How RingCentral Uses AI to Improve Conversations Without Losing the Human Touch

[00:00:04] - [Speaker 0]
Welcome to AI at Work, a podcast which is part of the Tech Talks Network. And in this podcast, we're gonna venture into the transformative influence of artificial intelligence inside the workplace. And our discussions will focus on both the remarkable breakthroughs, but also the complex challenges of integrating AI into our everyday business functions and workflows. And in today's episode of the AI at Work podcast, I'm joined by John Finch from RingCentral. And together, we're gonna explore how AI is reshaping the customer journey across contact centers and indeed wider customer operations.

[00:00:48] - [Speaker 0]
And we'll also look at how real time agent assistance, AI receptionists, and voice intelligence are all beginning to change the way that organizations manage missed calls, reduce friction, and improve both employee and customer experiences. So from those early handoff moments in a call to the strategic power of conversation data. Today's conversation will shed light on what practical AI adoption really looks like inside the modern contact center. And so on that note, let me warmly introduce you to John now. So a massive warm welcome to the show.

[00:01:30] - [Speaker 0]
Can you tell everyone listening a little about who you are and what you do?

[00:01:34] - [Speaker 1]
Yes. So thanks for having me, Neil. I I appreciate it. My name is John Finch. I head up product marketing here at RingCentral, which means a lot of things.

[00:01:44] - [Speaker 1]
I wear a lot of hats, but, the my primary focus is is really bringing these great products to market and focusing on innovation and driving the narrative across the universe in terms of who we are, what we are, and how AI is helping organizations to perform better and to optimize their customer experiences overall.

[00:02:05] - [Speaker 0]
Well, thank you for sitting down with me today. We are at that time of the year. We're near at the end of the year. It's also three years since ChatGPT landed, the world became obsessed with all things AI. And I think we've been on quite a journey from the hype, jumping on bandwagons to now, okay.

[00:02:23] - [Speaker 0]
What's the ROI? What difference are we making? So when you look at the early stages of a customer journey, I'm curious. Where do you see AI already making a real difference in things like preventing missed calls, lost inquiries, or even early friction? And and how are teams combining forecasting with smarter routing to fix this?

[00:02:42] - [Speaker 0]
Because you must be seeing so many great things, I'd look to shine a light on it.

[00:02:46] - [Speaker 1]
Well, we look we look at this in in a couple of different ways because I think there's so many different components of the customer journey that we tend to forget. We tend to forget about, like, the during the call or, you know, sometimes it's pre call before it hits a human, if you will. But then there's a lot of things that go on after the call that we sometimes don't think about kinda universally. And so the way we break this down here at RingCentral to sort of simplify, I mean, AI is helping at every stage of that customer journey. And if you look at it from the front door coming in and using, you know, a chatbot or what we, you know, clinically call, I guess, an IVA, interactive virtual assistant, to triage a lot of those capabilities of getting resolution, self-service, twenty four seven completed and and in a way that is efficient and done right the first time, then it never gets has to get passed off to human.

[00:03:44] - [Speaker 1]
Right? So the containment, if you will, of the promise of AI and agentic AI of really being able to contain that and provide a level of efficacy that's at least 80% or greater in terms of resolution and customer satisfaction, that's kinda where we see that taking taking a big stab. But then there's also the components of you know, during the call. Right? So, know, you what percentage of of these agents are actually able to do what we need them to do?

[00:04:13] - [Speaker 1]
Well, there's learning. There's training. Things are changing all the time. So they're constantly and forever changing how they're interacting. But in a lot of cases, you have to transfer to a human.

[00:04:23] - [Speaker 1]
But the challenge is making sure that that information gets handed off contextually to the human so the human could pick up right where that, digital worker left off. Right? So being able to transfer it there and then assisting the human and utilizing AI to assist the human during that live interaction to write properly, to find information, to have AI make suggestions during the conversation, and then after the call, being able to improve their performance. Right? So looking at the metrics, looking at information that's going on during the call so that you can be, as an agent, scored on your effectiveness.

[00:05:00] - [Speaker 1]
Right? And then suggested gently areas of improvement, right, to better your performance for next time. And then that cycle continues. Right? At the same time, there's information that's gleaned from those conversations that a business can use to ultimately make decisions on their business.

