Customerland
Customerland is a podcast about …. Customers. How to get more of them. How to keep them. What makes them tick. We talk to the experts, the technologies and occasionally, actual people – you know, customers – to find out what they’re all about.So if you’re a CX pro, a loyalty marketer, a brand owner, an agency planner … if you’re a CRM & personalization geek, if you’re a customer service / CSAT / NPS nerd – you finally have a home.
Customerland
How Pega Is Reimagining Customer Engagement Through Agentic AI and Automation
The marketing technology landscape has exploded to over 15,000 applications, creating both opportunities and challenges for businesses seeking to maximize their existing investments. In this enlightening conversation, Tara DeZao and Rebecca Miller of Pega, share their unique perspectives on navigating this complex ecosystem while thoughtfully implementing AI solutions.
The conversation reveals how Pega's approach to AI has evolved dramatically since 2018, shifting from basic natural language processing to sophisticated generative and agentic applications that transform both customer and employee experiences. What makes this discussion particularly valuable is their candid exploration of the trust challenges organizations face when implementing AI at scale.
One of the most fascinating insights comes from Pega's innovative internal solution—"Intern Iris," an AI assistant deliberately positioned as an intern to encourage appropriate oversight and verification. This clever framing builds trust while still delivering significant productivity benefits, demonstrating how thoughtful implementation can address legitimate AI concerns.
The conversation dives into the critical balance between automation and authenticity in customer engagement. As Miller notes, "If you have one bad experience as a consumer, you're done," highlighting why governance and control remain essential even as AI capabilities advance. She offers practical guidance for organizations, recommending a measured approach that focuses on one process at a time rather than attempting wholesale transformation.
Looking toward the future, De Zao predicts a significant shift in customer service over the next five to seven years—an increasingly autonomous landscape where routine transactions are handled through AI while human agents evolve into specialists managing complex emotional situations. This vision acknowledges both the transformative potential of technology and the enduring value of human connection.
Whether you're a marketing leader evaluating AI solutions, a customer experience professional reimagining service delivery, or a technology strategist planning your organization's digital future, this discussion provides valuable perspective on balancing innovation with appropriate controls to deliver experiences that build rather than erode trust.
I like it because it's really about, like one of the things that we've been trying to articulate more is how we can like maximize your existing investments in your MarTech stack. And I feel like if you look, you can go all the way back to data ingest for a brand and maybe that goes down through Google and then into Pega and then we deliver through the brand channels and then the customer sees it. But through that whole, just the data alone travels through sort of a complex path even before it hits Pega. Right, it's like could be onboarding offline data into the online data world, like through a live ramp, gets in, maybe goes into a CDP, cdp's hooked up to us. Now there's a lot of ways that data can even flow through, of bringing some kind of enlightenment if you will to these technologies that's more purpose and results driven rather than just technological efficiency.
Tara DeZao:Yes, I like it, it's a different story. Yeah.
Mike Giambattista:Which I think you heard it here is going to resonate with the buyers.
Tara DeZao:Yeah, absolutely.
Mike Giambattista:Or it could be completely washed out.
Tara DeZao:Why aren't there any measurement of better together stories?
Mike Giambattista:That's kind of what this is. Yeah, it doesn't really exist out there. Yeah, it doesn't, for sure, Except as, like the Pega case studies, or whoever's case studies that are, you know they're objective, but they're not really objective.
Tara DeZao:Yeah.
Mike Giambattista:So I think that's where we're headed, that's where we're building out here.
Tara DeZao:It's very cool, I think it would be. I think it's desired.
Mike Giambattista:I'll take your critical input. You can hate it, and I'll still love you. Okay, I can hate it and I'll still love you. Okay, I'll be honest. Wait, now that you said it like that, like I don't want to know, never mind, I'm turning off the recording anyway. Um, let's talk about pegas. More great, so you have a giant and growing remit yes um, that I think like that's another couple of conversations, because it's literally like wow, it was big before. Yes, Like MarTech is what did you say?
Tara DeZao:15,000 in the map right now 15,000 plus apps out there. Yeah.
