Hospitality’s Data Problem Is Now an AI Problem with Wouter Geerts (Abode Worldwide)

SPEAKER_00 0:00

A way of looking at AI that I think of it is that it sort of has democratized intelligence, right? But it also is democratized stupidity in a way. Like you can have all of that ability to have super intelligence, but you do need to work with it in a smart way rather than completely delegating rigor and sense checking.

SPEAKER_01 0:19

What I see as a problem is that AI can be very convincing and it can work without necessarily having all the context and knowing what the right number is or should be. And convince people that what it has come up with is actually the truth. Operators might start falling into a trap where they start making business decisions based on what they believe is good data or good conclusions, but do they really understand where the data comes from and can they actually trust it? Maybe not.

SPEAKER_00 0:55

Welcome to the Pillow Talk Sessions podcast. My name is Jessica Gillingham, and I am your host. And in today's episode, I have a very special guest. I have Vouter Gertz, who works with me actually at Abode Worldwide. He is our head of market intelligence and research. And we decided to have a conversation about, guess what? AI, artificial intelligence. I know we're all talking about it all of the time, but we've got a bit of a different take on it. And we had some predictions that Valter talked about on this episode about what the narrative is going to be next year. So we've both been talking for years, it feels, well, not feels, it is, years with tech vendors and actually also operators across the hotel space and the short-term rental space. And the narrative changes, but everyone's always talking about the same thing for a while when it comes to AI, and then it shifts a little bit, and then it shifts a little bit. But the big fundamentals are not, are still not being talked about really. We're not talking about how to make sure that you have a business that actually is structured right, that you have the fundamentals of your data structured right so that you get actual business intelligence coming to you. We also talk about how important trust is within this conversation. So listen in. I hope you enjoy the conversation as much as I enjoyed having it with Valta. And welcome to Pillow Talk Sessions. VALTA, welcome to Pillow Talk Sessions podcast. I'm super excited to have you as a guest on the show today. You've recently joined us at Abode Worldwide as our head of market intelligence and research. And we will go into that a little bit on this episode. But today we're going to talk about guess what? AI, artificial intelligence. And but we're going to look at it from a sort of a different perspective today. So welcome and thank you very much for joining me, Valta.

SPEAKER_01 3:09

Thanks for having me and and and thanks for having me in the boat. It's very nice. Um just joined, what is it, two months ago. Um, but it's been uh it's been a whirlwind ride so far, and really excited to be here.

SPEAKER_00 3:21

Yeah, brilliant. And we're gonna look at how artificial intelligence is being, I guess, positioned within hospitality technology. We both have conversations with operators, tech vendors, consultants all day, every day, as being in the hospitality tech space, whether it's in the hotels or the short-term rental side, is our day-to-day job. So we've been talking about AI for literally years now, it it seems. And we we've we've both seen the conversations change. And then also, I know for me, I see everyone talks about exactly the same thing for a while, and then they shift to something else, and then it's something else. But there's often massive gaps missing as well in the conversation, whether that's around compliance, or whether it's around governance, or whether it's around what actually you can use AI for within a hospitality business. But from just I I'm interested because you before you joined us at Abode, you were with Muse, and then prior to that you were with Skift as head of research. So you've also seen over several years the change in hospitality technology. So I would love just for you to give an overview, I guess, of how you've seen the AI narrative play out in let's talk about particularly in the hotel space.

