Will AI be Your Next Contact Center Employee?

08 October, 18

Today, powerful technologies are merging the contact center with artificial intelligence (AI), machine learning, and voice recognition. While AI offers excellent potential in the contact center space, all the pieces are yet to link together. Although there is a popular conception among the public that AI merely is someone chatting to a voice assistant, the amount of machine learning and artificial intelligence behind the scenes is significant. Precisely how these technologies will change the contact center landscape are not yet clear. However, one thing is certain: There will be fundamental changes in the next decade.

Until now, communication with devices meant knowing their programming language. Now, software with natural language processing, and machines that can understand what we say and respond with reasonable accuracy are available – making the task of conversing with a computer no longer a thing of science fiction, but a reality.

In the next few years, with technologies like Google’s Duplex and Vonage’s Nexmo, we can see the future of contact centers. Duplex was introduced in May, and while there is still more of a lag in the conversation between AI systems and the human on the other end, as computing power improves, these irregularities will only become less noticeable to the end user.

Vonage Chief Product Officer Omar Javaid told IT Business Edge that the entire category is developing rapidly. “The thing is that while it’s early, it’s moving fast,” he said. “The popular image of AI is somebody chatting with a voice assistant that is indistinguishable from a human. Also, there is a lot of AI and machine learning on the back end concerning data analysis. In contact centers, there is typically a lot of post-call analysis.” Nexmo, Vonage’s API platform, announced partnerships, expanded target businesses and introduced features in June.

But AI and voice are about more than a nice human-to-machine chat. A conversation with AI can lead to angry calls, frustration, dissatisfaction, and other adverse customer reactions when not implemented without sufficient technology to meet user expectations. Systems today are working to tailor human and automated vocal responses, making it less likely that users will recognize that they are talking to a machine.

“I would say from a technical perspective, we have reached kind of a unique tipping point,” said Cory Treffiletti, the chief marketing officer of Voicera, which just joined the Nexmo network. “Until now, you had to learn the language of a computer to communicate with it. Now we have software with natural language processing and machines that understand what we say. They understand our language. It makes it so you can talk to a machine.”

Compelling Uses
The advances in voice recognition are evident in both of these systems. One of the most distinguishing advances is how natural the voice assistant can sound. For instance, adding “filler” noise humans make during conversations (i.e., “Ummm” and “Mm-hmm”), with almost perfect inflections, make these systems not only sound realistic but also improve the overall user experience.

While the lag between when the human speaks and the assistant answers is a tiny bit longer than in a human-to-human interaction, that flaw is becoming less and less noticeable, reducing the likelihood users would know they are talking to a machine.

But AI in the contact center goes well beyond intelligent conversation and can combine a wide range of data points to make the user experience even more beneficial. In a blog at Nexmo, Thomas Soulez describes an example where a woman calls for roadside assistance from a cold climate locale late on a Saturday night. The AI platform quickly calls up the information associated with her account.

That investigation may find that the subscriber has never called roadside assistance in 10 years, signaling the situation has a high probability of being severe. The system also will know that exposure to cold can quickly become life-threatening – thus giving the call top priority. The AI system may even the contact center help in finding the woman’s precise location.

Soulez goes on to say, “While it’s not a leap to assume someone calling late at night from an icy city might need urgent help, non-obvious patterns will be revealed in both public and private sources of data. Machine-learning tools will then anticipate how best to respond when it sees those patterns unfolding. Everything from staffing levels, through the best promotions to run, to the type of interaction a customer prefers will be set by software programmed through machine learning.”

Enter Voice
Voice eventually will be part of this example, Javaid said. At some point, customers will be able to discuss more complex scenarios with AI contact center systems. There are many things that the system may not have data on that would influence the response, the person may have questions or other more subtle details that future systems will be able to handle.

AI and voice in the contact center are still in their infancy and will come in stages. The first step generally is the use of purpose-built chatbots. Next, embedding intelligence in the system, such as software that determines the best person to whom to route a call, keyword detection, or voice analysis to detect fraudulent insurance claims.

Despite the current accomplishments, the technology still has a long way to go – with many technological hurdles before this solution truly takes hold. Currently, these systems generally only work well for English and a few other languages, but even have difficulty with accented English and difficult to pronounce names.

Even Google, which has the most extensive data repositories, has trouble. “No company can compete with Google when it comes to data,” Vanderseypen wrote. “Because of this, they have the very best language-understanding right now. This understanding is, however, generic. If your business is health care or something very specific, the Google services will fail [in] understanding the domain-specific language.”

There is a lot of research and innovative thinking at the nexus of AI, machine learning, voice interfaces, and the contact center. The next few years will prove to be interesting.

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