[00:05:16] - [Speaker 1]
Right? And so we can talk more about that, and I can go on forever on that. But it really is about the analytics that come out of the voice and digital conversations that becomes information that businesses now can effectively use to change the way they operate, to change the way they staff organizations, you know, and change the way that they're they're looking at expanding into certain geos, launching products, and general customer happiness overall.

[00:05:44] - [Speaker 0]
And I think many leaders are talking about real time agent support, but the experience as a customer can vary wildly in practice. So from your viewpoint here, what does effective in the moment guidance look like from your perspective? And and how do you keep that that support helpful rather than overwhelming, frustrating, or confusing?

[00:06:04] - [Speaker 1]
It's interesting. Right? Because we've seen this evolution for a long time. And I've been in this space for a very long time, and, you know, we've all had customer service experiences our entire lives. Right?

[00:06:14] - [Speaker 1]
And most of them happen over the phone, and a lot of them now over the last, you know, let's call it, decade or so, we've been having, you know, multiple mow multimodal types of interactions. Right? Interactions where individuals could come in and use digital, you know, applications that they're using for the mobile device or other. So I think, you know, from from this, the agent really is, in a lot of times, overwhelmed. Right?

[00:06:40] - [Speaker 1]
And I think there's also the happiness factor of their job, sort of who they are as individuals, what they're paid, the environment that they're in. So lots of factors. Right? And so if you can make their job any easier with all of those other things that are sort of crushing down on them on a daily basis, they're gonna be happier and happier. Right?

[00:07:02] - [Speaker 1]
And so number one, like we just talked about, offloading menial, mundane tasks at the beginning. Brilliant. Right? Love that. Secondarily to it, in the moment, to your point and your question, it is about having a copilot or a buddy sitting right there listening to the conversation and going, hey.

[00:07:21] - [Speaker 1]
You might wanna say this or, you know, you're doing a good job. You know? Oh, slow down. You know? Speed up.

[00:07:26] - [Speaker 1]
You know? You're talking too slow. The customer's overwhelming you. You know? Just restart.

[00:07:30] - [Speaker 1]
Providing some level of guidance, providing the information that they don't have to toggle between multiple windows and dig through FAQs and go to a different system and log in, put the customer on hold, you know, go talk to a supervisor. That digital copilot, if you will, that what we call AIVA agent assist provides that capability to the agent in real time where it's listening to the call. It's digging into the knowledge bases and other assets and information that has access to within the organization to provide the agent with the real time coaching and information that they need to respond to the customer. And it's done in a way that's in a window that they use every day. So it happens to be the RingCentral app where every user of RingCentral can be from the phone user all the way through to a contact center agent to a supervisor and to a business leader.

[00:08:24] - [Speaker 1]
They have all of those activities, and they have all of that from that one window. But it also works from the apps they use every day. So if they're using Zendesk or they're using Salesforce or they're using HubSpot, RingCentral works inside that same app where they're using that app, but they're gaining the accessibility of RingCentral's capabilities right within that window. So it's leveraging and utilizing the tools that they use every day to provide them with the guidance that they need to feel good about the customer resolutions that they're handling at that moment and ensuring that the information that they're giving to that customer is correct and done the first time. And the great thing about that too is is the ability to sit anybody down, a seasoned agent or a brand new agent that maybe just took a couple learning courses themselves, pop them into, you know, call queue, boom, they're done.

[00:09:11] - [Speaker 1]
They can actually answer questions. You could throw me into, you know, Comcast as a big cable company here in The US and be able to you know, I could answer the phone if they had if I had agent assist. Right? I could answer calls. And I probably wouldn't start out with, did you turn it on and turn it off?

[00:09:27] - [Speaker 0]
Yeah. The one finger fixed fixes everything. I suppose in some circles, there were some people listening, there will be that that thought that too much automation can almost create a detached customer experience. So where do you think the automation genuinely strengthens that interaction like that example you've given? And and, also, when does it start to get in the way of that natural conversation?

[00:09:50] - [Speaker 0]
Is it a quite a fine balancing act there?

[00:09:54] - [Speaker 1]
You know, it's not really a balancing act because what's what the difference really is is you're it's not a script.

[00:10:04] - [Speaker 0]
Yeah.

[00:10:05] - [Speaker 1]
So in the old world, we sort of were like, okay. We can't control what the agents are saying, so we're gonna write scripts. And these things are gonna pop up at certain moments throughout the call, and they're going to provide the the agent with information they need to read. Right? And that is sort of the canned, bad approach, you know, way of looking at providing customer service that fits within a parameter that or guidelines that the company has set forth.

