AI-First Hotel Technology and the Art of Possibility - Kevin King, Shiji International [Sponsor Bonus]

Josiah Intro: Early in my career, I worked at ReviewPro, which is now part of Shiji Group, and since then I've had the chance to speak with their customers around the world. What stood out to me is their appreciation for how Shiji designs and develops technology, and that's why I'm excited to bring you this conversation with Kevin King, CEO of Shiji International.

His global perspective is something I've wanted to share on this show for some time. We talk a lot about technology and hospitality on this show, but hospitality and travel, of course, is global, and it's important to understand the nuances and complexities and opportunities from operating with a global mindset.

And it's hard to think of someone better positioned to speak to this and from this than Kevin. In this episode, we talk about Shiji's approach to becoming an AI-first company, what that allows them to create with and for hotels, and how it can give hotel teams more time with their guests. Towards the end, Kevin shares an idea he calls the art of possibility, and I found it to be a compelling framework that excites me about this technology and the future that we can build with it.

It was inspiring to me, and I think it's going to inspire you as well. So without further ado, let's get into it.

===

Josiah: Kevin, thank you for making time to talk today. I've been looking forward to this conversation, and we have a lot to get into. And maybe as a way into the conversation, I would like to talk about an article that you published at Shiji talking about transitioning to becoming an AI-first hospitality platform. We're going to talk about a lot of elements of AI in our conversation today, and I would like to start by defining this. What does AI-first mean to you?

Kevin King: AI-first to us means, like API-first, that you have the technology foundation and the accessibility foundation in order to connect to a platform, a true platform across the different services that we offer within our technology stack. And we have a lot of different technology crossing over different functional requirements within the various disciplines within a hotel.

So to me, the whole AI-first idea means the end game is that you shouldn't really be talking about it being AI. It should just be part of what we breathe. And that's why we termed it AIR, A-I-R, because we believe that it's just going to become a natural evolution of how AI helps the industry that we work in. And what do I mean by that? I mean that we as technology providers need to listen to the customer, listen to the industry, and build utilizing AI tooling. It's a tool, just like every development tool is a tool. It's a clever tool, but we restrict our use of it to focus only on what's going to make the industry more efficient, so that we never forget that we're servicing a guest, because that's what hospitality is all about.

Josiah: So Kevin, I would love to pick up on this because listening to customers has some nuance. You listen to them across so many conversations. You also listen to what is going on and listen to what needs to be done in service of the guest, in service of the real needs of your customers. You've thought about rolling out AI and building AI in a very responsible way, but tell me about that moment a while back where you told the customer, "We're going to wait and we're going to look into some things."

Kevin King: Yeah. Just like other vendors in the market, when AI came out, it was really about, we can do so many things so quickly and we can just go to town and try everything. Give our developers open access to AI and let them do whatever they want to do. Just create and create fast. And the main reason that I held back is because we have a reputation in the market of being very secure, secure in our platforms, secure in all of our data. We host data for the customer, and it always belongs to the customer. We don't own the data. But when a customer comes to us and says, "Okay, look, we want to give this out to here, we want to be able to have access to the data to populate it into AI and get social information about individuals," you have to be responsible in this.

Sometimes people, whether it's a customer or an employee, have a particular view. And I'm the type of person that wants to have a seat at the table. I want to be not just a giver. I also want to learn and I want to understand from them. But I also need to be part of the decision making of what we do as the custodian of the information that sits on the platform that we've got. And so we have to be very, very careful of what we allow customers to do. Of course, at the end of the day, it's customer choice. But we have to make sure that we have our opinions and that our opinions are heard.

But if I even take that back further, to when a customer first asked me, "What are you doing with AI?" I said, "No, I'm not doing anything with AI yet." They were totally shocked. They said, "Why not? Everybody else is rushing in. They're doing everything with AI." And I said, "Well, that's the point. Everybody's rushing in." And when you're rushing in and you're running, you actually have no visibility of what the risks are along the side and along the way. We saw that there was some risk with AI, and that was because we had time to look at it and utilize a little bit of AI internally within the organization, which we found very important.

And we were then able to work with great partners like AWS. We got so much value from AWS in learning from them about AI and how AI needs to be controlled in terms of sovereignty of data. So we decided early in the piece that, no, no, no, we need to organize AI before we become an AI organization. And we took about a year to organize AI across all of our company, as well as the various different departments, from security to compliance to the development group, the product group. We all came together and we created a committee. And that committee included everybody, and I tell you, we learned so much that when we were able to start building, it became much easier.

