REIMAGINING TRADITION: AI'S INFLUENCE ON REAL ESTATE AND INSURANCE WITH LUKE TATMAN

E81 REIMAGINING TRADITION_ AI'S INFLUENCE ON REAL ESTATE AND INSURANCE WITH LUKE TATMAN

Transcript

Dalton Anderson (00:01.454) Welcome to Midget Step Podcast, where we discuss entrepreneurship, industry trends, and the occasional book review. For generations, large corporations have guarded their data, and that was their largest value proposition. We're going to be talking today with Luke Tatman and discussing how AI could potentially level the flame field a little bit. Today on the show, we have Luke Tatman. Luke Tatman is a corporate strategist at one of the largest privately held real estate firms in the world.

We're going to be discussing today some things that he's seeing on the industry side and then providing some background on why are some of these industries at risk? Like I work in insurance, Luke Tatman works in real estate and both of these industries are kind of considered the old guard where they haven't changed very much. They haven't changed because no one's really forced them to change and people who have tried to force change have failed miserably. But I think AI

potentially has some abilities that previously hasn't been around. And I think that would open up opportunities for change a little bit more than before. So today in this episode, we're going to be discussing jobs at risk, which is basically providing a background about how JATU-D came out in 2022 and how quickly it's been adopted either by individuals or corporations. then from shifting from

individuals to institutions and then how AI is potentially reaching real estate. Luke, welcome to the show,

Luke Tatman (01:36.842) Thanks for having me. Excited to be here.

Dalton Anderson (01:39.928) Yeah, man. Appreciate carving out the time to get on the show.

Luke Tatman (01:46.154) Again, happy to be here and I look forward to talking with you. think it's a fairly interesting topic. Definitely prevalent right now in modern society. I think hopefully we're able to solve all the world's problems in the next hour.

Dalton Anderson (01:57.71) Of course, man, let's start out with, I think, recalibrating jobs at risk. I would say, I the initial idea of these LLMs, these chat bots, these chats that are available, ChatGPT, Gemini from Google, Anthropic, they're pretty new. Like ChatGPT was initially launched publicly in 2022.

There was university betas available to select professors and for, you know, academia work and just how quickly this technology has been adapted and becoming mainstream. I think is unprecedented. Like in 2025, a survey found that 75 % of employed adults use AI. And then another survey found that 67 % of businesses globally use generative AI. That's by Hostslinger and Minrow Ventures.

And so I think from your perspective, that aligns, right? Where the initial perception was this is going to attack entry level jobs, junior positions. There's going to be a lack of hiring in those areas, correct?

Luke Tatman (03:13.194) Yeah, you I think it's you look back historically at times like this, you you think industrial revolution, the creation of the Internet, you know, a lot of people thought that, you know, the world was ending, that this was coming for their jobs and and that, you know, everything was going to change, which it did. But I think what you saw is, really, you know, the the breaking down of the meticulous labor.

and a lot of areas, you know, you think about that with the, you know, the assembly line as it relates to manufacturing, right? That just enhanced, you know, workers to be better at their job. yeah, sure. A lot of people lost their jobs when things changed, but it really was just an enhancement. same thing with the internet, you know, it definitely changed a lot of businesses, but, know, here we are 20 years later, still, still thriving. I think this is, this is different in a lot of ways. and I think.

You know, we'll probably talk about it, a little bit down the road, but it is, you know, what you're saying is, you know, very aligned with, you know, what we're seeing in our world. mean, it's, been to your point two years and the, the means in which this has evolved and changed. you know, you look at one of the, know, the LLMs or, know, modules, from Chatch GBT just two and a half years ago. It was good and it was scary.

to a lot of people, but now you get back into it and you really start playing with it it has evolved 20-fold. So it's very interesting to see where it's gone.

