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市場調查報告書
商品編碼
1981206

2026年全球物流生成式人工智慧（AI）市場報告

Generative Artificial Intelligence (AI) in Logistics Global Market Report 2026
出版日期: | 出版商: The Business Research Company | 英文 250 Pages | 商品交期: 2-10個工作天內

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簡介目錄

近年來，物流領域生成式人工智慧（AI）的市場規模呈現爆炸性成長。預計該市場規模將從2025年的8億美元成長到2026年的10.6億美元，複合年成長率（CAGR）高達32.6%。過去幾年的成長主要歸功於電子商務和物流需求的擴張、倉儲管理系統的普及、預測分析在運輸領域的早期應用、車輛管理投資的增加以及供應鏈自動化的擴展。

預計未來幾年，生成式人工智慧在物流市場的規模將大幅成長。到2030年，該市場規模預計將達到32.5億美元，複合年成長率（CAGR）為32.3%。預測期內的成長預計將受到以下因素的驅動：生成式人工智慧在即時物流決策中的應用、利用人工智慧進行車輛預測性維護的擴展、先進路線模擬工具的採用、混合和邊緣人工智慧模型的日益普及，以及人工智慧驅動的物流客戶服務營運的擴展。預測期間的關鍵趨勢包括：人工智慧驅動的路線最佳化、需求預測、自動化庫存管理、供應鏈分析解決方案以及最後一公里配送最佳化。

電子商務銷售額的成長預計將推動生成式人工智慧在物流市場的發展。電子商務日益普及的原因在於其便利性、產品供應範圍的擴大以及數位技術的廣泛應用。生成式人工智慧在電子商務物流的應用將透過增強庫存管理、最佳化路線和預測需求，提高效率並降低成本。例如，根據美國商務部下屬機構人口普查局的數據，截至2024年5月，2023年電子商務銷售額約為1.1187兆美元。預計2024年第一季零售總額將達到1.82兆美元，其中電子商務銷售額將比2023年同期成長8.5%（±1.1%），而同期零售總額的增幅僅為2.8%（±0.5%）。因此，電子商務銷售額的成長正在促進生成式人工智慧在物流市場的擴張。

在物流市場中，主要企業正在採用自然語言介面等先進技術，以提高供應鏈管理營運的效率和準確性。自然語言介面允許使用者使用日常語言與物流系統交互，從而簡化資料查詢和報告生成。例如，2023年9月，總部位於美國的物流技術公司FourKites發布了FinAI，這是一款生成式人工智慧解決方案，它透過自然語言互動分析大量的運輸數據、預計到達時間（ETA）和里程數據，從而提取洞察、自動化工作流程並最佳化營運。

目錄

第1章：執行摘要

第2章 市場特徵

  • 市場定義和範圍
  • 市場區隔
  • 主要產品和服務概述
  • 全球物流領域生成式人工智慧（AI）市場：吸引力評分與分析
  • 成長潛力分析、競爭評估、策略適宜性評估、風險狀況評估

第3章 市場供應鏈分析

  • 供應鏈與生態系概述
  • 清單：主要原料、資源和供應商
  • 主要經銷商和通路合作夥伴名單
  • 主要最終用戶列表

第4章：全球市場趨勢與策略

  • 關鍵科技與未來趨勢
    • 人工智慧（AI）和自主人工智慧
    • 自主系統、機器人、智慧運輸
    • 數位化、雲端運算、巨量資料、網路安全
    • 工業4.0和智慧製造
    • 物聯網、智慧基礎設施、互聯生態系統
  • 主要趨勢
    • 人工智慧驅動的路線最佳化
    • 需求預測
    • 庫存管理自動化
    • 供應鏈分析解決方案
    • 最佳化最後一公里配送

第5章 終端用戶產業市場分析

  • 零售
  • 衛生保健
  • 銀行與金融
  • 航太
  • 溝通

第6章 市場：宏觀經濟情景，包括利率、通貨膨脹、地緣政治、貿易戰和關稅的影響、關稅戰和貿易保護主義對供應鏈的影響，以及 COVID-19 疫情對市場的影響。

第7章：全球策略分析架構、目前市場規模、市場對比及成長率分析

  • 全球物流領域生成式人工智慧（AI）市場：PESTEL 分析（政治、社會、技術、環境、法律因素、促進因素和限制因素）
  • 全球生成式人工智慧（AI）市場規模、對比及成長率分析（物流）
  • 全球生成式人工智慧（AI）物流市場表現：規模與成長，2020-2025年
  • 全球物流生成式人工智慧（AI）市場預測：規模與成長，2025-2030年及2035年預測

