The CX Shift AI Just Triggered

Customer expectations are shifting faster than most organizations can respond. In this episode of the AI Proving Ground Podcast, leaders from healthcare, utilities and retail break down how AI is redefining what “good” customer experience looks like — and how their industries are rethinking service models, operational workflows and human touchpoints to keep pace with a new, AI-shaped standard.

More about this week's guests:

Dr. Eric Quinones is a physician leader committed to the Quintuple Aim—elevating patient experience, improving population health, lowering costs, strengthening clinician well-being, and addressing social determinants of health. He drives these outcomes through digital innovation and data-driven transformation that advance both clinical and business goals.

Eric's top pick: HLTH USA 2025: The Year Healthcare Took its Relationship with AI to the Next Level

Adam Nathan is an analytical, curious leader focused on helping organizations align business priorities with modern technology to drive meaningful transformation. Motivated by impact at societal scale, he is dedicated to advancing the Utility and Energy sectors—modernizing the critical infrastructure that powers everyday life.

Adam's top pick: Accelerating Utility Rate Case Filings with Generative AI

Brian Murphy is a seasoned executive and strategist with 30+ years of success at the intersection of business and technology. A trusted solution architect and thought leader, he has guided major organizations through complex transformations, consistently delivering measurable impact and strategic clarity.

Brian's top pick: From Kiosks to AI: What RLC 2025 Means for the Future of Restaurant Tech

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions.

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.

Chapters

• 0:00 AI Just Flipped CX
• 0:52 Who’s Driving This Shift
• 2:25 Healthcare’s Two-Front War
• 5:46 Data Chaos in Healthcare
• 6:55 Utilities Wake Up
• 9:10 Retail’s Personalization Crunch
• 11:15 Escaping Pilot Purgatory
• 13:50 ROI Wins That Don’t Hurt
• 16:12 The Data Bottleneck
• 18:22 Build the CX Flywheel
• 20:54 The New Digital Front Door
• 23:58 EX = CX (Deal With It)
• 26:37 Burnout Meets Ambient AI
• 28:33 Agentic AI: Real or Hype?

Transcript

SPEAKER_02: 0:00

From Worldwide Technology, this is the AI Proving Ground Podcast. Today, customer experience, the front line of every industry, is going through one of the fastest transformations we've seen in years. Not because customer expectations are rising, they already have, but because AI is now reshaping what good even looks like. Pick your industry, retail, healthcare, financial services. Customers expect to be understood instantly, supported seamlessly, and engaged on their own terms. And companies are discovering that the journey from pilot projects to real operational AI is a grind, filled with false starts, unexpected wins, and the quiet lessons that only come from getting it wrong first. So today, we'll be talking with three industry experts seeing these shifts unfold in real time. These are leaders on the front lines of how AI is reshaping customer expectations, operations, and outcomes. We'll be talking with Dr. Eric Kinitz, who brings a rare blend of clinical insight and technical vision, helping healthcare organizations use AI to reduce friction, improve outcomes, and transform the patient experience. We'll also have Adam Nathan, who is working with utilities on the ground as they modernize aging systems, adapt to rising demand, and use AI to deliver more reliable, resilient, and customer-focused service. And finally, we'll have Brian Murphy, who is helping retailers navigate rapid shifts in consumer behavior, using AI to improve personalization, streamline operations, and create more connected customer journeys. Together, we'll unpack the tensions CX leaders feel between cost and return. It's a gap that's widening even as the data shows AI can dramatically improve outcomes. And we'll talk about one of the biggest barriers few want to admit fragmented data that promises insight yet often derails transformation before it even begins. So let's dive in.