SPEAKER_01 4:55

Yeah, let's just start with an easy question, right? Um so I think um what what I find fascinating, and like you said, I I covered the the sort of the hotel tech and short-term rental tech landscape and and and trends uh at Skift, and then I was more um internal in one of the tech vendors uh in Muse, um doing exactly the same thing, uh obviously focused more on hotel technology. What I find fascinating is there's there's a a couple of narratives, if you like, um uh fault lines um that that sort of have played out throughout my entire time that that I've been in this industry, which is over a decade now. Um and at the same time, there's there's always new layers on top. And AI is one of those current layers that that we're that everyone is sort of jumping on, like you said. Um extremely um valid and and extremely exciting, of course, what's happening with AI. Let's not downplay that at all. Um it is a it it's it's a technology that's that is definitely transforming um how the industry is being run, what technology vendors can provide, and how quickly they can provide it. So um I think that's that's really interesting. But there's always these um more foundational problems that um uh both operators and tech vendors um have been dealing with and probably still don't have a solution. And AI, again, isn't this necessarily the solution for all of these? And and some of that is we're still talking about the move to cloud um from on-premise systems, how do we move everyone onto cloud systems? And and with that comes specific things around security, uh, cyber um crime, and all these kind of things. Um there's a there's a massive threat around um data, silos, um, understanding your guest, and and where does all of that data data live? These are things that have been going on, and and we've been talking about this not for years, for decades. Um, and that hasn't actually changed. And yes, with AI that that um sort of shifts slightly because AI has some impact on it and and changes some of some of the perception, but there's still that issue. Um, and so I find it really fascinating to to see how uh different topics come and go, crypto, AI, whatever it might be, mobile.

SPEAKER_00 7:28

Um, exactly.

SPEAKER_01 7:32

But at the same time, there's there's this continued underlying uh list of problems almost that that still haven't been resolved. Um, and and that everyone sort of knows that needs to be addressed, but no one probably has has a really good solution for it, or or maybe there just isn't a solution for it. And so that that really fascinates me about the landscape and how it continues to move.

SPEAKER_00 7:58

It's interesting because there is always the elephant in the room, and delivering operationally hospitality is challenging, like it is just inherently challenging. And I guess we're always looking for this is the thing that's gonna solve this challenge. This is the thing that's gonna make it easier for operators, and and we we've gone there maybe a little, we're definitely a little closer with artificial intelligence, but there's still the elephant in the room, there's still the challenges. So, what do you see as those kind of inherent challenges that we're perhaps not necessarily addressing either in practice or through narrative when we talk about artificial intelligence within hospitality?

SPEAKER_01 8:44

I think today, um yes, there is some AI hype. Um yes, sure, there's also some really good solutions. I think what we aren't talking um enough about is probably um the trust that we can have in AI or not. Um and um can we trust what AI puts out? I think I feel that with um with all of these AI solutions now coming on board, the speed of of innovation is so much more rapid. And and um the ability of laymen, people that that don't sort of um necessarily know um how a system works, how operations work, um, to come up with a solution, come up with a product, a feature, uh a platform, um is is so much easier um and so much um uh quicker to get to. Um but I think that the fundamental problem that AI doesn't solve is is still, like I said before, this issue of data. Um and where does the data come from? Can we trust it? Um is there potentially a single source of truth, as the industry has has been talking about again for for many, many years. Um and what I see as a problem is that um AI can be very convincing, um and it can work without necessarily having all the context and and knowing what the right number is or should be, um, and convince people that what it has come up with is actually the truth, um, even though that might not be the case and people losing sight of how did this AI solution actually get to this conclusion? Um and not really understanding the steps it went through. And if you have a person that has a spreadsheet um that has some numbers that needs to be checked, um sure, stuff gets overseen. You you there there might be over uh the the might you might lose um and and miss certain issues, but it's much more likely that you understand what what process you go through and that you understand um what decisions uh you what you base decisions on. And with AI, I think we we might start falling into a trap, or operators might f start falling into a trap where they start making business decisions based on what they believe is good data or good conclusions, but do they really understand where the data comes from and and and can they actually trust it? Maybe not. And I feel that that will become a really big topic say in 2027. Uh maybe it's it's the topic of the year.

SPEAKER_00 11:31

So it goes beyond just hallucinating then. This is deeper than just the AI tool hallucinating something.

