세계의 공급망용 AI 시장 규모, 점유율, 예측 및 동향 분석 : 공급망용 AI 시장 규모, 점유율, 예측 및 동향 분석 : 제공 제품별, 기술별, 배포 모드별, 용도별, 최종 사용 산업별, 지역별 예측(-2031년)

The research report titled 'Global AI in Supply Chain Market by Offering (Hardware, Software, Other), Technology (ML, NLP, RPA, Other), Deployment Mode, Application (Demand Forecasting, Other), End-use Industry (Manufacturing, Retail, F&B, Other) & Geography-Forecasts to 2031', provides in-depth analysis of AI in supply chain market across five major geographies and emphasizes on the current market trends, market sizes, market shares, recent developments, and forecasts till 2031.

The AI in supply chain market is projected to reach $58.55 billion by 2031, at a CAGR of 40.4% from 2024 to 2031. The growth of this market is driven by the increasing incorporation of artificial intelligence in supply chain operations and the rising need for greater visibility & transparency in supply chain processes. However, the high procurement and operating costs of AI-based supply chain solutions and the lack of supporting infrastructure restrain the growth of this market.

Furthermore, the growing demand for AI-based business automation solutions is expected to generate growth opportunities for the players operating in this market. However, performance issues in integrating data from multiple sources and data security & privacy concerns are major challenges impacting market growth. Additionally, the rising demand for cloud-based supply chain solutions is a prominent trend in the AI in supply chain market.

Based on offering, the global AI in supply chain market is segmented into hardware, software, and services. In 2024, the hardware segment is expected to account for the largest share of the global AI in supply chain market. The large market share of this segment is attributed to advancements in data center capabilities, the growing need for storage hardware due to increasing storage requirements for AI applications, the crucial need for constant connectivity in the supply chain operations, and the emphasis on product development and enhancement by manufacturers. For instance, in January 2023, Intel Corporation launched its 4th Gen Intel Xeon Scalable processors (code-named Sapphire Rapids), the Intel Xeon CPU Max Series (code-named Sapphire Rapids HBM), and the Intel Data Center GPU Max Series (code-named Ponte Vecchio). These new processors deliver significant improvements in data center performance, efficiency, security, and AI capabilities.

However, the software segment is expected to record the highest CAGR during the forecast period. The growth of this segment is driven by the rising focus on product development and the enhancement of supply chain software, and the benefits offered by supply chain software in facilitating supply chain visibility and centralized operations.

Based on technology, the global AI in supply chain market is segmented into machine learning, computer vision, natural language processing, context-aware computing, and robotic process automation. In 2024, the machine learning segment is expected to account for the largest share of the global AI in supply chain market. The large market share of this segment is attributed to the advancements in data center capabilities, increasing deployment of machine learning solutions and its ability to perform tasks without relying on human input, and the rapid adoption of cloud-based technology across several industries. For instance, in June 2022, FedEx Corporation (U.S.) invested in FourKites, Inc. (U.S.), a supply chain visibility startup. This strategic collaboration allows FedEx to leverage its machine learning and AI capabilities with data from FedEx, enhancing its operational efficiency and visibility.

However, the robotic process automation segment is expected to record the highest CAGR during the forecast period. This segment's growth is driven by the increased adoption of RPA across various industries and the rising demand for automating business processes to meet heightened customer expectations.

Based on deployment mode, the global AI in supply chain market is segmented into cloud-based deployments and on-premise deployments. In 2024, the cloud-based deployments segment is expected to account for the larger share of the global AI in supply chain market. The large market share of this segment is attributed to the increasing avenues for cloud-based deployments, the superior flexibility and affordability offered by cloud-based deployments, and the increasing adoption of cloud-based solutions by small & medium-sized enterprises.

Moreover, the cloud-based deployments segment is expected to record the highest CAGR during the forecast period. The rapid development of new security measures for cloud-based deployments is expected to drive this segment's growth in the coming years.

Based on application, the global AI in supply chain market is segmented into demand forecasting, supply chain planning, warehouse management, fleet management, risk management, inventory management, predictive maintenance, real-time supply chain visibility, and other applications. In 2024, the demand forecasting segment is expected to account for the largest share of the global AI in supply chain market. The large market share of this segment is attributed to the rising initiatives to integrate AI capabilities in supply chain solutions, dynamic changes in customer behaviors and expectations, and the rising need to achieve accuracy and resilience in the supply chain. For instance, in March 2023, Zionex, Inc. (South Korea), a prominent provider of advanced supply chain and integrated business planning platforms, launched PlanNEL Beta. This AI-powered SaaS platform is designed for demand forecasting and inventory optimization.

However, the real-time supply chain visibility segment is expected to record the highest CAGR during the forecast period. This segment's growth is driven by the rising integration of AI capabilities into supply chains to obtain real-time data on them.