Mike Giambattista:And AdTech, if you want to carve that out or layer it on, is another of its own thing.
Tara DeZao:It's a big part of that. It's giant, it's giant. And then you've got the media ecosystem and all that. They, the media ecosystem and all that.
Mike Giambattista:that you're not really even, they're not on that no, yeah, and that's a lot of fun too. So so you're kind of Intel recon.
Tara DeZao:Yeah.
Mike Giambattista:Figuring out what the competitive landscape looks like.
Tara DeZao:Yeah, we're just always trying to understand, you know, customer behavior, market behavior, just how can we be the best advisors for our clients? And that's part of the reason I was hired here at Pega, and even though my remits changed a little bit, it's still a passion for me to know what's coming next.
Mike Giambattista:It's a relentless curiosity. Yes, that's probably at the core of why we get along so well. I think you're right, plus all the other stuff yeah.
Tara DeZao:Because another thing with ad tech and mar tech is we create something here and then somebody starts using it in a completely different way than it was intended to be used and find out that it's amazing for this other thing.
Mike Giambattista:Right right.
Tara DeZao:Countless times I've seen this, so that's another fun part of it.
Mike Giambattista:It this, so that's another fun part of it. It's like very innovative, creative sector. Yeah, so I'm gonna I'm gonna be thinking after this conversation about how we could work together, because I talked to a lot of technology providers out there. That's kind of what I do, uh, and my, I don't really do it because I need to provide, like, advisory services, although we're starting to do that. Um, it's more because I think my value to the market is understanding what the landscape looks like. Yes, like I just got to know who's out there. Where do you fit? Yeah, what do you do here? Totally, and I, I feel like that's kind of um answer some stuff there. So my people be talking to your people yeah, great, set it up anyway back to the back to get us on the rails.
Mike Giambattista:I, we need to get back on the rails here. I'm looking at you like yes, that's isn't that your stated role, like keep us on the rails? Yes, isn't that your stated?
:role Like keep us on the rails On the rails Right Okay.
Mike Giambattista:Sorry, okay, good job. Thanks, because now I'm doing it On AI integration. You're going to love this. It sounds so professional.
Tara DeZao:Yeah.
Mike Giambattista:Because you and I would never speak like this. No, but I have notes. You've positioned AI integration as no longer experimental. What kinds of AI use cases do you believe are most valuable right now in marketing, and which ones are still overhyped?
Tara DeZao:Oh, that's such a good question. Yeah, I mean, I think the thing that's valuable is the thing that's like overhyped in a sense, which is dynamic, creative optimization. You know it's using Gen AI to create, you know, marketing messages and interactions and things. We see a tension between people that really want to clamp down on their brand and so don't, you know, trust AI fully to execute the creative things that they need it to? Um, but that's like the most exciting thing. The most exciting part of ai for marketers is scaling content and scaling marketing and scaling messages. Um, but I think it's also the sort of uh, you know, you have to be a brand that's willing to take a little bit of risks, like a calculated risk, and sort of not have a super tight hold over your brand Right, right.
Mike Giambattista:I think it's an interesting moment in that respect, because Gen AI creative. It's almost like it's a must-have it. You can't. You can't compete, no, at scale and speed if you're not using it somehow. Right, um, and, and I think a lot of brands are coming to terms with like, but wait, we have our brand standards yes and yes and what's happening here, like in my use of the genii tools that I use, like drift, is wild.
Mike Giambattista:It's just nuts like, and I loved what alan was saying on stage today with his chess game yeah, yeah, the right, absolutely right. This is completely wrong. Let me do this and get it exactly right this time and I'll waste you know, two hours trying to get this stupid like chat thing to do what it's supposed to do when it's very capable, but it's just not listening. Yeah, so there's all that drift to contend with. That's an interesting thing right now.
Tara DeZao:Yeah, and you know we're starting to see and like, for example, in Blueprint you can, you know, import your branding and see what creative might look like. But we're starting to see brands that do say, okay, I'm gonna upload our brand guidelines and our tone and voice and like let's see what ai can do with it. So we do have those. You know, those are the first in people that are experimenting and now they're in a great place to actually differentiate because they were early adopters of that and now they're actually going to have AI embedded into their entire marketing strategy, embedded into their entire marketing strategy.
