United Parcel Service (UPS) implemented a package flow system nearly 50 years ago using a computer network to automate sorting and optimize delivery routes. Although it did not involve the advanced AI technologies we have today, this system from the world’s largest package delivery company laid the groundwork for integrating automated processes into logistics operations.
Since then, the use of AI in logistics has continued to evolve and expand, with companies adopting sophisticated algorithms, machine learning, and robotics to enhance efficiency and decision-making.
Today, there is hardly any segment of the transport and logistics industry untouched by artificial intelligence.
“This is a robot, your new colleague.”
Greater efficiency and productivity, lower costs, reduced room for errors caused by human factors, and addressing labor shortages are some of the leading reasons companies are incorporating AI-driven technology into their operations.
The first application segment worth mentioning is route optimization. Automatic route planning practically uses AI to sift through vast amounts of data – such as weather conditions, road events, weekend and holiday driving restrictions, roadwork, traffic congestion, vehicle performance, delivery schedules, and other related factors. This determines the most efficient and cost-effective routes for timely delivery while also avoiding empty trips.
Lithuanian Girteka, one of Europe’s largest road transport companies, recently revealed interesting details from its practice. Artificial intelligence collects data about their fleet of over 9,000 trucks, which is then entered into the company’s AI Operator along with information about road conditions, safe parking, and available gas stations. The system defines the route and provides the driver with instructions “from A to Z”: where to go, which route to take, where to take mandatory breaks, and where to refuel the vehicle.
Autonomous vehicles take the next spot on the list. From forklifts in warehouses to heavy trucks, artificial intelligence is crucial in providing the adaptability needed for autonomous vehicles to navigate and make informed decisions. AI processes data from sensors, cameras, and lidars to interpret the environment and make real-time decisions, enable communication between autonomous vehicles, and has the capability of so-called “predictive analytics.”
On one hand, driverless vehicles in the future can be a way to fill chronically vacant jobs and at least partially solve the problem of driver or warehouse worker shortages. At the same time, they are also “tools that enhance human talent,” as one of the founders of the Croatian startup Gideon said while presenting their autonomous forklift, “Tray.”
Warehouse logistics is an area where AI usage may have advanced the furthest. Artificial intelligence optimizes inventory levels, reducing excess and preventing accumulation, for more efficient supply chain management. Various robots automate tasks in warehouses, improving speed and accuracy in processes such as picking and packing.
There are countless examples: an interesting one comes from Berlin where Amazon Fulfillment Technologies developers have developed advanced artificial intelligence that can spot irregularities and mark damaged goods before delivery to the customer. Amazon innovation managers claim that this AI system is three times more efficient than manual identification of damaged products.
Artificial intelligence in transport and logistics is also used in predictive maintenance, demand forecasting, smart traffic management, chatbots for customer support, in combination with blockchain to improve transparency and traceability, and many other areas.
And the cost counts.
Despite the clear advantages of using AI in the logistics chain, many companies face obstacles in adopting such technology.
First and foremost are the costs – often requiring significant investments in software and hardware, which can be a big bite for smaller firms. Then there is the necessity of constant maintenance and updating to ensure that the system provides accurate results and operates correctly over time. Also, a problem may arise from the lack of personnel to maintain and manage the system. We must not forget the questions of data privacy protection as well as compliance with regulatory requirements which often vary from state to state.
Although artificial intelligence, of course, is not the answer to all questions and problems in the logistics chain, current trends clearly show that its influence will continue to grow in the future. For example, more than 70% of participants in a German study, “Digitalization in Logistics,” in 2019 believed that AI would be indispensable for this industry in ten years, but at that time, less than 15% of them were using it. Just three years later, 22% of surveyed German logistics companies were using AI, and 26% were negotiating its implementation. Over half (58%) stated that artificial intelligence would become widely used and take over many tasks in the near future.