Based on end-use industry, the global AI in supply chain market is segmented into manufacturing, food and beverage, healthcare & pharmaceuticals, automotive, retail, building & construction, medical devices & consumables, aerospace & defense, and other end-use industries. In 2024, the manufacturing segment is expected to account for the largest share of the global AI in supply chain market. The large market share of this segment is attributed to the increasing number of manufacturing companies, favorable initiatives to integrate artificial capabilities in the supply chain, and the increasing focus on achieving accuracy and resilience in the supply chain among manufacturers.

However, the retail segment is expected to record the highest CAGR during the forecast period. This segment's growth is driven by the rising integration of AI capabilities in the retail supply chain to forecast inventory and demand and retailers' growing focus on meeting consumer expectations.

Based on geography, the AI in supply chain market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. In 2024, Asia-Pacific is expected to account for the largest share of the global AI in supply chain market. The large market share of this region is attributed to the rapid pace of digitalization and modernization across industries, the advent of Industry 4.0, and the growing adoption of advanced technologies across various businesses.

Moreover, the Asia-Pacific region is projected to record the highest CAGR during the forecast period. The growth of this market is driven by the proliferation of advanced supply chain solutions, the rising deployment of AI tools across the region, and efforts by major market players to implement AI technology across various sectors.

Key Players:

Some of the key players operating in the AI in supply chain market are IBM Corporation (U.S.), SAP SE (Germany), Microsoft Corporation (U.S.), Google LLC (U.S.), Amazon Web Services, Inc. (U.S.), Intel Corporation (U.S.), NVIDIA Corporation (U.S.), Oracle Corporation (U.S.), C3.ai, Inc. (U.S.), Samsung SDS CO., Ltd. (South Korea), Coupa Software Inc. (U.S.), Micron Technology, Inc. (U.S.), Advanced Micro Devices, Inc. (U.S.), FedEx Corporation (U.S.), and Deutsche Post DHL Group (Germany).

Key questions answered in the report-

• Which are the high-growth market segments based on offering, technology, deployment mode, application, and end-use industry?
• What was the historical market for AI in supply chain?
• What are the market forecasts and estimates for the period 2024-2031?
• What are the major drivers, restraints, and opportunities in AI in supply chain market?
• Who are the major players in the AI in supply chain market?
• What is the competitive landscape like in the AI in supply chain market?
• What are the recent developments in AI in supply chain market?
• What are the different strategies adopted by the major players in AI in supply chain market?
• What are the key geographic trends, and which are the high-growth countries?
• Who are the local emerging players in the global AI in supply chain market, and how do they compete with the other players?

Scope of the report:

AI in Supply Chain Market Assessment, by Offering

• Hardware
  • Processors
  • Networking
  • Storage
• Software
• Services
  • Deployment & Integration Services
  • Support & Maintenance Services
  • Consulting Services
  • Connectivity Services

AI in Supply Chain Market Assessment, by Technology

• Machine Learning
• Computer Vision
• Natural Language Processing
• Context-aware Computing
• Robotic Process Automation

AI in Supply Chain Market Assessment, by Deployment Mode

• Cloud-based Deployments
• On-premise Deployments

AI in Supply Chain Market Assessment, by Application

• Demand Forecasting
• Supply Chain Planning
• Warehouse Management
• Fleet Management
• Inventory Management
• Real-time Supply Chain Visibility
• Other Applications

AI in Supply Chain Market Assessment, by End-Use Industry

• Manufacturing
• Food and Beverage
• Healthcare & Pharmaceuticals
• Automotive
• Retail
• Building & Construction
• Medical Devices & Consumables
• Aerospace & Defense
• Other End-use Industries

AI in Supply Chain Market Assessment, by Geography

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • U.K.
  • France
  • Italy
  • Spain
  • Sweden
  • Rest of Europe
• Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Rest of Asia-Pacific
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• Middle East & Africa
  • UAE
  • Israel
  • Rest of the Middle East & Africa

TABLE OF CONTENTS

1. Introduction

• 1.1. Market Definition & Scope
• 1.2. Currency & Limitations
  • 1.2.1. Currency
  • 1.2.2. Limitations

2. Research Methodology

• 2.1. Research Approach
• 2.2. Process of Data Collection and Validation
  • 2.2.1. Secondary Research
  • 2.2.2. Primary Research/Interviews with Key Opinion Leaders of the Industry
• 2.3. Market Sizing and Forecast
  • 2.3.1. Market Size Estimation Approach
  • 2.3.2. Growth Forecast
• 2.4. Assumptions for the Study

3. Executive Summary

• 3.1. Overview
• 3.2. Market Analysis, by Offering
• 3.3. Market Analysis, by Technology
• 3.4. Market Analysis, by Deployment Mode
• 3.5. Market Analysis, by Application
• 3.6. Market Analysis, by End-use Industry
• 3.7. Market Analysis, by Geography
• 3.8. Competition Analysis

