I feel the identical applies after we discuss either agents or employees or supervisors. They do not necessarily wish to be alt-tabbing or searching multiple different solutions, knowledge bases, different pieces of technology to get their work done or answering the identical questions over and once again. They wish to be doing meaningful work that basically engages them, that helps them feel like they’re making an impact. And in this fashion we’re seeing the contact center and customer experience generally evolve to have the ability to fulfill those changing needs of each the [employee experience] EX and the CX of all the pieces inside a contact center and customer experience.

And we’re also seeing AI with the ability to help uplift that to make all of those struggles and hurdles that we’re seeing on this more complex landscape to be simpler, to be more oriented towards actually serving those needs and needs of each employees and customers.

A critical element of great customer experience is constructing that relationship along with your customer base. So then how can technologies, like you’ve got been saying, AI generally, help with this relationship constructing? After which what are a few of the most effective practices that you have discovered?

That is a very complicated one, and I re-evaluate, it goes back to the thought of with the ability to use technology to facilitate those effective solutions or those impactful resolutions. And what which means is determined by the use case.

So I feel that is where generative AI and AI generally may help us break down silos between different technologies that we’re using in a company to facilitate CX, which may result in a Franken-stack of nature that may silo and fracture and create friction inside that have.

One other is to actually be flexible and personalize to create an experience that is smart for the one that’s in search of a solution or an answer. I feel all of us have been consumers where we have asked an issue of a chatbot or on a web site and received a solution that either says they do not understand what we’re asking or an inventory of links that perhaps are generally related to at least one keyword we have now typed into the bot. And people are, I might say, the infant notions of what we’re trying to realize now. And now with generative AI and with this technology, we’re capable of say something like, “Can I get a direct flight from X to Y at the moment with these parameters?” And the self-service in query can respond back in a human-readable, fully formed answer that is targeting only what I’ve asked and nothing else without having me to click into numerous different links, sort for myself and really make me feel just like the interface that I have been using is not actually meeting my need. So I feel that is what we’re driving for.

And despite the fact that I gave a use case there as a consumer, you’ll be able to see how that applies in the worker experience as well. Because the worker is coping with multiple interactions, possibly voice, possibly text, possibly each. They’re attempting to do more with less. They’ve many technologies at their fingertips that will or will not be making things more complicated while they’re presupposed to make things simpler. And so with the ability to interface with AI on this method to help them get answers, get solutions, get troubleshooting to support their work and make their customer’s lives easier is a large game changer for the worker experience. And so I feel that is really what we would like to take a look at. And at its core that’s how artificial intelligence is interfacing with our data to really facilitate these higher and more optimal and effective outcomes.

And also you mentioned how individuals are acquainted with chatbots and virtual assistants, but are you able to explain the recent progression of conversational AI and its emerging use cases for customer experience in the decision centers?

Yes, and I feel it is important to notice that so often within the Venn diagram of conversational AI and generative AI, we see an overlap because we’re generally talking about text-based interactions. And conversational AI is that, and I’m being type of high level here as I make our definitions for this purpose of the conversation, is about that human-readable output that is tailored to the query being asked. Generative AI is creating that recent and novel content. It is not just limited to text, it might be video, it might be music, it might be a picture. For our purposes, it is mostly all text.

I feel that is where we’re seeing those gains in conversational AI with the ability to be much more flexible and adaptable to create that recent content that’s endlessly adaptable to the situation at hand. And which means in some ways, we’re seeing much more gains that regardless of how I ask an issue otherwise you ask an issue, the reply getting back from self-service or from that bot goes to grasp not only what we said however the intent behind what we said and it may have the ability to attract on the info behind us.