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Artificial intelligence in logistics

Artificial intelligence in logistics

Artificial intelligence in logistics

Artificial intelligence gives systems the ability to intelligently make decisions and execute automated operations without human intervention. It is a technology that can help transportation and logistics companies differentiate themselves from their competitors, provide better service, or reduce costs.

However, figures indicate that currently 40% of Spanish companies in the sector have no artificial intelligence project at all, compared to 23% of the world average.

In spite of these data, it is not science fiction, since, like the autonomous ships we have already talked about, many companies are going to include this type of technology in the medium term in order to improve their logistical processes.

Logistics applications

The applications of artificial intelligence in logistics are still under development, with a view to reaching their full potential within a few years. However, there are some that have already begun to be used:

  • Automated warehouses. They combine robotics applied to the warehouse and management software. In this way, transport and product placement operations are carried out autonomously.
  • Selection of transport routes with the most efficient displacements. The software traces the most suitable routes for the delivery of the different goods and corrects the itineraries in real time in the event of incidents.
  • Greater control of information in the supply chain. Process automation, enhanced by the presence of artificial intelligence, opens the door to real-time inventory maintenance, instant supply order issuance or accurate order tracking.

Three elements

Artificial intelligence is based on three aspects:

  • Algorithms, orderly sequences of operations that are applied to carry out a task optimally according to the starting conditions.
  • Software, which dictates the precise instructions for the execution of each of the tasks by the hardware.
  • Machine Learning, that is, developments that allow the machines themselves, based on the recorded history and the repetition of operations, to learn and improve the processes themselves gradually.

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