SPEAKER_01: 2:23

Great question, Ryan. Well, first, what I want to do is kind of pause and just kind of like describe, you know, in healthcare how we see the word customer, right? So what does that mean? So for us or for me, customer means, I mean, the obvious is is the patient. Um, but the not so obvious is the clinician. So they're also the customer. Um, they're the ones taking care of the patient. So um that's really important to denote. Um, you know, both have very, I would say they're they have expectations of high personalization and also frictionless experiences now. And, you know, for example, patients, they want to feel, you know, that they're activated, that they're engaged and, you know, um in control of how and when and where they're gonna receive their care, you know, with um convenience of access, you know, that they see in other industries, right? So the experiences they're seeing there. Um, you know, they they want it to be personalized for them. So that's that's something that patients really want. Um, they want these tailored engagements, you know, personalized reminders, um, not generic things that are generic. They want uh, you know, custom care plans and uh, you know, real-time connectivity to their care teams is very important as well. Um, you know, they want to feel like, you know, in in, you know, hopefully they don't, but they will, you know, we all will sometimes get you know ill. Um that when that does happen, that they are understood, that they are guided along that journey, their care journey. And and um, and unfortunately today that's that's not the case. There's a lot of um fragmentation there. So, you know, they want to I think of it as a parent and a child. You know, a parent lovingly cares for their child. They want to fill that kind of bond, right? Where that they're being, you know, looked after, you know, um, you know, and cared for proactively. Now, where AI kind of meets that, it's uh, you know, it plays a significant role in this area. So healthcare systems today are not only bringing in the clinical data, but they're also bringing in data such as social determinants of health data. They're bringing in uh genomic and microbiome data, um, behavioral data, and then other data sources like wearable data that that patients may have. So they're bringing in a lot of data. And now, you know, with AI, you can actually bring in that personalized, proactive uh attention that these patients are yearning for. You know, some patients now, you know, with with certain health systems, they have, you know, kind of these personal AI assistance that can handle, you know, check-ins, pre-visit uh questions, uh summarizing lab results and things like that, and even digital triage via chat or or voice. Um, you know, they receive proactive reminders, you know, for their health maintenance screening, um, which is awesome. And and they have uh, you know, these follow-up visit uh reminders. Again, these are very personal to them and and things that help identify their personal care gaps. That happens a lot in healthcare. And so, you know, these AI assistants can really help guide, you know, these patients along their next steps when it comes down to uh empowering them and giving them self-service. You know, for example, really quick, I think this needs a shout-out. So, for example, you know, we here at at uh WWT, we were engaged with uh uh a unified omni-channel experience with a very large non-for-profit healthcare system in in the Midwest. Um they're serving like 2.4 million patients annually, and their patients are dealing with about 40 plus different data sources or applications, and they wanted to bring that into a single pane of glass, if you will, so a unified experience. So our amazing digital team and WWT got involved, applied their methodologies, and um, and were able to actually create a roadmap and develop this uh an application that brings this into a unified uh omni-channel experience for them. And then overlaying on top of that is uh an AI platform that will help really kind of keep um you know healthcare on all the time for them, and even bringing in tools where helping to guide the patients along their journey. So we're doing this kind of work here today.

SPEAKER_02: 6:54

Yeah, yeah. Uh Adam, build on that a little bit. I don't want to make assumptions, uh, a valuable lesson I learned on a prior episode, thanks to uh Mr. Mike Trijecki, go and give that one a lesson. Um, but you know, Adam, build on that is is are we seeing a relatively same story in utilities, or is it something uh different in terms of customer experience and how AI is enabling it?

SPEAKER_00: 7:15

I mean, I think it's there's there's some similarity in that I think no one thought about these two uh industries historically as you know the pinnacle of of the customer experience, right? It's uh you don't think of your utility. And actually, for a long time, for a hundred years, the utility has wanted you to not think about the utility. They didn't want you to have to have a customer experience other than your power shows up. And I think when power is not there, that's something everyone you know ruse and doesn't want to happen, and then they hate making that call to the utility, or they feel like the digital experience has been bad. And so uh this is this is something that the customers or that the utilities are are investing more and more in. There are uh drivers to incentivize that. Leaders are judged on and there are bonuses paid based on JD Power um uh scores. And so looking at things like observability and and um and customer sentiment is is increasingly important. Uh and and so they're investing in systems that can do that, as well as there's some some quick wins related to things like real-time translation. You think about a utility, a utility serves everybody, and so they need they get calls from people that speak myriad languages, and so they need to be able to serve provide that high quality service to everybody. And you know, you can't go higher 24-7 coverage for every language out there, and then that you know, that opening uh that opening line when you call in would would have, you know, you'd have to have you know 50 buttons to press with different languages. This now allows you to to staff more efficiently while serving the customer much better. And and it's a quick win and and it's an AI use case, right? So that's that's sort of a win all the way around. And and that's table stakes for a lot of these systems today.