[00:10:32] - [Speaker 1]
You know? And those things are fine. Like, you know, there are sales motions where you're going through, you know, specific, you know, points during the conversation to ensure that you're hitting these marks so you can close the deal. There are certain things you need to say based on, compliance or other things that maybe need to be said by a financial institution or or health care institution or other things like that. But the way that this has been set up now is it's more conversational.

[00:10:58] - [Speaker 1]
It's more free flow. So you're not reading a script. It is prompting you with a human like suggestion on the side just like you would be sitting next to me in the contact center and poking and going, hey. You know, you might wanna say this instead. Then that's a better way.

[00:11:14] - [Speaker 1]
It's a more human sort of way to enable the digital worker and the human worker to work together in concert. And I think that that that really provides, those agents with a better experience than they've had in the past. I won't say it's perfect. Right? I'll say it's getting better.

[00:11:34] - [Speaker 1]
And I also am a big advocate of of, you know, the human. Right? So everything we do is for the human. It isn't about replacement. It isn't about the bot or the digital worker can do it better, in any case.

[00:11:49] - [Speaker 1]
It really is something that helps the the performance of the human, therefore helping the performance of the customer who is also human. So that human piece is always woven through, and that's why we're so into the fact I mean, anything that we're doing with AI is does it sound human enough. Right? And we're also very tuned to the fact of, like, sounds still so robotic. And then they're like, wow.

[00:12:13] - [Speaker 1]
That's a real person's voice. So we're getting to a point, right, where we're starting to see this bleed over between the two. Right? Because some people do sound like robots. Let's be honest.

[00:12:23] - [Speaker 1]
And I think at the end of the day, you know, that is that is a component that we always have to keep in tune. Right? And and and I you know, like you talk to a lot of people that are really into AI, and if it doesn't sound like it, I'm really into AI and I'm really into customer service. And, you know, I think the blending of these two really is this tipping point of perfection. And we get to a point where, you know, we've all had such bad experiences.

[00:12:48] - [Speaker 1]
There's got to be another level of innovation. And I think we're just at the cusp of this. Right? We we hear this from everybody we talk to. We're just at the cusp of what AI is doing.

[00:12:58] - [Speaker 1]
We've all watched the shows about the big, you know, large language model components and the details about how they're interacting with their builders, right, and and certain challenges, we have a long way to go. And I think we're just we're just hitting this. There's a lot more for us that we're doing internally that we haven't talked about yet, to the public world, we're gonna be excited about in 2026, that really kinda gives us another layer of how these performances across the board are enhanced in in another level of a way to assist humans and assist business in doing things better, being more productive, making more money, keeping customers longer, and identifying problems before they actually occur. Right? So the data is key when it comes down to some of those things.

[00:13:46] - [Speaker 0]
And before you came on the podcast today, I was reading that you I think you previously said that conversations themselves are becoming a strategic dataset. So for anybody listening that are working in this industry, what does that shift look like inside the modern contact center, and how are teams using insights from those conversations to reshape routing scripts and maybe even workforce planning?

[00:14:09] - [Speaker 1]
Yeah. I mean, voice is still king or queen, however you wanna look at it. It it absolutely is. It's what we're doing right now. Right?

[00:14:19] - [Speaker 1]
It is the most human thing. And if you look and step back strategically for a minute, any sort of situation you're in, you can't communicate emotions, feelings, intent properly through a digital interaction. You know? Some people can. Right?

[00:14:41] - [Speaker 1]
I can't. I'm really bad at it. I'm pretty straightforward. I type things. People are like, oh, are you mad?

[00:14:45] - [Speaker 1]
No. Not at all. I'm just asking for something. Just because I didn't put a bunch of niceties beforehand in the opening statements doesn't mean that I'm angry whatsoever. Right?

[00:14:53] - [Speaker 1]
It's just the way I communicate effectively through a digital interaction. But the way I talk is definitely different. And so having the live conversation is one of those things where you really understand the tone, the feeling, the emotions, and it's the most complete. So where it kinda comes into where RingCentral is superior in my mind, and I've been in a lot of other companies in my history as well, is the voice. Right?

