Austin, Aug. 11, 2025 (GLOBE NEWSWIRE) -- The SNS Insider report indicates Generative AI in Logistics Market size was valued at USD 816.15 million in 2023 and is estimated to reach USD 13621.30 million by 2032, expanding at a CAGR of 36.93% from 2024 to 2032.
The U.S. market is driven by strong adoption of AI-powered automation, robust e-commerce infrastructure, and high investment in smart logistics. In 2024, the U.S. Generative AI in Logistics Market is valued at USD 349.23 million, projected to reach USD 4273.06 million by 2032, growing at a CAGR of 36.76%. Future growth will be fueled by federal AI initiatives, advanced cloud ecosystems, and rising demand for predictive logistics solutions.
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Key Players:
- Deutsche Post AG
- UPS (United Parcel Services)
- Schneider Electric
- C.H. Robinson
- XPO Logistics
- FedEx Corp
- A.P. Moller - Maersk AS
- Blue Yonder
- Google Cloud
- International Business Machines (IBM)
- Microsoft
- PackageX
- Salesforce
Generative AI in Logistics Market Report Scope:
| Report Attributes | Details |
| Market Size in 2024 | USD 816.15 Million |
| Market Size by 2032 | USD 13621.30 Million |
| CAGR | CAGR of 36.93% From 2025 to 2032 |
| Base Year | 2024 |
| Forecast Period | 2025-2032 |
| Historical Data | 2021-2023 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Type (Variational Autoencoder (VAE), Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, Others) • By Deployment Mode (Cloud Based, On-premise) • By End User (Road Transportation, Railway Transportation, Aviation, Shipping and Ports) |
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By Type: VAE Dominated the Market in 2024, GANs Projected to Grow Fastest
The Variational Autoencoder (VAE) dominated the market in 2024, accounting for a 30% revenue share, as it can accurately simulate various logistics scenarios and process structured data. VAE models also enable demand forecasting, route optimization, and capacity planning with superior interpretability, hence, are suitable for large logistics firms aiming for accuracy and scalability. Their unique advantage comes from their seamless integration with existing ERP and supply chain systems. As logistics become increasingly data-intensive, VAEs are likely to retain an advantage over other architectures in applications that require stability and explainability for enterprise use.
Generative Adversarial Networks (GANs) are projected to grow at the fastest CAGR during the forecast period, due to their ability to generate synthetic data and model complex multi-variable logistics systems. In autonomous delivery companies, GANs are increasingly being used to simulate delivery routes, optimize drone paths, and train AI systems on edge-case logistics scenarios. Moving from reactive scenario planning and risk simulation to proactive logistics that run adjustments on real-time changes will drive GANs into an essential role of strategic AI investments in shipping, warehousing, and delivery logistics.
By Deployment Mode: Cloud-Based Dominated the Market in 2024, On-Premise Set for Rapid Growth
Cloud-Based deployment dominated the market in 2024 and accounted for 68% of revenue share, due to the need for scalable and economical NAS models. Infrastructure-intensive generative AI capabilities are now being opened to logistics providers via cloud platforms. Enabling real-time route changes, international synchronization, and communication with mobile fleets and IoT devices. With a lower barrier to entry and the flexibility that comes with a cloud-based model, AI-as-a-Service will be further entrenched in the logistics sector as SMEs and global freight players alike take up the technology.
On-premise solutions are projected to register the fastest CAGR during 2024–2032 as businesses with sensitive data, such as defense, customs, and luxury logistics, will achieve full control and data security through AI systems. Local data governance laws, along with latency and third-party concerns, are driving the need for in-house AI infrastructure. With generative AI modularisation making it less resource-intensive, on-premise is even starting to appeal to mid-tier functions, particularly for in-region supply chain intelligence.
By End User: Road Transportation Dominated the Market in 2024, Shipping & Ports to Grow Fastest
Road Transportation dominated the market in 2024 and accounted for 34% of revenue share its pivotal role in last-mile deliveries and inland freight. Fleet efficiency is being reinvented thanks to generative AI applications for fuel optimization, predicting driver behavior, dynamic rerouting, and simulating cargo safety. As roadways form the core of the world and regional logistics networks, investment in both AI-enabled autonomous vehicle systems and predictive analytics will keep this part as a major contributor over the forecast period.
Shipping and Ports are expected to grow at the fastest CAGR from 2024 to 2032, owing to the digitization initiative in maritime logistics. The increasing trade volume globally has forced ports to utilize AI, such as automating procedures to manage congestion, simulating the operation of vessels under different scenarios, and container assignment. The power of generative AI in Transshipment scheduling optimization, weather-induced rerouting decision making, and fuel consumption optimization while at sea is making it essential for modern port operations and ocean freight logistics planning.
By Region: North America Dominated in 2024, Asia-Pacific to Witness Fastest Growth
North America dominated the market in 2024 and accounted for 44% of revenue share, owing to early adoption of advanced logistics automation and AI. With huge investments in AI infrastructure in recent years, a mature e-commerce industry, and a vast base of tech adjacencies/outcomes, the region stands to benefit significantly. North America Musters Generative Intelligence on the Road and In the Sky. The boldest industry-leading generative AI logistics transformation trends in North America are being solidified further by U.S.-based governmental initiatives on AI innovation supporting third-party transportation and defense logistics.
Asia-Pacific is expected to record the fastest CAGR from 2024 to 2032. With the booming e-commerce in China, India, and the Southeast Asian region, coupled with increasing investments in smart cities and digital logistics corridors, the region is rapidly emerging as an epicentre for AI-driven supply chain transformation. The rapid adoption of generative AI for smart warehousing, autonomous transport, port automation, supportive cloud infrastructure at low cost, and a rising AI-skilled workforce is pushing governments and private sector investments into this space too.
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USP’s:
- Time-to-Implementation Statistics – Measures average deployment duration of generative AI logistics tools across fleet, inventory, and warehouse systems for rapid ROI.
- Predictive Accuracy Improvements – Tracks enhancements in delivery time estimation, demand forecasting, and route optimization accuracy driven by AI-generated insights.
- Supply Chain Risk Mitigation – Evaluates AI’s role in identifying disruptions, forecasting delays, and improving contingency planning through scenario simulation.
- AI Training Data Volumes – Analyzes dataset scale (shipment logs, GPS data, warehouse activity) used to train LLMs for logistics-specific tasks.
- Carbon Footprint Reduction – Assesses emissions saved via AI-optimized routing, idle time reduction, packaging efficiency, and fleet utilization improvements.
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