AI in outsourced customer service

Robots will steal all our jobs. While this sentiment was mostly in the realm of sci-fi back in the 1980s, nowadays people have started taking it seriously. And with good reason.

Slowly but steadily, artificial intelligence (AI) has seeped into our daily lives. Alexa or Google Assistant help us navigate our personal lives, while various AI applications man our businesses. (Let’s just hope no one invents an app that can go on holiday for us.)

No wonder customer service isn’t exempt from the process. Chatbots line up as the first line of defense against disgruntled customers. And through the rapid development of AI technology, these bots are able to solve increasingly complicated issues.

But what about outsourced customer service centers? Are all those people working there going to lose their jobs? Do business owners have to brace themselves for working in an office populated by boring versions of Wall-E? (Not that Wall-E could be boring in any circumstance.)

The short and simple answer is no, or at least not yet. But the situation is complex, far more so than we’d initially think.

AI in customer service centers

We already talked about chatbots. These handy AI applications can seriously lighten the workload of a flesh-and-bone customer service representative.

They’re ideal for answering simple, FAQ-like questions by customers who weren’t able (or couldn’t be bothered) to find the information in the actual FAQ section of a company’s website.

But they’re far from perfect. In fact, epic chatbot fails are a source of great delight on the internet. Why is that?

While bots have an eerie ability to sound human in a chat window, they still lack a considerable amount of skills that can out them to customers in a second.

At their current level of development, chatbots have a hard time understanding sarcasm, slang, and an abrupt change of subject in the conversation. Similarly, chatbots usually can’t exhibit compassion, don’t have a sense of humor, and can’t follow through multi-level customer issues. And the list goes on.

Plus, there’s another thing: time. While chatbots powered by AI can work faster in the long run, their training takes forever (and costs a lot of money).

Typically, AI gains new skills through machine learning. An AI algorithm looks at large chunks of categorized data and “memorizes” the sorting criteria, as well as the appropriate response it should give when it encounters a particular type of data.

But considering the vast amount of issues an outsourced customer service center can face, getting all the necessary data and “teaching” it to the algorithm is a lot more difficult and time-consuming than hiring a human or two.

The best of both worlds

This means two things.

First of all, outsourced customer service centers don’t have to fire all their human employees to make way for R2D2 & Co. For the foreseeable future, human interaction will be indispensable for more complicated customer service issues, as well as simple conversations with sarcasm and slang that bots just aren’t ready for.

But customer service centers can’t just ignore AI. In fact, the best, most efficient and cost-effective way to approach customer service is through a combination of artificial and human intelligence.

AI apps can take simple, straightforward customer issues. In addition, bots can help customer service representatives with research in the background. However, if an issue proves to be more than a chatbot can handle, a human should take over immediately and seamlessly to avoid (further) angering the customer.

Similarly, you should keep in mind that AI is not infallible. Letting a chatbot do its job without any supervision could result in a disastrous outcome, should something go wrong along the way.

Have frequent check-ins scheduled for all chatbots, even the ones seemingly performing without a hitch. The earlier you pick up a potential problem (preferably even before it becomes a problem), the better.

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AI as a customer

No, don’t expect 3PO calling your outsourced customer service center and demanding an oil change (unless you work for Disney). What you can fully expect, though, is your customers turning to AI to handle issues for them.


There are several apps that act as a buffer between customers and customer service centers. It works like this: The customers upload their data and issues into the app. Acting on their behalf, the app starts bombarding the customer service center with complaints, letters, notes, messages, until it gets the issue resolved.

Before you envision mass AI messages over every single customer issue, take a deep, calming breath. Not every customer problem is worth outsourcing that way.

Since these apps (or rather, their owners) work for a fee, customers won’t hand over all their issues, especially not the simple, mundane ones that usually form the bulk of a customer service center’s daily work.

Customers will most likely outsource the issues where they’re looking for significant financial gains, like compensation.

For example, the apps AirHelp and Service help airline customers get compensation for canceled or delayed flights. Since this procedure is often tiresome and unproductive, getting AI to bug airline customer services is the perfect solution for weary passengers. Why?

Airlines aren’t always forthcoming with compensation. Their strategy is often to wear customers out, making them give up the whole thing and walk away from a potential compensation. However, AI doesn’t give up. This feature makes it the perfect compensation-enforcing weapon in customers’ hands.

Whether you’re dealing with airlines at your outsourced customer service center or not, it’s quite likely that AI apps will make an entrance in other industries as well, so it’s best to be prepared.


While it’s not feasible that AI will wipe out customer service centers and replace all human employees in the next few years, the technology’s presence is still expected to increase.

To make the most of the rapidly developing technology, it’s important that both customer service operators and customers adapt to this change.



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