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市场调查报告书
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1529412

全球供应链和物流人工智慧市场规模研究（按类型、应用和 2022-2032 年区域预测）

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个工作天内

价格
简介目录

2023年全球供应链和物流市场人工智慧（AI）价值约为17.13亿美元，预计在2024-2032年预测期内将以超过10.1%的健康成长率成长。供应链和物流中的人工智慧（AI）包括使用人工智慧技术和技术来提高供应链营运的效率、有效性和永续性。透过利用人工智慧，供应链和物流专业人员可以应对复杂的挑战、自动化任务、优化决策并最终创造价值。人工智慧的应用涵盖供应链和物流的各个方面，包括需求预测、库存管理、生产计划、运输路线、仓库管理、订单履行、客户服务和风险管理。

巨量资料量的快速成长，加上对供应链营运的可见度和透明度的需求，是推动市场成长的关键驱动力。人工智慧的采用因其提升消费者服务和满意度水准的能力而进一步加强。儘管如此，阻碍市场进步的一个显着挑战是人工智慧技术专业知识的缺乏。对透明和可观察的供应链方法的需求极大地推动了市场。人工智慧在物流领域的整合，特别是在仓库库存管理、库存管理、产品安全和及时交付等领域的自主资料处理，凸显了其在现代供应链中的重要角色。此外，促进机器自动化和人工智慧运算的政府法规和措施进一步促进了市场成长。然而，发展中国家采用有效的供应链资讯解决方案受到多种限制，促使政府投资以提高意识并将先进技术融入业务营运。

供应链营运中的人工智慧技术消除了人力的需要，从而节省了大量的时间和成本。这种营运优势是关键的市场驱动力，大公司越来越多地投资于机器自动化，以降低未来的营运成本。各个终端用户产业正在供应链市场中利用人工智慧应用，为该产业的成长做出贡献。物联网设备和云端运算服务的日益普及彻底改变了资料处理，巨量资料技术已经在物流业盛行。透过人工智慧实现供应链自动化的趋势显示对自动化解决方案的持续需求。

北美在供应链市场的人工智慧领域占据主导地位，这归因于已开发经济体专注于增强现有供应链解决方案和关键产业参与者的存在。由于汽车、零售和製造业采用深度学习和自然语言处理 (NLP) 技术，以及人工智慧主要参与者的存在，预计亚太地区在预测期内将经历最高的复合年增长率生态系统。

目录

第 1 章：供应链和物流市场中的全球人工智慧执行摘要

  • 全球供应链及物流人工智慧市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 按类型
    • 按申请
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球供应链和物流中的人工智慧市场定义和研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包容与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：供应链与物流市场动态中的全球人工智慧

  • 市场驱动因素
    • 大数据量不断增加
    • 需要更高的可见性和透明度
    • 人工智慧的采用率不断上升
  • 市场挑战
    • 人工智慧专家稀缺
    • 供应链的复杂性
  • 市场机会
    • 政府措施和法规
    • 物联网和云端运算的进步

第 4 章：全球供应链与物流市场人工智慧产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的五力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：供应链与物流市场中的全球人工智慧市场规模与预测：按类型 - 2022-2032

  • 细分仪表板
  • 全球供应链和物流市场人工智慧：类型收入趋势分析，2022 年和 2032 年
    • 人工神经网络
    • 机器学习
    • 其他的

第 6 章：供应链与物流市场中的全球人工智慧市场规模与预测：按应用分类 - 2022-2032

  • 细分仪表板
  • 全球供应链和物流市场人工智慧：2022年和2032年应用收入趋势分析
    • 库存控制和计划
    • 交通网设计
    • 采购和供应管理
    • 需求规划与预测
    • 其他的

第 7 章：全球供应链与物流中的人工智慧市场规模与预测：按地区 - 2022-2032

  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 西班牙
    • 义大利
    • 欧洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 中东和非洲其他地区

第 8 章：竞争情报

  • 重点企业SWOT分析
  • 顶级市场策略
  • 公司简介
    • IBM Corporation
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • 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：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

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