Generative AI in Logistics Market size is evaluated at USD 1.5 billion in 2024 and is expected to exceed USD 37 billion by the end of 2037, expanding at over 33.5% CAGR during the forecast period i.e., between 2025-2037. In 2025, the industry size of generative AI in logistics is estimated at USD 454.7 million.
Generative AI in supply chains provides an opportunity to accelerate end-to-end logistics operations and companies have identified this trait and are training models on their own data sets to implement AI for optimized productivity and efficiency. Also, predictive maintenance is another key area where generative AI has helped companies determine the assembly-line machines that are most likely to fail in the future, thus improving equipment effectiveness (OEE)- a vital manufacturing metric. Siemens and Microsoft partnered in October 2023 to strategically adopt cross-industry AI, orchestrating copilots for raw material management, distribution networks, production processes, and customer demands.
Such supply chain responsiveness, resilience, and efficiency dictate an organization’s competitiveness. Conventional supply chain management solutions rely on experience-driven decision-making and established methodologies, where logistic partners navigate the complexities of inventory management, demand forecasting, and distribution scheduling using heuristic algorithms and historical data analysis. These methods often failed to address modern logistics complexities and in turn, aided generative AI in logistics market adoption. The manufacturing and logistic sectors are fertile grounds for generative AI applications, owing to demand fluctuations and the presence of intricate supply chain networks.
The emergence of ChatGPT in the public sphere ignited an interest in the AI chatbot sector. Microsoft's announcement of a USD 10.0 billion investment in OpenAI in January 2023 galvanized this trend, imploring other technology providers to contest the trend. Later in March 2023, Google introduced Bard and Project Magi, while in February 2023 Meta unveiled a language model with 65 billion parameters called LlaMA. Concurrently, OECD data also suggests that AI could readily automate 27% roles in the OECD nations, including inventory management and customer service. Early adopters of AI-powered supply chain management recorded a reduction in logistics costs by 15%, improved service levels by 65%, and inventory levels by 35%.
Growth Drivers
Challenges
|
Base Year |
2024 |
|
Forecast Year |
2025-2037 |
|
CAGR |
33.5% |
|
Base Year Market Size (2024) |
USD 1.5 billion |
|
Forecast Year Market Size (2037) |
USD 37 billion |
|
Regional Scope |
|
Component (Software, Solution)
Solution segment is projected to account for around 53.1% generative AI in logistics market share by 2037. This market category mostly consists of all-inclusive software programs and systems that are made to smoothly fit into current logistics processes and provide end-to-end automation and optimization features. The market's desire for comprehensive, instantly deployable systems that handle a wide range of logistical difficulties, from inventory management to route optimization, is highlighted by the prominence of solutions over discrete software components. Although crucial, the software subsegment usually consists of standalone programs or instruments that address particular facets of the logistics procedure. While these tools are essential for focused enhancements, they do not provide the extensive range of features found in full solutions.
Deployment (Cloud Based, On-premise)
By the end of 2037, cloud segment is expected to account for more than 63.9% generative AI in logistics market share. The benefits of cloud computing for logistics and its capacity to optimize processes are credited with the segment's rise. Logistics companies' significant data storage needs for operations management and analysis serve as a driving force behind the segment's growth. For instance, 21% of supply chain executives have integrated cloud-based technologies throughout their workflow. 97% of them have approximately 3/4 of their supply chains operating in the cloud.
Logistics service providers can track and manage supplies, shipments, and delivery in real-time due to cloud-based logistics management systems. Logistics service providers can save costs and boost efficiency by leveraging this real-time data to better correctly estimate inventory levels, delivery timetables, and route optimization. Cloud computing also facilitates better customer and supplier collaboration for logistics service providers. Logistics organizations can improve coordination and collaboration by sharing information and data in real-time with their suppliers and customers through the use of cloud-based communication technology.
Our in-depth analysis of the generative AI in logistics market includes the following segments
|
Component |
|
|
Deployment |
|
|
End user |
|
North America Market Analysis
North America in generative AI in logistics market is projected to dominate over 44.9% revenue share by 2037. The increasing adoption of modern automation solutions for various industry operations and the growing use of technology in every sector is credited with the region's success. The major sectors' growing demand for supply chain management and logistics, along with the expanding industrial infrastructure, are driving up the need for generative AI in logistics throughout the region. By investing USD 40 billion in new machinery, United Parcel Service, Inc. was able to increase its daily processing capacity from 60 million packages in 2022 to 70 million packages in 2023.
The U.S.' supremacy in the logistics industry can be ascribed to its substantial investments in AI research and development, the country's robust tech giant presence, and its innovative culture. Furthermore, the sophisticated infrastructure in the area facilitates the smooth integration of IoT and AI technologies, augmenting operational effectiveness.
Asia Pacific Market Analysis
Asia Pacific in generative AI in logistics market is expected to experience a stable CAGR during the forecast period due to the rise in the region’s population. Every other industry experiences a surge in demand for inventory owing to the growing need for lifestyle products ranging from everyday necessities to technical necessities. There will be a greater need for generative AI in the logistics business as supply chain and logistics management become more sophisticated.
Driven by rising disposable incomes and economic growth, China is gradually emerging as a center for generative AI in the logistics sector. China is leading the way in AI investment which propels advances in generative AI for logistics, including predictive maintenance and AI-driven route optimization.
The varied supply chain environment in India encourages the use of generative AI to improve supply chain visibility, expedite logistical procedures, and reduce risks. The country adopts cutting-edge technologies like blockchain and IoT and combines them with generative AI to build reliable logistics solutions that save costs and increase productivity. For instance, in June 2023, the logistics technology company Pidge, which has already offered its services in numerous large and medium-sized Indian cities, proclaimed the arrival of digital parity in the mostly unorganized logistics industry. With its first industry low-code and self-serve logistics (Software-as-a-services) technology platform, the launch will completely alter the logistics business.
With generative AI in logistics market shares of more than 15%, Google Cloud and IBM are the leaders in the generative AI space in the logistics sector. TensorFlow and AutoML, two of Google Cloud's AI and ML tools, enable logistics firms to create complex generative AI models. Because of the flexibility and agility of its cloud architecture, real-time data processing and analysis for logistics optimization is made possible. Logistics organizations benefit from Google's proficiency in data analytics and AI-driven insights, which enhance supply-chain visibility, demand forecasting, and route optimization.
With products like Watson AI and IBM Cloud Pak for Data, IBM offers cutting-edge generative AI capabilities specifically designed for the logistics sector. Predictive analytics, anomaly detection, and intelligent decision-making in logistics processes are made possible by its AI-driven solutions. Low latency and data protection are ensured by IBM's expertise in edge computing and hybrid cloud, which makes AI adoption across distributed logistics networks easier.
Here are some leading players in the generative AI in logistics market
Author Credits: Abhishek Verma
Copyright © 2024 Research Nester. All Rights Reserved
FREE Sample Copy includes market overview, growth trends, statistical charts & tables, forecast estimates, and much more.
Have questions before ordering this report?