Mike Giambattista:I'm curious as to your views on how people let's just say people in organizations are working through their AI trust issues.
Tara DeZao:That's such a good question too, yeah, so I mean, I think part of it is you don't trust what you don't know. So, within Pega, we have a mark, you know, we have our own marketing organization, and they've done a really great job of training or offering training and education to the rest of the company on what AI products are available to us, how to use them, how to get the best outcomes. Some of those products we sell to other people, some of them are just ones that we use for our own purposes, but we are unable to use it. We are unable to try it, learn it, sometimes, gamify it Cool, and I think it makes us all more efficient individually, because we then can use these tools in a proficient way. And the fear is not there. There is a fear, though, I think, for marketers of AI taking away their job.
Mike Giambattista:Not entirely unjustified.
Tara DeZao:It's not unjustified, but it's also. There's a partnership to be had with AI where it's making you better at your job. Of course, there are probably certain functions that are going to go away, right, but you know, you're a writer, I'm a writer. You ask AI to write you something. You don't then take that thing and put it out exactly as is.
Mike Giambattista:You're like is this right?
Tara DeZao:Does it sound good? Does it sound like me? You know, there's still, uh, such a human element to all of this. There is a lot of things that could go wrong, of course, but I don't think we need to have the fear dialed up so high. I think we can figure out how to partner together with AI to drive better outcomes.
Mike Giambattista:Completely agree. And well said, I was looking at a post, was it today or yesterday? Rick Rubin, famous producer.
Tara DeZao:Oh yeah.
Mike Giambattista:Music, yeah, and he wrote a book which is all over the place now. But somebody interviewed him on AI and creativity and I'm going to blow it because I wish I had the exact words, because it was really well said. It made you stop and think. Essentially, what he's saying is that if you're a true creative I'm doing air quotes, you can't see that on the audio, but you know then creativity is part of you.
Tara DeZao:Yes.
Mike Giambattista:And this is just another tool that enables you to do what you would be doing anyway. In some lesser state. It elevates what you can produce and you know again better words from Rick Rubin, but that's the idea, and I think it's brilliant. I don't know, maybe a month or two ago, chatgpt started like showing you how it was thinking.
Tara DeZao:Oh, interesting.
Mike Giambattista:Do you remember seeing that at all?
Tara DeZao:Well, I went off ChatGPT in favor of. I don't want to play favorites or something or endorse something. This is not an endorsement, but I went over to Copilot. I've been using Copilot. Do you like it? It's okay.
Speaker 4:Others are available. Others are.
Tara DeZao:And then we have actually, can I talk about intern Iris? Yeah, okay, okay, we can yeah.
Mike Giambattista:Okay, okay, we can edit it.
Tara DeZao:It's okay Okay we have an AI intern at Pega and it's really great because so you know, with ChatGPT, you're there, you're interacting with it, you know you have to be like interacting with it to get it to work. With Iris, you can send Iris an email like hey, iris can send iris an email like hey, iris, bring me back 10 stats on um customer experience in 2025. And then iris goes away. Email iris, maybe you switch over to something else you're working on your deck and then the next time you check your email, iris has returned with the stats and the sources. I love iris, so iris is actually what I use the most, more than anything I think the distinction is as well.
Speaker 4:Just to be clear, she's called intern iris yeah, very specifically and everyone in the company needs to be aware, when you're asking for help with any work from iris, she is an intern, so you check the work as if an intern has done it.
Tara DeZao:Yes, it's really smart. Yes, and here's another good point, which is that in early days, the intern makes some mistakes right, and that's why we have oversight over the intern, and that's a really important distinction as well, which is like okay, iris is not ready for her intern job yet, she needs to go back to college, and then yes, exactly, get some good sleep, yeah, for sure. And again to the partnership AI point. Iris is an intern. She's meant to do tactical manual work for us so that we can do more strategic stuff.
