AI in Logistics & Supply Chain:
17 Best Use Cases for 2025

Logistics and artificial intelligence are a match made in heaven at first glance. So, it should be no surprise that 82% of the space is occupied by AI supply chain companies*. The question is, should you join them?

In essence, logistics are just the practice of strategically moving numbers around. Excuse the gross over-simplification, we’re making a point. AI is uniquely able to work with large data sets while making careful, logical decisions. So, unsurprisingly, it excels.

But it’s actually more than that. AI in transportation and logistics is completely revolutionizing the industry from the ground up. And we’ll show you how with our 17 best AI in supply chain examples. Keep reading to learn more!

Key Takeaways:

• AI in logistics enhances efficiency by automating workflows, predicting demand, and optimizing transportation and warehouse operations.
• AI use cases include demand forecasting, real-time tracking, warehouse robotics, route optimization, and fraud prevention, improving supply chain performance.
• CloudTalk’s AI-powered calling solution streamlines supplier communication, automates call routing, and enhances coordination for seamless operations.

What Is AI in Logistics?

AI in logistics encompasses a wide range of software tools and solutions, ranging from demand forecasting and route optimization to predictive maintenance and real-time tracking. Overall, its goal is to raise efficiency and lower costs in the supply chain.

To do so, AI for supply chain optimization combines machine learning algorithms (ML) with computer vision, robotics, and natural language processing (NLP) to analyze data, identify patterns, and automate workflows.

What Are the Benefits of AI in the Supply Chain?

These solutions provide numerous benefits, from helping you improve delivery times, reduce fuel consumption, manage inventory more effectively, and even have better, more productive conversations with providers and customers alike.

More specifically, according to Capgemini’s The Future of Logistics, AI has contributed significant improvements to supply chain performance via use cases in traceability, quality control, and strategic planning, leading to:

• 22% increase in operational efficiency 
• 18% decrease in product defects 
• 15% decrease in logistics costs
• 35% decrease in inventory levels
• 65% improvement in service levels

17 Best Logistics AI Use Cases & Examples for Supply Chain Efficiency

As explained in the previous sections, there are numerous examples of supply chain AI use cases from which to draw inspiration if you’re looking to improve specific aspects of your business. Below, we’ll introduce you to the 17 most important ones:

AI-Driven Demand & Inventory Optimization

Managing inventory and forecasting demand are critical components of supply chain efficiency. But as we’ll discuss, you can take advantage of AI-powered solutions to analyze data to optimize stock levels, minimize waste, and improve coordination.

#1: Demand Forecasting

You can use machine learning in the logistics industry to predict future demand by analyzing historical data, market trends, and external factors. This helps you optimize inventory, reduce stockouts, and improve order fulfillment.

For example, Loadsmart, a freight technology provider, embedded a generative AI tool in its systems that allowed shippers to generate reports, maps, and charts based on internal data simply by asking questions.

#2: Inventory Management

Having too much or too little stock is a never-ending issue companies face, leading to overfilled warehouses or, in the other extreme, delays in manufacturing and shipments due to missing vital materials and components.

For example, Gaviota, an automated sun protection and shutter maker, deployed the SO99+ AI solution that defined optimal inventory levels across the company’s supply chain to ensure service level success while slashing stock levels by 43%.

#3: Supplier Selection & Management

Equally problematic can be the process of finding and selecting providers that can meet your business requirements in an agile way. Requesting proposals can be particularly time-consuming and paper-intensive. 

Thankfully, tools like Verusen’s Trusted Supply application and its contemporaries are able to improve the match rate for materials requested through ML-enabled recommendations and their natural language interfaces.

AI for Warehouse Management & Automation

Warehouses are at the heart of supply chain operations, and AI is helping businesses improve efficiency by automating tasks, optimizing space, and predicting equipment failures to prevent unscheduled downtime and save money on breakdowns.

#4: Warehouse Robotics

Thanks to advancements made in robotics, warehouse operators are now able to increase efficiency in picking, packing, and sorting operations. These solutions range from real-time updates regarding stock to customer-facing deliveries. 

For example, Symbiotic, a provider of AI-enabled robotics of supply chains, offers case-pick capabilities that help distributors serve customers faster, such as in the Utah-based Associated Food Stores.

#5: Predictive Maintenance

With revolutionary tools, such as computer vision and internal Internet of Things (IoT) networks, you can predict and prevent breakdowns, even caused by rare factors that a human wouldn’t be able to anticipate, saving thousands per issue.

The Railcar Inspection Portal (RIP) from Duos Technologies is a prime example, leveraging algorithms to identify problems with railcars used in shipping, which allows maintenance workers to act before standard wear and tear tears into their wallets. 

#6: Warehouse Management

Warehouses are incredibly sizable operations, part of an even bigger whole. As such, it can be very easy to lose track of what’s going on and where, often to great detriment for the company. Thankfully, AI can help here, too.

Tools like AutoScheduler.AI and Synkrato are able to improve operations by keeping track of all ongoing operations and responsible workers while also creating a real-time 3D representation of the warehouse to help with navigation.

AI in Transportation & Logistics

AI-driven transportation solutions enhance delivery efficiency, reduce operational costs, and improve customer satisfaction. AI is transforming logistics operations worldwide, from optimizing routes to enabling autonomous delivery.

#7: Last-Mile Optimization

The last-mile problem remains one of the biggest cost drivers in logistics, with unpredictable delays, inefficient routing, and delivery failures leading to wasted resources. But real-time visibility is able to solve that issue.

