In this Communications in Context video segment, Head of Platform Marketing Francisco Kattan explains human plus conversations, an emerging customer engagement concept where artificial intelligence makes human agents more efficient and customers happier. (To read the full transcript, scroll below the video.)
Human Plus AI in the Contact Center (Full Transcript)
Francisco Kattan, Head of Platform Marketing at Nexmo: Yeah. I mean, the idea with human plus, as I mentioned earlier, is that artificial intelligence can be used to augment the capabilities of human agents, not a replacement. So we’re all familiar in the past with the traditional use of machines to automate highly repetitive interactions, especially within a contact center, right? So in the past, if we wanted to check our balance, our bank balance, we would have to wait in queue, then finally talk to an agent, and then, finally, find out what our balance is, after probably a lengthy conversation to figure out who I am and why I’m calling, right?
“artificial intelligence can be used to augment the capabilities of human agents”
And so, we’ve seen things like IVR in the past automate those kinds of very repetitive, mundane type of interactions. And so machines have already automated those kinds of capabilities. What we see with human plus now is the ability of machines to help not only automate more complex interactions that are maybe not repetitive in nature, that require more cognitive ability, but also help the agent solve those highly complex problems that come up occasionally in a contact center.
So let’s see. As an example, let’s say that you’re talking to an agent. And then an AI bot is magically listening into the conversation. And you get to the point where the agent doesn’t have an answer or doesn’t have all the context for the conversation or for the question that the caller is asking about. And you can imagine the AI bot quickly doing a query behind the scene and then popping up information on the agent’s screen so that the agent can guide the user through the answer to his or her problems, right? And this will all be done without the user really realizing that there was an AI bot behind the scenes helping this agent.
Another example that you might imagine in a contact center is sentiment analysis. So imagine again this AI bot magically listening to a conversation where I as a customer may be calling my bank, and, for whatever reason, I’m upset about what happened, trying to get a fee overwritten or something like that. I’m getting upset. Then the AI bot behind the scenes can detect the fact that I’m upset and automatically notify a supervisor. A supervisor can then quietly be conferenced into the call and then, behind the scenes, help the agent so that the agent in the end provides a good experience for the consumer.
So the bot is working behind the scenes, just analyzing what’s going on with the call, and, if necessary, taking action, whether it’s providing information on a screen or conferencing in someone else, maybe even taking notes or transcribing a call for future analysis.