第8章：全球市場總規模（TAM）

第9章 市場細分

  • 按類型
  • 變分自編碼器（VAE）、生成對抗網路（GAN）、循環神經網路（RNN）、長期短期記憶（LSTM）網路等類型。
  • 按組件
  • 軟體、解決方案
  • 部署模式
  • 本機部署、雲端部署
  • 透過使用
  • 倉庫管理、路線最佳化、庫存管理、供應鏈分析、最後一公里配送最佳化、客戶服務營運等用途。
  • 最終用戶
  • 零售、醫療保健、航太、電信、科技和其他終端用戶
  • 按類型進行子分割：變分自編碼器（VAE）
  • 需求預測模型、物流運營異常檢測、車輛管理預測性維護、不完整記錄的數據補充以及供應鏈最佳化解決方案。
  • 按類型細分：生成式衝突網路（GAN）
  • 透過情境模擬生成用於模型學習、路線最佳化和模擬的合成數據，用於庫存和資產管理的影像生成，用於運輸和交付中的詐欺檢測，以及產品需求預測。
  • 按類型細分：循環神經網路（RNN）
  • 時間序列分析用於需求預測、出貨追蹤和預測、配送服務中的客戶行為預測、庫存管理預測、交貨時間估算模型。
  • 按類型細分：長短期記憶（LSTM）網路
  • 進階時間序列預測、供應鏈績效預測分析、運輸最佳化模型、訂單履行預測、產能規劃和資源分配。
  • 按類型細分：其他類型
  • 強化學習用於路徑最佳化，結合多種人工智慧方法的混合模式，基於串流的即時數據分析模型，自我監督學習技術，以及用於現場決策的邊緣人工智慧。

第10章 市場與產業指標：依國家分類

第11章 區域與國別分析

  • 全球物流領域生成式人工智慧（AI）市場：按地區分類，實際數據和預測數據，2020-2025年、2025-2030年、2035年
  • 全球物流領域生成式人工智慧（AI）市場：按國家/地區分類，實際數據和預測數據，2020-2025年、2025-2030年預測數據、2035年預測數據

第12章 亞太市場

第13章：中國市場

第14章：印度市場

第15章：日本市場

第16章：澳洲市場

第17章：印尼市場

第18章：韓國市場

第19章 台灣市場

第20章：東南亞市場

第21章 西歐市場

第22章英國市場

第23章：德國市場

第24章：法國市場

第25章：義大利市場

第26章：西班牙市場

第27章 東歐市場

第28章：俄羅斯市場

第29章 北美市場

第30章：美國市場

第31章：加拿大市場

第32章：南美洲市場

第33章：巴西市場

第34章 中東市場

第35章：非洲市場

第36章 市場監理與投資環境

第37章：競爭格局與公司概況

  • 物流生成式人工智慧（AI）市場：競爭格局與市場佔有率（2024年）
  • 物流生成式人工智慧（AI）市場：公司估值矩陣
  • 物流的生成式人工智慧（AI）市場：公司概況
    • Microsoft Corporation
    • Amazon Web Services Inc.
    • Intel Corporation
    • Accenture plc
    • International Business Machines Corporation

第38章 其他大型企業和創新企業

  • Oracle Corporation, Honeywell International Inc., SAP SE, NVIDIA Corporation, Cognizant Technology Solutions Corporation, Epicor Software Corporation, Blue Yonder Group Inc., Coupa Software Incorporated, Kinaxis Inc., ShipBob Inc., Project44 Inc., Vorto Inc., Logility Inc., FourKites Inc., Shippeo SAS

第39章 全球市場競爭基準分析與儀錶板

第40章 重大併購

第41章 具有高市場潛力的國家、細分市場與策略

  • 2030年物流生成式人工智慧（AI）市場：提供新機會的國家
  • 2030年物流生成式人工智慧（AI）市場：充滿新機會的細分市場
  • 2030年物流生成式人工智慧（AI）市場：成長策略
    • 基於市場趨勢的策略
    • 競爭對手的策略

第42章附錄

簡介目錄
Product Code: IT4MGAIA15_G26Q1

Generative artificial intelligence (AI) in logistics involves leveraging sophisticated algorithms and machine learning to improve logistics processes. This includes forecasting demand, optimizing delivery routes, and efficiently managing inventory, leading to reduced costs, more precise deliveries, better operational efficiency, and enhanced customer satisfaction.

