Yes, in the vast majority of cases. Compiling an overview of not-yet-settled receivables and debts per period is exactly the type of task that an automated process can handle well: fixed source, fixed rules, no interpretation needed. This is one of the tasks where the shift to AI processing has already largely taken place today, not something for a few years from now.
Three axes are decisive here: structuredness, volume, and cost of errors.
The structuredness is high. An open items list is not free text or a conversation that needs to be explained, it is a sum of items that are already in the accounting system: invoice date, due date, amount, status paid or unpaid. The system already knows this, the task is to compile it and sort it by period. That is a task with a fixed procedure, not a task requiring judgment.
The volume is high, and that is precisely where automation proves its value. At a company with hundreds or thousands of open items per month, a manual overview is error-prone and time-consuming, while an automated query produces the same list in seconds and without deviation. At a company with a handful of items per month, the time savings are smaller, but the reliability of the overview improves regardless.
The cost of errors is relatively low because this concerns an overview, not a payment or an entry that moves money. If there is an error in it, it is visible and correctable before anything financial happens. That is different from, for example, recording purchase invoices in the accounting system, where an error immediately carries through into the administration.
The remaining axes confirm this picture. Judgment scope is barely needed: nothing is being assessed or weighed, it is being counted and sorted. Customer contact, physical actions, and creativity play no role; this is internal reporting, not interaction with a third party. Compliance plays a role because an open items list is often part of periodic reporting and sometimes external accountability, but the requirements for that are fixed and repeatable, not something that changes per case.
The technology that suffices for this is RPA: software that pulls data from the accounting system according to fixed rules, filters by status and period, and puts the result into a reporting tool. No language model is needed to interpret anything, because there is nothing to interpret. That makes this one of the simpler tasks in the accounting chain to automate, in contrast to tasks that do require judgment.
The automation only works if the underlying data is up to date. If invoices are recorded too late, the items list will not be correct, no matter how well the overview is technically compiled. That makes this task dependent on other links in the chain: the reading in and matching of bank statements must be up to date, and the compiling and sending of sales invoices must happen in a timely manner, otherwise items will be missing from the overview. Furthermore, no further manual input is needed once that foundation is in order; the overview then largely runs without intervention.
At companies where the bookkeeping is still partly done on paper or in loose spreadsheets, the structured source that this automation needs is missing. Then compiling the list remains largely manual work, not because the task itself is more complicated, but because the data is not in the right place. Also at companies with many deviating payment arrangements per customer or supplier — partial payments, discounts, disputes — more judgment is needed to determine what does and does not count as "open," which pulls the judgment scope axis up and makes the process less a matter of straightforward automation. This kind of difference plays a role, for example, in hospitality, where payment flows run through multiple point-of-sale and booking systems; see what AI can take over in hospitality for how that sector-specific complexity plays out.
The related work, such as reconciling transactions from payment providers, also determines how clean the foundation is on which the open items list is built. Where that reconciliation is still done manually, the reliability of the items list shifts accordingly.
This overview is not an assessment of which debtor should be reminded or which creditor gets priority for payment. That remains a judgment call that lies with the employee or manager involved. And if a shift in tasks touches on personnel decisions, its own statutory requirements apply to that; that is for the employer and their advisors to determine, not something this page makes any statements about.
To see how many of the hours in your own accounting process fall into this profile, such as reports with fixed volume and low cost of errors, you can fill out the free quickscan: twelve questions, no account needed, with an indication of what portion of the hours in that profile can be taken over by AI today. The full work scan, which assesses your company's work per task on all eight axes, 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.