Josiah: Kevin, I'd love to get into the details of this, but let's spend a few moments talking about risk. At the time of our recording, in September of 2026, there's a lot of global media attention about some security risk. You have leaders of leading labs talking about this. You saw some of this a while back. And this article that I'll link in the show notes talks about how hotels are built on trust, so trust is foundational. Tell me a little bit more about some of the risks that you were evaluating, because I think this has a lot of attention right now, and you've been looking at this for a long time.

Kevin King: Yeah. I think one of the biggest risks we saw in the beginning, and there's been some changes to this, but not as much as what I expect, is that whatever we give to AI, the companies that you partner with and the different LLMs that you connect to can keep that data and they can use that data for learning.

And even though you may have a paid subscription and you can turn on a function that says they won't use it for learning, how do you know? How do you know it's not going to be used for learning? And with all the various different models that were coming out, one day there'll be a new one and the developers want to start using that new one. Well, hang on a minute, what are you doing? You're giving more data to somebody else.

So we made sure that when we give the builders access, we must have contracts in play with the different companies that we work with, where they take liability. There are liability clauses within that. And of course, it makes us a little bit slower because we go through this process, but we are protecting not only ourselves, we're also protecting our customers when we deliver product to them. And then there's having access to the various different AI components, and there are many: the MCPs, the LLMs, this, that, and everything else. There's so much in the AI world that you can access. So that was the biggest thing.

Josiah: It's interesting to me because I feel like this notion of accountability has not been talked about enough. So it's interesting to see this handled contractually. And one of the reasons I've been looking forward to this conversation, Kevin, is that a lot of my conversations are US-focused, but you run a global company, and I know you work with hotel groups around the world that are extremely complex.

Kevin King: That's right.

Josiah: Many of our listeners may work with Shiji in some capacity, but for those that are unfamiliar with the company, I wonder if you could describe at a high level what you do and some of the components of your business that might help set the stage as we get into some of the details.

Kevin King: Sure. We have technology from when the guest is looking to book, to transitioning to book, to moving into bookings in a guest-facing environment, to the technology that all of that sits on, in terms of central reservation systems, PMS solutions, meeting and event solutions, spa, golf. All of these various different solutions are part of a guest journey.

Some of it is acquired technology and some of it is self-built technology, like our Daylight platform, Meridian Experiences, and so forth. And our purpose in acquiring those technologies wasn't to continue to run them in their traditional legacy scenario. It was to rebuild them on this platform, what we call the Daylight platform or the Shiji platform, depending on how the context is being presented. And we've been able to achieve that. That's been very, very important for us. It's not just talking about it, it's actually making it happen, and it really being one platform from that standpoint.

And then, very, very important, and you know this very well because you used to work very closely with us on ReviewPro, is being able to have the voice of the customer. When you have the voice of the customer, you can take different directions and you can make different decisions. Our customers get great value out of ReviewPro for that reason. They want to know what is great for the customer and what the customer's sentiment is.

But we turned it on its head. When we bought ReviewPro many years ago, we said, well, we're listening to what they said yesterday. They've already gone. We need a solution for while they're in the theme park or while they're in the hotel. Let's listen to what they're saying and let's rectify anything that happens while they're there. With this great platform that we built and the connectivity that we have into ReviewPro, we can listen to the guests and we can service the guests. We can address their problems while they're in the hotel, so when they leave the hotel, they're writing positive stories about it. And more importantly, they'll come back, because they see that you listened to them. So having these connected services across the various different platforms that we've got really does help us in delivering software and services. That's why this whole data thing and AI is so very important, and you need to be responsible.

Josiah: I appreciate the context there, because it helps our listeners understand the global scale. And understanding consumer behavior outside of just the world of hotels is important, because we're navigating our lives and our travel, and we're interacting with a lot of different businesses. You have a very wide scope of understanding how people do that. And it's interesting with ReviewPro, understanding the original offering and then how it evolved. Fundamentally, it's about understanding the customer and how we serve them.

And it feels more relevant than ever. I was talking to Cornell Professor Chris Anderson, and we did some research with him with ReviewPro data years ago. He was saying that attentiveness to customers is more important than ever. The importance of reviews is more important than ever. So it's interesting to watch this evolve over the years, and this thesis that you had, that we need to listen to customers and serve them in every way possible, is playing out.

I wonder if you could speak a little bit about Daylight. You mentioned Daylight is one of the proud moments of your career. Why is that? What was special about the formation of it?