Dalton Anderson (04:43.95) Yeah, Luke, that's some great points about the industrial revolution and these, these different periods that humans have went through. And you said this is a little different. And I think the unprecedented thing is the adoption, the adoption rate of this technology. And then this technology doesn't have a straight through replacement or these jobs that, you know, people used to ride on a carriage and then

light the streetlights at night before electricity and people were freaking out like, like, what are all these people going to do? They no longer have to light the streetlights and then they could maintain the electricity grid or something else. Whereas AI is just straight up. Like you don't need that many people to run a massive data center. Like a, a multi million square foot data center needs like 30 full-time employees. Like that's it. And so you need more people on the power grid and you need more people doing other things, but you won't necessarily need as many people doing what they used to do.

And I think that's the real threat there.

Luke Tatman (05:40.468) Yeah, yeah, I think, you know, to your point, it's it's identifying the at risk jobs, you know, and I think, you know, specifically as it relates to, you know, our industry and a lot of other industries, I think there are a lot of, you know, jobs that maybe were highly sought after that won't, but even, you know, even when we just see the adoption levels, you know, right now, I think one of the great things about America historically is that, you know, post the industrial revolution, the

you know, America has been supercharged, you know, by its white collar, you know, workforce. And a lot of that comes from, you know, their creativity and, and entrepreneurship, which has been driven by capitalism. But it's, you know, now we're, kind of approaching, you know, a place where we're looking at those at risk jobs. It's, know, it's, it's easy for us to kind of look at it now and go, okay, well, you know, this isn't, these aren't, you know, manual labor. These are, you know, this, these tools are being implemented to really help with.

not necessarily lot of the creative thinking, but streamline creative thinking and really very quickly increasing the abilities of entrepreneurship and self-starting. it's really going to be interesting because I think it's going to come for the white collar jobs that a lot of people thought were safe historically. And I think that we can dive into it little bit more, but I think there are a lot of areas that are going to be greatly affected by this.

Dalton Anderson (07:09.198) Yeah, no, think that's another great point to where not only does it have, it causes problems, but it also creates things that might be a strength where this AI piece will be a catalyst for innovation, a hundred percent. It allows any tinkerer or curious mind to just get down, get their sleeves up and just start creating stuff and get to idea to point a concept or a prototype.

to get to the market and then understand whether that the market is willing to, pay for that. But before that would take months, maybe a year, depending on how complex the idea is, hundreds of thousand dollars potentially. Now you can do that with a couple hundred bucks and some free time, which makes a massive difference on a society that values creativity and innovation and is willing to pay you for that.

Luke Tatman (08:04.842) Yeah, yeah, I agree. I mean, I think it's it is, you know, when we're looking from my perspective, when we're looking at the jobs that are at risk, you know, within my industry, you know, you have a lot of tasks that are very, you know, detail oriented, they're very specifically laid out, you need to come in every day, you need to make a marketing brochure, you need to come in, you need to fill out this pro forma, you need to come in and write this research. There are a lot of things that are, you know,

process where it's one, two, three, one, two, three, that don't necessarily require a lot of, you know, outside thought. And there are a lot of people in this country that think, you know, have kind of gotten used to that and said, this is great. I mean, I go to work, I'm an accountant. I know I got to plug the numbers in. I'm great with numbers. And, you know, I think while a lot of those, you know, jobs are, are, are definitely in my eyes identified as risk or at risk. I think it provides an opportunity to the best in class.

and the entrepreneurs in there. And I think that's kind of what I was referring to earlier is it just further exacerbates the ability of entrepreneurship. know, any of the people that are in these at risk jobs, you know, within my industry, or with anyone under industries, I think, you what I've told people when they say, hey, like, you know, what can I do to stay relevant? I think it's just really pushing people to adopt that mindset of

you know, being an entrepreneur and thinking differently because now, you know, if, your entire job is putting together marketing decks and you know, there's a machine now that can make marketing decks way quicker and way faster than you. Well, you need to identify where there may be shortcomings in, know, in your role and what you could be doing to be even better in your role. and so I think it's, it's really going to fall on the individual, at least from a corporate strategy perspective for people to find their best paths forward.

