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1529412

全球供應鏈和物流人工智慧市場規模研究（按類型、應用和 2022-2032 年區域預測）

Global Artificial Intelligence in Supply Chain and Logistics Market Size study, by Type, by Application, and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 285 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2023年全球供應鏈和物流市場人工智慧（AI）價值約為17.13億美元，預計在2024-2032年預測期內將以超過10.1%的健康成長率成長。供應鏈和物流中的人工智慧（AI）包括使用人工智慧技術和技術來提高供應鏈營運的效率、有效性和永續性。透過利用人工智慧，供應鏈和物流專業人員可以應對複雜的挑戰、自動化任務、最佳化決策並最終創造價值。人工智慧的應用涵蓋供應鏈和物流的各個方面，包括需求預測、庫存管理、生產計劃、運輸路線、倉庫管理、訂單履行、客戶服務和風險管理。

巨量資料量的快速成長，加上對供應鏈營運的可見度和透明度的需求，是推動市場成長的關鍵驅動力。人工智慧的採用因其提升消費者服務和滿意度水準的能力而進一步加強。儘管如此，阻礙市場進步的一個顯著挑戰是人工智慧技術專業知識的缺乏。對透明和可觀察的供應鏈方法的需求極大地推動了市場。人工智慧在物流領域的整合，特別是在倉庫庫存管理、庫存管理、產品安全和及時交付等領域的自主資料處理，凸顯了其在現代供應鏈中的重要角色。此外，促進機器自動化和人工智慧運算的政府法規和措施進一步促進了市場成長。然而，發展中國家採用有效的供應鏈資訊解決方案受到多種限制，促使政府投資以提高意識並將先進技術融入業務營運。

供應鏈營運中的人工智慧技術消除了人力的需要，從而節省了大量的時間和成本。這種營運優勢是關鍵的市場驅動力，大公司擴大投資於機器自動化，以降低未來的營運成本。各個終端用戶產業正在供應鏈市場中利用人工智慧應用，為該產業的成長做出貢獻。物聯網設備和雲端運算服務的日益普及徹底改變了資料處理，巨量資料技術已經在物流業盛行。透過人工智慧實現供應鏈自動化的趨勢顯示對自動化解決方案的持續需求。

北美在供應鏈市場的人工智慧領域佔據主導地位，這歸因於已開發經濟體專注於增強現有供應鏈解決方案和關鍵產業參與者的存在。由於汽車、零售和製造業採用深度學習和自然語言處理 (NLP) 技術，以及人工智慧主要參與者的存在，預計亞太地區在預測期內將經歷最高的複合年成長率生態系統。

目錄

第 1 章：供應鏈和物流市場中的全球人工智慧執行摘要

  • 全球供應鏈及物流人工智慧市場規模及預測（2022-2032）
  • 區域概要
  • 分部摘要
    • 按類型
    • 按申請
  • 主要趨勢
  • 經濟衰退的影響
  • 分析師推薦與結論

第 2 章：全球供應鏈和物流中的人工智慧市場定義和研究假設

  • 研究目的
  • 市場定義
  • 研究假設
    • 包容與排除
    • 限制
    • 供給側分析
      • 可用性
      • 基礎設施
      • 監管環境
      • 市場競爭
      • 經濟可行性（消費者的角度）
    • 需求面分析
      • 監理框架
      • 技術進步
      • 環境考慮
      • 消費者意識和接受度
  • 估算方法
  • 研究涵蓋的年份
  • 貨幣兌換率

第 3 章：供應鏈與物流市場動態中的全球人工智慧

  • 市場促進因素
    • 巨量資料量不斷增加
    • 需要更高的可見性和透明度
    • 人工智慧的採用率不斷上升
  • 市場挑戰
    • 人工智慧專家稀缺
    • 供應鏈的複雜性
  • 市場機會
    • 政府措施和法規
    • 物聯網和雲端運算的進步

第 4 章：全球供應鏈與物流市場人工智慧產業分析

  • 波特的五力模型
    • 供應商的議價能力
    • 買家的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭競爭
    • 波特五力模型的未來方法
    • 波特的五力影響分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社會的
    • 技術性
    • 環境的
    • 合法的
  • 頂級投資機會
  • 最佳制勝策略
  • 顛覆性趨勢
  • 產業專家視角
  • 分析師推薦與結論

第 5 章：供應鏈與物流市場中的全球人工智慧市場規模與預測：按類型 - 2022-2032

  • 細分儀表板
  • 全球供應鏈和物流市場人工智慧：類型收入趨勢分析，2022 年和 2032 年
    • 人工神經網路
    • 機器學習
    • 其他

第 6 章：供應鏈與物流市場中的全球人工智慧市場規模與預測：按應用分類 - 2022-2032

  • 細分儀表板
  • 全球供應鏈和物流市場人工智慧：2022年和2032年應用收入趨勢分析
    • 庫存控制和計劃
    • 交通網設計
    • 採購和供應管理
    • 需求規劃與預測
    • 其他

第 7 章：全球供應鏈與物流中的人工智慧市場規模與預測：按地區 - 2022-2032

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 西班牙
    • 義大利
    • 歐洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 亞太地區其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 南非
    • 中東和非洲其他地區

第 8 章：競爭情報

  • 重點企業SWOT分析
  • 頂級市場策略
  • 公司簡介
    • IBM Corporation
      • 關鍵訊息
      • 概述
      • 財務（視數據可用性而定）
      • 產品概要
      • 市場策略
    • 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

第 9 章：研究過程

  • 研究過程
    • 資料探勘
    • 分析
    • 市場預測
    • 驗證
    • 出版
  • 研究屬性
簡介目錄

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
  • 7.2. 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

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