全球物流和供应链人工智慧市场规模（按产品、应用、最终用户、区域覆盖范围和预测）

物流及供应链人工智慧市场规模及预测

2024 年物流和供应链人工智慧市场规模价值 44.5064 亿美元，预计到 2032 年将达到 650.3934 亿美元，在 2026-2032 年预测期内的复合年增长率为 46.50%。

物流和供应链中的人工智慧是指将机器学习、预测分析和自动化等人工智慧技术应用于供应链各层级的商品、服务和资讯管理。人工智慧能够评估来自众多资讯来源的大量数据，并透过优化路线、管理库存和预测需求来改善决策。其应用包括用于运输的自动驾驶汽车和无人机、用于客户支援的人工智慧聊天机器人，以及用于提高生产力的自动化仓库业务。该技术能够提高准确性、降低成本并减少物流行业的人为错误。

随着电子商务、製造业和零售业等行业对更灵活、更敏捷的供应链的需求不断增长，人工智慧在物流和供应链管理中的应用正在迅速扩展。随着人工智慧的发展，其潜在的应用领域包括提升供应链可视性、即时追踪和预测性资产维护。

人工智慧能够透过资源优化降低风险和延误，并提高永续性，这将成为全球物流网路转型的关键。随着物联网、巨量资料和机器人技术在物流业务中的应用日益广泛，预计该产业对人工智慧解决方案的市场将迅速扩张。

全球物流与供应链人工智慧市场动态

影响全球物流和供应链人工智慧市场的关键市场动态是：

关键市场驱动因素

电子商务普及率提升：电子商务的快速成长推动了对更有效率物流和供应链管理的需求。预计2021年美国电子商务销售额将达8,708亿美元，较2020年成长14.2%。这种激增带来了许多复杂问题，例如管理大量订单、确保按时送达以及处理退货。人工智慧可以透过路线优化、仓库自动化和需求预测来帮助应对这些挑战，从而提高营运效率并提升客户满意度。

供应链可视性和透明度需求日益增长：应对供应链中断的需求推动了对供应链可视性和透明度的需求。根据业务连续性研究所 (BCI) 预测，2021 年 69% 的公司将至少经历一次供应链中断。企业和消费者都希望获得即时追踪，以确保更顺畅的营运、更快的问题解决和更可靠的交付。人工智慧 (AI) 提供了必要的预测技能和即时数据分析，以提高整个供应链的可视性、降低风险并增强韧性。

需要降低成本并提高业务效率：根据美国供应链管理协会 (CSCMP) 的数据，美国企业的物流支出预计将在 2020 年达到 1.63 兆美元，占 GDP 的 7.4%。企业越来越依赖人工智慧 (AI) 来优化流程、降低人事费用并简化业务。人工智慧透过自动化、预测分析和库存管理来提高效率，使企业能够在竞争激烈的市场中保持卓越服务水准的同时降低成本。

主要问题

高品质资料存取受限：人工智慧依赖高品质、组织良好的数据来做出准确的预测和决策。许多供应链处理的资料片段化或格式混乱，导致人工智慧效能低落。即时、纯净数据的存取受限，使得企业难以充分利用人工智慧的潜力，从而降低其优化业务的有效性。

监理与合规挑战：物流的人工智慧营运面临复杂的法规环境，且因地区和产业而异。遵守资料隐私、劳动法和环境要求等诸多规则并非易事。企业必须检验其人工智慧系统是否符合众多法规结构，这可能会阻碍其部署并增加营运成本。

资料隐私和安全问题：人工智慧系统依赖大量数据，因此隐私和安全是主要问题。随着企业在供应链中转移敏感讯息，资料外洩的风险也随之增加。更严格的数据标准和客户隐私期望要求企业保护其数据，这减缓了人工智慧的采用并增加了合规成本。

主要趋势

需求预测的预测分析：人工智慧驱动的预测分析正成为预测整个供应链需求的重要工具。透过分析历史数据和外部因素，人工智慧可以帮助企业更好地预测需求波动，从而减少缺货和库存过剩。这一趋势源于对更敏捷的供应链的需求，这些供应链能够即时回应变化，从而提高客户满意度并减少浪费。