For example, TXI’s AI-powered delivery systems use smart sensors, driver input, and location tracking to streamline last-mile logistics. By analyzing traffic patterns, weather conditions, and environmental factors, AI improves delivery times and drive experiences.

#8: Inbound Logistics

Coordinating inbound logistics can be a complex challenge, especially when managing multiple suppliers and delivery assets. Without an efficient system in place, delays, miscommunications, and inefficient asset use can lead to costly bottlenecks.

For example, an auto manufacturing giant is piloting nuVizz’s RoboDispatch Solution to automate trailer dispatching. Using AI, RoboDispatch dynamically assigns shipments to the best available fleet driver, ensuring on-time deliveries and reducing inefficiencies.

#9: Real-Time Shipment Tracking

Given the distances cargo travels, unexpected delays and issues are a completely expected part of the job. But they don’t have to be. Thanks to advanced algorithms, you can accurately predict weather changes for current and future shipments alike.

For example, solutions like Movement GPT are able to make sense of large data sets and accurately answer any shippers’ questions, like “Is my shipment to Amsterdam negatively affected by the storm in the North Atlantic?”, in natural language.

AI-Powered Supply Chain Communication & Automation

Seamless communication and process automation are vital for an efficient supply chain. AI-driven tools streamline procurement, enhance customer interactions, and improve overall logistics coordination.

#10: Automated Customer Support

Customer service in logistics is often bogged down by repetitive inquiries, making it harder for teams to focus on complex issues. AI-powered chat and self-service tools help businesses streamline support while improving response accuracy.

For example, eezyimport’s AI tool helps small importers classify goods by converting text into harmonized tariff schedule (HTS) codes. Using ML, suggestions are refined over time, allowing shippers to enter detailed descriptions for more precise results.

#11: AI in Procurement & Automation

Finding the right suppliers can be a slow, complex process, often leading to inefficiencies and delayed responses. AI streamlines procurement by matching businesses with the best suppliers while improving negotiation transparency.

For example, Procureship’s AI-powered platform accelerates e-procurement for marine equipment by recommending suppliers through machine learning. Its marketplace-driven approach simplifies purchasing, reducing delays and improving supplier collaboration.

#12: AI for Call & Customer Service Automation

Communication is a crucial aspect of every well-oiled supply chain. Whether you’re reaching out to potential customers, prospective providers, or just answering service questions, you need to ensure all your calls are crystal clear.

Tools like CloudTalk’s AI-powered business communication software help companies save time and effort with their Conversational Intelligence, automating call recording and transcription while giving them insights into call sentiment, topics, and performance. 

Combined with the provider’s wide offer of 1+ international numbers, + native integrations with leading 3rd party software, and numerous automation opportunities, it can help you make 300% more calls daily.

#13: Returns Management

Handling returns efficiently is a major challenge for retailers, often leading to lost revenue and logistical headaches. AI helps by analyzing return patterns, identifying root causes, and optimizing the entire reverse logistics process.

AI-powered chatbots can guide customers through returns while machine learning models suggest improvements,  refine product descriptions, determine the most cost-effective return routes, factor in warehouses, shipping options, etc.

AI for Supply Chain Optimization & Sustainability

AI is playing a crucial role in making supply chains more sustainable and resilient. From optimizing energy consumption to improving fraud detection, AI helps businesses achieve operational excellence.

#14: Energy Management

Measuring carbon emissions across supply chains is challenging, especially when dealing with fragmented data from multiple sources. AI simplifies this process by integrating and analyzing emissions data to support sustainability efforts.

For example, BlueNode’s and Yara Marine Technologies’ AI solutions help track Scope 3 emissions from ports, carriers, and shippers, enabling informed carbon mitigation strategies while reducing fuel consumption and environmental impact.

#15: AI for Worker Safety 

Long hours, unpredictable conditions, and tedious administrative tasks can contribute to worker fatigue in logistics. AI helps by optimizing workflows, automating paperwork, and flagging hazardous conditions to improve overall job satisfaction.

AI-powered safety systems can detect extreme weather risks and automatically recall delivery drivers in dangerous conditions. By reducing unnecessary exposure and streamlining daily tasks, AI enhances both efficiency and employee well-being.

#16: AI for Customs & Clearance

Navigating customs can be time-consuming and error-prone, with paperwork bottlenecks delaying shipments. AI streamlines the process by automating documentation, reducing errors, and ensuring regulatory compliance.

For example, KlearNow.AI’s Customs Engine uses deep learning to digitize customs filings, eliminating manual data entry. Automatically generating importer security filings and transmitting them to authorities helps move goods faster and more efficiently.

#17: Cargo Theft

Cargo theft remains a persistent issue in logistics, leading to significant financial losses. AI enhances security by improving incident response times, detecting risks in real-time, and automating corrective actions.

For example, Overhaul’s RiskGPT provides AI-driven risk assessment for in-transit shipments. Trained on Overhaul’s proprietary data, it enables shippers to respond to security threats instantly, mitigating risks and ensuring cargo safety.

Remove Confusion from the Supply Chain with Crystal-Clear AI-Powered Calls

Clarity in the supply chain is paramount. Whether you’re trying to find out where your shipments currently are, selling products to a prospective customer, or just bargaining for the best deal possible with your providers, you need to be able to communicate clearly.

With CloudTalk, you can be sure that all it comes down to is your ability. No jitter or dropped calls, just efficient conversations at scale, fueled with powerful automation and AI tools, such as our AI Dialer and AI Smart Notes. Now for 30 days free.

Sources:

1. GlobalTradeMag