SPEAKER_02: 9:01

Yeah. Brian, uh, wrap us up here on this question. Uh, I think you know, retail is you know something that a lot of us are are very uh intimately familiar with, just as you know, part of our everyday lives. What are you seeing in terms of the experience there on the customer side and how is AI pushing it forward to make it better?

SPEAKER_03: 9:17

Yeah, I would I would just plus one, the comments already mentioned around personalization, a frictionless experience. I think where retailers are spending most of their time is trying to understand and gain access or ownership to the data that will drive um the ability to leverage AI for a better customer experience. Uh data is very fragmented in the retail space, especially um in the what we might refer to as the mid-market retailers. Big box retailers have a pretty good sense of their data. The Walmart of the world, as an example, just launched a chat uh GBT tool to help in your online buying effort. Um, but 80%, 90% of heather retailers don't have the technical wherewithal or uh they haven't thought about how data will drive a personalized experience with enough depth to drive their strategy around their IT efforts. Therefore, they're buying product's off the shelf to as point solutions. Those products typically want to own the data because they know how valuable it is, and it makes it very difficult for the retailers to leverage that data in a way to drive that personalized, frictionless experience. Um, I'd also add that part of that customer experience is the ability to buy, which speaks to you got to have product to sell, which speaks to supply chain and warehouse management. And we're doing a lot of work here at WWT in the retail space, leveraging AI to drive efficiency in the supply chain, in demand management and demand prediction. Um and then uh lastly, I just share personalization not only drives a better experience for the customer, but it drives things like increased revenue because you can provide personalized offers to the customer that actually will be relevant to that customer, therefore they will buy. Um, and that's critical. And we're doing a lot of work in that space as well.

SPEAKER_02: 11:10

Yeah, Adam, you had mentioned um a couple use cases, at least within the utilities um sector. So many of the organizations that we interact with or organizations just from around the world are struggling to push some of those pilot, some of those use cases that are pilots out into production. Um what can we say? Uh how do we advise some of our customers on how to get out of that kind of uh trap and start to move more towards the flywheel effect where you know the second and third, fourth, fifth, sixth uh use cases are a little bit easier to deliver than the first one?

SPEAKER_00: 11:43

I think it it's in line with a lot of what what Brian and Dr. Kinonis mentioned, which is you're not going to connect every one of your operational systems into your AI platform on day one, right? It just you just can't have a comprehensive chat bot that engages with your customers at a time of need right out of the gate because and in the utility space, and I know in the healthcare space as well, there's a lot of regulatory hurdles to jump through in order to be able to connect these systems in and make sure the right permissions are there and you're only allowed to share certain data. So it's and and some of these are, you know, for for the utilities are 50-year-old software systems sitting on mainframes. So integrating with them is not exactly easy. So I think it's about finding those quicker wins. So, you know, it's it's instead of having to think about uh your outage management system in the utility space where you're integrating that maybe on day one, that's going to be really hard. There are regulatory hurdles around that. Instead, you could focus on the billing system, which doesn't have as many hurdles uh in terms of like grid data that that uh where your security team might not be as as um concerned about that. And and and so now you can answer billing questions much more easily and maybe even get a chat bot. So instead of waiting on hold for you know 10 minutes before you talk to someone, 15 minutes, 30 minutes, you're able to answer those questions in a in a humanistic way, right? Maybe even on a call where it sounds and feels like you're talking to a human, but you're getting the answer that you need, having that dialogue. Those are some of the quicker wins. And then as you integrate other systems, you're able to enhance that experience over time. And that's really where the flywheel effect comes in.

SPEAKER_02: 13:25

Yeah, no, absolutely. Dr. Kinonas, you know, I'm wondering, you know, uh Adam mentions a couple uh use cases, you know, whether it's uh, you know, billing or chatbots, things that you know you could see applying within the healthcare uh sphere. Is there anything uh to to be said about you know leaning into some of those low-hanging fruit or uh use cases that are really enhancing the customer experiences? And does that help build momentum for future investment?

