Alexis
Hi, everyone. Welcome to another episode of Talk Tech with Data Dave. I’m Alexis, your host, and today I am here, well, not with Data Dave.
So, here’s a little story. I was talking to Dave about this question, and Dave was just like, “Alexis, this is not a question for me. This is a question for Preston. Bring him in. It’ll just make more sense that way.” So, I brought in Preston.
You guys have seen him on the pod before. Preston’s the big boss. He’s our General Manager. So,hey, Preston, nice to have you on the podcast again. I’m happy to have you here.
Preston Gregg
Hey, Alexis, glad to be here.
Alexis
Dave is 100% right. This is a question for you. We were just talking, and I was like, “You and I have had this conversation before, so I think this will be a great conversation for the podcast.” And I actually might be able to contribute a little bit to it, so I’m excited.
Preston Gregg
Yeah.
Alexis
But here’s the question, and I think Dave was right. This is a question for you.
I’m looking for practical uses for generative AI that can be used today. It seems like customer service could be a good fit, but there might be some other good fits. Are you seeing any of your clients using generative AI in this way?
Practical uses of generative AI. Maybe practical uses of generative AI in customer service. Looking for examples.
Preston Gregg
Okay, cool. That’s a great question. And I think we all know generative AI — it’s everywhere. And it’s hard to go on the web and not find examples of it. We’re seeing a lot of creative uses, and customer service is perfect because generally customer service generates a lot of activity, and a lot of the activity that it generates are the same types of questions happening over and over.
I mean, it makes sense. If there’s something wrong with your product, a lot of people call about the same issue.
Alexis
Right.
Preston Gregg
And so, as you know, through all the work you’ve been doing with AI, it does really well on repetitive tasks that have a common pattern.
Alexis
Yes.
Preston Gregg
So, looking for real world scenarios where that pattern plays out is often a perfect use of generative AI.
So, looking for patterns that repeat are a great use of Generative AI, typically, not because it’s required, but because the results that you can get can be very consistent, and that’s what our customers are looking for.
Alexis
I 100% with you there on, like, patterns and repetitive. Because, especially in customer service, you can really burn out your agents because they’re doing the same thing over and over again. Like, if you think about a call center, they’re picking up their phone, they’re answering the same questions over and over again. And so, you’re just picking up the phone and saying, “Have you tried turning it off and turning it back on again?” I say that as someone who’s acting as an IT professional sometimes in our organization.
Preston Gregg
Yeah.
Alexis
And so, if you’re kind of saying those same things over and over again, and to your point, you can train generative AI to know how to respond to those things, which it does really, really well. Customer service is the perfect use case for it.
Preston Gregg
And that’s really the magic there, you know, we’ve seen across the spectrum. And you can certainly go too far with it. I don’t know if you’ve been to a large website or maybe a big bank or insurance company that has gone a little too far, and your only interface is generative AI, and it’s obviously not answering your question, and you cannot get to a person. That isn’t what you want to do.
Alexis
Yes.
Preston Gregg
Because that just causes extra frustration. But if you can make that experience better, if you can solve that customer’s problem faster and more clearly using generative AI, then you’ve got a big win.
Alexis
Mhm.
Preston Gregg
But you can’t lock them in.
Alexis
Yeah. So, like, it was really handy the other day when I needed to tell my grocery store, “You didn’t give me the chicken that I ordered in my grocery order, and I want a refund.” It was super handy to do that with generative AI because it knew exactly what I was saying. Tt understood me in normal language. It repeated things back to me. It gave me my answers. And I got my $14 back, and I was happy. And, yes, I spent $14 on chicken because I buy bougie chicken. Like, don’t judge me.
But, like, when I was trying to talk to my insurance company about my EpiPen, and I couldn’t get to a human, and I kept going in a circle with their chatbot. I was ready to pull my hair out.
Preston Gregg
Yeah, those are perfect examples. And it’s also generational, at least from my own personal experience. You know, I have two boys that are a little bit past college age, and they want an automated path. If they could avoid talking to a human to get the problem solved, they would pick that every time.
My parents, on the other hand, they like to pick up the phone and talk to somebody.
Alexis
Yeah.
Preston Gregg
And for me, I just want to get whatever task I need to get done, done as fast as possible.
And I definitely don’t want to sit on hold.
Alexis
I think that’s kind of the other beauty. You just hit it. You don’t want to sit on hold.
And so, if we have an AI agent handling the repetitive tasks only escalating to a human whenever it really needs to, you can eliminate the wait time significantly for a lot of people because the AI agents can handle the bulk of the calls. And then we don’t have to sit on hold for most of the people. And we can reduce your caller wait time, significantly.
