Prominent Generative Artificial Intelligence (AI) in Logistics Market Trend for 2025: Leveraging Generative AI And Advanced Technologies Adoption In Supply Chain Management

"What Are the Projected Growth and Market Size Trends for the Generative Artificial Intelligence (AI) in Logistics Market?
The market size for generative artificial intelligence (AI) in logistics has seen significant growth recently. It is expected to escalate from $0.6 billion in 2024 to $0.8 billion in 2025, with a compound annual growth rate (CAGR) of 32.7%. Factors such as the rising need for real-time data analysis, e-commerce growth, the broadening of global supply chains, industrial infrastructure enhancement, and the emergence of automation in warehouse management have contributed to this remarkable growth during the historic period.

In the coming years, it is predicted that there will be a significant increase in the size of the generative artificial intelligence (AI) logistics market, with an estimated value of $2.46 billion by 2029 and a compound annual growth rate (CAGR) of 32.4%. The anticipated growth can be credited to a surge in the necessity for instant data, expanding usage of IoT devices, an increase in investments into AI technologies, a growing need for transparency in supply chains, and an escalating demand for improved customer services. The forecast period is also expected to see major trends such as technological evolution, self-driving vehicles, predictive analysis, automation through robots, and the use of digital twins.

What Is Driving the Growth Trajectory of the Generative Artificial Intelligence (AI) in Logistics Market?
The anticipated surge in e-commerce sales will likely fuel the expansion of the generative artificial intelligence (AI) in the logistics market. The rising popularity of e-commerce, attributed to its convenience, broad product range, and growing digital technology use, is a contributing factor. Generative AI augments the efficiency of e-commerce logistics through optimized inventory control, improved route mapping, and demand forecasting, thereby resulting in cost savings and increased productivity. For example, a report released by the Department of Commerce's Census Bureau, a US government agency, in May 2024 stated that in 2023, e-commerce sales approximated at about $1,118.7 billion. The estimated total retail sales for the first quarter of 2024 amounted to $1,820.0 billion. Compared to the same quarter in 2023, e-commerce sales during this duration registered an 8.5% increase (±1.1%), whereas total retail sales rose by 2.8% (±0.5%). Thus, it is the uptick in e-commerce sales that is fostering the development of the generative AI in the logistics market.

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Which Leading Companies Are Shaping the Growth of the Generative Artificial Intelligence (AI) in Logistics Market?
Major companies operating in the generative artificial intelligence (AI) in logistics market are Microsoft Corporation, Amazon Web Services Inc., Intel Corporation, Accent*ure 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.

What Are the Major Trends Shaping the Generative Artificial Intelligence (AI) in Logistics Market?
Leading corporations in the generative AI in logistics sector are honing their focus on the integration of cutting-edge technology like natural language interfaces in an effort to boost operational productivity and achieve greater precision in supply chain management. The term 'natural language interface' describes a system that enables users to communicate with supply chain management software or equipment using common language. This simplifies the process of data querying, report generation, and operations management, without requiring any specific technical know-how. Take for instance, FourKites, Inc., a US-based supply chain visibility and logistics tech firm, launched a generative AI tool, FinAI, in September 2023. Designed to bolster supply chain management, FinAI makes use of a natural language interface to unveil insights, automate tasks, and optimize operations using a comprehensive data analysis of daily shipments (3 million), estimated times of arrival (18 million ETAs), and the total mileage tracked on a yearly basis (62 billion miles).

What Are the Key Segments of the Generative Artificial Intelligence (AI) in Logistics Market?
The generative artificial intelligence (AI) in logistics market covered in this report is segmented -

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.

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Which Region Dominates the Generative Artificial Intelligence (AI) in Logistics Market?
North America was the largest region in the generative artificial intelligence (AI) in logistics market in 2024. 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, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

What Is Covered In The Generative Artificial Intelligence (AI) in Logistics Global Market Report?

- Market Size Analysis: Analyze the Generative Artificial Intelligence (AI) in Logistics Market size by key regions, countries, product types, and applications.
- Market Segmentation Analysis: Identify various subsegments within the Generative Artificial Intelligence (AI) in Logistics Market for effective categorization.
- Key Player Focus: Focus on key players to define their market value, share, and competitive landscape.
- Growth Trends Analysis: Examine individual growth trends and prospects in the Market.
- Market Contribution: Evaluate contributions of different segments to the overall Generative Artificial Intelligence (AI) in Logistics Market growth.
- Growth Drivers: Detail key factors influencing market growth, including opportunities and drivers.
- Industry Challenges: Analyze challenges and risks affecting the Generative Artificial Intelligence (AI) in Logistics Market.
- Competitive Developments: Analyze competitive developments, such as expansions, agreements, and new product launches in the market.

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