Because I think it's moving so fast that a lot of people from a corporate perspective aren't thinking about these things. So I think to anyone listening to this that's wondering, what can I do? I'm in one of those at-risk jobs. I would definitely take some time to figure out what can I do to be more entrepreneurial? Where is my current role? Maybe falling short. How can I get ahead of the eight ball and go to my boss and say, hey, I'd like to start doing this, this and this? Because if you can enable yourself with these new AI tools, be proactive and be entrepreneurial.

Luke Tatman (10:25.672) those people will be the people that will be coming out on top at the end of this golden age of AI.

Dalton Anderson (10:31.823) No, a hundred percent. And maybe just add a little bit of clarification. When Luke says entrepreneurial mindset, it doesn't mean that you have to go and leave and start your own thing. You could do that, but you could be an entrepreneur and help innovate within the company and maybe start a new initiative that you're in charge of. It doesn't necessarily mean you've got to go and jump ship and do your own thing. But I would like to double click into

the concept of this siloed knowledge or these processes like in the financial market or the commercial real estate. Can you just provide a little bit background on how real estate firms traditionally would provide value to a client and how maybe AI is moving into this great equalizer, maybe on just a background perspective before we dive in a little bit more detail.

Luke Tatman (11:07.53) Thank you.

Luke Tatman (11:20.522) Yeah, yeah, definitely. And I think it's important for me to just clarify a little bit more about what it is that I do. Some people will hear corporate strategy and they don't necessarily understand what that means. And I think it can mean a lot of different things to a lot of different people. But one of the interesting things within being in real estate, specifically my job is to help drive and steer some of the strategy of our company. So whether that's implementing new technologies, allocation of resources,

And, you know, just identifying different patterns, data analysis, things like along those lines. The interesting part is as a, you know, a commercial real estate company, we have our clients that are, you know, that are a lot of large clients all over the board. And they are, you know, they range from, you know, manufacturing to law firms. And so we actually, you know, use some of that information to drive

our decision making just because we see what other people are doing in the market, which is one of the very interesting pieces of real estate is that we get to see in real time the decision that people are making as it relates to the workplace. But to that point, I think commercial real estate specifically is a industry that is like many others, has a very old way of thinking, not very entrepreneurial as I just mentioned.

And they are, you know, the value proposition for commercial real estate brokers or lawyers or anyone within finance is a pairing of data and high level barriers to entry and high level barriers to entry are generally like a specific knowledge you're going to school for things like that. you know, you have other industries, you know, that don't necessarily have one of the two commercial real estate, much like banking.

much like law is very siloed in the sense that we have had the professionalism. We've gotten past the hybrid entry to become professionals and we've had the data to back that up. And I think that, you know, it is, it's now, the problem is that now the data has never been more easily accessible to the consumer, to the end user. And with these new AI tools,

Luke Tatman (13:46.824) the knowledge barrier, that high barrier to entry is as easy as it's ever been to break down. And so when you start seeing the dissolution of the two of those, it really reflects that, okay, well, this industry is going to have to change, much like a lot of industries. And just one more example, it's like, see lawyers, there's a lot of lawyers that they have a law degree, which legally allows them to operate as a lawyer.

But then they have this legal expertise and a bunch of data and well-informed decisions of the past that helped drive their decisions as lawyers. I don't know what the specific status, but it is an insane amount of legal documents are being read now by Chachi, these LLMs. it's interesting because it's going to just completely shift the dynamics of the hiring market. So I think industries like these,

are gonna have to go through incredible transformation. They've been very old fashioned. They've made a lot of money. But I think we're approaching an era in which that's going to have to change.

Dalton Anderson (14:58.594) And yeah, throwing bodies at it is not going to, it's not going to solve the problem on this one. On this scenario, more capital thrown at labor expenses is not going to make you the next breadwinner on that one, unfortunately for many. So you're on the front lines of this, right? What, like, what are you seeing? I think the main thing that people would say is a counter argument, like, well, we've got human relationships.

