There is a lot to do. Let's do it. This is a motto from advertising. And who wouldn't want technology to help them with complex problems or support them in dull tasks? We take a look at fields of application for artificial intelligence (AI), which has been very much in the public eye lately, in our industry.
Waiting at a red light at an intersection while there are no cars as potential oncoming traffic on the other three roads nags at drivers who are under time pressure. Who - for example, as a truck driver in road haulage with a tight schedule - would not wish for an intelligent traffic guidance system at such a moment that proactively switches to "green", literally.
Many logistics experts see such a scenario as an exciting, positively connoted field of application for artificial intelligence. It is not the only one that was considered in the transport business in the course of 2023 - after generative AI, especially in the form of the texting programme ChatGTP, dominated the news for many weeks, even outside the IT world. Horror scenarios and options for the future were discussed for almost every sector and special discipline under the pressure to change.
Don't use AI for AI's sake
If exaggerated visions that fear the rule of machines, as once shown in the "Terminator" films, are ignored, any technical progress in road haulage will of course encounter the central challenges that exist here in real everyday haulage. A shortage of skilled workers, whether at the steering wheel or at the ramp in the hub, cost pressure, the desire for more sustainability (not only) in the transport sector and the infrastructure problems are omnipresent in this context.
In this respect, it is not surprising that two fields of application stand out in particular in the contributions on the (future) use of AI: On the one hand, as indicated above, an optimised flow of goods through AI-controlled traffic management systems and, on the other hand, the leveraging of potentials in simple, recurring processes in everyday logistics.
Big Data as an invisible hand in traffic
In view of the immense data that can now be obtained regarding traffic volume, load status or even the conditions both at the point of departure and at the destination, AI-based guidance of transport routes offers the possibility of saving valuable time and unnecessary emissions in a resource-saving manner. What truck driver, faced with annoying hours in a traffic jam, does not wish for a free ride? Unnecessary exhaust gases in stop-and-go can also be avoided in this way.
Whether all the ideas envisioned in this context can be realised quickly also depends on the legislator. Anyone who has followed the discussions about the autonomous driving of the first Tesla cars and the legal issues discussed in this context will be able to imagine what needs to be decided on in terms of the necessary regulations for AI-controlled control structures.
Scan, organise and file 4.0
Every industry representative, not only those from the administrative arm of logistics, knows about the extensive documentation requirements for every transport. The recording, interpretation and archiving of documents is rarely exciting - but all these work steps are indispensable for a complete presentation of the transports and their billing.
The experts see a lot of savings potential here through the AI-fuelled trio of standardisation, digitisation and automation, which must be exploited in the future. The personnel resources thus freed up are generally put to more purposeful use in other task areas that require human creativity and flexibility in an industry plagued by a shortage of skilled workers.