Key types of generative AI used in logistics include variational autoencoders (VAEs), generative adversarial networks (GANs), recurrent neural networks (RNNs), and long short-term memory (LSTM) networks, among others. A Variational Autoencoder (VAE) is an artificial neural network designed to create new data similar to the input data. Components of generative AI encompass software, hardware, and various solutions, with deployment options available both on-premises and in the cloud. Generative AI applications in logistics span warehouse management, route optimization, inventory control, supply chain analytics, last-mile delivery optimization, and customer service, with use cases across industries such as retail, healthcare, banking and finance, aerospace, telecommunications, and technology.

Tariffs have impacted the generative AI in logistics market by raising the cost of importing AI hardware, software, and cloud-based logistics solutions. Regions such as North America and Asia-Pacific that rely heavily on imported logistics technology are most affected. Segments including route optimization, predictive demand forecasting, and warehouse management systems experience higher operational costs. On the positive side, tariffs are encouraging local production of AI logistics solutions, fostering innovation, and enabling companies to implement more cost-efficient and domestically sourced technologies.

The generative artificial intelligence (AI) in logistics market research report is one of a series of new reports from The Business Research Company that provides generative artificial intelligence (AI) in logistics market statistics, including generative artificial intelligence (AI) in logistics industry global market size, regional shares, competitors with a generative artificial intelligence (AI) in logistics market share, detailed generative artificial intelligence (AI) in logistics market segments, market trends and opportunities, and any further data you may need to thrive in the generative artificial intelligence (AI) in logistics industry. This generative artificial intelligence (AI) in logistics market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The generative artificial intelligence (AI) in logistics market size has grown exponentially in recent years. It will grow from $0.8 billion in 2025 to $1.06 billion in 2026 at a compound annual growth rate (CAGR) of 32.6%. The growth in the historic period can be attributed to growth of e-commerce and logistics demand, adoption of warehouse management systems, early use of predictive analytics in transportation, increasing investment in fleet management, expansion of supply chain automation.

The generative artificial intelligence (AI) in logistics market size is expected to see exponential growth in the next few years. It will grow to $3.25 billion in 2030 at a compound annual growth rate (CAGR) of 32.3%. The growth in the forecast period can be attributed to integration of generative AI for real-time logistics decision making, expansion of AI-enabled predictive maintenance for fleets, adoption of advanced route simulation tools, increased use of hybrid and edge AI models, growth of AI-powered customer service operations in logistics. Major trends in the forecast period include AI-powered route optimization, predictive demand forecasting, inventory management automation, supply chain analytics solutions, last-mile delivery optimization.

The rise in e-commerce sales is expected to support the growth of the generative artificial intelligence (AI) in logistics market going forward. The growing popularity of e-commerce is driven by convenience, broader product availability, and increased adoption of digital technologies. Generative AI in e-commerce logistics enhances inventory management, improves route optimization, and forecasts demand, resulting in greater efficiency and cost savings. For example, in May 2024, according to the Census Bureau of the Department of Commerce, a US-based government organization, e-commerce sales reached approximately $1,118.7 billion in 2023. During the first quarter of 2024, total retail sales were estimated at $1,820.0 billion, with e-commerce sales increasing by 8.5% (+-1.1%) compared with the same quarter in 2023, while overall retail sales grew by 2.8% (+-0.5%). Therefore, the rise in e-commerce sales is contributing to the expansion of the generative artificial intelligence (AI) in the logistics market.

Leading companies operating in the generative artificial intelligence (AI) in logistics market are adopting advanced technologies, such as natural language interfaces, to improve operational efficiency and accuracy in supply chain management. A natural language interface enables users to interact with logistics systems using everyday language, simplifying data queries and reporting. For example, in September 2023, FourKites, Inc., a US-based logistics technology company, launched FinAI, a generative AI solution that uses natural language interaction to uncover insights, automate workflows, and optimize operations by analyzing extensive shipment, ETA, and mileage data.