Speaker 4:Yeah, I think that's the other thing as well. Is that there's the other thing as well is that there's, you know, there's the whole governance issue. So we all are very aware as well. Is that if you're going to email iris, the intern, think about what information you're giving her, so you know you don't just email her any old thing, you know confidential right right so you do treat this as an intern in the information that you give and the information that you ask for and how you check it yes, I love that.
Mike Giambattista:Yeah, so it's just. It's built in like you have your own guardrails. You've been given these guardrails to work within as a user of Intern Iris.
Speaker 4:It's very collaborative as well, because, as well as being able to interact with the intern Intern, iris, there's also a WebEx group where you can share best practice. You can talk to everybody Everyone in Pega has access to that so that we can talk to each other about what we found out where it felt like she might have been hallucinating oh, yeah, you know she's a bit slow today. You know was she out on the lash last night? I don't know. Wait, what does that?
:mean you know.
Speaker 4:So there's a lot of chat that goes on in there as well about Iris and how she's performing on the day.
Tara DeZao:Yeah, and I think honestly, when you work at a company that sells AI-enabled products or AI-powered products, you're more responsible yourself with AI, because you know what can go wrong, because you know what can go wrong. So I, if, even if I see the source, I click on the source because I want to make sure that it's being pulled correctly and then I'm not citing some like once that was from pwc from 2010. You know, I don't want to be using that stat.
Speaker 4:That's not correct she gives you a reasoning document yeah, as well I love that too too.
Mike Giambattista:So that's one thing. At ChatGPT I have to go back and say, okay, give me your sources and citations. I've got to see everything you've pulled from to see this, but I did notice at one point, when it was showing you how it was reasoning and its processes which I thought was brilliant to address trust issues. Yeah, now you can see what I'm doing kind of behind the curtain, absolutely. But it doesn't do that anymore.
Tara DeZao:Huh Interesting.
Mike Giambattista:Yeah, I'm not sure why. Maybe I don't. You know, I didn't qualify for the upgrade yeah, maybe not.
:It's just like you know what.
Mike Giambattista:I'm tired of showing you what's behind a curtain or something Crazy, crazy.
Tara DeZao:So the highest utility right now is the same as the most hyped AI in your view. Yeah, I mean for marketers. I think scaling content and making sure it resonates with your audience is probably the critical use case that is going to have to be embedded in your strategy, and I think it's also going to be more of like a long tail of organizations that can adopt that fully. I sort of I bucket marketers into three buckets so transitional, traditional and transformational. So traditional marketers are doing mostly human-led labor. They're still running just traditional campaigns like Batch and Blast. Transitional are partway there on their journey, right, they're doing maybe dynamic customer journeys. They can take advantage of streaming data. They're more down the path of full transformation. And then transformational are like 100% bought in on self-optimizing AI, ai-powered decisioning, understand that they need to be leading the pack and their next steps are really just to expand how many use cases they're using it for in their business.
Mike Giambattista:I'd love to know more about like, because I don't really see many of those people who are like at the transformational stage in any, not just marketing, but whatever. No, seriously, this is great fun and there's so much like legitimate to talk about.
Tara DeZao:I knew this was going to happen. I know.
Mike Giambattista:Today I'm here with Rebecca Miller, who is Senior Manager of Product Strategy at Pega. Thank you for joining me.
:Thank you, really excited to be here.
Mike Giambattista:So, as titles go, senior Manager Product Strategy at Pega and what I know about Pega, there's an awful lot going on here. So what areas plural do you focus on in your work here?
:Yeah, that is a great question. So at PEGA, product strategy sits within our go-to-market team, where I take what the product team is going and building and translate that into stories and messaging for our clients, for our partners, for our analysts, and get their feedback and hopefully kind of have a feedback loop where we are able to influence the roadmap as well as our vision for the future.
Mike Giambattista:So it's a pretty cool job. Yeah, it sounds like that literally the best job.
:Yeah, yeah.
Mike Giambattista:Unless you're a developer and you love that kind of stuff. That sounds like the best job.
:I've been at Pega for about seven years.
Mike Giambattista:And always the same kind of roles.
:Always in the product marketing and product strategy space. But I would say, just with the nature of technology, my job looks completely different than it did in 2018. So what did it look?