Kevin King: Well, in 2015 we had the opportunity to come outside of China and be given the funding and the responsibility to build the next generation of technology. Because there were many companies in the market, and even today there are still many companies in the market, that just drop a box. They drop a box and they walk away, and then you're in contract for a period of time. We were given the responsibility to create a new company, which we did, Shiji International, and to build technology that was going to fit the next generation of hospitality. We were the first company, on a global scale, that put technology for hospitality in the cloud.

And it was in collaboration and cooperation with AWS, but also in collaboration and cooperation with The Peninsula group. They were the first ones. They were the boarding customers. And we worked with some other hospitality groups that came in a very stealthy way. They came very quietly. We didn't tell anybody we were building it for many years, because we needed to give time for the new developers that we brought on. And they were all based out of Poland, and still are in Poland.

We asked a lot of industry leaders to come and work with Shiji from a product point of view and an industry point of view. Many of them were building on other technologies, and they saw the problem and they wanted to fix the problem. And we gave them the platform in order to fix the problem. We brought in a guy who was the chief architect for this technology in the cloud.

Nobody trusted the cloud when we first came into play with this. Nobody trusted it. Nobody believed in it. And then over time, everybody realized, but we were ready. We were ready to deliver what we built by that time. We were out there educating people. And not only did we build technology, which is Daylight, and it has great functionality from a property standpoint, but also from the activity side, being golf, spa, and other activities, tennis courts and the like. We really added functionality around that, the membership, the guest profiles, and so forth. And then being able to add meetings and events onto one platform. So you had a whole journey of a guest.

That's the proudest thing, I think: getting to the point of not coupling different software together, but staying true to putting it all on one platform. So you really have one guest. We have lots of different companies around the world today that are making business from collecting data from multiple systems and consolidating that data. For the most part, we have all that data on one system, and now data lakes. So it's been a great journey to be able to have and lead an amazing team of people to build this technology, to think about it, to work with it, and to build it. But we would be nowhere if we didn't have the input from our amazing customers.

And we've recently taken that Daylight platform and put it into a casino operation. We were only able to do that...

Josiah: Which is so complex.

Kevin King: Which is so complex. And we were only able to do that, one, because of the knowledge of the team members that we have, and second, because of the technology that we have, because it's very new. It was able to be done very quickly without it just being an add-on or a workaround. And we reshaped what we do on the casino side.

Josiah: Kevin, I would love to spend a few more minutes talking about the technology, because this context is really important. We're trying to help listeners understand what AI-first means. When you talk about being an AI-first platform, an AI-first company, what does that mean? There are also a lot of hospitality leaders thinking about what this means for themselves. So I think getting into the details is really important.

I've spoken with so many of your customers in the US, in Europe, in Asia, and in the Middle East over the years, and talking with the technology leaders at these companies, what stands out to me is the collaborators you bring together, whether it's AWS or others. There are so many complexities to think about, especially on a global level, where there are different jurisdictions and different legal requirements beyond the requirements that you might have as an organization. So there are many layers of complexity. Beyond AWS and moving to the cloud, are there any other architectural or technical components you've been working on over the past years that lay the groundwork for the work that you're now doing in AI, whether it's with data or architecture? I'm curious about some of the underlying factors here.

Kevin King: The technology we use, and obviously a lot of companies now are using it, is what's known as microservices. So you spread the load. It's not a monolithic style of code, where before you had one package of code, you developed it within one package of code, and you delivered one package of code. What we have is a series of microservices across the different services that we provide, and they're all connected in light of that development.

One of the advantages of AI is this. Before AI, we needed to have the different disciplines within those microservices, like a finance microservice, an AR microservice, reservations, a profile, and they could be built in parallel rather than all in one. So the disciplines could be separated, and then they come together and get packaged up to deliver. What AI enables us to do, rather than having people go out there and stitch everything together at the end, is that AI is able to go across that development group and across those microservices with all the functionality, and work at a much faster pace to deliver functionality, or dream up a different way of doing different services or functions in a hotel, based upon somebody telling a story.

And not just telling a story in terms of writing it down and giving it to somebody in a development group who's got to imagine it and then put it into code. We now call our team, when they move into the AI world in product, product engineers. Because they're not having to write a story as a document to send to somebody who then has to do something further. They're able to write a story in a product that we've developed. Our AI core team has developed a product for our product team to enter the stories into, and it will go across all those microservices, bring the story together into one, and then really deliver that.

Why is that so very important? In the past, we were API-first, and lots of companies now say they're API-first. We have lots of APIs. We don't do anything without using APIs. But what AI actually does for us is it enables our teams time to think better. For us, it's not used to say, "Okay, I've got 500 people in development. I can get rid of half of those development teams and put in the AI bot." That's the worst thing to do, with all the security and compliance, and you've got to have the human in the loop. Of course you can get efficiencies out of AI. But at the same time, you really need to have the clever people to monitor and make sure that it's being done correctly.

So from our point of view, we are enabling our people to be smarter. We're enabling our people to tell stories. And when they're telling stories, this inanimate object called AI, which people give names to, is actually taking all the information and curating it, taking our design concepts without anyone having to think about them, and putting it into the end product. It creates and presents code that is then given to development, to the human in the loop, to ensure that the code is compliant with all of our security and code security. When you're giving something to a machine, you have to have the human-in-the-loop value proposition in front. So from that standpoint, the way that we have the platform today, it's not in pieces. It is a platform. And the different microservices that we run are very, very important.

Josiah: I appreciate getting into the detail of that, because I do want to get into the applications and the opportunities that you see. Doing what you want to do, especially at a global scale, especially in complex operations when you're operating in different jurisdictions, or when you have a business strategy where you need to do a lot of things with AI, it's not as simple as just bolting AI on top.

Kevin King: No, no.

Josiah: It requires an infrastructure. We've talked about data governance, the partners you bring in like AWS, all of these things. It's digitizing work. Unless the work is digitized, you don't have the data. It all builds on each other. It's sort of like a multi-layered cake. So I appreciate getting into the detail there.

I would love to talk about opportunities. You've spent years building this foundation. You've had this very thoughtful approach to becoming an AI-first company with an AI-first set of technologies. What do you do with that? You have this amazing foundation to build on. How did you think about identifying opportunities and building capabilities that build on all of that?

Kevin King: In the context of AI, when we look at all the functionality and the competence that we have on the platform, and all the workflows that are on the platform today, it all sits behind a front desk. We still deliver technology to a front desk in front of a computer, and the computer is the barrier to the guest. That's something that I think the industry needs to solve for. We need to solve for that. Why? Because it comes back down to the guest.

You talked about your Cornell interview and the professor that you worked with, who said we've really got to look after that end guest. At the time that you had that interview, we had very well-staffed hotels. We had many people that could look after the guest. You had a duty manager, an assistant manager. You had a lobby manager. You had the restaurant... You had all these people that knew about hospitality and wanted to be in hospitality. Then we had COVID, as an example, and everybody went to work remotely and they didn't come back to the industry. The industry still suffers from not having enough people in the hotel. And of course, the hotels also want to reduce the reliance upon having too many people within the hotel as well. Cost savings, occupancies, rates, and so on have changed since COVID.

So the opportunity that we see, and it's not only an opportunity, it's actually a reality that we are delivering quite quickly and iteratively, is to change from being a PC-based solution to being mobile-first, functionally mobile-first, and in many ways, take away the front desk. Take away the need of having a front desk. We have a back office, yes, but a front desk? Let's have the team members actually work with the guest.

When you go to a luxury hotel and you walk in, there is a person in the lobby that greets you, person to person, not behind a physical object that is creating a barrier. And depending on which country and which style of hotel, even at the point that you're having a conversation with a guest, you're asking, "Do you have a reservation? Credit card. Name." That's what we have to solve for. We need to bring people to deal with people. Why? Because we want guests to return to the hotel. They've got to feel like they're coming home. They've got to feel like they're getting value. They've got to feel like they're getting recognized. "I'm recognized. They know me, and therefore I'm going to come back." And more so, I'm going to stay and I'm going to spend my money in the hotel, if the hotel has the different services that are there. Technology needs to solve for that.

Josiah: I agree. Technology needs to solve for that. And I'm curious how you could apply AI to helping with that. I was talking to one of your customers in Spain a while back, a food and beverage director, and he talked about using your technology, all mobile-based. He and his teams were able to serve guests dining in their restaurants faster and spend more time in conversation.

Kevin King: Yes.

Josiah: Instead of paper tickets running around, the order is instantly going to the kitchen. So that whole process was sped up, and the team enjoyed their work more. Food and beverage operations are sometimes some of the most complex within a hotel. Then you take that mindset and think about the greeting, the lobby experience. Tell me a little bit more about where AI can help with that. I love that notion of greeting people, spending more time with them, getting away from the computer. How do you apply AI in that workflow?