In September 2023, Logility Inc., a US-based software company, acquired Garvis BV for an undisclosed amount. This acquisition is intended to accelerate the integration of AI-driven demand forecasting technologies into Logility's supply chain learning solutions. Garvis BV is a Belgium-based provider of generative artificial intelligence solutions for logistics.

Major companies operating in the generative artificial intelligence (AI) in logistics market are Microsoft Corporation, Amazon Web Services Inc., Intel Corporation, Accenture plc, International Business Machines Corporation, Oracle Corporation, Honeywell International Inc., SAP SE, NVIDIA Corporation, Cognizant Technology Solutions Corporation, Epicor Software Corporation, Blue Yonder Group Inc., Coupa Software Incorporated, Kinaxis Inc., ShipBob Inc., Project44 Inc., Vorto Inc., Logility Inc., FourKites Inc., Shippeo SAS, Freightos Ltd., Slync.io Inc., Locus.sh, ClearMetal Inc.

North America was the largest region in the generative artificial intelligence (AI) in logistics market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative artificial intelligence (AI) in logistics market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the generative artificial intelligence (AI) in logistics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The generative artificial intelligence (AI) in logistics market consists of revenues earned by entities by providing services such as real-time data analysis, dynamic pricing optimization, predictive maintenance, customer behavior analysis, and fraud detection. The market value includes the value of related goods sold by the service provider or included within the service offering. The generative artificial intelligence (AI) in logistics market also includes sales of autonomous vehicles, autonomous vehicle drones, and warehouse robotic solutions. Values in this market are 'factory gate' values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Generative Artificial Intelligence (AI) in Logistics Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses generative artificial intelligence (AI) in logistics market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for generative artificial intelligence (AI) in logistics ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The generative artificial intelligence (AI) in logistics market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

  • The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
  • The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
  • The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
  • The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
  • The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
  • The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
  • The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
  • The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
  • Market segmentations break down the market into sub markets.
  • The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
  • Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
  • The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
  • The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.

Scope

  • Markets Covered:1) By Type: Variational Autoencoder (VAE); Generative Adversarial Networks (GANs); Recurrent Neural Networks (RNNs); Long Short-Term Memory (LSTM) Networks; Other Types
  • 2) By Component: Software; Solution
  • 3) By Deployment Mode: On-Premises; Cloud-Based
  • 4) By Application: Warehouse Management; Route Optimization; Inventory Management; Supply Chain Analytics; Last-Mile Delivery Optimization; Customer Service Operations; Other Applications
  • 5) By End-User: Retail; Healthcare; Aerospace; Telecommunication; Technology; Other End-Users
  • Subsegments:
  • 1) By Variational Autoencoder (VAE): Demand Forecasting Models; Anomaly Detection In Logistics Operations; Predictive Maintenance For Fleet Management; Data Imputation For Incomplete Records; Supply Chain Optimization Solutions
  • 2) By Generative Adversarial Networks (GANs): Synthetic Data Generation For Training Models; Route Optimization And Simulation; Image Generation For Inventory And Asset Management; Fraud Detection In Shipment And Delivery; Product Demand Forecasting Through Scenario Simulation
  • 3) By Recurrent Neural Networks (RNNs): Time Series Analysis For Demand Prediction; Shipment Tracking And Forecasting; Customer Behavior Prediction For Delivery Services; Inventory Management Forecasting; Delivery Time Estimation Models
  • 4) By Long Short-Term Memory (LSTM) Networks: Advanced Time Series Forecasting; Predictive Analytics For Supply Chain Performance; Transportation Optimization Models; Order Fulfillment Prediction; Capacity Planning And Resource Allocation
  • 5) By Other Types: Reinforcement Learning For Route Optimization; Hybrid Models Combining Multiple AI Approaches; Flow-Based Models For Real-Time Data Analysis; Self-Supervised Learning Techniques; Edge AI For On-Site Decision Making
  • Companies Mentioned: Microsoft Corporation; Amazon Web Services Inc.; Intel Corporation; Accenture plc; International Business Machines Corporation; Oracle Corporation; Honeywell International Inc.; SAP SE; NVIDIA Corporation; Cognizant Technology Solutions Corporation; Epicor Software Corporation; Blue Yonder Group Inc.; Coupa Software Incorporated; Kinaxis Inc.; ShipBob Inc.; Project44 Inc.; Vorto Inc.; Logility Inc.; FourKites Inc.; Shippeo SAS; Freightos Ltd.; Slync.io Inc.; Locus.sh; ClearMetal Inc.
  • Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
  • Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
  • Time Series: Five years historic and ten years forecast.
  • Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
  • Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
  • Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
  • Delivery Format: Word, PDF or Interactive Report
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Table of Contents

