PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1529412
PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1529412
Global Artificial Intelligence in Supply Chain and Logistics Market Size study, by Type, by Application, and Regional Forecasts 2022-2032
The global Artificial Intelligence (AI) in Supply Chain and Logistics Market is valued at approximately USD 1713 million in 2023 and is anticipated to grow with a healthy growth rate of more than 10.1% over the forecast period 2024-2032. Artificial intelligence (AI) in supply chain and logistics encompasses the use of AI techniques and technologies to enhance the efficiency, effectiveness, and sustainability of supply chain operations. By leveraging AI, supply chain and logistics professionals can address complex challenges, automate tasks, optimize decision-making, and ultimately create value. AI's application spans various facets of supply chain and logistics, including demand forecasting, inventory management, production planning, transportation routing, warehouse management, order fulfilment, customer service, and risk management.
The burgeoning volume of big data, coupled with the need for greater visibility and transparency in supply chain operations, are key drivers propelling market growth. The adoption of AI is further enhanced by its ability to elevate consumer services and satisfaction levels. Nonetheless, a notable challenge impeding market progress is the scarcity of expertise in AI technology. The demand for transparent and observable supply chain methodologies significantly drives the market. AI's integration within the logistics sector, particularly for autonomous data processing in areas like warehouse stock management, inventory management, product safety, and timely delivery, underscores its essential role in modern supply chains. Additionally, government regulations and initiatives promoting machine automation and AI computing further bolster market growth. However, the adoption of effective supply chain information solutions in developing countries is limited by several constraints, prompting government investments to raise awareness and integrate advanced technologies into business operations.
AI technologies in supply chain operations eliminate the need for human effort, resulting in substantial time and cost savings. This operational advantage is a crucial market driver, with large companies increasingly investing in machine automation to reduce future operating costs. Various end-user industries are leveraging AI applications in the supply chain market, contributing to the sector's growth. The increasing adoption of IoT devices and cloud computing services revolutionizes data processing, with big data technology already prevalent in the logistics industry. The trend towards supply chain automation through AI suggests continued demand for automated solutions.
North America dominates the AI in supply chain market, attributed to the presence of developed economies focused on enhancing existing supply chain solutions and key industry players. The Asia Pacific region is projected to experience the highest CAGR during the forecast period, driven by the adoption of deep learning and Natural Language Processing (NLP) technologies in automotive, retail, and manufacturing industries, along with the presence of major players in the AI ecosystem.
Major market players included in this report are:
- IBM Corporation
- Microsoft Corporation
- Google LLC
- Amazon Web Services (AWS)
- Oracle Corporation
- SAP SE
- Nvidia Corporation
- Intel Corporation
- Cisco Systems, Inc.
- Siemens AG
- General Electric Company
- Accenture plc
- Splice Machine
- PricewaterhouseCoopers (PwC)
- Xilinx
The detailed segments and sub-segment of the market are explained below:
By Type:
- Artificial Neural Networks
- Machine Learning
- Others
By Application:
- Inventory Control and Planning
- Transportation Network Design
- Purchasing and Supply Management
- Demand Planning and Forecasting
- Others
By Region:
- North America
- U.S.
- Canada
- Europe
- UK
- Germany
- France
- Spain
- Italy
- ROE
- Asia Pacific
- China
- India
- Japan
- Australia
- South Korea
- RoAPAC
- Latin America
- Brazil
- Mexico
- RoLA
- Middle East & Africa
- Saudi Arabia
- South Africa
- RoMEA
Years considered for the study are as follows:
- Historical year - 2022
- Base year - 2023
- Forecast period - 2024 to 2032
Key Takeaways:
- Market Estimates & Forecast for 10 years from 2022 to 2032.
- Annualized revenues and regional level analysis for each market segment.
- Detailed analysis of geographical landscape with Country level analysis of major regions.
- Competitive landscape with information on major players in the market.
- Analysis of key business strategies and recommendations on future market approach.
- Analysis of competitive structure of the market.
- Demand side and supply side analysis of the market.