SPEAKER_01 11:41

Yeah. Yeah, I think I think it's more dangerous than that. I totally agree. I think hallucinations we understand. It's it's um the AI making up something that's not real. Um, I think what I'm talking about here is the AI is using data um that is factually correct um to draw a conclusion, but the data that it has might not be correct, or it might have um different points of data and it's it's it's actually choosing uh one over the other. Um so if I if I think about operationally a hotel or a short-term rental um uh operator has a ton of data, a ton of different systems that work with this data or that produce this data, if you like. Um something simple like occupancy rates, um, revenue that's generated on a on a daily basis might be defined very differently in in different systems or by different departments in your operations. And so um just thinking about occupancy, is occupancy um does that include rooms that are um down for maintenance or closed for maintenance? Does it for a for a short-term rental provider, does it include nights where the owner actually stays in the property? These kind of things, there's there's definitions um that that uh sort of define what what that means. And each system is likely to have a slightly diff different definitions. And the AI doesn't tend to have, at least today, a lot of that context. Um and so it will start draw potentially start drawing conclusions on uh data that's not true or is not accurate. Um and and so really understanding whether your AI has the business context that it needs to make certain conclusions is very important. But it is also really hard to know that if if we don't really know what the AI is doing under the hood. And and I feel like that is that is a bigger problem than than a simple hallucination of an AI making up something. Um it's it's it's not making up something, it's drawing a conclusion based on data that exists, but might not be well defined or might be wrong in the context that you're looking at it.

SPEAKER_00 14:11

So it is, it might not be that it's it's not incorrect data or even an incorrect definition of the data. It's just that each department within a hospitality organization, especially when we look at much bigger organizations, and then within each technology solution or parts of the business, there'll be different. So it might be correct data for that particular use case or that particular technology or that particular department, just not unified across the business. So is a solution to that, and do you think that what we'll be talking about in 2027 is redefining that single source of truth or looking at how actually, maybe it even goes back to just fundamental org structures of how you think about how you are defining certain terms within the business, the way that your tech is defining certain terms, so that then you're able to make sure that the data, I guess, is clean or not sloppy, or or whatever it is, that then can help make better business intelligence decisions. What do you think of that? Does that sound about right or not right?

SPEAKER_01 15:29

Uh um I would I would sort of challenge the idea of a single source of truth. Um I think it's it's an idea that's been around for a long time. Uh I don't think it's practical, and I don't think it it necessarily solves this problem. Um, I don't think there in we we live in a in an industry um that has multiple tech vendors and and each um operator is unique and therefore needs a specific set of technology that works for them. Um I don't think there's a there's a single tech vendor that can provide everything uh for for a specific operator. There you're always gonna have different systems. And then within that, uh as part of that, you also have obviously humans that work in your operations that know certain things that that the technology doesn't. Um so you're never gonna have a single platform or or database that has all the knowledge of your organization in it. And I I think trying to achieve that probably you're gonna waste a lot of money and and you're you're just not gonna get there. Um and so um I think it's more important to yeah, pro provide that AI as much as possible with the context um that it needs to understand your business, to understand what you're trying to um automate or or trying to use AI for. Um but it's also for operators and for for the humans that work in your business to not start uh relying blindly on what AI tells you. Um and I think this is the same in in daily life as it as it is in in working life, is do you really understand what data um is being used? Um, what does it mean? Um are the definitions of what ADR is in your property management system the same as what it is in your revenue management system? Uh are they tracking the same thing? Is total revenue that lives in your PMS tracking the same thing as sort of the sum of the different spa, uh fmb, room service, all of these things combined, or is it not? Um I think we we we work with such a um uh plethora of of different systems and different departments of their own systems that it it becomes really hard, but it be it's it becomes more and more important to have this overarching AI layer, I suppose, um that that sort of understands the business and can can capture that context so that it can actually um provide answers that that can be trustworthy. And and it's it's not an easy thing to do. But I think the the thing for the for operators is to don't trust what AI spits out to you and continue to be very vigilant um because yes, you can get answers much quicker, um, but at the same time you gotta be sure that you understand and trust um what those answers actually mean for you.

