Answering incoming phone calls and transferring them to the right person or department is a task that at first glance seems simple to automate: a question comes in, that question is recognized, and the call goes to the right place. In practice this falls into the category partly, with human oversight as a safety net for the cases where the assessment goes wrong.
The customer contact axis scores low (1), and that is the main reason why full automation is not self-evident here. A phone call is by definition direct contact with a customer, supplier or other external party, often at a moment when someone already feels some tension or urgency: a complaint, a malfunction, an invoice that is not correct. A misjudged call that ends up with the wrong department, or a caller who feels like they are talking to a system while expecting a human, directly affects the relationship with that customer. At a company where phone traffic mainly consists of standard questions — opening hours, address changes, passing on a simple status request — this is different than at a company where callers often have a problem that requires explanation and empathy.
Structuredness scores low with a 2: the question behind a phone call is not known in advance, the caller formulates it freely, uses jargon or not quite the right term, and the context of the call must be built up live. That makes assessing the right destination error-prone. At the same time, volume scores a 5: telephony is by definition a task with a lot of repetition, and precisely with high volume it is attractive to automate part of it. That tension — low structure, but high volume — is exactly why speech recognition is used today for the first, rough filter: is this a question for customer service, the finance department or a specific contact person. The finer assessment, especially in case of doubt or with a caller who asks multiple questions at once, remains human work.
The physical axis scores favorably for automation with a 4: no physical action is needed, the call runs entirely digitally through the phone exchange or the VoIP system. Cost of errors scores average (3): a wrongly transferred call is annoying but usually not irreparable, someone calls back or is still transferred. Compliance scores relatively favorably with a 4, because the transfer itself generally does not involve legal obligations — that is different as soon as the call moves on to recording personal data or sensitive information, for which its own legal requirements apply.
The technology that works here today is speech recognition: converting spoken language into text and recognizing intent, combined with a routing table that determines which department or person belongs to which type of question. For simple, common requests — a caller who wants the finance department, or asks for a specific employee by name — this is by now fairly reliable. For more complex or emotionally charged calls, where the caller does not immediately make clear where they want to go, a human remains the safer link.
Three conditions determine whether automation is responsible here. First, speech recognition of sufficient quality, even with accents, background noise or poor connections. Second, an up-to-date routing table: if departments change, people change roles or new teams emerge without the system being updated, the quality of the transfer visibly deteriorates. Third, an escalation path to a human, so that a caller who gets stuck in the system does not end up in a loop but reaches a person within a limited number of steps. This is in line with how what work can AI take over in customer service is also assessed: automation of the first point of contact works best when the escalation to a human is well set up, not when it is missing.
The outcome for this task is not a fixed rule. A company with a small, manageable customer base and many recurring, simple questions can have a larger share of phone traffic automated than a company with complex, technical products where every call is slightly different. The nature of the organization also plays a role: internal phone traffic between colleagues, such as transferring within a team, is more predictable than external customer contact. That is exactly the reason why a task-by-task scan yields more than a general statement about 'automating telephony' — just as with setting up what work can AI take over in purchasing, the outcome strongly depends on how standardized the underlying processes already are.
This page describes the task in general terms; how this plays out for a specific phone line, reception function or department depends on the actual call volume, the complexity of the questions and the quality of the existing systems. The free quickscan from ftetoai gives, based on twelve questions, without an account, a first indication of what share of the hours in a job profile can be taken over by AI today. The full work scan, which goes deeper into individual tasks and systems, is still under construction.
Vraag maar. Ik ken de kennisbank van deze site; wat ik niet weet, zeg ik erbij.
Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.