4. Market Insights

• 4.1. Overview
• 4.2. Factors Affecting Market Growth
  • 4.2.1. Increasing Incorporation of AI in Supply Chain Operations Driving Market Growth
  • 4.2.2. Rising Need for Greater Visibility & Transparency in Supply Chain Processes Driving the Demand for AI-based Solutions
  • 4.2.3. High Procurement & Operating Costs Limiting the Adoption of AI-based Supply Chain Solutions
  • 4.2.4. Lack of Supporting Infrastructure Restricting the Implementation of AI-based Supply Chain Solutions
  • 4.2.5. Growing Demand for AI-Based Business Automation Solutions Generating Growth Opportunities for Market Players
  • 4.2.6. Data Security & Privacy Concerns Impacting the Acceptance of AI-based Supply Chain Solutions
  • 4.2.7. Performance Issues in Integrating Data From Multiple Sources Leading To Inaccurate Business Insights
• 4.3. Trends
  • 4.3.1. Rising Demand for Cloud-Based Supply Chain Solutions
• 4.4. Case Studies
  • 4.4.1. Case Study A
  • 4.4.2. Case Study B
  • 4.4.3. Case Study C

5. AI in Supply Chain Market Assessment-by Offering

• 5.1. Overview
• 5.2. Hardware
  • 5.2.1. Processors
  • 5.2.2. Storage
  • 5.2.3. Networking
• 5.3. Software
• 5.4. Services
  • 5.4.1. Deployment & Integration Services
  • 5.4.2. Connectivity Services
  • 5.4.3. Support & Maintenance Services
  • 5.4.4. Consulting Services

6. AI in Supply Chain Market Assessment-by Technology

• 6.1. Overview
• 6.2. Machine Learning
• 6.3. Natural Language Processing
• 6.4. Computer Vision
• 6.5. Robotic Process Automation
• 6.6. Context-aware Computing

7. AI in Supply Chain Market Assessment-by Deployment Mode

• 7.1. Overview
• 7.2. Cloud-based Deployments
• 7.3. On-premise Deployments

8. AI in Supply Chain Market Assessment-by Application

• 8.1. Overview
• 8.2. Demand Forecasting
• 8.3. Real-time Supply Chain Visibility
• 8.4. Supply Chain Planning
• 8.5. Inventory Management
• 8.6. Fleet Management
• 8.7. Warehouse Management
• 8.8. Other Applications

9. AI in Supply Chain Market Assessment-by End-use Industry

• 9.1. Overview
• 9.2. Manufacturing
• 9.3. Retail
• 9.4. Food and Beverage
• 9.5. Automotive
• 9.6. Healthcare & Pharmaceuticals
• 9.7. Medical Devices & Consumables
• 9.8. Aerospace & Defense
• 9.9. Building & Construction
• 9.10. Other End-use Industries

10. AI in Supply Chain Market Assessment-by Geography

• 10.1. Overview
• 10.2. Asia-Pacific
  • 10.2.1. China
  • 10.2.2. Japan
  • 10.2.3. India
  • 10.2.4. South Korea
  • 10.2.5. Singapore
  • 10.2.6. Rest of Asia-Pacific
• 10.3. North America
  • 10.3.1. U.S.
  • 10.3.2. Canada
• 10.4. Europe
  • 10.4.1. U.K.
  • 10.4.2. Italy
  • 10.4.3. Germany
  • 10.4.4. Sweden
  • 10.4.5. Spain
  • 10.4.6. France
  • 10.4.7. Rest of Europe
• 10.5. Latin America
  • 10.5.1. Mexico
  • 10.5.2. Brazil
  • 10.5.3. Rest of Latin America
• 10.6. Middle East & Africa
  • 10.6.1. Israel
  • 10.6.2. UAE
  • 10.6.3. Rest of Middle East & Africa

11. Competition Analysis

• 11.1. Overview
• 11.2. Key Growth Strategies
• 11.3. Competitive Benchmarking
• 11.4. Competitive Dashboard
  • 11.4.1. Industry Leaders
  • 11.4.2. Market Differentiators
  • 11.4.3. Vanguards
  • 11.4.4. Emerging Companies
• 11.5. Market Ranking by the Key Players

12. Company Profiles

• 12.1. IBM Corporation
• 12.2. SAP SE
• 12.3. Microsoft Corporation
• 12.4. Google LLC (a subsidiary of Alphabet, Inc.)
• 12.5. Amazon Web Services, Inc. (a subsidiary of Amazon.com, Inc.)
• 12.6. NVIDIA Corporation
• 12.7. Oracle Corporation
• 12.8. C3.ai, Inc.
• 12.9. Intel Corporation
• 12.10. Samsung SDS CO., Ltd.
• 12.11. Coupa Software Inc.
• 12.12. Micron Technology, Inc.
• 12.13. Advanced Micro Devices, Inc.
• 12.14. FedEx Corporation
• 12.15. Deutsche Post DHL Group

(Note: SWOT analysis of the top 5 companies will be provided.)

13. Appendix

• 13.1. Available Customization
• 13.2. Related Reports