SPEAKER_01: 13:50

Yeah, I think I think that's really important to note. The you know, healthcare systems don't have a lot of money to spend, right? So they have to be very strategic in how they're spending that money. So they're looking for things that really do impact, you know, um, you know, the ROI. Um, there has to be that. Um, and then they're looking at things that, okay, is this going to require a lot of regulation if we're gonna deploy this? Um, that can be a headache. And they're also looking at do we even have the data? Do we have a sense of where the data is at? So, you know, taking those three things into consideration, um, they are in uh in regards to um, you know, the client or the customer experience, in this case, maybe the patient, they're definitely trying to find those high uh sticky, low uh lift uh solutions to help engage them. You know, one of the things that that's happening today in healthcare is that you have the ability to pick up and leave and go to another healthcare system. So keeping their members, keeping their their patients is really critical. So they're they're bringing in tools to help engage their patients, like I mentioned before, um, where they're um you know really making them feel part of a uh a team or a part, yeah, because they have to be part of the team. I'll say that. You know, a lot of times I think patients think that it magically happens, but they have to be engaged in their healthcare too. So um so they're bringing in these kinds of tools that are really going to help, you know, uh make that bond. And those are, you know, that are not necessarily very um, I would say, uh heavy lift tools. These are tools that that can actually bring value right away. So again, some of the things I mentioned initially, um, you know, that you think that they're simple, but they're and you think that they're they're already there, but they're not. So, you know, just having things to help, you know, promote that patient's health through nudging and letting them know that, hey, you know, you're you're doing good, you know, but you can be doing better if you make some, you know, changes and explaining it to them in a way that they understand. So again, in their native language and in in um, you know, at the level that they can understand is really important. Yeah.

SPEAKER_02: 16:11

Yeah. Hey, Brian, uh Joe, right before we started uh recording this episode, showed that iceberg slide that talked about how customer experiences demand that full stack approach, you know, with the top being experiences on down to the AI and data letter and then, you know, into the more hardcore infrastructure. From what you see in interacting with uh with retailers around the world or any organization for that matter, is there a particular area that um organizations are struggling with or make missteps in, like they're focusing too much on something or not enough in another area?

SPEAKER_03: 16:43

Um I would say the number one thing we probably talk about is there's a great amount of demand or interest in leveraging AI in retail, as there is in many industries. And it's interesting when you start talking to a customer about it, they want to learn, they want to know how to leverage AI. Is this real? Does it is it really to deliver value? And then we'll talk about use cases and we'll come with some good use cases they could leverage. And they go, great, let's go after that. And then we say, okay, well, let's look at your data. And the foundation of any AI solution is going to be the data. And unfortunately, in retail, um, years and years of core data management and data governance leads to making the ability to leverage AI very difficult for many of them. Um it's very siloed, the data can be very siloed, it's not well architected, it's not easily accessible. Or as I mentioned earlier, it's it's in essence owned by a third-party product that they use, and so they can't gain access to it. Probably the number one challenge they're facing today uh is just that. It's the it's the basics. It's like, is your data in a position to l to leverage effectively to drive value out of AI?

SPEAKER_02: 17:52

Yeah. Adam, you know, uh Brian mentions data being siloed. I was I was reading a report, I think it was from uh next next Diva. I hope I'm pronouncing it correctly, but they found that 86% of companies using multiple CX tools experience these data silos. Um, there's so many tools out there. How can we advise clients or organizations to get a better handle on their data estate so that they can move forward and deliver those personalized experiences, those new age experiences?

SPEAKER_00: 18:22

I think it goes back to the flywheel, right? You gotta get, no one's gonna, you're not gonna solve one of the challenges that that a lot of companies are making right now is they're going after their highest value opportunities, not thinking about the complexity side of it. Right. If it takes so in the utility space, I'll give you an example. They they want to serve up the uh uh an automated message to customers about their how long it's gonna be before they get restoration. Uh not too long ago, I was wait wait in an outage, not too long ago, I was I was at dinner with someone uh who runs that program for a utility and there was an outage and he got the notification and we asked him how long until it's fixed, and he said, I don't believe that number. So the you know, if you tell someone 45 minutes and it's four hours, or you tell them four hours, I mean, obviously they'll be happier if it's 45 minutes, but either way, they can't plan their life around that. And and so that's an example of solving that problem for the customer, that providing that customer experience with the automated message is only valuable if that data is right. And so selecting the the problems you can actually solve while laying the foundation for improving that data over time, and that's really where we see things like asset 360 uh is is a way we engage around fixing a lot of the underlying asset data in order to be able to get to to establish that foundation. Well, and but we always do it while solving problems that are near term so that they're seeing that value along the way. And I think that's really that that's one way to I think that the fastest way to get these things shut down is go after a really big hairy problem that you can't solve in a short in a short amount of time, where you you're not gonna add value for two years and and people will will burn out that way. You really got to get that flywheel effect going.