Mike Giambattista:like 2018, think back, pre-pandemic, pre oh gosh, there were no technology crises happening at that point, or very few anyway. So what was it like then? What's it like now?
:So in 2018, I feel like we were talking about AI at Pega quite a lot, but it was a lot around natural language processing and AI chatbots and our customer decision hub and I think that we were pretty ahead of the game in terms of just our AI capabilities and we coupled that with our workflow automation. So I was spending a lot of time kind of talking about NLP, trying to get people more comfortable with self-service, because we know that customers don't always love self-service.
Mike Giambattista:I've heard this yes.
:And now I really feel like, as we all know, ai has just exploded in a whole new way and I feel like Pega and then really take the creativity of Gen AI and apply that in customer service. A lot of the conversations we're having now are with clients on how they can become more autonomous, so how they can automate more work out of the contact center and closer to the customer, and I think that there's more trust in digital channels. I think that we still have to do a lot of work there.
Mike Giambattista:Do you? Because I want to talk about that. That seems to be something that comes up on my radar a lot too. It's just like you know, adoption doesn't really happen as fast as it could for a lot of different reasons, and it seems to me like if you really peel back a couple of the layers, it kind of boils down to trust.
:A hundred percent, and if you have one bad experience as a consumer, you're done.
:I feel, like you are like okay, I'm going to go somewhere else. So customer expectations are rising and they expect that you're going to get their questions answered the first time. So I think that there is this hump now with agentic AI where we're hearing about all these agents that are doing work on behalf of companies. But the problem with that is that without governance and control, these agents are basically going out and providing a bunch of different answers to different customers, so that's not super beneficial either. But when you again kind of apply that workflow automation with your agentic AI in a predictable way, you can really provide a seamless experience across any channel, which I think is kind of what customers want. I don't know if every customer actually wants to call in and talk to a customer service agent.
Mike Giambattista:No, I've heard that as well.
:Yeah.
Mike Giambattista:That seems to be a thing as well. You know, I think I started following Pega in 2019, and I spoke with somebody here whose name I just Robin Collier.
Mike Giambattista:I don't know if he still works here, um, but brilliant guy and we're we were talking about this idea that Pega was developing systems that could deliver empathy at scale, which at the time was like come on, can't, can't really do that. I mean, nobody's going to believe it. First of all, it's fake empathy, it's not real. And you know, the more we talked and the more I I saw how you were approaching this, um, you know, I became a believer because I I got to see it. But what was interesting to me along the way was that, um and again I've been a kind of following from the sidelines for quite a while was how well, like what you and Alan were saying, the development of AI and LLMs has played into your development of workflows and how you approach those to kind of get you to this place.
Mike Giambattista:And this interview is not meant to be a series of softballs that I just kind of throw your way, but I talk to a lot of technology providers. Almost every one of them has got an AI thing because you must, you must, and some of them are really interesting and robust and well done and well thought out. But I don't recall I can't really think of anybody and some of them are really interesting and robust and well done and well thought out. But I don't recall, I can't really think of anybody where the times and the technologies kind of just came together in this perfect, seemingly perfect, kind of meshing of the gears. That seemed to have happened with Pega, just to get you to this point. It all seems like, okay, well, we're here, of course we're here. We planned on being here.
:We created AI to make us here or whatever it is.
Mike Giambattista:So there's trust on the consumer side because, as you said, if you have a bad experience, forget it. I'm out.
:Yep.
Mike Giambattista:Super low tolerance and super high expectations, but on the corporate side, the people who are buying these technologies, forget it. I'm out, yep, super low tolerance and super high expectations, but on the corporate side, the people who are buying these technologies. There's also and I think there's lots of data to back this up as well there's lots of kind of trepidation around like do I just jump in headfirst to the AI-driven solutions, or how can I establish guardrails or safety nets? Or is it just a? Is it just strong governance? But what do I do? Like, because the downsides to getting AI wrong at scale are are pretty significant. So do you have those conversations?