[00:15:18] - [Speaker 1]
Voice is king queen. And, you know, I already said that. But at the end of the day, it is that most human level of conversation. Now let's take that one step further. Right?

[00:15:27] - [Speaker 1]
So it's not gonna die in the contact center. It's not gonna die in communications of us interacting with one another, being social. And when we have a big problem, we're gonna call someone or we're gonna, like, find them and have a physical conversation with them. So you take that one step further. You look at the data that's out there, like the central data repositories that people are using inside organizations.

[00:15:47] - [Speaker 1]
And a lot of them is numbers data. A lot of it is written data, that's all over the place, and a lot of it is, like, CRM data, for example. Right? But none of that stuff is really complete and organized in such a way. So there are AI tools.

[00:16:00] - [Speaker 1]
There are, you know, big databases with AI that can kinda bring these things together and big data lakes and all of those things. But voice data, once transcribed, is the most complete. And that data can be used to ascertain information and provide businesses with the insights they need. It's also the data that is used to train models and to provide information to agents to support them during live conversations. And the AI is gonna look at those transcripts and information for that particular business because all that data for those businesses is their data.

[00:16:37] - [Speaker 1]
Right? That data then can be used to improve the performance of those agents every time they're talking. So every time multiple agents are having conversations and there's success in those conversations, that information is then fed to the AI that can then provide those correct responses to the agent to better and better and better the improvement in the performance and customer satisfaction. So that voice data is key to that success. It's the most complete.

[00:17:04] - [Speaker 1]
It's the most human. We can mine that information to provide us with all sorts of insights and information. So from from competitor analysis all the way through to what's the intent of customers. Are they a churn risk based on what they're saying because there's intonations in their voice? Are there certain things that they're ultimately, you know, being said about your company's customer satisfaction?

[00:17:27] - [Speaker 1]
All of these things can be mined from all of that data.

[00:17:31] - [Speaker 0]
And I'm curious. If you look across all the industries that you work with at RingCentral, what are there any particular sectors that are leaning into AI fastest? Which ones are taking a more measured or cautious approach? And what's driving the the differences in expectations and adoption? Are are there any that are clearly running away here and and some that are holding back?

[00:17:54] - [Speaker 0]
What are you seeing?

[00:17:55] - [Speaker 1]
Yeah. It's a good question. I mean, we've got a number of products. Right? One of our biggest ones that we announced at the beginning of this year and have continued to do a lot of, innovation on is our AI receptionist or we call her AIR.

[00:18:08] - [Speaker 1]
And AIR really is built for any size business, and it is basically a receptionist as the front door. It's providing the ability for any size business to never miss a call. The skills that this agent ultimately has is to, you know, basically answer the call, answer basic questions that may or may not exist in a website, provide support to these people, book appointments, you know, transfer calls with with a handoff to the the person that actually answers the phone. We see the adoption of that in in in a way that we had never seen anything else, and it's really for small to medium sized businesses. It isn't complex.

[00:18:47] - [Speaker 1]
Right? So it doesn't do the functionality across the board that you would need for what we would call, you know, a full agentic, you know, agent at the front door of a contact center, but it does provide most of the functionality to a certain point to do that. So these businesses are seeing it in a way that that, you know, is game changing for them. Because in the past, it would ring to voice mail, and, you know, sometimes if they had more advanced settings in their cloud based PBX, they would route these calls into a call queue. And, you know, eventually, if it didn't get to anybody because no one had time to answer it, it would still ring to voice mail, they or they'd miss it.

[00:19:22] - [Speaker 1]
People would hang up. And so this captures it because it's almost like that digital human is picking up every single call and answering it like a receptionist would back in the old days. And it allows these individuals to not staff, and, you know, there's lots of positive ROI on this. Where we're seeing this is is across the board. We see a lot of health care.

[00:19:41] - [Speaker 1]
We see, small businesses from, you know, like plumbers to dentist offices, doctor's offices, a lot of those organizations are seeing the value of this technology. Now when you look at some of the contact center kind of functionality, so go beyond just the front door of answering the call, you get into what we've been speaking about with full context and the capability for agent assist as an example. Those organizations, definitely financial institutions and health care are ones that are bubbling up to the top for RingCentral specifically. We also have automotive. We have manufacturing, travel and hospitality.

[00:20:17] - [Speaker 1]
So there's a number of organizations that we're working with that are adopting AI across the board, but the top two that we see is definitely health care and financial services right now.