SPEAKER_02: 20:16

Yeah. Dr. Kinone is um, you know, the reactor the the possibility and the potential of AI is is right there to understand. But the reality, you know, seems to be a little bit more messy. There's so many tools out there, there's so much hype, there's so much going on in the AI space. Um, from a CX leader perspective, I think, you know, or at least from from what I've read and understood, cost is still one of the major barriers to driving adoption of some of these AI solutions. I'm wondering how how can we have customer experience and thinking of the customer experience first, how can that help articulate ROI uh for an organization to keep going?

SPEAKER_01: 20:54

Yeah, I think, you know, again, like I mentioned, you know, that the budgets are tight. So they have to be very strategic in how they look at that, how they're investing uh, you know, those those dollars they have. So but they have to do it. I mean, it has to be done because if they're not gonna put it this way, everyone else is going to do it. And they have to do it in a way that they can stay competitive because they're all trying to, you know, either can't maintain their their the number of patients they have, or if they're going through acquisitions, right, you know, and they're acquiring new new systems and they're bringing in those new patients. Again, a lot of times there's this uh disconnect, right? So the patients may be on just say one EHR and there's another electronic health record they're on because uh, you know, just again, the nature of the the deal. And they have to bring them into for branding purposes and and for purposes to to really um you know offer the same services that that the the acquiring organization is offering. So they have to be very strategic there in the way they spend their money. And um, you know, I think that you know, their their practices um that that we see today is that when they don't do these things, when they're missing that boat, patients feel neglected, patients feel like they can do better. Um, you know, I I personally had an experience where I was with one healthcare organization, their digital engagement um was very power, very, very poor. Um it literally they were giving misinformation. And I and I know enough you know to get to be dangerous, so I'm like, no, this is not the experience that I want. So I left. I I literally left and went to another healthcare organization, which they I knew that they had a very mature, you know, digital presence. And my experience is completely different, you know. Um, so again, they made the investment um strategically to to do that or to make to make sure that they're sticky with their patients. And I uh and they continue to make those investments. So I don't see them losing patience. Um, so that's that's a I think a good example where you know you need to make these investments to make sure that you you maintain your your patients and uh you don't lose them.

SPEAKER_03: 23:24

Digital is the front door for almost every business now, and it's gotta be a differentiated experience if you're gonna compete. Um today, tomorrow, for sure, right? You've got to have a differentiated experience. It's so true in healthcare, it's true in retail, even more so. There are so many competitors in almost every industry that you're dealing with, maybe not utilities because it's regulated, but um if you don't have a differentiated digital experience, you're gonna lose customers and therefore your business is gonna suffer.

SPEAKER_00: 23:56

100%. One area in the utility space where, yeah, sure, you don't have choice necessarily on which utility you use, but employees have a choice of where they go to work. And you know, you they are having trouble finding people that want to show up and and and take a job at the utility. And some of it is they they're they're seeing 30, 50, sometimes some reports are saying 70% of their skilled workforce is is at or near retirement age. That is a cliff that they are about to fall off of and are already experiencing. I mean, you walk around the halls on a Friday and there are you know retirement parties going on all over the place. And and so you can't just replace all of those people on the tribal knowledge. And you think about how many, how many utilities are running 37-year-old networks that are critical infant that are critical to running the grid. And and so that's why so uh an example of of the employee experience, which is to in so many ways, like Dr. Kanyuna said, the clinician experience, the the the customer experience for IT is so often that employee experience. And uh we were we're doing some work with Southern California Edison. It's a a case study on on our on the platform, and we are we were working with them on you know, how do we bring this into your NOC? How do we bring AI and better experience into your NOC? And you know, somebody from the NOC came out and said, well, just stop thinking about the you know, the futuristic networks, the private cellular network we're building and all of the cool stuff. We have a 38-year-old network, we have five people that know how to run it, and they're all gonna retire before the end of the decade. And that's well before we're gonna get off of that network. So if if we don't figure out a way to upskill people and allow people who don't have 35 years of experience with this to manage it, then we are not going to have a solution to manage our critical infrastructure. And that I think is one of the ways that we need to think about this is that's the cost of doing nothing is incredibly high in some of these situations. Whereas you know, you you can't necessarily show an ROI of you know better revenue or lower cost. It's it's more cost avoidance or problem avoidance.