:Absolutely. I think that everyone is having those conversations and I was at a conference earlier this year in March, where it was an expert in agentic AI who was speaking. The core message was be patient. So everyone is really excited around agentic AI, but the reality is that it is going to take time. This is a seismic shift and we're seeing the beginning of this transformation of the front office and customer service, but it's not going to happen overnight and we don't necessarily expect it to.
:Especially with enterprises that have such complex processes, you want to make sure that you have control.
:So at Pega, we don't encourage our clients to do everything at once.
:We really do suggest that they focus maybe on one process or a set of processes at a time, so they can use tools like Blueprint, you know, from a design standpoint, if they have an idea or if they have a legacy customer service application and rethink that in an expedited way, and then they can actually preview that through our agentic self-service and see it in, you know, real life without actually having to, you know, spend countless months trying to build this. So we really want to provide kind of an experiential mode of understanding self-service and understanding the power of agentic AI so they can really decide. Oh, where should I actually inject agentic into my processes? Maybe it's in claims, for example, or I need to. You know, my employees are spending a huge amount of time right now summarizing costs or just those types of things, and you can automatically inject our Gen AI capabilities pretty quickly because of our center out business architecture. So it's a lot easier to again kind of build that workflow and then apply it to your different channels without having to rebuild.
Mike Giambattista:Interesting Beginning of the conversation. You were talking about how it might be playing into the employee experience and what's happening in front office. Quote unquote Considerable amount of the work that I do and we do at customer land happens to fall into the CX space. Um, and you know, EX is always I can't say always, but up until very recently EX was kind of always acknowledged but never really treated as you know. Uh, a front seat at the table, yeah, it was right, it was over here behind the cx guys. Um, and pandemic started to open some people awaken some people to that. But you know, and the applications for ai within cx are are wide and, you know, pretty exciting. But let's talk a little bit about the applications for AI, especially as Pegasus in the EX world.
:Yeah, and your point around employee engagement is so important and I think that you know businesses need to be focused on that, because the reality is that if your employees aren't engaged, you're not going to be successful, like it's the heart of your business. Gallup Research did a survey last year and I think it was. They saw 21% decline in overall employee engagement. That's pretty significant, and it's not just an HR metric. So why is that? Well, think about all the things that employees have to deal with. There's a lot of legacy systems, there's inefficient processes, maybe a lack of training or just they have to get up to speed really quickly and then they're having to be bogged down with so many manual tasks that they are basically getting burnt out. And you really do need to consider how can we change the paradigm for that and actually use some of these agentic and gen AI tools to improve employee engagement. So that's really our focus at Pega.
Mike Giambattista:How do you, how do you navigate that on the corporate side? Because you know one thing I see, and I know you do, is that so much of this change gets bogged down because of cultural reasons. I'm just going to say cultural. I was in a meeting earlier and the guy who was speaking said no, it's all political. It's all political. I'm basically a really good politician. That's how I get things done. But whatever word you want to use, oftentimes the catch here really isn't what the technology can do or how efficient it can make things, it's getting it implemented and adopted. Yes, so how do you do it? Because Pega deals with some of the largest organizations in the world, which to me means some of the most complex column architectures, political architectures, in the world. So what's the secret sauce?
:That is such a good question and I think it really depends on the organization in terms of the secret sauce.
:But at a high level, you have to gain trust, and we're talking about control, and trust and governance mean by that is whether or not you are doing a pilot program or something like that really getting people to experience the technology and understand how it's going to improve their days. So really being able to provide a system that is delivering insight and taking the burden away that has caused, you know, employee turnover and all of these different things. One of my favorite new capabilities that we came out with a couple of years ago is our agent simulator tool. So even you know, before you're a Pega client, you can actually have this hands-on experience and right now at Pega has these AI capabilities and automation features that really save a huge amount of time, whether that's next best actions or auto form fill or interaction summary. So really being able to bring that to life faster, I think, is so important and really a key to kind of putting proof to the pudding, because there's so much noise in the market right now.
Mike Giambattista:Yeah, yeah, we should have another conversation just on the noise in the market, you know again, because this is kind of what I do for a living.
