You can’t spend five minutes on the internet these days without running across something that is either about AI or was created by it. Call centers are no exception.
In fact, depending on the type of call center, many people are saying that AI tools are the main driving force behind some of the most successful call centers today.
We say hold your horses.
The Reasons You Shouldn’t Believe the Hype About Call Center AI
Articles gassing up AI tend to paint a picture of how this technology will eventually do everything humans have done until now, except better. The truth is, no matter the AI tools a call center uses, they can’t function completely independently from humans.
Instead, what AI tools are able to replace at call centers is simply a bulk of monotonous tasks that humans didn’t like doing anyway, ultimately freeing up time for more important and engaging matters.
This isn’t because AI has some inherent failing or simply hasn’t evolved enough yet. It’s because of what it is—a tool.
And as a tool, AI requires people to program it to ensure that it does what they want it to do. Once it’s able to perform these tasks effectively, human agents are able to move around the tasks on their plates.
For instance, let’s say that an agent takes the time to set up a chatbot to handle some routine customer inquiries that they used to have to perform manually. The agent not only has to create the chat flow scripts for the chatbot to answer, but they also have to track and maintain the functionality so that it keeps performing as intended. Of course, the whole point is to reduce the overall amount of work for the agent, but even if it fails, they’ll end up having to take the call anyway because the chatbot was ineffective. In either case, the agent does not become redundant.
In an even worse scenario, let’s say you set up an AI chatbot but don’t consider the fact that AIs notoriously hallucinate or just make stuff up. Your shiny new chatbot could be telling your customers completely inaccurate information. There have been several very high-profile failures of AI chatbots, including cases of giving away high-value items to customers for free and making guarantees the company is legally required to uphold.
At the end of the day, the human element remains essential to ensure that what the AI is saying and doing is both accurate and in alignment with your call center’s culture and values. Despite what the hype articles may say, it simply can’t do these things alone. Therefore, instead of thinking of AI as a replacement for staff, it’s better to think of it as another tool that agents have to learn and operate.
Call Center AI Isn’t the Same As AI In Other Industries
One key factor that can’t be overlooked is that AI’s use in call centers is very different from its use in other industries. In the call center industry, AI is primarily used to automate and assist humans in executing specific tasks. In many other industries, it’s used to imitate creativity and take on other, more open-ended endeavors.
Here are the main ways AI is used in call centers:
Automatic Call Distribution (ACD)
Many call centers are adopting AI to work with the ACD feature on VoIP phone systems. This allows them to collect caller information automatically based on spoken responses and route calls to a specific customer service agent or department queue based on the criteria they previously determined.
In order to get the most out of ACD technology, you have to do a lot of upfront work. That said, you also have to update the criteria each time you want the system to respond differently or accommodate a new service. In other words, there is no “set and forget” method for this type of AI.
Interactive Voice Response (IVR)
When interacting with an AI-assisted IVR, callers obtain information and support by speaking to an automated phone system or responding to it via their keypad.
If you’ve ever called a customer support line and were asked what kind of support you need or instructed to enter your customer ID via your keypad, then you’ve likely interacted with a basic IVR before.
AI takes this tool to the next level by identifying customer issues and then deploying specific scripts based on predetermined criteria. Once again, this is just a case of automating a process that you have to set up and continually refine.
Of course, there are also smart or intelligent IVRs that use natural language processing technology to respond and chat with callers as if they were having a real human conversation. These come with the same rules, just on a bigger scale, as the AI tool needs to be set up with access to a knowledge base and other databases in order to be able to respond to customers with any level of accuracy.
Furthermore, the human element is once again required to make sure that the system doesn’t cause any unintended problems or make any unauthorized decisions.
Sentiment Analysis
Any of your call center agents would tell you that they’d feel a lot more prepared for customer interactions if they could know how callers are feeling before they pick up the phone. This is what sentiment analysis technology tries to do for them.
Sentiment analysis works by having the AI listen to calls and try to identify how the caller is feeling based on what they say and how they say it.
For instance, if a customer calls and tells the automated menu something like, “I’m trying to get this stupid product to work,” the AI will recognize that this person is likely in a bad mood. In response, the system can inform the agent of the situation and provide them helpful resources for handling the interaction before they connect with the caller.
Meanwhile, the AI will continue to listen in and can escalate the call to upper management if it detects that things are getting out of hand.
Ultimately, this can be a great use case for AI, but sentiment analysis still requires human agents to set up and continually monitor for improvement. After all, an AI doesn’t know the difference between “frustrated” and “excited” unless someone programs it to.
Missing Features of Call Center AI
Until AI can do something new—like completing all the post-call work by doing call analysis and pulling the necessary information directly from the recorded call—it’s nothing for call centers to get hyped about.
This isn’t to say that AI will never reach that point. For now, however, it’s simply not there yet.
Customers Don’t Want AI – They Want Options
While it is true that some customers prefer interacting with AI-based tools like chatbots and IVRs over human agents—like Nextiva’s Advanced IVR with Conversational AI, for instance—it’s not a great idea to force it upon them.
What we do know for sure is that customers like to have options. This makes sense because customers are people, and different people want different things at different times. While a phone call might work in some instances, like in a car or sitting at your desk, it’s impossible in others, like when you’re stuck in a noisy environment.
It’s important to allow people to connect with the customer service channel they like best, even if that means dialing down your technology and going against some of the latest call center trends. For now, it’s best not to fall for the AI hype just yet, because human agents would be sorely missed.