1. Executive Summary

  • 1.1. Key Market Insights (2020-2035)
  • 1.2. Visual Dashboard: Market Size, Growth Rate, Hotspots
  • 1.3. Major Factors Driving the Market
  • 1.4. Top Three Trends Shaping the Market

2. Generative Artificial Intelligence (AI) in Logistics Market Characteristics

  • 2.1. Market Definition & Scope
  • 2.2. Market Segmentations
  • 2.3. Overview of Key Products and Services
  • 2.4. Global Generative Artificial Intelligence (AI) in Logistics Market Attractiveness Scoring And Analysis
    • 2.4.1. Overview of Market Attractiveness Framework
    • 2.4.2. Quantitative Scoring Methodology
    • 2.4.3. Factor-Wise Evaluation
  • Growth Potential Analysis, Competitive Dynamics Assessment, Strategic Fit Assessment And Risk Profile Evaluation
    • 2.4.4. Market Attractiveness Scoring and Interpretation
    • 2.4.5. Strategic Implications and Recommendations

3. Generative Artificial Intelligence (AI) in Logistics Market Supply Chain Analysis

  • 3.1. Overview of the Supply Chain and Ecosystem
  • 3.2. List Of Key Raw Materials, Resources & Suppliers
  • 3.3. List Of Major Distributors and Channel Partners
  • 3.4. List Of Major End Users

4. Global Generative Artificial Intelligence (AI) in Logistics Market Trends And Strategies

  • 4.1. Key Technologies & Future Trends
    • 4.1.1 Artificial Intelligence & Autonomous Intelligence
    • 4.1.2 Autonomous Systems, Robotics & Smart Mobility
    • 4.1.3 Digitalization, Cloud, Big Data & Cybersecurity
    • 4.1.4 Industry 4.0 & Intelligent Manufacturing
    • 4.1.5 Internet Of Things (Iot), Smart Infrastructure & Connected Ecosystems
  • 4.2. Major Trends
    • 4.2.1 AI-Powered Route Optimization
    • 4.2.2 Predictive Demand Forecasting
    • 4.2.3 Inventory Management Automation
    • 4.2.4 Supply Chain Analytics Solutions
    • 4.2.5 Last-Mile Delivery Optimization

5. Generative Artificial Intelligence (AI) in Logistics Market Analysis Of End Use Industries

  • 5.1 Retail
  • 5.2 Healthcare
  • 5.3 Banking And Finance
  • 5.4 Aerospace
  • 5.5 Telecommunication

6. Generative Artificial Intelligence (AI) in Logistics Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, Supply Chain Impact from Tariff War & Trade Protectionism, And Covid And Recovery On The Market

7. Global Generative Artificial Intelligence (AI) in Logistics Strategic Analysis Framework, Current Market Size, Market Comparisons And Growth Rate Analysis

  • 7.1. Global Generative Artificial Intelligence (AI) in Logistics PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
  • 7.2. Global Generative Artificial Intelligence (AI) in Logistics Market Size, Comparisons And Growth Rate Analysis
  • 7.3. Global Generative Artificial Intelligence (AI) in Logistics Historic Market Size and Growth, 2020 - 2025, Value ($ Billion)
  • 7.4. Global Generative Artificial Intelligence (AI) in Logistics Forecast Market Size and Growth, 2025 - 2030, 2035F, Value ($ Billion)

8. Global Generative Artificial Intelligence (AI) in Logistics Total Addressable Market (TAM) Analysis for the Market

  • 8.1. Definition and Scope of Total Addressable Market (TAM)
  • 8.2. Methodology and Assumptions
  • 8.3. Global Total Addressable Market (TAM) Estimation
  • 8.4. TAM vs. Current Market Size Analysis
  • 8.5. Strategic Insights and Growth Opportunities from TAM Analysis