Kevin King: Actually, what you're talking about, we've probably already done through normal development work. We were able to do that by connecting systems and making the whole workflow work a lot better. On the food service side, there has been quite a pivotal change over the years, because now you can have a bank device, and the bank device can have our software running on it and the banking software running on it, and you can do everything from that device. But the reality is that behind that banking terminal with our software on it, it's actually communicating with all the other solutions that have been set up in the hotel.

So it really comes down to not necessarily functionality, but how we connect. How do we get faster information into the hands of the waiter about that guest? What allergies do they have? What wine do they like? All of this comes from the central profile that we have within our solutions. And if you have all that information available to you, AI can then do further recommendations for you. It can identify, do we have that wine in the store? Go and get that wine, order the wine, and have that wine brought to the table. I can't say that's a very big example of AI on the guest service side of things.

But if I take it to the front desk, for example, we have lots of workflows. Even in food and beverage, we have workflows, but food and beverage is relatively simpler than the front desk. At the front desk, one of the things that we have been able to achieve with AI is understanding the guest's need, but again, not being constrained by the desk.

I use an example all the time where a guest comes and says, "I would like to check out at 4 p.m." I use this because I travel 300 days a year and I always have these nuances of requests. Today I find that people have to go through a multitude of screens and find out 10 different pieces of information to come up with a thought process. Can I give him 4 p.m.? And if I give him 4 p.m., do I need to charge him for it? Or let me go and talk to the manager about that 4 p.m. And once I've made a decision, yes, you can have 4 p.m. and it's going to be $30, I've got to do a whole lot of other functions in order to post that $30. And then I need to go and extend, tell housekeeping, do this, do that, and everything else.

A very simple example of what we were able to do, just as part of our scratch work, within a day, was to put a microflow in play that enables you to either type or say to AI, or what we call Shiji AIR, "Mr. King, room number 101, wants to have a 4 p.m. checkout." That's it. It'll go away, it'll think, and it will come up with a whole checklist of things that you need to do, or a checklist of functions that need to run. One, I've found out he's a platinum member. I've found out that he's entitled to a 4 p.m. checkout, and the availability is there, and the room is going to be available for his 4 p.m. checkout. And so all you need to do is say yes, and it does everything for you.

Josiah: Kevin, I appreciate going into the details of this, because some people will talk about this notion of wanting more time with guests, and I feel like I haven't heard the level of detail of what exactly that takes. I also heard from you a distinction between what traditional software offers, which is powerful and valuable, and I don't want to diminish that. When I was talking to that Spanish restaurant manager, he saw a lot of efficiencies with cloud-based, mobile software. So there's a lot there.

What I'm hearing from you is that AI applied to that helps with data processing, connectivity, and context. It's a layer beyond that. It builds on SaaS software, cloud-based software, but it goes a layer beyond with more context. And what you're just describing is fascinating to me as well, because it seems like more than just generative AI. This seems more like agentic AI, where it is having work done for you.

Kevin King: Yes, very much that.

Josiah: That whole behind-the-scenes, work-done-for-you idea is interesting to me, because it helps me understand this type of practical example beyond just saying, "We need more time with guests." It's like, okay, how do you get there? It sounds like this is one of the applications for improving guests' lives. But I imagine in the back of house, maybe for above-property financial reporting, there are also applications for agentic AI, because it seems this mentality could be used across a hotel business.

Kevin King: Yes. Reconciliation is a very big thing in hotels before it gets to the finance system. We have very good reconciliation in the core of our application and always have, but it's about being able to analyze that better and faster before we actually give it to finance. You need to give curated data to finance. And while that is possible, there's always a lot of manual work and checking that needs to be done before information gets from one department to another department. So it's about being able to do validity testing on various different data sets during the night audit, and after the night audit, while the night audit team is working, and then they can take the result and put it into the finance systems.

One good example is our casino model. We're starting to roll out our casino module in Macau. When we started with the hotel, the hotel said, "Just do what I was doing before. That's all I need." But we talked to the users, because they had a process in play. And the process was actually a whole series of workarounds of the previous systems that they were using, and a couple of other functions that the finance team needed to have. What we were able to do, utilizing AI but also utilizing traditional development, was to simplify that, so that everything is reconciled. Rather than taking a day and a half to do all the reconciliation, it takes less than one hour to do the validation. And they don't have to do any real work other than double-checking and validating that it's all done.

And this is the beauty of being able to have a newer platform, being able to have AI in play, but also the comfort that the process that we have is very safe and secure in the transmission of data.

