The Global AI in Logistics and Supply Chain Market Ecosystem was valued at USD 1.7 bn in 2018 and is expected to reach USD xx.xx million in 2026, growing at a CAGR of 45.5% by 2027.

The on-going evolution of technologies like artificial intelligence (AI) and machine learning (ML) brings in disruption and innovation in the AI Logistics and Supply Chain Ecosystem. The efficiency of a company in network planning and predictive demand are getting improved with AI capabilities. Companies are becoming more proactive with tools and technology that can help with accurate demand forecasting and capacity planning. With the help of AI technology, market expectations can be tapped, by which people working in this area can quickly move vehicles to the exact locations where demand is more. Thus, it helps in bringing down operational costs.

AI is transforming global logistics and supply chain management. Merck, a well-known Pharmaceutical company in the US, deployed a suite of sensors coupled with machine learning predictive analytics software to improve its inventory and distribution efficiency. Dematic, a U.S-based Software company, acquired Reddwerks (a startup in WES space) to create its own WES based on Reddwerks’ Distribution Science, which is called Dematic Reddwerks. Dematic Reddwerks’ warehouse management operations are identifying efficient picking density for warehouse robots. Companies like Waymo, Rolls-Royce are coming up with driverless vehicles such as trucks and underwater ships which will speed up the delivery process, optimize routes, reduce human errors and accidents, work 24/7, and more. According to our estimates, the Global AI in Logistics and Supply Chain Ecosystem was valued approximately USD 1.7 Billion in 2018.

Figure 1: Ecosystem Snapshot: Artificial Intelligence in Logistics and Supply Chain Market

Companies like DHL Supply Chain has invested $300 million to modernize 60 percent of its warehouses in North America with the help of Artificial technology. This will reduce workflow interruptions in DHL and make logistics smoother. More than 4 million commercial robots will be installed in over 50,000 warehouses by 2025. Amazon, a leading E-commerce company, is expanding its delivery capabilities by launching Amazon's all-electric Prime Air drone, which is expected in 2020, for autonomous delivery of packages to customers. The company has hired 20 aircrafts to handle its 30mins delivery offer.

Several companies like UPS is using an AI-powered GPS tool called ORION for making efficient routes for its fleet and for making changes in real time to account for road conditions and other factors. By optimizing delivery efficiency, the company estimates that it will save $50 million a year. In retail clothing, brands such as Gap Inc. is using AI-assisted mechanical arms to help sort clothing orders. In North America and Europe, companies like Connecticut-based XPO Logistics Inc. has begun the roll-out of 5,000 intelligent robots throughout its logistics sites for bringing mobile storage racks full of products to workers who fill customer orders.

Figure 2: Artificial Intelligence: Segmentation of AI in Logistics and Supply Chain Ecosystem

Components Offering Application Technology Deployment End -User Micro Processors Solution Fleet Management Predictive Maintenance/Self Diagnostics Cloud Automotive Memory Services Supply Chain Planning Machine learning On-Premise Aerospace Storage Warehouse Management Deep learning Manufacturing FPGA Virtual Assistant NLP Retail GPU Risk Management Computer Vision Healthcare Camera Freight Brokerage Predictive Analytics Others Sensors Others Connectivity IC Others

Global AI in Logistics and Supply Chain Ecosystem

Globally, artificial intelligence in Logistics and Supply Chain is growing at a fast pace and so, by 2030, one-third of workers in the U.S. will need to switch occupations due to increased use of robotics. While Amazon leads the way, other companies, including carriers such as FedEx and DHL are testing and developing robotic-based systems to speed operations. According to one estimate, a 10% to 30% increase in efficiency in the EU logistics sector would translate into €100-300 billion in cost savings for the European industry. In Asia pacific, Chinese company Alibaba invested $248 billion in transactions which is more than the investments made by eBay and Amazon in artificial intelligence and machine learning for supply chain and logistics. China is on a path to overtake the United States as the world’s leader in technology.

Figure 3 – Market Statistics Glimpse: AI in Logistics and Supply Chain Ecosystem

There are many trends that are having an impact on the market forecast. These, when evaluated from a company’s perspective, can drive growth. Our numerous consulting projects have generated sizeable synergies across all regions and all sizes of companies.

The major players operating in the global AI in Logistics and Supply Chain Ecosystem are as follows:

Company Ecosystem Positioning Total Revenue Industry Region UPS Service Provider $72 Billion Supply chain and logistics Global FedEx Service Provider $65.45 Billion Supply chain and logistics Global CSX Service Provider $11.4 Billion Supply chain and logistics Global McLane Company Service Provider $50 Billion Supply chain and logistics Global DHL Service Provider $67.76 Billion Supply chain and logistics Global

Very few markets have interconnectivity with other markets like AI. Our Interconnectivity module focuses on the key nodes of heterogeneous markets in detail. Data analytics, Cloud Logistics, Blockchain, Drones, Autonomous vehicles markets are some of our key researched markets.

Figure 4 – Artificial Intelligence Major Interconnectivities Ecosystem

Glance on Global AI in Logistics and Supply Chain Ecosystem Trends:

Trends Components Offering Application Technology Deployment End-User Impact AI-enabled RPA in the transportation & logistics industry allows the vendors to reduce expensive manual functions through automatic acquisition, integration and delivery of data across the supply chain. AI enabled RPA is also used to automate the scheduling process of shipments Service Supply Chain Planning RPA (Transportation & logistics) Others 050% Machine learning makes it possible to discover patterns in supply chain data by relying on algorithms that quickly pinpoint the most influential factors to a supply networks’ success, while constantly learning in the process. Service ML 0.32% Companies are extending the life of key supply chain assets including machinery, engines, transportation and warehouse equipment by finding new pattern in the usage of data collected via IoT sensors Service (Transportation & logistics) Others 0.21% Trend 4 XX xx xx XX Trend 5 XX xx XX

Research methodology: