AI is becoming part of more freight workflows, from reading documents and extracting information to spotting missing details and flagging exceptions.
But the technology only helps if the people using it can make sense of what it is doing.
In freight and logistics, teams are already working across emails, documents, spreadsheets, customer portals, legacy systems and internal processes. Information can be difficult to find, and it is not always clear what needs attention next.
A shipment might involve a commercial invoice, a packing list, a customer instruction, a carrier update and several internal records, all arriving at different times. The information may be there, but someone still needs to bring it together and work out whether anything is missing or out of place.
AI can take some of that repetitive work away. It can pull details from a document, highlight something that looks incomplete, or bring an issue to the surface earlier.
Still, that is only useful when the experience around it is clear.
A user needs to know what the system has found, where that information came from and whether they need to do anything with it. They should be able to see what has changed without having to search through several systems to check the answer for themselves.
This is where the user experience becomes important. It is not only about making a system look simple or modern. It is about helping people understand what is happening in the course of their work.
When a detail has been extracted from a document, it should be easy to trace. When something does not look right, it should be easy to spot. When an exception needs attention, the next step should be clear.
When that clarity is missing, people tend to fall back on old habits. They double-check everything manually, keep their own spreadsheets, or work around the system altogether. The AI may be doing the work, but it has not really made the day any easier.
That is often where automation loses its value. It may save time in one part of the process, but create doubt somewhere else. If people are not confident in what the system is showing them, they will naturally spend time checking it.
Good UX gives people a clearer view of what is happening. It shows what has been completed, what still needs attention and where someone needs to step in. It does not hide the process behind a result that looks confident but gives no context.
That matters in freight, where a small missing detail or overlooked instruction can hold up a shipment and create more work further down the line. There will also always be situations where experience and judgement matter, particularly when a customer request is unusual or documents do not follow the usual pattern.
The most useful AI tools do not try to remove people from every decision. They take care of the more repetitive work and make the things that need human attention easier to find and deal with.
They also should not feel like another system to manage. They should fit into the existing workflow and make the next step easier to see.
AI can process information quickly. UX helps people use that information with confidence.
At Verso Waves, we see the two as part of the same job. Better automation is not just about what the technology can do. It is also about how clearly it helps people do their work.
Also Read: Nielsen Norman Group, How Service Design Will Evolve with AI Agents