Josiah: This is super helpful, Kevin. One thing I'm trying to do on the show and in these conversations is help people make decisions. A lot of leaders across the hospitality industry are trying to decide who the right technology partners are for their organization and how to think about evaluating and purchasing technology. We've covered a lot of that in this conversation, but how would you speak to a hotel leader who's saying, "We want to take advantage of the capabilities of AI"? What guidance would you have for evaluating potential technology partners?

Kevin King: Well, first of all, I would applaud them for saying that they want to take advantage of AI. I would sit with them and I would actually say, stop talking about AI. Talk about what efficiencies you want to get. What are your problems today? And how do you see technology helping you with those problems? What I do often is get my teams to sit together with customers, just to get the ideas and to help edge them along in their thought process. What if? How can? Why should we? All of these questions need to be asked. Don't worry about AI. We'll worry about AI. We'll worry about how we get that efficiency for you. And you must trust us, and understand that we are very compliant in the way that we deliver AI. We're very thoughtful in the way that we deliver anything, not only AI.

If a hotelier comes and says, "I want to do this, and I want to do this, and I want to do this," like a child in a candy shop, you want everything. And they think that AI can just give them everything in a couple of minutes. It's a little bit more complex than that. But it is possible. This is the thing, what I call the art of possibility. I always look at what's the art of possibility, and I love people to tell me what the art of possibility is.

And I use it in my own organization. I will tell you a story now, because I'm a disruptor. I don't mind disrupting something. When AI came into play, I said to our chief architect, "I want you to disrupt. I need a full guest journey on a web front end, to actually put into the consumer space." And within three weeks, he had a great concept. Within six weeks, he had it connected to the platform.

Josiah: Wow.

Kevin King: In the past, it would take months, maybe a year, and cost a fortune, an absolute fortune. So we were able to create that in an agentic way, very, very fast. But at the same time, okay, here is the front end, then you've got to build the back end, but again with AI. So it speeds up the whole process.

So it was like me. I was holding the candy jar and I didn't know which candy to have, but I thought I needed them all. "Michael, I need to have this." And I sat down with him and I told him what we actually wanted. When he delivered that, he went back to the product group and he said, "I want to demonstrate something to you." And they'd been writing their stories for this for many years. We went through it, and at the end of the hour, the head of product for that particular function was saying, "That's exactly what I need. All the stories that I've got, you've been able to deliver in four weeks." But that's only the beginning of it. That's the front end of the work. You've still got to do the security and you've got to do the back end of the work to actually put it on the platform. And so we invested further. From that project that took three or four weeks, we invested more people in order to now build it and put it onto the platform in a very safe, secure way. And that'll go to market very soon.

Josiah: I love that example. And I think that's what gets me excited about AI. It's not the technology for its own sake. It's what's possible. And I like that idea of the art of the possible. And before we go, Kevin, I'm curious about that future world that you see as possible. I feel like we've touched on it a number of times in our conversation. I appreciate how you went into the groundwork, the foundation, how you've led your organization to be AI-first and bring these capabilities, and then what's possible from a technology creation perspective. You go from idea to implementation so much faster. You create things with your customers. But as you look into the future and think about the art of the possible, any closing thoughts about what you're looking forward to, what you're excited by?

Kevin King: Yeah, I'm excited that we get to reinvent again. Like I say, I'm a disruptor, so I love to continue to do the reinvention. The amazing thing is that we have a really good platform that enables us to reinvent quickly. We don't have to have many people working on it in order to reinvent.

The biggest thing I'm interested in and want to deliver upon is this: today, people have to learn a system. People are hired because they know a particular system. "I need this person that knows this system, or I need this person that knows that system." Actually, that's got to go away, because it's not about people learning a system. It's about the system learning how people want and need to operate. So today, people are asking. Tomorrow, AI will actually learn, and it continues to learn over time. You've got to control it. You've got to give it guardrails. But it will learn over time what's more efficient. And that gives my people more time to spend with customers, directing, listening, and then delivering. And it gives the industry a really good opportunity to change the way they service their guests.

I'm a hospitality guy that got into technology earlier in my life, but I've never stopped being a hospitality guy. And when I see that a guest is behind a desk, and even myself, being asked, "Credit card, name," that's it, and they don't even look at you, that annoys me.

Josiah: There's a better world possible, and you're building that with your customers. So I'm very inspired, Kevin. Thank you so much for taking the time to talk.

Kevin King: Very happy, and thank you very much for inviting me.