With a delivery or a return, labels, packing slips and sometimes customs documents need to be created. This is done based on data that is already somewhere in the system: address, weight, contents, destination. The question is whether AI can take over that process, and what portion of the hours of an order processor or logistics employee this frees up.
The answer is yes, with one caveat. This is one of the tasks for which not even the newest AI models are needed: robotic process automation (RPA) suffices, and many companies already run this this way.
Three axes are decisive: structuredness, volume and judgment latitude.
Structuredness scores a 5. A shipping label follows a fixed format, a packing slip follows a fixed format, a customs document follows a fixed format prescribed by customs authorities themselves. No interpretation is needed about what should be on the document — that is fixed in the template and the input data.
Volume also scores a 5. This is not a task that occurs a few times a week; at a company of some size, it involves tens to thousands of shipments per day. The higher the volume, the greater the time savings per automated step, and the sooner the investment in integrations pays for itself.
Judgment latitude scores a 5, which is favorable here: there is little to weigh. The system knows the weight, the destination and the type of shipment, and from that it follows mechanically which document with which content is generated. There is no situation in which the employee must judge what the best document is — that question does not exist.
Creativity scores a 5, which in this case means that no creativity is needed — here that is an advantage, not a disadvantage. Customer contact scores a 4: there is usually no direct contact when creating these documents, although an address change may come in through a customer query, which touches on what also happens with checking and communicating order status.
Physical scores a 3, and that is the reason this is not entirely an office task: a label eventually has to be affixed to a box, and that remains human work, or work for a different kind of automation than AI. The document generation itself is digital; the affixing is not.
Error costs and compliance both score a 3, and that deserves attention. A wrong address on a packing slip costs a return shipment. An incorrect customs document can hold up a shipment at the border, with fines or delays as a result. This is not a catastrophic risk like with financial reporting — hence the middle score — but it is also not without consequence. This is why the precondition for this task is not optional: the document generation is only as good as the data it relies on.
A webshop that only ships domestically with one fixed shipping partner integration can today have this practically fully generated: address from the order system, weight from the WMS, label automatically created as soon as the order is packed. The employee checks by spot-checking, not line by line.
A company that ships internationally, with varying customs rules per country and products falling under different HS codes, faces a trickier scenario. The basic documents can still be automated, but the classification of products for customs purposes sometimes requires a verification step that cannot simply be left to a script. There the task shifts from "AI can take it over" to "partly, with human oversight that approves or rejects with reason" — precisely the middle category that occurs more often with more complex shipping flows than with simple ones.
Two preconditions are not optional. The first is an integration with the shipping partner: without an API connection between the company's own system and that of the carrier, someone keeps retyping data, and then little is gained. The second is correct address data at the front end. If an order already enters the system with a wrong address — something related to how that order was entered, as seen with entering orders into the system — then the document generation flawlessly produces an incorrect document. The quality of this step therefore depends partly on steps that precede it, just as the quality of customer communication depends on how up to date the customer data in the CRM is.
For an order processor or logistics employee for whom document generation forms a substantial part of the task package, this is one of the tasks where a large portion of the hours can already be freed up today — not to the same extent at every company, and not without having the mentioned integrations in place. At companies with international shipments, the share is lower, because compliance checking on documents remains human work.
What that means for a role or workforce is not a question this page answers: which legal requirements apply to personnel decisions is for the employer to determine.
To see how this plays out for your own order process, a free quickscan is available: twelve questions, no account required, with an indication of what portion of the hours in this profile can be taken over by AI today. The full work scan, which breaks down the work of an entire company task by task, is still under construction.
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Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.