Mike Giambattista:But talking to so many technology providers out there, it seems like one of the universal challenges to getting a product sold in is boiling it down to a real direct ROI for the purchase.
Mike Giambattista:Like you know, um, if you, if you just take a super, super high level of what the C-suite is looking at, it's you know revenue, it's expenses and it's risk, and if you can prove out on any one of those levels that you're going to prove things, it seems like the people that I have seen do this consistently successfully are all able to do that. And that was one of the things I saw when I was first introduced to the Blueprint thing. It didn't show me ROI, there's no number at the end of it to see the time savings and the beautiful effectiveness and complexity. I'm probably not saying that right, but it could build these beautifully constructed, thought-out campaigns that are almost not humanly possible to develop and it could do so at scale super quick. I mean, you know I didn't see a number at the end of the equation, but I absolutely saw improvement. So that seems like an easy one. Is that kind of what you're seeing as you present that kind of system to the C-suite?
:Yes, absolutely, and you know, events like this are so important as well. Bringing different clients and the melding of ideas and things like our client advisory board are really important for that.
Mike Giambattista:I think that having that a fairly unique position, you work with a big organization that's doing some cutting edge stuff and you're dealing with some of the world's largest organizations, so you probably have a perspective that not many people do. So you probably have a perspective that not many people do. Having said that, where do you think this? What do you think this is going to look like in, say, a year? The idea of agentic AI, because a year is nothing right now, but you know, a year or two years, look ahead. What do you see?
:I think you're going to see more and more AI and automation take over the tasks that you have seen customer service reps do.
:But I think that that is going to take time.
:I think in five to seven years you are going to see a massive transformation in terms of what a contact center looks like, and the reality is that there are going to be less contact center agents.
:That doesn't mean that they're not important. They're going to have vastly different roles. There's going to be a whole set of new skills that's going to be needed to kind of manage heightened customer expectations because those are going to continue to escalate as well and manage emotional intelligence, and I don't think that any sort of AI is ever really going to be able to fully replace that rep experience and maybe make you more reactive so you know exactly where that customer is in their customer journey. But I still think that sometimes in certain situations you need that human touch. You want to actually have a conversation, but for the ones that are kind of tedious, where you just want to get something done I want to change my airline ticket, I don't want to talk to somebody that is going to become more and more automated, and we're hearing that from clients and from C-suites where they are expecting that there's going to be shifts in the contact center.
:So I really see an autonomous future.
Mike Giambattista:Wow, okay, you heard it here, maybe not first, but but you heard it here from credibility. How?
:about that.
Mike Giambattista:Well, Rebecca, thank you so much for the time and for your opinions and insights and for inviting me out to PegaWorld.
:Thank you, Really happy to meet you and this has been a great conversation.
Mike Giambattista:Sure, and look, if there's other stuff we want to talk about, we can still add that on. So if we've got any other topics you want to hit, we can still do that.
:Let's see what else. Well, you were talking about empathy, some.
Mike Giambattista:Empathy is hard.
:Yeah.
Mike Giambattista:It's like AI has gotten so much better, the LLMs have gotten so much better, but I think people are also getting more attuned to what's real and what's not.
:Yeah.
Mike Giambattista:And authenticity is becoming like for certain brands, authenticity is just like critical is becoming like. For certain brands, authenticity is just like critical. If you, if you're caught faking it, or even the appearance of faking it, you're doomed. So you prompted me.
:Now you answer sorry I don't have an answer. I just have questions. I don't know if I have an answer to that. Um, yeah, I mean it is so important and just kind of talking about the future. I mean, even myself personally, I have reservations about AI myself. I expect a certain level of personalization and authenticity, like you said. So what I think is really nice about working for a big company like Pega is also having that other side, which I think that you've talked to a lot of my colleagues around customer decision hub and the one-to-one customer engagement that you know also was kind of a factor that made me really interested in working at Pega.
:It's a completely different approach than these, you know, batch marketing campaigns where you're actually able to you know, not only market to that customer but, if you know it's not the right time, actually hold back a message, and I think that that's really important. So I think that going forward customer service, as well as that one-to-one customer engagement, is going to continue to meld and be more and more important.
