Artificial Intelligent Agents: Your New Help in Daily Logistics?
No more boring, repetitive tasks!
Game Changer for Logistics: How AI Agents are Changing Processes
In our LogTech Podcast episode with Bernhard Hauser, Jannik and I delved very deeply into the world of AI agents. Bernhard was able to show us clearly that these intelligent helpers not only automate but also effectively understand processes and function independently. Sounds like science fiction, but it isn't!
Do you understand that? How it differs from ordinary automation
Sure, existing automations are great. But AI agents can do so much more. They know processes and can independently give "if-then" recommendations – as long as the space defined by the framework conditions of this task does not turn out to be a dead end. This is a true game changer for logistics. And as Bernhard so aptly put it: We are at a crossroads.
This is closely linked to the recent explosion of large language models (LLMs) like ChatGPT or Claude. These are, in a sense, the "brains" of AI agents. They are becoming more and more powerful and can use tools to communicate with other systems. This makes them so potential.
Saying goodbye to traditional automation as we know it – such as simply reading a delivery note – is the origin of an intelligent decision. Bernhard had a great example ready: Typically, automation is set up so that a document from company A is transferred to folder A. But what happens if the document suddenly comes from company B or C and there is no folder for it yet? An AI agent would know that it needs to create folders B or C and register the document there. It evaluates and makes decisions within a framework – exactly what people expect from automation.
Goodbye Data Silos: How AI Agents Open Old IT Silos
Come on, be honest: Many logistics companies are plagued by data silos and systems that don't communicate with each other. That's a real problem. AI agents, Bernhard added, can play the role of bridge builders in this context. These silos are accessed with tools or interfaces built solely to extract or insert information. Thus, AI agents can help to overcome these obstacles quite quickly and, above all, cost-effectively instead of costly data conversion and migration efforts. This could be a huge opportunity for medium-sized companies with an existing IT landscape.
Especially in document processing (which apparently accounts for about 80% of the day in logistics), AI agents can add a lot of value. They help to understand large amounts of data, extract information from documents, and process it in context. This saves time and nerves – for example, in dispatching. Suddenly, a dispatcher can do business with eight or nine transport service providers at the same time, instead of just five, because all routine tasks are handled automatically. That's a strong statement!
CO2 Footprint vs. Efficiency: A Successful Duo for Green Logistics
Yes, the discussion about the CO2 emissions of AI is necessary and legitimate. But Bernhard gave us an interesting insight: Yes, an AI query is costly. But if it makes only two to three percent of journeys more efficient or eliminates them entirely – keyword: route optimization and fewer empty runs – then the calculation obviously yields a positive result. The added value of the savings is real, and it also pays off in monetary terms. Ultimately, AI agents can even contribute to the ecological footprint of logistics. That's really clever!
The Future of Work: From Job Killer to Job Creator
It is understandable that AI agents could lead to job losses. But Bernhard doesn't see it that way – and neither do we. New roles follow the introduction of new technologies. For example, system design suddenly becomes much more important. AI agents replace some of the monotonous, repetitive tasks. This allows us to focus on things that actually create value. Especially with a shortage of skilled workers in logistics – this is not a threat, but a great opportunity to make existing employees more efficient and, very importantly, more satisfied. AI agents can already do this today – to stop pushing paper.
How to Create Your Own AI Agents: Not Rocket Science, But Process Power
Do you want to get hands-on and build your own AI agent? Bernhard mentioned two great tools that make this possible even without programming knowledge: Zapier and Make.com (and for those who are technically savvy and want to try an alternative: N8n). These tools have graphical user interfaces where you can drag and drop workflows and processes together. It comes down to process knowledge: What does my process look like today, and what should it ideally become with the support of an AI agent?
Bernhard even had a personal recommendation: Automating customer inquiries and classifying documents are a good start. There are many repetitive tasks here. There are countless free templates you can use immediately to learn how these workflows look. Try it out, it's far more entertaining than any Excel report!
Conclusion & Outlook: We are moving slowly and cautiously – that is our goal.
We also asked Bernhard whether we should opt for a rapid and unregulated development of AI agents or a cautious and regulated one. His answer was clear: Opt for slow, regulated growth. Not too fast technologically, but too fast for us as a society to fully understand what is happening. Technology in itself is neither good nor bad: It depends on what we do with it. For that, we need time to find out the societal consequences. Keyword: Prisoner's dilemma.
But one thing is clear: AI agents are a big topic and will have a huge impact on our working world. We are on a journey and will see where it leads, and we are here to do it for you.
Now I want to know: Where exactly do you believe AI agents will be instrumental and most promising in your processes? Share your opinion in the comments and join our community!
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