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AI in Transport and Logistics: Current Applications & What is to Come

April 3, 2025

The transport and logistics industry is undergoing a significant transformation, primarily driven by the rapid advancement of technology. At the forefront of this shift is artificial intelligence (AI), which is reshaping how organisations optimise supply chains, manage fleets, and overcome operational challenges. But what exactly are its current applications, and what potential does it hold for the future of the sector?

The Role of AI in Transport and Logistics

The role of AI in the transport and logistics industry is to increase efficiency across supply chain and distribution processes. This is achieved through its ability to process vast amounts of data, make intelligent decisions, and predict outcomes.

For instance, AI-driven sensors can monitor warehouse inventory in real time, automatically adjusting stock levels to match demand. This lessens waste, prevents shortages, and accelerates order fulfilment.

Moreover, real-time data collected via AI-powered systems feeds back into predictive analytics, allowing fleet managers to support distribution by optimising routes and thereby reducing fuel consumption while improving customer satisfaction.

The Benefits of AI in Transport and Logistics

1. Enhanced Supply Chain Visibility

Logistics operations are vulnerable to various disruptions, including labour shortages, geopolitical tensions, and natural disasters. For logistics managers and fleet operators, maintaining comprehensive visibility across the supply chain is vital for effective risk management.

AI’s predictive capabilities enable operators to identify potential threats in advance, assess their impact, and implement proactive contingency plans. By leveraging AI-based insights, they can minimise disruptions, maximise resource allocation, and ensure a more resilient supply chain.

2. Streamlined Communication and Collaboration

AI empowers fleet managers and logistics operators to strengthen communication by providing real-time updates and forecasts to suppliers, partners, and customers. Specifically, using AI-driven data, they can generate accurate ETAs, predict demand fluctuations, and refine delivery schedules.

A higher degree of transparency fosters trust, strengthens collaboration across the supply chain, and facilitates faster, data-driven decision-making. This both elevates operational efficiency and customer satisfaction by guaranteeing timely and reliable service.

3. Optimised Asset Utilisation

AI-powered systems use historical data and real-time insights to anticipate demand fluctuations and inventory changes. This helps logistics operators to adjust inventory levels to make sure that the right products are available at the right time and place.

Similarly, AI enhances fleet management by predicting demand hotspots and directing vehicles accordingly. In turn, managers can eliminate unnecessary journeys and optimise route planning, resulting in lower fuel consumption and improved overall efficiency.

4. Task Automation

AI can complete administrative tasks that traditionally consume valuable time and resources. By automating processes such as data entry and invoicing, AI reduces operational costs and allows logistics and fleet managers to focus on higher-value tasks.

5. Increased Fleet Productivity

Maintaining a fleet can be costly, and unexpected breakdowns add to expenses. AI-based predictive maintenance helps managers stay ahead of potential issues by analysing sensor data and performance patterns to detect early signs of wear and tear.

Determining maintenance needs before failures occur means operators can schedule preventive repairs, minimise downtime, and extend vehicle lifespan. This proactive approach not only improves reliability, but also decreases total maintenance costs.

The Potential of AI in Transport and Logistics

While AI offers numerous advantages, it still has limitations when it comes to mapping every variable, restriction, and real-world condition. Algorithms struggle to account for unexpected disruptions, and the general dynamic nature of transport and logistics.

This is where human expertise remains essential. Logistics and fleet managers play an integral role in interpreting AI-driven insights, applying industry knowledge, and making strategic decisions that AI alone cannot fully address. Rather than replacing human input, AI serves as an increasingly valuable tool to amplify efficiency and drive innovation.

At MICHELIN Connected Fleet, we recognise AI’s transformative potential and have already integrated it into our fleet management solutions. From AI-powered dash cams that detect and prevent incidents to advanced data analytics that optimise workflows, our technology enables logistics operators and fleet managers to stay ahead in a competitive industry.


If your logistics company or business is looking to gain a competitive edge, then be sure to make an enquiry into how we can support your operations today.
MICHELIN Connected Fleet

Written by MICHELIN Connected Fleet

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