利用人工智慧优化最后一公里配送：人工智慧正在透过优化路线、降低油耗和缩短配送时间，彻底改变最后一公里配送。电子商务的兴起以及消费者对快速、经济高效配送的期望，促使企业利用人工智慧来提升配送流程最后一环节的效率。这一趋势源自于企业日益增长的需求，即提高配送速度和准确性，同时降低物流成本。

人工智慧主导的风险管理和中断缓解：人工智慧正迅速被用于预测和缓解供应链中断、自然灾害和地缘政治事件等风险。透过分析多种资料来源，人工智慧可以预测未来的中断，并为不可预见的事件做好准备。这一趋势是由供应链日益复杂和国际化所驱动的，这需要主动的风险管理技术来确保平稳运作。

人工智慧与物联网 (IoT) 的融合：人工智慧与物联网 (IoT) 的融合正在透过打造更智慧、更互联的物流系统来改善供应链自动化。物联网感测器收集来自卡车、仓库和产品的即时数据，人工智慧分析这些资讯以优化营运。这一趋势源于人们对更聪明、更有效率的供应网路的渴望，这些网路能够自我监控并持续改进。

目录

第一章 全球人工智慧市场在物流和供应链的应用

• 市场概览
• 研究范围
• 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

• 资料探勘
• 验证
• 第一手资料
• 资料来源列表

第四章 全球物流与供应链人工智慧市场展望

• 概述
• 市场动态
  • 驱动程式
  • 限制因素
  • 机会
• 波特五力模型
• 价值链分析

第五章物流与供应链人工智慧的全球市场（按产品提供）

• 概述
• 硬体
• 软体

第六章 人工智慧在物流和供应链的应用全球市场

• 概述
• 供应链计划
• 仓库管理
• 需求预测
• 库存管理

7. 全球物流和供应链人工智慧市场（按最终用户）

• 概述
• 车
• 零售
• 饮食
• 卫生保健
• 製造业

第八章全球物流与供应链人工智慧市场（按地区）

• 概述
• 北美洲
  • 美国
  • 加拿大
  • 墨西哥
• 欧洲
  • 德国
  • 英国
  • 法国
  • 其他欧洲国家
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 其他的
  • 中东和非洲
  • 南美洲

9. 全球物流市场竞争格局

• 概述
• 各公司市场排名
• 重点发展策略

第十章 公司简介

• IBM Corporation
• Microsoft Corporation
• Google LLC
• Amazon.com, Inc.
• Intel Corporation
• Nvidia Corporation
• Oracle Corporation
• Samsung
• Lamasoft, Inc.

第十一章 附录

• 相关调查

AI In Logistics And Supply Chain Market Size And Forecast

AI In Logistics And Supply Chain Market size was valued at USD 4450.64 Million in 2024 and is projected to reach USD 65039.34 Million by 2032, growing at a CAGR of 46.50% from 2026 to 2032.

AI in logistics and supply chain is the application of artificial intelligence technologies such as machine learning, predictive analytics, and automation to the management of commodities, services, and information at various levels of the supply chain. AI improves decision-making by evaluating massive amounts of data from many sources, optimizing routes, controlling inventories, and forecasting demand. Applications include self-driving cars and drones for transportation, AI-powered chatbots for customer support, and automated warehousing operations for increased productivity. This technology enhances accuracy, lowers costs, and reduces human error in the logistics industry.

AI in logistics and supply chain management is rapidly expanding, driven by the growing demand for more flexible and responsive supply chains in industries such as e-commerce, manufacturing, and retailing. As AI advances, potential applications include improved supply chain visibility, real-time tracking, and predictive asset maintenance.

AI's ability to decrease risks, delays, and boost sustainability through resource optimization will be important in altering global logistics networks. The market for AI-powered solutions in this industry is predicted to expand rapidly, driven by the growing use of IoT, big data, and robotics in logistics operations.

