(MENAFN- GlobeNewsWire - Nasdaq) Generative AI Revolutionizes Logistics: Elevating Supply Chains with Real-Time Intelligence, Personalized Services, & Sustainable Solutions

Dublin, Oct. 03, 2025 (GLOBE NEWSWIRE) -- The "Generative AI in Logistics Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025-2034" has been added to ResearchAndMarkets's offering.

The Global Generative AI In Logistics Market was valued at USD 1.3 billion in 2024 and is estimated to grow at a CAGR of 33.7% to reach USD 23.1 billion by 2034. This technology is transforming supply chain operations by delivering real-time intelligence and long-term strategic forecasting.

By simulating delivery routes and transport scenarios, logistics providers can improve inventory planning, reduce freight expenses, and prepare for disruptions. AI-powered demand forecasting streamlines resource use, and dynamic routing tools enhance delivery timelines. Operational efficiency and cost control, driven by generative AI, are shaping the market's future.

In 2024, the software segment held a 66% share and is set to grow at a CAGR of 32% through 2034. Logistics teams prioritize AI-driven predictive tools that simulate disruptions like stock shortages and delivery delays. These tools allow firms to adjust operations proactively, improving efficiency and cost outcomes. Modern solutions integrate easily with legacy systems, offering faster results than custom-built options.

The cloud deployment segment held a 67% share in 2024 and is expected to maintain strong growth at a CAGR of 32% through 2034. As logistics operations become more dispersed, firms choose flexible, cloud-based AI solutions that scale instantly based on needs. Unlike traditional setups, cloud platforms provide real-time computing power and data storage during demand surges, crucial for global supply chains.

North America Generative AI In Logistics Market held 85% share and generated USD 355.2 million in 2024. The country is a hub for advanced AI adoption in supply chains, supported by tech firms like IBM, Microsoft, Amazon, and Google. These companies offer enterprise-ready AI infrastructure, accelerating algorithm development and deployment. This positions the U.S. as a frontrunner in logistics AI worldwide.

Leading firms in the Generative AI in Logistics Market are focusing on cloud partnerships, scalable AI models, and industry-specific machine learning tools. They prioritize modular AI solutions that adapt to regional logistics challenges. Enhancing user accessibility through API integration, building plug-and-play platforms, and enabling real-time data visibility are common goals. These companies invest in agile environments and low-latency computing to meet logistics demands, focusing on customization, sustainability, and predictive analytics to improve customer engagement and reduce risks, giving brands a competitive edge.

Comprehensive Market Analysis and Forecast

• Industry trends, key growth drivers, challenges, future opportunities, and regulatory landscape
• Competitive landscape with Porter's Five Forces and PESTEL analysis
• Market size, segmentation, and regional forecasts
• In-depth company profiles, business strategies, financial insights, and SWOT analysis

Key Attributes

Report Attribute	Details
No. of Pages	190
Forecast Period	2024-2034
Estimated Market Value (USD) in 2024	$1.3 Billion
Forecasted Market Value (USD) by 2034	$23.1 Billion
Compound Annual Growth Rate	33.7%
Regions Covered	Global

