Scaling Agentic AI in CX Without Losing the Customer - with Shri Nandan of Comcast

**Daniel Faggella** (0:12)
Welcome everyone to the Emerge AI in Business Podcast. Today's guest is Shri Nandan, VP of AI Experiences at Comcast. Shri discusses how the urgency for CX automation is being driven equally by rapidly evolving customer expectations and the pace of AI development. And why moving from proof of concept to production scale deployment requires a fundamentally different approach to data, governance and human agent design. Today's episode is sponsored by NICE. A quick note for our audience that the views and opinions expressed by Shri Nandan on today's program are her own and do not reflect those of Comcast or its leadership. In this episode, we cover how enterprises are scaling agentic AI in customer experience. To go deeper on this topic and learn how to structure landing pages for higher conversion and how to use self-qualification systems to prioritize high intent leads, download our free PDF report B2B AI Lead Generation Guide at emerge.com/aig1.
That's emerj.com/aig1 to download your copy. Now the conversation with Shri.
Shri, welcome to our show.

**Shri Nandan** (1:40)
Thank you so much for having me.

**Daniel Faggella** (1:41)
Yeah, I think we're going to have a great conversation around CX and AI in CX today. I want to start this conversation where I think most conversations end. I don't want us to get into what is technically possible because I feel that's the conversation everyone's having at the moment. I want us to get into what is actually forcing the urgency right now, because when you talk to CX leaders across industries, there's almost kind of a pattern that keeps coming up.
The tools have matured considerably, but so is the pressure. We see volume that spikes in ways that fixed capacity teams can't absorb. Even our customers are getting more demanding. Their customers now expect a fluent contextual interaction in whatever language or time zone they happen to be in. And all of this is applying more pressure than what we used to. And that's before we get into the foundational question of whether the underlying architecture was ever built to handle any of this. So I think you are the right person to ask, what has shifted in the last year or two that's turned this from a, oh, we should probably explore this conversation into a very urgent boardroom type conversation?

**Shri Nandan** (2:46)
Great question. And I think you hit on a big force that's driving this, which is customer demand. There is a lot of interest in AI, especially in the last few years. But what has changed in the last couple of years is how the technology is improving and evolving at lightning speed. When that happens, that empowers the customer to be more demanding of what is possible. If I have eight competitors out there who are able to use AI and affect positive customer experience, then I have no reason to believe that my customer is going to stay with me. So in order to keep up with that kind of pace, I think it's important for all of us from the leadership level down to understand that this is not just experimental anymore. This is here. This is the thing that's going to drive the business forward and generate revenue and handle the increasing volume that's coming our way. It's also going to help the workforce develop and code and behave in a way that's faster and keeps up with all of this pace.
So the adoption is being driven by the customer demand as well as the technology that's evolving at a rapid speed.

**Daniel Faggella** (4:05)
Yeah. I think almost every conversation that we have, speed is brought up in some way, shape or form, because I think to the entire human race, the speed at which things are developing in AI is just unmatched. And I think we didn't expect it to be as fast as it is. I think even things that we discussed three weeks ago might now sound like, oh yeah, we're already used to that. And it's strange that we see that customers also know this. They're also involved in keeping themselves up to date with what is possible, like you mentioned. So we have that part for the demand coming from the customers. And then obviously that relays into our organizations. Where do we see the internal pressure coming from? Is it top down or are we seeing its surface from the people that are actually doing the work?

**Shri Nandan** (4:53)
I think it's both ways. I think top down, you have several C-suite that want to use AI to move the business forward, but may not have the technical know-how. So what would help at that level is for them to be able to ask the right questions and ask what are all the things that can go wrong if I use AI in this product. Bottom up, I think the pressure is to be able to build faster, is to be able to prove that the proof of concept can scale and actually be of use to the customer.