Global AI In Logistics And Supply Chain Market Dynamics

The key market dynamics that are shaping the global AI In Logistics And Supply Chain Market include:

Key Market Drivers:

Increasing E-Commerce Adoption: The rapid growth in e-commerce, with US e-commerce sales expected to reach USD 870.8 Billion in 2021, up 14.2% from 2020, is pushing the demand for more efficient logistics and supply chain management. This spike presents complicated issues such as managing high-order quantities, ensuring timely deliveries, and handling returns. AI can assist address these difficulties by optimizing routes, automating warehouses, and forecasting demand, resulting in more efficient operations and more customer satisfaction.

Rising Demand for Supply Chain Visibility and Transparency: The rising need for supply chain visibility and transparency is driven by the need to manage disruptions, with the Business Continuity Institute projecting that 69% of firms would experience at least one supply chain disruption in 2021. Both organizations and consumers want real-time tracking to ensure smoother operations, faster problem resolution, and more consistent deliveries. AI provides the predictive skills and real-time data analytics required to improve visibility, decrease risks, and strengthen the overall supply chain resilience.

Need for Cost Reduction and Operational Efficiency: The need for cost reduction and operational efficiency is a fundamental driver in supply chain management, with U.S. company logistics expenditures expected to reach USD 1.63 Trillion in 2020, accounting for 7.4% of GDP, according to the CSCMP. Companies are increasingly depending on artificial intelligence (AI) to optimize processes, cut personnel costs, and streamline operations. AI increases efficiency through automation, predictive analytics, and inventory management, allowing firms to reduce costs while maintaining excellent service levels in a competitive market.

Key Challenges:

Limited Access to Quality Data: AI relies on high-quality, well-organized data to make accurate predictions and decisions. Many supply chains still work with fragmented or poorly formatted data, resulting in inadequate AI performance. Limited access to real-time, clean data makes it difficult for businesses to fully leverage AI's assurance, lowering its efficacy in optimizing operations.

Regulatory and Compliance Challenges: AI in logistics operates in a complicated regulatory environment that varies by region and industry. Adhering to many rules, such as those governing data privacy, labor legislation, and environmental requirements, can be difficult. Companies must verify that their AI systems adhere to numerous regulatory frameworks, which can hinder deployment and increase operational costs.

Data Privacy and Security Concerns: As AI systems rely on massive volumes of data, privacy and security are major concerns. As firms communicate sensitive information throughout the supply chain, the danger of data breaches grows. Stricter data standards and customer privacy expectations require enterprises to secure their data, which slows AI adoption and raises compliance costs.

Key Trends:

Predictive Analytics for Demand Forecasting: AI-powered predictive analytics is becoming an essential tool for anticipating demand throughout supply chains. AI assists businesses in better anticipating demand swings by studying past data and external factors, resulting in fewer stockouts and overstocking. This trend is motivated by the demand for more agile supply chains that can react to market developments in real-time, hence increasing customer satisfaction and lowering waste.

AI-Enhanced Last-Mile Delivery Optimization: AI is transforming last-mile delivery by optimizing routes, lowering fuel usage, and shortening delivery times. With the advent of e-commerce and consumer expectations for speedy, cost-effective shipping, businesses are turning to artificial intelligence to increase efficiency in the final leg of the delivery process. This trend is driven by the growing need to improve delivery speed and accuracy while lowering logistical costs.

AI-Driven Risk Management and Disruption Mitigation: AI is rapidly being utilized to predict and mitigate risks such as supply chain disruptions, natural disasters, and geopolitical incidents. AI may anticipate future interruptions and provide contingency preparations by analyzing multiple data sources. This trend is being driven by the increased complexity and internationalization of supply chains, which requires proactive risk management techniques to ensure smooth operations.

Integration of AI and Internet of Things (IoT): The integration of AI and the Internet of Things (IoT) is improving supply chain automation by enabling smarter and more connected logistics systems. IoT sensors collect real-time data from trucks, warehouses, and products, and AI analyzes this information to optimize operations. This trend is motivated by the desire for smarter, more efficient supply networks that can self-monitor and continuously improve.

