated to increase from US$ million in 2024 to US$ million by 2031, at a CAGR of % from 2025 through 2031.
Global key AI-based Raw Material Sourcing Optimization players cover Amazon, IBM, FedEx, American Software, Inc., Kinaxis, etc. In terms of revenue, the global two largest companies occupied for a share nearly % in 2024.
LPI (LP Information)' newest research report, the “AI-based Raw Material Sourcing Optimization Industry Forecast” looks at past sales and reviews total world AI-based Raw Material Sourcing Optimization sales in 2024, providing a comprehensive analysis by region and market sector of projected AI-based Raw Material Sourcing Optimization sales for 2025 through 2031. With AI-based Raw Material Sourcing Optimization sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world AI-based Raw Material Sourcing Optimization industry.
This Insight Report provides a comprehensive analysis of the global AI-based Raw Material Sourcing Optimization landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyses the strategies of leading global companies with a focus on AI-based Raw Material Sourcing Optimization portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global AI-based Raw Material Sourcing Optimization market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for AI-based Raw Material Sourcing Optimization and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global AI-based Raw Material Sourcing Optimization.
This report presents a comprehensive overview, market shares, and growth opportunities of AI-based Raw Material Sourcing Optimization market by product type, application, key players and key regions and countries.
Segmentation by Type:
Demand Forecasting and Inventory Management
Supplier Selection and Evaluation
Logistics and Transportation Optimization
Resource Allocation and Quality Control
Automated Procurement Process
Others
Segmentation by Application:
Metals and Mining
Manufacturing
Agriculture
Food Processing
Textiles and Clothing
Pharmaceuticals
Other
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Amazon
IBM
FedEx
American Software, Inc.
Kinaxis
Blue Yonder
SAP
Intellinum
Alpha Augmented Services AG
ToolsGroup
RightChain Healthcare
QAD
Inspur Information
Neo Tangent
Please note: The report will take approximately 2 business days to prepare and deliver.
Table of Contents
110 Pages
- *This is a tentative TOC and the final deliverable is subject to change.*
- 1 Scope of the Report
- 2 Executive Summary
- 3 Semiconductor Yield Optimization Software Market Size by Player
- 4 Semiconductor Yield Optimization Software by Region
- 5 Americas
- 6 APAC
- 7 Europe
- 8 Middle East & Africa
- 9 Market Drivers, Challenges and Trends
- 10 Global Semiconductor Yield Optimization Software Market Forecast
- 11 Key Players Analysis
- 12 Research Findings and Conclusion
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