[00:20:27] - [Speaker 0]
Interesting. You got two examples there, health care financial services. And a couple of the other ones you mentioned as well, they all one of the things that stands out to me is they all have very different pressures. So how are their Mhmm. AI priorities diverging, and what does that tell us about the the future of customer operations in those environments?

[00:20:46] - [Speaker 0]
Because it isn't a one size fits all, is it? It does all seem to differ from industry.

[00:20:51] - [Speaker 1]
No. It it really isn't. Right? I mean, I think that smaller businesses really see significant value in a lot of what we're doing because they don't have to staff. Right?

[00:21:02] - [Speaker 1]
And and they're pinched right now. The economy in the world is, you know, struggling and and it's not struggling in many different ways. Right? So I think at the end of the day, it's it's it's how can we use this to our advantage, and and can I get more business? Can I get more revenue?

[00:21:17] - [Speaker 1]
Can I just beat my competition? Can I make sure my calendar is full so that, you know, I'm making money? All the way through to larger organizations really looking to, you know, ensure that in a formal contact center situation with our Ring CX product, that we brought to market in late twenty twenty three and has grown significantly over the last couple of years, we're seeing larger organizations really kind of using what we call the AI quality management component of the product. Right? So I was mentioning the automated call scoring and the coaching.

[00:21:52] - [Speaker 1]
Those mechanisms to improve, the actual, handle times and sort of, like, the triage of making or getting agents to to perform better, right, without a lot of, like, you know, learning and training in between and and failure points in between, sort of a full automated process. So some of the results that we get across the board from organizations, is really about agent performance and how AI is doing that. And and we've got, you know, companies of all different types using that as well. So, you know, any you know, example, like San Francisco, or sorry, San Diego Symphony using it. Right?

[00:22:31] - [Speaker 1]
Health care organizations, a manufacturing company. So it just depends on on what they are, but we sort of focus on specific verticals in health care. Financial services has always been been one, that we've really kind of leaned in on, and and been very successful as a company in in sort of even, you know, just with the Cloud PBX components and and the video components that we've had, for quite some time.

[00:22:58] - [Speaker 0]
And I think many organizations continue to be excited about AI, but they still fall into the the familiar traps and pitfalls. So what are the most common mistakes that you see, teams making when they're trying to embed AI into their contact center or indeed wider customer operations? You've probably seen a lot of myths, misconceptions, same mistakes, and a few people make doing everything right. But what are they the the most common mistakes, that people are making?

[00:23:28] - [Speaker 1]
Well, you know, common mistakes are are tough to identify. I think

[00:23:33] - [Speaker 0]
Yeah.

[00:23:34] - [Speaker 1]
What I'm seeing is that organizations we're speaking to are looking for companies to provide a full solution to them, and that one vendor supplies that from end to end. So where where we've been successful is is the combination of unified communications and contact center customer engagement solutions together on one platform. Right? So bringing those together brings the front office and the back office and and the contact center all together. Right?

[00:24:03] - [Speaker 1]
So one one communications platform. And then what we've done over the course of the years, of course, is brought AI into that picture. So everything from that journey that I was talking about at the beginning from before, during, and after. Those aspects of that technology exist for those that might be in the enterprise that don't have a formal contact center but are just using the cloud PBX component, they can use those things too. So call queues, the routing from air to the right individual, handing that off, and then providing the assistance during the call from Ava that will ultimately, you know, add better performance and provide them with information that they may not know and then, you know, triaging afterwards for, you know, how how well did that call go and what kind of improvements should we have as well as the data behind that in terms of business decision making.

[00:24:52] - [Speaker 1]
So we're providing all of these tools within the solution itself based on the solution that a customer is looking to leverage to solve their pain points. So this common mistake early on, and and it's less of it now because I think people and companies have learned, is that you should utilize the AI that your solution providers like RingCentral provide you with for business communications and customer service and make sure that those AI involved in those journeys or those use cases for the humans that are involved in answering the phone and doing all these things to rather than just adding on components from multiple different vendors and trying to orchestrate and manage that. Because there are different vendors that will do only the AI receptionist or only the cloud phone or only the contact center or only one piece of the contact center, right, like workforce management. But the whole piece now comes together. And if you think about it, now you have digital workers working alongside human workers, and you wanna make sure that all of this stuff comes together.

