Not long ago, artificial intelligence in logistics felt like something out of science fiction. It was associated with robots in Amazon warehouses or data-crunching algorithms in Silicon Valley. But today, it’s becoming increasingly clear: AI is no longer the domain of tech giants. It has entered the everyday operational reality, including in the world of transport, shipping, and logistics (TSL).
And although AI hasn’t yet replaced humans in logistics (nor is it planning to), it is already changing the way we manage transport, plan deliveries, and respond to the unpredictable, which is the very foundation of TSL.
What does artificial intelligence in logistics already bring today?
Artificial intelligence in logistics primarily helps us make better decisions, faster. That’s the theory. But what about the practice?
Properly implemented AI tools can analyze thousands of data points in real time. GPS data, telematics, vehicle condition, weather reports, schedules, shipment statuses – all of it gathered in one place, interpreted, and presented to the dispatcher.
This translates into real benefits:
✔️ route planning that accounts for traffic and driver availability,
✔️ better fleet management – who’s on the road, when they’ll return, when maintenance is due,
✔️ automatic risk detection (delays, working time violations, schedule conflicts),
✔️ forecasting seasonal peaks based on past data,
✔️ automated customer communication,
✔️ documentation support – from delivery status reports to generating complete CMRs with OCR and AI-powered data checks.
Sounds like the future? It’s already happening – even in Poland.
Western European and U.S. companies are increasingly implementing AI-based solutions – and it’s not just the big players.
Logistics operators in Spain and Italy have introduced predictive fleet management systems, using data analysis to predict failures before the first symptom appears.
Polish companies are already testing AI agents for dynamic route planning and “internal dispatchers” – bots that assign loads based on available orders and vehicle locations.
Drivers use AI voice assistants – not only to ask about routes, but also to find out where to refuel, where traffic jams are, or where other drivers from the same company are taking breaks.
What about people?
AI doesn’t replace people. It augments them, supporting their decisions and eliminating repetitive, frustrating tasks.
But there’s a catch: for AI to work effectively, people need to know how to use it. It’s not enough to buy a tool – you need to build your team’s competencies, teach them how to interpret data, ask the right questions, and spot when AI makes mistakes. Because yes, AI does make mistakes. But it’s the human who must be the operator, not the victim.
Why is this especially important now?
Because the market is changing faster than ever, margins are shrinking. Customers demand more, while resources (read: people, vehicles, time) are becoming scarce. This means you either use technology to improve efficiency, or you get left behind.
Just look at the data:
According to the DHL Logistics Trend Radar 2024, artificial intelligence is one of the key trends set to shape the logistics sector in the coming years. More and more companies are declaring strategic investments in AI-powered solutions.
McKinsey reports that AI in logistics can lead to a significant increase in operational efficiency and cost reduction, in some areas, by 10-20%. The scale of benefits depends on the scope and pace of new technology implementation.
Gartner, meanwhile, forecasts that by 2028, around 25% of key performance indicator (KPI) reporting in logistics will be supported by generative AI. Increasingly, companies will use AI tools to make operational decisions and optimize processes.
But what if AI fails?
It’s worth remembering that AI, like any technology, has its limitations. Algorithms work based on historical data, which means they may struggle in entirely new, unpredictable situations. Errors in input data can lead to incorrect conclusions and automated decisions, while fast, aren’t always accurate. Sometimes an AI system will plan a route while ignoring local roadworks, simply because it didn’t access the right data source. Or it might assign a shipment to a vehicle… that just went into maintenance.
That’s why it’s crucial to treat AI as a decision support tool, not a thinking substitute. Training your team properly, monitoring the systems continuously, and being ready to intervene manually are essential. AI can significantly boost efficiency – but only if humans stay “at the helm.”
AI is not a buzzword. It’s a tool.
A tool that can be implemented today, not just by a corporation with a million-euro budget. Also, by a small, agile freight forwarder who knows that the future won’t wait.
If your company is still doing things the way they’ve “always been done,” maybe it’s time to ask:
Isn’t AI already doing it faster, cheaper, and without errors?