9. Generative Artificial Intelligence (AI) in Logistics Market Segmentation

  • 9.1. Global Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Variational Autoencoder (VAE), Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, Other Types
  • 9.2. Global Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Component, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Software, Solution
  • 9.3. Global Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • On-Premises, Cloud-Based
  • 9.4. Global Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Application, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Warehouse Management, Route Optimization, Inventory Management, Supply Chain Analytics, Last-Mile Delivery Optimization, Customer Service Operations, Other Applications
  • 9.5. Global Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By End-User, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Retail, Healthcare, Aerospace, Telecommunication, Technology, Other End-Users
  • 9.6. Global Generative Artificial Intelligence (AI) in Logistics Market, Sub-Segmentation Of Variational Autoencoder (VAE), By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Demand Forecasting Models, Anomaly Detection In Logistics Operations, Predictive Maintenance For Fleet Management, Data Imputation For Incomplete Records, Supply Chain Optimization Solutions
  • 9.7. Global Generative Artificial Intelligence (AI) in Logistics Market, Sub-Segmentation Of Generative Adversarial Networks (GANs), By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Synthetic Data Generation For Training Models, Route Optimization And Simulation, Image Generation For Inventory And Asset Management, Fraud Detection In Shipment And Delivery, Product Demand Forecasting Through Scenario Simulation
  • 9.8. Global Generative Artificial Intelligence (AI) in Logistics Market, Sub-Segmentation Of Recurrent Neural Networks (RNNs), By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Time Series Analysis For Demand Prediction, Shipment Tracking And Forecasting, Customer Behavior Prediction For Delivery Services, Inventory Management Forecasting, Delivery Time Estimation Models
  • 9.9. Global Generative Artificial Intelligence (AI) in Logistics Market, Sub-Segmentation Of Long Short-Term Memory (LSTM) Networks, By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Advanced Time Series Forecasting, Predictive Analytics For Supply Chain Performance, Transportation Optimization Models, Order Fulfillment Prediction, Capacity Planning And Resource Allocation
  • 9.10. Global Generative Artificial Intelligence (AI) in Logistics Market, Sub-Segmentation Of Other Types, By Type, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • Reinforcement Learning For Route Optimization, Hybrid Models Combining Multiple AI Approaches, Flow-Based Models For Real-Time Data Analysis, Self-Supervised Learning Techniques, Edge AI For On-Site Decision Making

10. Generative Artificial Intelligence (AI) in Logistics Market, Industry Metrics By Country

  • 10.1. Global Generative Artificial Intelligence (AI) in Logistics Market, Average Selling Price By Country, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $
  • 10.2. Global Generative Artificial Intelligence (AI) in Logistics Market, Average Spending Per Capita (Employed) By Country, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $

11. Generative Artificial Intelligence (AI) in Logistics Market Regional And Country Analysis

  • 11.1. Global Generative Artificial Intelligence (AI) in Logistics Market, Split By Region, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion
  • 11.2. Global Generative Artificial Intelligence (AI) in Logistics Market, Split By Country, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

12. Asia-Pacific Generative Artificial Intelligence (AI) in Logistics Market

  • 12.1. Asia-Pacific Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 12.2. Asia-Pacific Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

13. China Generative Artificial Intelligence (AI) in Logistics Market

  • 13.1. China Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 13.2. China Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

14. India Generative Artificial Intelligence (AI) in Logistics Market

  • 14.1. India Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

15. Japan Generative Artificial Intelligence (AI) in Logistics Market

  • 15.1. Japan Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 15.2. Japan Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

16. Australia Generative Artificial Intelligence (AI) in Logistics Market

  • 16.1. Australia Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

17. Indonesia Generative Artificial Intelligence (AI) in Logistics Market

  • 17.1. Indonesia Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

18. South Korea Generative Artificial Intelligence (AI) in Logistics Market

  • 18.1. South Korea Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 18.2. South Korea Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

19. Taiwan Generative Artificial Intelligence (AI) in Logistics Market

  • 19.1. Taiwan Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 19.2. Taiwan Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

20. South East Asia Generative Artificial Intelligence (AI) in Logistics Market

  • 20.1. South East Asia Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 20.2. South East Asia Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

21. Western Europe Generative Artificial Intelligence (AI) in Logistics Market

  • 21.1. Western Europe Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 21.2. Western Europe Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

22. UK Generative Artificial Intelligence (AI) in Logistics Market

  • 22.1. UK Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

23. Germany Generative Artificial Intelligence (AI) in Logistics Market

  • 23.1. Germany Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

24. France Generative Artificial Intelligence (AI) in Logistics Market

  • 24.1. France Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

25. Italy Generative Artificial Intelligence (AI) in Logistics Market

  • 25.1. Italy Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

26. Spain Generative Artificial Intelligence (AI) in Logistics Market

  • 26.1. Spain Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

27. Eastern Europe Generative Artificial Intelligence (AI) in Logistics Market

  • 27.1. Eastern Europe Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 27.2. Eastern Europe Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