I told you I could actually be part of this conversation. I’ve been reading a lot about this. I actually can talk about this finally.
But like, that’s one of the huge pros, if you will, of using generative AI and AI agents in your customer service call centers, in your SMS, in your chatbots, and actually being able to stream all those together.
Preston Gregg
Yeah, you nailed it. And that’s the way to look at it.
If your strategy is to eliminate the human call center agent, that’s the wrong strategy. But using generative AI to augment your human agents is a great strategy for the reason that you just mentioned. As far as, “Let’s let the AI handle the repetitive stuff that frustrates the humans and also makes the end customers happier if they can get their answer.” Like your grocery store scenario.
And so, it’s that AI augmenting your people and your subject matter experts; that’s the key. And if I look across just like, recent customer projects, I mean, it really falls into probably three categories.
There’s the AI-powered virtual agents, which is what we’ve been talking about, Certainly that’s great in a chat model, whether it’s web chat or even an email or SMS. But voice has really come on strong, especially in 2026. And so, being able to do that through a voice channel with an AI agent is now absolutely possible and pretty affordable. It’s more expensive than the chat channel, but there’s a big future in that. So that’s something people should definitely be looking at now.
But there’s also some other uses of LLM AI that are really interesting.
Agent Assist is one that is really easy to implement and usually one of the first things that we would recommend people implement. That is creating a chat agent, not really for your end customers yet, but for your employees and for your call center reps. To be able to chat with it to get answers for the person they’re talking to faster than having to go look in multiple systems or search a knowledge base. You can have an AI agent that’s just there ready to answer questions, and you can tune it to where it gives the human agent the exact thing to say or cut and paste and put in a chat window and the specific pages of the documentation that they need to reference, or they need to send to the client. And so that’s a real accelerator. And it also can help some of your less experienced people act on the level of some of your most experienced people.
So that’s really cool. And the technology is changing so fast. It’s like now, rather than the call center agent having to interact with the Agent Assist, it can actually, like, listen to phone calls or listen to chat sessions going on between the human agent and the end customer and then automatically recommend, “Hey, maybe it’s this. Look at this article. Say this. Ask them this question.” To where it makes it even more efficient. It’s pretty crazy.
Alexis
That would just make life so much more simple for somebody who, like you said, is like onboarding, who maybe doesn’t know everything right up front. Okay, the AI agent is listening into the conversation or is reading the chat as the chat goes and is automatically triggering. “Here are some ideas. Here’s some suggestions to help them with their conversation.” Or even the most experienced agent is still getting those recommendations and is straight up getting the language to use to make sure the agent is using the correct language.
Preston Gregg
That’s right.
Alexis
That is a game changer versus having to say to somebody, “Give me a moment,” and then clickety, clickety, clickety, and then look up what to say and how to answer. I mean, that’s speed to get that person off the phone faster. That’s speed to help that person get their answer faster and to get the next person on the phone faster. And don’t get me wrong, it’s important that we spend time with our customers, and we understand them, and we help them, but you have to be able to make them happy. And a lot of people, just like you said, like your sons, just want to get off the phone.
Preston Gregg
That’s right. And you’re on the clock. Even if you get to the right answer, but it takes you a long time and multiple tries. That’s not the experience you want your customers to have.
Alexis
Exactly. Before we wrap up, Preston, we’ve been talking about customer service, but what other use case sort of examples might there be for generative AI outside of customer service? Any other practical uses for generative AI in business today?
Preston Gregg
There’s a lot.
It started on the content side in getting assistance on content creation, but now with the concept of AI agents that can do complex tasks or multi step tasks and be able to search the Internet and able to integrate easily with applications through some of the new technologies — like MCP for integrating with your web apps or your traditional back office applications to be able to go look up and do transactions, look at logs. That opens up a whole world, and some of the more recent advances around agent-to-agent communication where you have a team of agents that are very specialized with special tools to be able to do different tasks, and once you can get those agents working together, it gets really interesting on the jobs you can have it do effectively.
Alexis
Agent to Agent … AI…. Ummmm…
Yes.
That might have to be another podcast for another day because now I’m very intrigued.
Preston Gregg
Yeah, it’d be a good one.
Alexis
Well, Preston, thank you for hopping on the podcast with me today and answering this question. Dave was right. You were the one to answer it for sure. I appreciate you being here with me today.
Listeners out there, if you have a question for Preston or for Data Dave, you can always send us your questions at talktech@d3clarity.com, or you can hit up myself or Dave right on LinkedIn. Preston, again, thank you so much for being with me today. I appreciate it.
Preston Gregg
Yeah, this was fun. Looking forward to the next one.
Alexis
Thanks.