SPEAKER_00 18:47

So kind of a a way of looking at AI that I think of it is that it sort of has democratized intelligence, right? It's democratized the ab sophistication, the ability to kind of be a much more sophisticated, if you like, operation. But it also is democratized stupidity in a way. Like you can you can have all of that ability to have super intelligence, but you do need to think of work with it in a smart way rather than sort of completely delegating the thought part of analysis of um uh like rigor and and sense checking and and just thinking about some of the foundational things as well.

SPEAKER_01 19:31

Yeah, yeah. I think that the there's I mean the industry doesn't have a have a great track record of on on some of not necessarily on what you're saying, but but just on on the data part, right? And I think we we should therefore go quite um um be quite careful with with handing over everything to AI. Um I think there was a there was an hotelier survey, hotelier is like um a hotel PMS vendor, um, one of the newer generations one. That they found that 15% of of um hoteliers that they surveyed were confident about the accuracy and the timeliness of the data. Only 15%. So 85% wasn't. Um and uh there was another study that I that I recently read from uh Access Hospitality, who's the owner of guestline PMS and some other systems, and they they found that that 60% um of hoteliers um believe that their data is incomplete, it's unreliable, um, they they struggle to even understand where the data sometimes come from. So if you are in that position to uh to then believe that AI is going to solve that, um is is is the wrong thing to do. Because yes, it will solve it for you, but will it be uh doing it in a in a truthful and trustworthy way, or will it start to give you answers that you're looking for without really understanding what it's trying to achieve or what's happening in the business or what's happening in the market around you? And therefore, it might actually provide you with with something that's that's worse than than uh where we are today.

SPEAKER_00 21:21

And that this brings to another point, Valter, that I want to explore with you. And I've I've had a couple of guests on this podcast talk about this, and it's a conversation I was recently at the Vacation Rental Management Association for the short-term rental um sector in Nashville a couple of weeks ago, a few weeks ago, and it was quite the talk there. It's it's quite the talk at various conferences, I'm sure it probably is, at least in some maybe independent hotel conferences, but about operators building their own tech now using clawed code. And and and you know, there's a lot. Of enthusiasm enthusiasm about it. There is a lot of like, we don't need to pay for this housekeeping app anymore. We're saving ourselves X dollars because we built it ourselves within so not necessarily building the core PMS, but building some of the point solutions that don't require hardware or don't require certain things. And it doesn't always work, does it? And one of the things is that that you, you know, if you if like, how do you make sure that you're not just getting back what you want to get back apart from anything else? So what are your thoughts on that? Like, is it is it should all the software companies in hospitality tech be really worried that they're going to be obsolete because operators can just use the frontier LLMs to do, you know, part of the work for them and then save themselves, even though we know that the frontier LLMs are pretty expensive and will get even more expensive. But that sort of kind of maybe is it a fallacy thinking that it's cheaper to do it yourself than to to pay a specialist hospitality tech.