[00:26:00] - [Speaker 1]
So no longer are the days of workforce management, if you're familiar with that, being able to schedule and schedule adherence of the humans and making sure they show up. But, like, how do you schedule the digital worker and the human worker, and how does that come together? So the holistic approach and looking at vendors that people wanna work with to solve the basic problem, ensuring that they have AI is the answer and how you approach it.

[00:26:26] - [Speaker 0]
Love that. And finally, before I let you go, we got one eye on 2026. A lot of people looking at improving things and and kick start the year with a bang. So when you think about the modern workplace and the expectations we have, not only as employees but also as customers, what does that AI done well really look like, and how far are we from becoming the the norm than the exception of those kind of experiences?

[00:26:52] - [Speaker 1]
I think we're we're 2026 is gonna be a pivotal year. I think there's gonna be, a lot of understanding in the market, just not in business communications alone, but across the board in terms of what AI is for businesses. If you look at a lot of, you know, large organizations, large enterprises like RingCentral is, the push and pull that we have in the market is to do more with less. Right? And so it isn't about get rid of all the human workers and try to figure out a way to bring in AI.

[00:27:24] - [Speaker 1]
It's how do you improve performance. It's not staffing up a marketing organization, for example. So you have, you know, multiple people that can write things. You're gonna use AI tools to write things. You're gonna, you know, streamline your operations of your contact center with solutions like RingCentral that are gonna provide, better outcomes.

[00:27:43] - [Speaker 1]
Right? And so anything from an outcomes based perspective that AI tools can do, it's going to become even more and more prevalent in 2026. And extending the capabilities of what you see from these agents, like our AIR, AIVA, and ACE is going to be a big thing in terms of how can you take these and and further extend capabilities across the organization. So for example, how can this work in IT? How can you create a workforce to help with HR matters?

[00:28:16] - [Speaker 1]
How can you extend a workforce to completely provide a 100% nonhuman touch customer service from end to end, like claims filing of an auto accident as an example? So all of these things will be sort of the next wave. It's the promise of things that we've talked about for a long time and have tried to do in the contact center world and done, but with out without avoiding a lot of cost in professional services. Now we're gonna start taking these capabilities and putting them in the hands of not only IT. IT is, like, gonna supervise us like they always do, but into the hands of the business user, making it that simple.

[00:29:00] - [Speaker 1]
ChatGPT, OpenAI interfaces as an example to communicate and create entire workforces. So things like that will be sort of the next realm of what we're gonna see.

[00:29:11] - [Speaker 0]
Oh, what a great moment to end on. So much, to look forward to there. It sounds like we need to get you back on next year, see how things are moving. But, but in the meantime, for anybody listening wanting to find out more information about anything we did discuss today, connect with you or your team, where would you like to point everyone?

[00:29:29] - [Speaker 1]
Ringcentral.com.

[00:29:31] - [Speaker 0]
Ringcentral.com. No problem. I will add that to the show notes, probably a link to your LinkedIn as well, but we covered a lot there. And I'd love everybody listening to share their experiences of before, during, and after, see what kind of measurable impact that they're having in their organization. But more than anything, John, just thank you for shining a light on this today.

[00:29:53] - [Speaker 0]
Really appreciate your time.

[00:29:54] - [Speaker 1]
Absolutely, Neil. Thanks for having me. Appreciate it.

[00:29:58] - [Speaker 0]
And that brings this episode of AI at Work to close with a clear look at how AI is shaping the future of customer operations. And we explored the role of voice as a strategic data source, the impact of real time agent support, and why thoughtful automation can strengthen rather than dilute human connection. So if you would like to learn more about RingCentral and the work John and his team are doing in this space, you will find the relevant links in the show notes. So just click on those. You'll find everything that you need.

[00:30:33] - [Speaker 0]
But as always, I'd be interested to hear in how AI is influencing your customer experience. What worked? What didn't work? I wanna hear it all. So pop by techtalksnetwork.com.

[00:30:47] - [Speaker 0]
You can leave me an audio message over there and also LinkedIn x Instagram just at Neil c Hughes. But that's it. We've reached the end already. I'll be back again very soon with another episode for you. Got a lot of guests lined up.

[00:31:00] - [Speaker 0]
But more than anything, just thank you for listening, and I'll speak with you all soon. Bye for now.