Table of Contents
Chapter 1. Global AI in Supply Chain and Logistics Market Executive Summary
- 1.1. Global AI in Supply Chain and Logistics Market Size & Forecast (2022-2032)
- 1.2. Regional Summary
- 1.3. Segmental Summary
- 1.3.1. By Type
- 1.3.2. By Application
- 1.4. Key Trends
- 1.5. Recession Impact
- 1.6. Analyst Recommendation & Conclusion
Chapter 2. Global AI in Supply Chain and Logistics Market Definition and Research Assumptions
- 2.1. Research Objective
- 2.2. Market Definition
- 2.3. Research Assumptions
- 2.3.1. Inclusion & Exclusion
- 2.3.2. Limitations
- 2.3.3. Supply Side Analysis
- 2.3.3.1. Availability
- 2.3.3.2. Infrastructure
- 2.3.3.3. Regulatory Environment
- 2.3.3.4. Market Competition
- 2.3.3.5. Economic Viability (Consumer's Perspective)
- 2.3.4. Demand Side Analysis
- 2.3.4.1. Regulatory frameworks
- 2.3.4.2. Technological Advancements
- 2.3.4.3. Environmental Considerations
- 2.3.4.4. Consumer Awareness & Acceptance
- 2.4. Estimation Methodology
- 2.5. Years Considered for the Study
- 2.6. Currency Conversion Rates
Chapter 3. Global AI in Supply Chain and Logistics Market Dynamics
- 3.1. Market Drivers
- 3.1.1. Increasing Volume of Big Data
- 3.1.2. Need for Greater Visibility and Transparency
- 3.1.3. Rising Adoption of AI
- 3.2. Market Challenges
- 3.2.1. Scarcity of AI Experts
- 3.2.2. Complexity in Supply Chain
- 3.3. Market Opportunities
- 3.3.1. Government Initiatives and Regulations
- 3.3.2. Advancements in IoT and Cloud Computing
Chapter 4. Global AI in Supply Chain and Logistics Market Industry Analysis
- 4.1. Porter's 5 Force Model
- 4.1.1. Bargaining Power of Suppliers
- 4.1.2. Bargaining Power of Buyers
- 4.1.3. Threat of New Entrants
- 4.1.4. Threat of Substitutes
- 4.1.5. Competitive Rivalry
- 4.1.6. Futuristic Approach to Porter's 5 Force Model
- 4.1.7. Porter's 5 Force Impact Analysis
- 4.2. PESTEL Analysis
- 4.2.1. Political
- 4.2.2. Economical
- 4.2.3. Social
- 4.2.4. Technological
- 4.2.5. Environmental
- 4.2.6. Legal
- 4.3. Top Investment Opportunity
- 4.4. Top Winning Strategies
- 4.5. Disruptive Trends
- 4.6. Industry Expert Perspective
- 4.7. Analyst Recommendation & Conclusion
Chapter 5. Global AI in Supply Chain and Logistics Market Size & Forecasts by Type 2022-2032
- 5.1. Segment Dashboard
- 5.2. Global AI in Supply Chain and Logistics Market: Type Revenue Trend Analysis, 2022 & 2032 (USD Million)
- 5.2.1. Artificial Neural Networks
- 5.2.2. Machine Learning
- 5.2.3. Others
Chapter 6. Global AI in Supply Chain and Logistics Market Size & Forecasts by Application 2022-2032
- 6.1. Segment Dashboard
- 6.2. Global AI in Supply Chain and Logistics Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Million)
- 6.2.1. Inventory Control and Planning
- 6.2.2. Transportation Network Design
- 6.2.3. Purchasing and Supply Management
- 6.2.4. Demand Planning and Forecasting
- 6.2.5. Others
Chapter 7. Global AI in Supply Chain and Logistics Market Size & Forecasts by Region 2022-2032
- 7.1. North America AI in Supply Chain and Logistics Market
- 7.1.1. U.S. AI in Supply Chain and Logistics Market
- 7.1.1.1. Type breakdown size & forecasts, 2022-2032
- 7.1.1.2. Application breakdown size & forecasts, 2022-2032
- 7.1.2. Canada AI in Supply Chain and Logistics Market
- 7.1.1. U.S. AI in Supply Chain and Logistics Market
- 7.2. Europe AI in Supply Chain and Logistics Market
- 7.2.1. U.K. AI in Supply Chain and Logistics Market
- 7.2.2. Germany AI in Supply Chain and Logistics Market
- 7.2.3. France AI in Supply Chain and Logistics Market
- 7.2.4. Spain AI in Supply Chain and Logistics Market
- 7.2.5. Italy AI in Supply Chain and Logistics Market
- 7.2.6. Rest of Europe AI in Supply Chain and Logistics Market
- 7.3. Asia-Pacific AI in Supply Chain and Logistics Market
- 7.3.1. China AI in Supply Chain and Logistics Market
- 7.3.2. India AI in Supply Chain and Logistics Market
- 7.3.3. Japan AI in Supply Chain and Logistics Market
- 7.3.4. Australia AI in Supply Chain and Logistics Market
- 7.3.5. South Korea AI in Supply Chain and Logistics Market
- 7.3.6. Rest of Asia Pacific AI in Supply Chain and Logistics Market
- 7.4. Latin America AI in Supply Chain and Logistics Market
- 7.4.1. Brazil AI in Supply Chain and Logistics Market
- 7.4.2. Mexico AI in Supply Chain and Logistics Market
- 7.4.3. Rest of Latin America AI in Supply Chain and Logistics Market
- 7.5. Middle East & Africa AI in Supply Chain and Logistics Market
- 7.5.1. Saudi Arabia AI in Supply Chain and Logistics Market
- 7.5.2. South Africa AI in Supply Chain and Logistics Market
- 7.5.3. Rest of Middle East & Africa AI in Supply Chain and Logistics Market
Chapter 8. Competitive Intelligence
- 8.1. Key Company SWOT Analysis
- 8.2. Top Market Strategies
- 8.3. Company Profiles
- 8.3.1. IBM Corporation
- 8.3.1.1. Key Information
- 8.3.1.2. Overview
- 8.3.1.3. Financial (Subject to Data Availability)
- 8.3.1.4. Product Summary
- 8.3.1.5. Market Strategies
- 8.3.2. Microsoft Corporation
- 8.3.3. Google LLC
- 8.3.4. Amazon Web Services (AWS)
- 8.3.5. Oracle Corporation
- 8.3.6. SAP SE
- 8.3.7. Nvidia Corporation
- 8.3.8. Intel Corporation
- 8.3.9. Cisco Systems, Inc.
- 8.3.10. Siemens AG
- 8.3.11. General Electric Company
- 8.3.12. Accenture plc
- 8.3.13. Splice Machine
- 8.3.14. PricewaterhouseCoopers (PwC)
- 8.3.15. Xilinx
- 8.3.1. IBM Corporation
Chapter 9. Research Process
- 9.1. Research Process
- 9.1.1. Data Mining
- 9.1.2. Analysis
- 9.1.3. Market Estimation
- 9.1.4. Validation
- 9.1.5. Publishing
- 9.2. Research Attributes