SPEAKER_01: 26:06

Could can I add to that really quick? Because Adam, you bring up a great point. So we're we're encountering the same problem in healthcare. So we're gonna have a pretty significant deficit, and we already are having a significant deficit with clinicians. And you know, I have colleagues of mine that, you know, during the pandemic or post-pandemic, they were, you know, thinking of uh early retirement or leaving healthcare altogether. And I would say because of some of these changes we're seeing now, some of the technologies we're seeing now that are being offered to them. So for example, ambient technologies for digit for documentation, um, you know, chart review, uh, inbox management, inbox inbox um, you know, messaging management to have it like their own um AI assistant, they are reconsidering that decision. They are like actually falling in love a little bit more with medicine that and and that's really critical because if you have two healthcare systems you know across the street from each other and they're offering, say, the same pay, right? And you have new clinicians that are coming out. Remember, it takes a long time to train a clinician. It does, it's this is not like a light switch. It takes a very long time. So you have new clinicians that are coming to the marketplace that are for work and they look at these two healthcare systems. If one has the technical and the digital tools that are gonna help make their job easier and reduce the friction burnout, I'm gonna choose that one. So, you know, that's also a competitive advantage.

SPEAKER_02: 27:31

Yeah. Well, I know we're running short on time here. So I'm gonna give uh the three of you some separate kind of uh factor fiction uh quick hit actions here just to end our episode. Uh Dr. Quinz, I'll start with you. Agentic AI will force organizations to rethink how they measure customer experience, or in your case, patient experience all together. Fact or fiction?

SPEAKER_01: 27:53

Um I I think it depends. It's uh I think it's uh uh fact aspirationally um fiction when it comes down to live clinical practice today. Um, you know, there's there's just too much at stake uh for agentic AI to be making decisions uh, you know, without my knowledge or you know, without you know proper regulation. You know, if a patient comes into the ED and and uh they're coming in with stable ventricular you know tachycardia and the agentic AI, you know, makes a decision to actually, you know, prescribe you know atropine instead of amiodorone, well, who's gonna be liable for that that death?

SPEAKER_02: 28:33

Yeah. Yeah. Brian, uh moving on to you, fact or fiction. Personalization is the most powerful capability that AI will bring to the customer experience in the future.

SPEAKER_03: 28:44

I'll go with fact. I think it's where most in the retail space at least, that's where most retailers are focused and thinking about. It's not the the only thing, obviously, as I mentioned earlier, um, there's other factors of the business management that are important. But but again, if you're gonna create a differentiated experience um and you want to leverage AI to help you do that, um it will drive a personalization that again creates a customer experience that's unique and hyper personalized and frictionless and therefore drives you know revenue, drives your business, helps you grow.

SPEAKER_02: 29:21

So I'll go with fact. Yeah. Yeah. Adam, last one here, fact or fiction. AI will eventually handle the entire customer journey end to end from first touch to resolution.

SPEAKER_00: 29:33

Facts. It's already handling, and we can handle a lot of customer related events with just, you know, touch tone kind of interactions. And the more humanoid that that the the that the interaction gets, I think the the more they won't be able to tell the difference. And they yeah, they absolutely won't care as long as they're getting the right information or the right resolution. Yeah.

SPEAKER_02: 29:55

Well, to the three of you, thanks so much for joining us on this episode of the AI Proving Ground podcast. And uh thanks to the ATSM crowd for sticking around and letting us crash the party. Hopefully, we'll do it again soon. Uh, okay, what we've heard today is that AI isn't just reshaping customer experience, it's redefining what every industry believes is possible. The companies making real progress aren't the ones chasing hype, they're the ones learning quickly, fixing what's broken, and building the foundations that let AI scale with purpose. For leaders, the takeaway is simple: the next wave of customer experience won't be won by technology alone, but by the organizations willing to rethink how they work, how they listen, and how they serve. This episode of the AI Proven Ground Podcast was co-produced by Joe Berger, Nas Baker, and Kara Kuhn. Our audio and video engineer is John Knoblok. My name is Brian Felt. We'll see you next time.