SPEAKER_01 23:13

I mean, let's not talk about tokens and and and cost too much. Um I totally agree. I mean, it's cheap for now, it it will most likely become more and more expensive, uh, and especially if you're trying to run something. Uh once once we are all sold to Claude and ChatGPT, I'm sure they're gonna up the prices because they're not profitable at the moment. So um that will definitely happen. Um, I think to to me, um, and and I I'm not an expert on this, of course, but to me it it it in a way doesn't make any sense um for people to have said up to about a year or two ago, um, I'm spending too much time on administration, uh, I just want to serve guests. And and I'm I've started in this industry to serve guests and and be hospitable, because that's the industry that that we're in. Um and I I hate all this technology that that sort of isn't allowing me to do that because I spent more time with the technology than than with um with my guests. To then go now and say, I don't need that technology, I'll build it myself, because you're still doing the same thing then. Um you're still spending time on stuff that you shouldn't be doing. Um and yes, the first MVP, the first draft and the first iteration of your tool will be great, and you'll you'll be blown away by what you can do. And I've done this myself, and it is really cool. And with a few AI tools, you can build some really impressive and interesting stuff. And there might be edge cases or or niche um solutions that no one is building, and and and you can sort of build yourself uh a small automation or whatever. But I think in the long run, you're not going to be able to build a solution that can compete with the tech companies that that have the resources and the time to actually build something out that's that's solid, that works, that continues to work, um, and and that's that's sort of value for money. So I personally wouldn't get involved necessarily in that, um, in sort of trying to replace um your technology vendors. What I would definitely do is is go to your technology vendors and say, how are you going to allow me to customize your system to my needs? How are you going to allow me to automate some of the processes that I have, hopefully within your system and hopefully within the budget that I'm already spending on you? Um and and and what is your roadmap? What AI are you implementing in your system? Um and of course, you will use ChatGPT or Cloud next to it, or maybe you have an um you you are able to integrate it into your into your PMS or whatever. But I think you're you should be able to use some of the the AI technology, but the the the stuff that we're talking about around trust, about understanding what or really trusting that the data that is being used and the context that's being used is accurate, that's the kind of stuff that that can take you down a rabbit hole that you don't want to go down. Um and I think you're much better suited to let the tech vendors do that for you. Um But yeah, do call them out on it if they don't allow you to or don't do that for you. And because I feel like that's where the tech vendors should be moving towards.

SPEAKER_00 26:48

So do you think that we're in a time actually where operators can have much higher or should have much higher expectations of their tech partners to develop quicker on their roadmaps or like innovate differently on their roadmaps? Like because it's not just operators that now have access to AI to improve things and do things, but so do tech vendors as well. So do you think that we should be raising our expectations of product innovation and even cost maybe?

SPEAKER_01 27:22

Yeah, I think so. I think um the the the operators that I've seen um can can produce and launch products and features much quicker today than than they did before. Um so yes, I I feel like there should be a higher expectation on vendors to do that. And if your vendor isn't engaging with this at all, um of course vendors have different perspectives on it, they have different client bases that have different perspectives on it. So it's not necessarily that everyone needs to have the same AI implementations, it's it's more have they thought about it? Have do they have a clear strategy around what they feel is is is uh fits um their customer base and and their product best. Um but if that's if vendors don't actually clearly communicate to you, then yes, I think I think they should be held accountable to that. I also think that um vendors should use AI more and and and and probably should have um clearer and and faster roadmaps and and should allow users um to start using AI within their systems as well. So yes, I I do think um things are speeding up. Um there is of course a little bit of hype, and that's always the downside to this, is that a lot of vendors now are just throwing stuff out there um which either might not be that useful, they might have to pull it back because actually it doesn't work or it breaks or or so there's a lot of um just throwing things um uh to the wall and and seeing if it sticks kind of kind of idea at the moment. And and I'm sure that will will slow down um and and and things are um g improving there. Um in terms of costs, that's an interesting one. Um something that I feel a lot of vendors are still struggling with today is how do we actually price this into our products. So it might actually mean that the costs go up as well of some of the technology that we have. Um but I feel like it it well let's see, let's see how vendors um will actually deal with with that issue. And and there might be some AI solutions that are included in in the current package that you have, and some that they will actually sell separately. Um they will also get a reckoning once um Claude and Chat GPT start increasing their prices. So it'll be interesting to see how that plays out. Um but yeah, I've I feel like there's it's it's a really interesting time. Um and I think what I what I really look forward to and what I'm really interested in is what can vendors now do beyond just being a software provider, how can they ensure that um the technol technology actually starts working for the operator and for the guest? Um and and um that roadmap has sped up so drastically that that some of the stuff that we've been talking about for years, as I said at the beginning of this podcast, now starts to um actually be achievable and and starts to be achieved. Um and and um it's it's interesting, but at the same time, the caution is there are some other more fundamental issues that will still need to be solved on that as well.