Key Topics Covered
Chapter 1 Methodology
Chapter 2 Executive Summary
2.1 Industry 360 synopsis
2.2 Key market trends
2.2.1 Regional
2.2.2 Type
2.2.3 Component
2.2.4 Deployment mode
2.2.5 Application
2.2.6 End Use
2.3 TAM Analysis, 2025-2034
2.4 CXO perspectives: strategic imperatives
2.4.1 Executive decision points
2.4.2 Critical success factors
2.5 Future outlook and strategic recommendations
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.1.1 Supplier landscape
3.1.2 Profit margin
3.1.3 Cost structure
3.1.4 Value addition at each stage
3.1.5 Factors affecting the value chain
3.1.6 Disruptions
3.2 Industry impact forces
3.2.1 Growth drivers
3.2.1.1 Enhanced supply chain optimization
3.2.1.2 Automation of repetitive process
3.2.1.3 Personalized experience of the customers
3.2.1.4 Cost-efficient fleet & route management
3.2.2 Industry pitfalls and challenges
3.2.2.1 Data privacy and security risks
3.2.2.2 Integration complexity with legacy systems
3.2.3 Market opportunities
3.2.3.1 AI driven demand forecasting and inventory optimization
3.2.3.2 Digital twin creation for smart warehousing
3.2.3.3 Autonomous route planning and fleet management
3.3 Growth potential analysis
3.4 Regulatory landscape
3.4.1 North America
3.4.2 Europe
3.4.3 Asia Pacific
3.4.4 Latin America
3.4.5 Middle East & Africa
3.5 Porter's analysis
3.6 PESTEL analysis
3.7 Technology and innovation landscape
3.7.1 Current technological trends
3.7.2 Emerging technologies
3.8 Case studies
3.9 Use cases
3.10 Cost breakdown analysis
3.11 Patent analysis
3.12 Sustainability and environmental aspects
3.12.1 Sustainable practices
3.12.2 Waste reduction strategies
3.12.3 Energy efficiency in production
3.12.4 Eco-friendly initiatives
3.12.5 Carbon footprint considerations
Chapter 4 Competitive Landscape, 2024
4.1 Introduction
4.2 Company market share analysis
4.2.1 North America
4.2.2 Europe
4.2.3 Asia Pacific
4.2.4 LATAM
4.2.5 MEA
4.3 Competitive analysis of major market players
4.4 Competitive positioning matrix
4.5 Strategic outlook matrix
4.6 Key developments
4.6.1 Mergers & acquisitions
4.6.2 Partnerships & collaborations
4.6.3 New product launches
4.6.4 Expansion plans and funding
Chapter 5 Market Estimates & Forecast, By Type, 2021 - 2034 (USD Million)
5.1 Key trends
5.2 Variational autoencoder
5.3 Generative adversarial networks
5.4 Recurrent neural networks
5.5 Long short-term memory networks
5.6 Transformers
Chapter 6 Market Estimates & Forecast, By Component, 2021 - 2034 (USD Million)
6.1 Key trends
6.2 Software
6.3 Services
Chapter 7 Market Estimates & Forecast, By Deployment Mode, 2021 - 2034 (USD Million)
7.1 Key trends
7.2 Cloud
7.3 On-premises
Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2034 (USD Million)
8.1 Key trends
8.2 Route optimization
8.3 Demand forecasting
8.4 Warehouse and inventory management
8.5 Supply chain automation
8.6 Predictive maintenance
8.7 Risk management
8.8 Customized logistics solution
8.9 Others
Chapter 9 Market Estimates & Forecast, By End Use, 2021- 2034 (USD Million)
9.1 Key trends
9.2 Third party logistics providers
9.3 Freight forwarders
9.4 E-commerce companies
9.5 Manufacturers
Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2034 (USD Million)
10.1 Key trends
10.2 North America
10.2.1 U.S.
10.2.2 Canada
10.3 Europe
10.3.1 UK
10.3.2 Germany
10.3.3 France
10.3.4 Italy
10.3.5 Spain
10.3.6 Russia
10.3.7 Nordics
10.4 Asia Pacific
10.4.1 China
10.4.2 India
10.4.3 Japan
10.4.4 South Korea
10.4.5 ANZ
10.4.6 Southeast Asia
10.5 Latin America
10.5.1 Brazil
10.5.2 Mexico
10.5.3 Argentina
10.6 MEA
10.6.1 UAE
10.6.2 Saudi Arabia
10.6.3 South Africa
Chapter 11 Company Profiles
11.1 Amazon Web Services
11.2 DHL Group
11.3 FedEx
11.4 Flexport
11.5 Four Kites
11.6 Google
11.7 IBM
11.8 Locus
11.9 Maersk
11.10 Microsoft
11.11 NVIDIA
11.12 Open AI
11.13 Optimal Dynamics
11.14 Oracle
11.15 Palantir Technologies
11.16 Project44
11.17 Salesforce
11.18 SAP
11.19 UPS
11.20 XPO Logistics
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• Generative AI in Logistics Market

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