Generative Artificial Intelligence (AI) in Logistics Market Global Report 2026

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.

Reasons to Purchase

• Gain a truly global perspective with the most comprehensive report available on this market covering 16 geographies.
• Assess the impact of key macro factors such as geopolitical conflicts, trade policies and tariffs, inflation and interest rate fluctuations, and evolving regulatory landscapes.
• Create regional and country strategies on the basis of local data and analysis.
• Identify growth segments for investment.
• Outperform competitors using forecast data and the drivers and trends shaping the market.
• Understand customers based on end user analysis.
• Benchmark performance against key competitors based on market share, innovation, and brand strength.
• Evaluate the total addressable market (TAM) and market attractiveness scoring to measure market potential.
• Suitable for supporting your internal and external presentations with reliable high-quality data and analysis
• Report will be updated with the latest data and delivered to you within 2-3 working days of order along with an Excel data sheet for easy data extraction and analysis.
• All data from the report will also be delivered in an excel dashboard format.

Description:

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.

Please Note: Report will be updated with the latest data and delivered to you within 2-3 working days of order. Show more