Global AI In Logistics And Supply Chain Market Regional Analysis

Here is a more detailed regional analysis of the global AI In Logistics And Supply Chain Market:

North America:

North America is dominant in the AI In Logistics And Supply Chain Market. North America leads in AI adoption in logistics and supply chain management due to its advanced technological infrastructure, strong research and development (R&D) skills, and large number of early adopters. The region's well-established logistics sector, combined with a constant focus on efficiency and innovation, creates ideal conditions for AI solutions to thrive. According to the US Bureau of Labor Statistics, employment in logistics and supply chain management is expected to increase by 30% between 2020 and 2030, owing in part to the growing incorporation of AI technology.

Government support and industry partnerships are speeding up AI deployment in North America. AI-driven logistics optimization has already produced incredible results, with enterprises reporting a 15% cost savings and a 20% improvement in delivery times. The Canadian government's Strategic Innovation Fund, which has committed CAD 950 million (USD 700 Million) for AI research and development from 2023 to 2025, demonstrates the region's leadership in this field. These characteristics - significant investment, strong government support, and tangible advantages - are propelling AI adoption in North America's logistics and supply chain sectors, establishing the region as a global leader in efficiency and competitiveness.

Asia Pacific:

The Asia-Pacific area is seeing huge growth in AI adoption for logistics and supply chain applications, making it the world's fastest-growing market. This spike is being driven by strong economic growth, increasing e-commerce, and an urgent need to improve supply chain efficiency across complicated networks. According to the Asian Development Bank (ADB), the region's e-commerce sector is expected to reach $2.8 trillion by 2025, with a compound annual growth rate (CAGR) of 18.5%. This vast expansion in online retail is putting huge pressure on logistical networks, forcing businesses to use AI-powered solutions to handle the increasing complexity and transaction volumes. Countries with substantial logistics sectors, such as China and India, are leading the drive, with China reporting that 72% of its large logistics enterprises had already deployed AI by 2023, and the figure is predicted to exceed 85% by 2026.

The region's emphasis on cost reduction and operational efficiency accelerates AI adoption. AI-driven solutions are already demonstrating substantial benefits across the region, with Japanese enterprises reporting an 18% cost reduction and a 25% increase in inventory turnover by 2023. Investments in AI for logistics are also increasing, with Southeast Asia alone experiencing a 45% year-over-year rise in AI spending in 2023, which is expected to treble by 2026. These reasons - rapid e-commerce growth, pressure on supply chains, government initiatives, and demonstrable efficiency - are propelling Asia-Pacific AI adoption, establishing it as a global leader in innovative logistics solutions.

Global AI In Logistics And Supply Chain Market: Segmentation Analysis

The Global AI In Logistics And Supply Chain Market is Segmented on the basis of Offering, Application, End-User, And Geography.

AI In Logistics And Supply Chain Market, By Offering

• Hardware
• Software

Based on Offering, the market is bifurcated into Hardware, and Software. Software is the fastest-growing segment, driven by rising demand for AI-powered solutions like as predictive analytics, route optimization, and warehouse automation. As logistics organizations seek to improve efficiency and cut costs, AI-based software systems are fast gaining popularity. Hardware dominates market share since AI requires powerful computing infrastructure, sensors, and robotics to work well, notably in automated warehouses and transportation systems. Due to the dependency on physical infrastructure, hardware is an essential component of AI logistics integration.

AI In Logistics And Supply Chain Market, By Application

• Supply Chain Planning
• Warehouse Management
• Demand Forecasting
• Inventory Management

Based on Application, the market is segmented into Supply Chain Planning, Warehouse Management, Demand Forecasting, and Inventory Management. Warehouse management is the most dominating segment, as it includes a wide range of AI applications that improve operational efficiency, such as automated inventory tracking, robotic picking systems, and optimized storage solutions. The use of artificial intelligence in warehouse management is critical for optimizing operations and lowering costs, cementing its place as a vital market area. Demand forecasting is the fastest-growing segment, driven by the requirement for precise forecasts to satisfy consumer expectations and optimize inventory levels. Companies are increasingly using AI algorithms to analyze historical data and market trends, which improves their ability to predict demand fluctuations.

