Pragmatic AI, Real Business Value: A Q&A With Chad Dunavant

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The ‘Right Ways’ for Telcos to Implement AI

Doug Do you feel that the CSPs have challenges in integrating AI into their operations? Chad I do, and I think it starts with data. Data exists across lots of different systems and subsystems, and normalizing that data has likely been on their product roadmap or their radar for the last decade. But what I've seen in conversations is they're not at a place where they can actually take some of those large data lakes or those large data initiatives and really turn them into an ability to garner returns. So, there are subsets of your data that are ready now to take advantage of in training these models. They're normalized. As a BSS supplier in this space, we sit on a lot of billing data—customer care data that already is normalized within our systems. So rather than trying to start a large data normalization project that might take you five years before you then engage in some of these AI use cases, I would implore the operator to think about how you can take those datasets that are already normalized and get the benefits of AI now, while you're working towards a long-term goal that normalizes maybe all of your data down the road. Doug I think there's a danger, as we move into the world of AI, to lose some of the human touch. Do you see that in the CSP world? Chad I do. I think what we would advocate for is giving some of the same tools you're giving to your end consumers to your call center agents, and to your staff that's supporting customers or technicians. And if you do that, you can actually create efficiencies both ways. I'll go back to that same use case we talked about around Bill Explainer. If I'm giving the end consumer insights about the changes in their bill, I should be giving my call center the same tooling. If a call does come in and a call center agent has the ability, then, to see those interactions and understand why things have changed, they’ll be able to communicate that in a much richer way with the customer. It creates a better conversation with the customer when they do call into the call center, number one. And number two, it reduces the training time. And we're never going to cut out entirely the need for human interaction. But if I can use those tools to make that human interaction richer and more fulfilling, then I think again, it increases that customer satisfaction score. And it actually enriches the employee satisfaction score because they feel more empowered to have those conversations because they have the right information in front of them. Doug Hasn't that always been the case with any digital transformation? That there's these sort-of wrong migrations, and companies sort of do it in a kind of oafish way? And you just sort of know someone out there is going to do it that way? Chad Yes, but I think we've all been through this long enough that we have to be pragmatic about how we make these changes. And I don't think it's a one-size-fits-all, especially for an industry like telecom that's been around for 30, 40, 50 years. There are customer expectations that we can't just turn off overnight. And so, I do think having a pragmatic approach, managing that evolution over time, is the right way to do it. We're hearing this all the time: ‘I want to talk to a human; I want to talk to somebody that can help me.' And so, right, let's embrace that, but let's make it more efficient for everybody in that process.

Getting Pragmatic With a Blended Approach to AI

Doug So part of your vision is to use the AI effectively to get you to the right human and to prep that human? Chad That's exactly right. And, in fact, we've used it. One of the use cases we've used within our customer experience division is a large organization—I cannot use the name—but they've got lots of different departments. And so even when you call in to, say, the helpdesk, you may be prompted with 15, 16 different prompts about where you want to go. And you may end up in the wrong department, which then you have to get routed back to another department and sit back in a queue. We've been able to use AI and intent-based natural language processing to identify what your challenges are, what your problems are, and get you right to the right human the first time. And so that efficiency gain is not only for the operator to make sure that they're talking with the right customer at the right touchpoint, but from a customer experience perspective, it's a huge gain because I'm not sitting on hold and I'm not getting frustrated as I get transferred around an organization.

Doug As we look into the future, I have a feeling a lot of people are just going to look at this as maybe a magic cure-all, a magic fix.

Chad AI is not new and it's going to continue to evolve. And I think we have to take that same approach when you look at this technology and the use cases, and find the use cases that are most suited for this type of technology. I don't think you can just apply it and assume you're going to cut out your call center representatives or your call handle time. I think there has to be a blended approach. And it's definitely how we're thinking about how this technology can be leveraged and how we can deploy it to create real benefit within the community.