Generative Artificial Intelligence (AI) in Logistics Global Market Report 2025

Generative Artificial Intelligence (AI) in Logistics Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on 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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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? 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, competitive landscape, market shares, 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.
• 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 forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.
• 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. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
• 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 trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

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; Hardware; 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; Banking And Finance; 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

Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain

Regions: Asia-Pacific; 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: PDF, Word and Excel Data Dashboard.

Please Note: Report will be updated with the latest data and delivered to you within 3-5 working days of order. Show more