SPEAKER_00 30:49

But what you're saying there, is it that that we're now in a time where actually the products fit the operators' needs much better, or we've got that opportunity for the products to fit the operators' needs.

SPEAKER_01 31:02

Is that what you mean by the I think we're at we're at a time where um operators themselves can customize the product to to their hopefully. I'm not saying that that's the case everywhere and and and we all know the the tech debt that this industry uh faces. Um but I think the potential is there for um technology to be built um not just by the tech vendors, but then also be customized by the operators themselves. So within the system, um allowing operators to automate certain processes, build their own workflows um with AI. And we've uh I hope everyone has sort of seen this already and got the idea of just going to Cloud or Chat GPT, and then it will be similar in in um in its functionality where you just ask it, can you automate this for me? I I have a problem, what is the solution to this? And it just builds something um within the system that you have that will solve that problem. And I think that's that's definitely something that that I see coming. Um I also see it becoming much more proactive, hopefully. Um I personally don't believe that the future of technology is um for us to ask it questions and it for it to come back with answers. I think it will start to go beyond that. To it will provide you with the answers before you know what to ask it. Um as a person and as as as operators, we don't always know what the right question is. Um because we it stuff you don't know you can't ask about. And so I think a really good technology system, maybe not today, but but uh in in the coming years, should start to um surface things to operators that they haven't even considered or they didn't even know about, um, without the need for sort of just chat box box where they ask that specific question.

SPEAKER_00 33:10

That's really interesting because you don't know what you don't know. And for what you're talking about is actually a very strategic intuitive tool to help you in your business that that can that can actually think, help you think or think for you in a way that is a different than we're using it today. Um, that is a very interesting future, but I also sort of really highlight actually that that that that divergence of the technology that will go down that road and the ones that just are not going to be able to even get close to it will see much more disparity of tech going forwards as well.

SPEAKER_01 33:53

Um yeah, and I I think that's um fine and and and it makes sense in a way, and and and actually if you pull it back to this this um initial thought that that we talked about earlier on uh on on uh on this call is is sort of there there will be uh vendors or or there will be operators that um that don't feel like they're in a place to to offer certain AI features because the data just isn't good. And they make this strategic decision of saying, actually, there's certain elements of of the operations that um we can't automate or we we we don't trust the AI to automate this. And and that's totally correct, if the context is correct, right? And and um the the human element continues to be extremely important, and every operator and and in in extension every vendor will have its have its own sort of uh thoughts around what parts of a hospitality experience should remain human and should be human-led or human-delivered, and and which can be automated. And so I think it's a it's a really interesting play where every operator and therefore every vendor um will decide where they believe AI will have the biggest impact or or where AI should be deployed or where it shouldn't be. And and there's not necessarily a a right or wrong answer, I think, in that. But also going in very clear-eyed around don't just throw AI everywhere and don't just trust it blindly to come up with some really good solutions. Because we do still have, and I keep hammering on about this, we do still have some of those foundational problems around siloed data, incorrect data, different definitions and and context that just doesn't align between the different systems, and AI isn't going to solve that problem per se. So I think that's that's something that that the industry and and and vendors and and operators do really need to continue to focus on.

SPEAKER_00 36:08

Yeah, and we anticipate that being a big topic for 2027, alongside you know, trust as being integral. Valta, while while I actually have you on here, and I'd like to talk to you about how you see AI changing market intelligence and research. And the reason that I want to ask you this is you've actually spent your career or much of your career in hospitality tech, market intelligence and research. Now, I'm AI will have quite dramatically, I would presume, have changed how you approach that. How do you approach your like the the work that you do and then also make sure that it that that trust is in there in terms of the outcomes and the outputs? And and how has it changed the whole kind of I guess the whole um uh what's the word I'm looking for? But the whole kind of um art, not the art, but the whole um concept of market intelligence and research. Because if if information is everywhere, we can all get information quite quickly in an instant, how does that then shape your role and what you offer and what we now offer at abode worldwide as well? That is really important.