AI In Logistics And Supply Chain Market, By End-User

• Automotive
• Retail
• Food and Beverages
• Healthcare
• Manufacturing

Based on End-User, the market is segmented into Automotive, Retail, Food and Beverages, Healthcare, and Manufacturing. The automotive segment is currently dominating, thanks to the industry's emphasis on streamlining production processes, increasing supply chain efficiency, and integrating autonomous car technologies. The automotive industry relies extensively on artificial intelligence (AI) for inventory management, predictive maintenance, and logistical coordination, making it a critical market player. The retail segment is the fastest-growing, driven by e-commerce's spectacular development and the need for real-time inventory tracking, individualized customer experiences, and demand forecasting. Retailers are increasingly using AI-powered solutions to optimize operations, manage complex supply chains, and boost consumer happiness.

Key Players

The "Global AI In Logistics And Supply Chain Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are IBM Corporation, Microsoft Corporation, Google LLC, Amazon.com, Inc., Intel Corporation, Nvidia Corporation, Oracle Corporation, Samsung, and Lamasoft, Inc. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

• AI In Logistics And Supply Chain Market Recent Developments
• In March 2024, Oracle's new AI-powered supply chain execution capabilities, Oracle Smart Operations, will be available allowing businesses to boost factory output by increasing productivity, improving quality, minimizing downtime, and improving visibility across operations.
• In November 2023, IBM and Amazon expanded their relationship to assist businesses in implementing generative AI in their supply chains. They intend to provide a virtual assistant to help supply chain professionals optimize operations and cut expenses.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4. Value Chain Analysis

5 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY OFFERING

• 5.1 Overview
• 5.2 Hardware
• 5.3 Software

6 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY APPLICATION

• 6.1 Overview
• 6.2 Supply Chain Planning
• 6.3 Warehouse Management
• 6.4 Demand Forecasting
• 6.5 Inventory Management

7 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY END-USER

• 7.1 Overview
• 7.2 Automotive
• 7.3 Retail
• 7.4 Food and Beverages
• 7.5 Healthcare
• 7.6 Manufacturing

8 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET, BY GEOGRAPHY

• 8.1 Overview
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
  • 8.2.3 Mexico
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 U.K.
  • 8.3.3 France
  • 8.3.4 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Rest of Asia Pacific
• 8.5 Rest of the World
  • 8.5.1 Middle East and Africa
  • 8.5.2 South America

9 GLOBAL AI IN LOGISTICS AND SUPPLY CHAIN MARKET COMPETITIVE LANDSCAPE

• 9.1 Overview
• 9.2 Company Market Ranking
• 9.3 Key Development Strategies

10 COMPANY PROFILES

• 10.1 IBM Corporation
  • 10.1.1 Overview
  • 10.1.2 Financial Performance
  • 10.1.3 Product Outlook
  • 10.1.4 Key Developments
• 10.2 Microsoft Corporation
  • 10.2.1 Overview
  • 10.2.2 Financial Performance
  • 10.2.3 Product Outlook
  • 10.2.4 Key Developments
• 10.3 Google LLC
  • 10.3.1 Overview
  • 10.3.2 Financial Performance
  • 10.3.3 Product Outlook
  • 10.3.4 Key Developments
• 10.4 Amazon.com, Inc.
  • 10.4.1 Overview
  • 10.4.2 Financial Performance
  • 10.4.3 Product Outlook
  • 10.4.4 Key Developments
• 10.5 Intel Corporation
  • 10.5.1 Overview
  • 10.5.2 Financial Performance
  • 10.5.3 Product Outlook
  • 10.5.4 Key Developments
• 10.6 Nvidia Corporation
  • 10.6.1 Overview
  • 10.6.2 Financial Performance
  • 10.6.3 Product Outlook
  • 10.6.4 Key Developments
• 10.7 Oracle Corporation
  • 10.7.1 Overview
  • 10.7.2 Financial Performance
  • 10.7.3 Product Outlook
  • 10.7.4 Key Developments
• 10.8 Samsung
  • 10.8.1 Overview
  • 10.8.2 Financial Performance
  • 10.8.3 Product Outlook
  • 10.8.4 Key Developments
• 10.9 Lamasoft, Inc.
  • 10.9.1 Overview
  • 10.9.2 Financial Performance
  • 10.9.3 Product Outlook
  • 10.9.4 Key Developments

11 APPENDIX

• 11.1 Related Research