Smarter logistics can drive sustainability gains

Artificial Intelligence is redefining logistics sustainability by transforming fleet maintenance, routing, and operational efficiency across the supply chain.

Freight and logistics contribute significantly to global greenhouse gas emissions, with freight alone accounting for about 7% of the worldwide total. As the demand for swift and flexible delivery soars, inefficiencies such as underserviced fleets, empty mileage, and poor planning are not only eroding profits but also amplifying the environmental impact of logistics. The industry faces mounting pressure to adapt, seeking innovative solutions to shrink this footprint without sacrificing performance or reliability.

Artificial Intelligence is emerging as a pivotal force for sustainability gains in logistics, targeting unexpected areas like fleet maintenance. Overservicing vehicles wastes resources and time, while neglect leads to breakdowns and inefficient asset replacement. Predictive and optimised maintenance, driven by Artificial Intelligence, is gaining popularity, especially in North America, where industry standards are setting the stage for widespread adoption. The Vehicle Maintenance Reporting Standards (VMRS), developed by the American Trucking Association’s Technology and Maintenance Council, are central to this transformation, providing a universal language for maintenance data. These frameworks enable Artificial Intelligence systems to make adaptive decisions, such as scheduling oil changes based on engine load and usage instead of inflexible schedules, reducing both unnecessary resource consumption and costly downtime.

Beyond maintenance, Artificial Intelligence is reimagining how freight is planned and executed. Empty mileage—wasted trips without cargo—remains a colossal challenge. Artificial Intelligence-powered platforms today analyse real-time and historical data, offering continuously optimised routing, dynamic load planning, and automated transport procurement. Such systems not only minimize waiting times and make better use of vehicle capacity, they also help reduce the frequency and length of journeys, cutting overall emissions. With collaborative, standardised data practices, these advancements are scalable, promising sector-wide impact through interoperable platforms and shared datasets. While Artificial Intelligence itself has an energy footprint, its role in streamlining logistics is already yielding net positive effects for sustainability. The journey hinges on industry-wide collaboration among carriers, shippers, technology providers, and original equipment manufacturers, ushering logistics into a smarter, cleaner future where every operational decision moves the sector closer to climate goals.

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