The application of artificial intelligence (AI) in logistics has enabled a radical change in the work system in the supply chain. Thanks to AI, companies have moved from a reactive scheme, in which logistics operations adapted to variations in demand, to a proactive one, in which managers anticipate market behavior and adapt their resources accordingly. In this way, there is an improvement in efficiency and an increase in profitability. Randall Castillo Ortega, an entrepreneur and expert in import/export operations, explains how AI can help export companies improve their logistics operations.
Castillo gives systems the ability to make intelligent decisions and execute automated operations without any human intervention. It is based on a combination of three elements, algorithms, ordered sequences of operations that are applied to carry out a task optimally based on the prevailing conditions; software, which dictates the precise instructions for the execution of each of the tasks by the hardware; and machine learning, developments that allow the machines themselves, relying on the recorded history and the repetition of operations, to learn and improve the processes themselves gradually.
Applications of AI in logistics are still under development, with a view to reaching their full potential within a few years. However, some are already settling in the sector. For example, they can predict consumption trends. “AI makes use of big data for logistical purposes,” explains Castillo. “It crosses internal information such as sales history with data extracted from forums, social networks or other internet sources. In this way, it is able to issue deductions on the consumption intention of users and predict the behavior of demand. This serves to put in place anticipatory logistics and prevent stock breaks or avoid storing excess goods. The waste of resources is, therefore, mitigated.”
One of the greatest exponents of AI in logistics are automated warehouses. They combine two fundamental systems: robotics applied to the winery and management software. Together, they carry out transport and product placement operations autonomously. Asserts Castillo, “This shared work generates patterns over time that are continuously analyzed. In this way, AI helps them to assign the ideal resource to each of the tasks that arise, as well as to adapt their movements in case of variations in the circuit.”
The coordination of logistics transport is simpler with AI and adopts two aspects. The first is intralogistics displacement management or warehouse management software that keeps a digital x-ray of the company’s facilities and records all movements. It processes this data and organizes the movements of goods, whether they are carried out by robots or automatic systems or by operators assisted by handling equipment.
The second is freight fleet management. AI interprets and incorporates up-to-date traffic information into local systems. With this, the software traces the most suitable routes for the delivery of the different goods, and corrects the itineraries in real-time in case of incidents.
Process automation in the enhanced supply chain with the presence of AI opens the door to real-time inventory maintenance, instant supply orders issuance, or accurate order tracking. Warehouse management software makes it easy to schedule all these actions in the day-to-day of the warehouse.
In addition, the integration of data and the improvement of traceability systems allows responding to the user’s need to know. For example, the usual question of where the package purchased in an eCommerce company is located can be solved quickly and effectively with the implementation of chatbots equipped with AI.
Thanks to AI in logistics, the risk of error is reduced and, therefore, the supply chain works with more precision, fewer inefficiencies occur and most repetitive operations are left in the hands of automatic systems that learn over time, to leave creative processes and strategic decision-making in the hands of people.