SPEAKER_01 37:29

Yeah, for sure. Really interesting question. I think the the I I guess there's two parts to it. There's there's sort of the the idea of or or the concept of research in first, and then the actual research process or design. Um I think that the concept of research, in my view, and I'm obviously biased because this is my my world, but um the concept of research is actually becoming more and more important, um, not less. Um as you say rightly, you can ask Chat GPT today to to write you a research report and it will do it. 40 pages, 100 pages, doesn't matter. Spend the tokens and you get it. Um I think people are catching on to sort of what is AI slop and what isn't, uh, for sure. Uh but it's it's it's doable. Um producing these these um extensive reports um is becoming easier and easier. Um so I think being able to have a very clear um strategy, very clear market positioning, very clear um understanding of what you want to stand for, and then have evidence behind that and evidence-based research that and and and output that sort of supports that um I feel is is um extremely important. Also, from a sort of AI LLM point of view, in terms of um uh searchability, visibility, how how do um operators uh as if if you are a tech vendor, how do operators find you? How do they um search for you um if they're looking for a tech vendor? Um similarly for hotels, how do guests find you and and and what do they do? More and more that will uh and and sure it's it's potentially a pretty small uh part now, but it will continue to be more and more through these AI LLM agents. And so um people will search using Chat GPT, using uh Claude, and and um these engines, even though no one fully understands how they come up with their answers, they will they do really um respect and and use um third-party evidence, um uh strong thought leadership, uh, strong strategic positioning, um, and consistent output in terms of what you're talking and and how you're you're talking about yourself, and as well as how others are talking about you uh through earned media or whatever it might be, reviews in in the case of uh hotel operators or short-term rental operators. So it's research, I think, is becoming a more an important and integral part to having your brand out there and being respected also by LLMs. The actual process of research completely changes with AI. Um and I think it's it's a good thing. Um, I think the the the really for me personally as well, the really interesting part about research is um sort of understanding what are we trying to achieve here, really understanding how are we going to achieve that, and then what are the actual findings of it after we've done all of this this middle bit, which is the actual research. And the actual research and the analysis of the findings and all this stuff have have sped up massively with AI. And so it it becomes available to to much many more uh companies, also smaller companies can do quite extensive research projects. I don't think LLMs uh or AI is very good yet at coming up with um um good ideas for what you should be researching. Um, how should you be positioning that research in the market, how should you position yourself in the market? And so I think I think there's still a very um uh integral part to having a research specialist um to to to help you uh with that. Um but it it definitely is democratizing access to it, I think, in in in some ways. Um but there's still a lot of quirks and issues with research as well. That um having having someone with experience there is is in my view, my biased view, uh still very important.

SPEAKER_00 41:56

Brilliant. Thank you, Vouter, and thank you for this conversation. I think that you know, the looking so thank you for for telling us more about market intelligence and research and the importance of that, but the wider conversation that we've had about AI and how trust is so important, how getting those foundations are so important rather than just relying on the answers in a way, you've still got to get the structure. We don't have the structure right in hospitality. And I know that we're going to be doing a webinar together next month where we're actually going to look at some practicalities that are around getting that structure right and around looking at trust within AI and like a little bit deeper. So, for any of our listeners who are interested in finding out about that, you can check on the Abode Worldwide website or LinkedIn page. It will be, I believe it's in the third week of November, and we both will be hosting a webinar that will be educational in value, and we look forward to welcoming any of the Pillow Talk audience to that webinar. So, Vauta, again, thank you so much for joining me for a Pillow Talk sessions conversation.

SPEAKER_01 43:17

Thanks, Jessica.