28. Russia Generative Artificial Intelligence (AI) in Logistics Market

  • 28.1. Russia Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

29. North America Generative Artificial Intelligence (AI) in Logistics Market

  • 29.1. North America Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 29.2. North America Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

30. USA Generative Artificial Intelligence (AI) in Logistics Market

  • 30.1. USA Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 30.2. USA Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

31. Canada Generative Artificial Intelligence (AI) in Logistics Market

  • 31.1. Canada Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Country Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 31.2. Canada Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

32. South America Generative Artificial Intelligence (AI) in Logistics Market

  • 32.1. South America Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 32.2. South America Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

33. Brazil Generative Artificial Intelligence (AI) in Logistics Market

  • 33.1. Brazil Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

34. Middle East Generative Artificial Intelligence (AI) in Logistics Market

  • 34.1. Middle East Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 34.2. Middle East Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

35. Africa Generative Artificial Intelligence (AI) in Logistics Market

  • 35.1. Africa Generative Artificial Intelligence (AI) in Logistics Market Overview
  • Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
  • 35.2. Africa Generative Artificial Intelligence (AI) in Logistics Market, Segmentation By Type, Segmentation By Component, Segmentation By Deployment Mode, Historic and Forecast, 2020-2025, 2025-2030F, 2035F, $ Billion

36. Generative Artificial Intelligence (AI) in Logistics Market Regulatory and Investment Landscape

37. Generative Artificial Intelligence (AI) in Logistics Market Competitive Landscape And Company Profiles

  • 37.1. Generative Artificial Intelligence (AI) in Logistics Market Competitive Landscape And Market Share 2024
    • 37.1.1. Top 10 Companies (Ranked by revenue/share)
  • 37.2. Generative Artificial Intelligence (AI) in Logistics Market - Company Scoring Matrix
    • 37.2.1. Market Revenues
    • 37.2.2. Product Innovation Score
    • 37.2.3. Brand Recognition
  • 37.3. Generative Artificial Intelligence (AI) in Logistics Market Company Profiles
    • 37.3.1. Microsoft Corporation Overview, Products and Services, Strategy and Financial Analysis
    • 37.3.2. Amazon Web Services Inc. Overview, Products and Services, Strategy and Financial Analysis
    • 37.3.3. Intel Corporation Overview, Products and Services, Strategy and Financial Analysis
    • 37.3.4. Accenture plc Overview, Products and Services, Strategy and Financial Analysis
    • 37.3.5. International Business Machines Corporation Overview, Products and Services, Strategy and Financial Analysis

38. Generative Artificial Intelligence (AI) in Logistics Market Other Major And Innovative Companies

  • Oracle Corporation, Honeywell International Inc., SAP SE, NVIDIA Corporation, Cognizant Technology Solutions Corporation, Epicor Software Corporation, Blue Yonder Group Inc., Coupa Software Incorporated, Kinaxis Inc., ShipBob Inc., Project44 Inc., Vorto Inc., Logility Inc., FourKites Inc., Shippeo SAS

39. Global Generative Artificial Intelligence (AI) in Logistics Market Competitive Benchmarking And Dashboard

40. Key Mergers And Acquisitions In The Generative Artificial Intelligence (AI) in Logistics Market

41. Generative Artificial Intelligence (AI) in Logistics Market High Potential Countries, Segments and Strategies

  • 41.1. Generative Artificial Intelligence (AI) in Logistics Market In 2030 - Countries Offering Most New Opportunities
  • 41.2. Generative Artificial Intelligence (AI) in Logistics Market In 2030 - Segments Offering Most New Opportunities
  • 41.3. Generative Artificial Intelligence (AI) in Logistics Market In 2030 - Growth Strategies
    • 41.3.1. Market Trend Based Strategies
    • 41.3.2. Competitor Strategies

42. Appendix

  • 42.1. Abbreviations
  • 42.2. Currencies
  • 42.3. Historic And Forecast Inflation Rates
  • 42.4. Research Inquiries
  • 42.5. The Business Research Company
  • 42.6. Copyright And Disclaimer