Luke Tatman (15:15.391) Agreed.

Dalton Anderson (15:27.096) I've been in the market 20 years. I built my relationship. built my firm and they say AI is not a threat to that. it doesn't matter what anyone says. is not part of part of my relationship. Like what, what would you say how AI could help integrate? know that's not going to take over the relationship, but I think at the end of the day, people are, people are sensitive. Like if you could get something either, and I would say sensitive to time and, or

information and or price. If you could provide me a better solution slash service in any of those three categories, I, and if it's like threefold better than your relationship is great. Like I love Mark known for 20 years, but in my opinion, I would have to reevaluate.

Luke Tatman (16:18.74) Yeah. Well, think so in my, in my opinion, you know, you have these consulting firms, law firms, commercial real estate firms, right? And there's, you know, there's, you know, large cap, middle market, small cap, you know, they're all doing, they all have their own market segments. And a lot of these, you know, smaller shops are driven to believe about relationships.

They don't have the best data, they don't have the best pricing, but that's Jim you went to college with. So of course you're going to let them do your corporate real estate. You're a CEO now, you go to Jim. And that's not going to change. That is the one thing the human element will never change. People will always continue to do business with people they like. To your point, sometimes it's a question of economics and sometimes it's a question of specific service offerings. Can you offer us the services we need at a price that we're willing to pay for it? And I think there's a...

It's just supply and demand at that point. And, but I think that it's the problem with where we are now is the fact of the matter is, you know, we have these companies that exist right now that are like Google, you know, we used to have a bunch of, you know, small third party, like data providers, advertising agencies, things like that. If you want to run an ad campaign, you go to Google, you go to LinkedIn, you go to these behemoths. Right. Um, and so it's, it's really the middle market.

much like the middle class in U S is starting to dissipate. because you, there's really two sides. Yeah. Am I looking at my relationship or am I looking at like, I'm looking at best in class and those best, the people that are doing it best in class, like in the commercial real estate industry, that would be like a CBRE. They have the best data. you know, they can offer things much more cost effectively because they don't necessarily, they don't have to assemble the certain data sets. They don't have to bring in these massive teams. have people that are specifically focused on each of the issues. it's.

It's really, I think the way that like the CBREs and the big guys are looking at it is, okay, how are we going to implement this technology and become the most effective we can? How can we build as many SEAL Team Sixes as we can with this technology to substantially cut down our footprint? So now they have the best data and they can offer you the best price. The other side of it too is that think there is that those small mom and pop

Luke Tatman (18:35.178) you know, people that depend on their relationships, they're going to continue to succeed as well because in this world where people are getting laid off and there's not a lot of human capital out there, it is going to be, you know, people are going to be looking for human interaction as things become less manual. So I think that the middle market within our industry and within a lot of industries similar to ours will start to shrink. And those, you know, large companies that do adopt and are at the forefront and

can streamline a lot of their processes and become more cost effective, they will be the ones leading the charge and the smaller shops will the people that are picking up the rest.

Dalton Anderson (19:13.52) I think that's a fair, fair opinion on that one. think that makes sense from a perspective, like an external perspective. You touched on it a little bit about the data piece where CBRE's got these teams that all they do is aggregate the data and the flow of the market and collect and scrape from public sources. How is AI enabling other firms to maybe compete on a day-to-day on a data

Luke Tatman (19:19.05) Thank

Dalton Anderson (19:43.44) process that allows them to compete on deals that they normally wouldn't be able to do that.

Luke Tatman (19:49.514) Yeah, guess so. You know, so I can't really speak specifically to what other firms are doing because I don't know, you know, the ins and outs of, you know, what their strategy is. But what I can say is, you know, the way this has worked is in a very traditional sense. You think about these companies have a room of analysts, a room of researchers, and they are their entire job is to, as you said, scrape the internet for data.

call other brokerage shops, look for comps, gather all this information. And over the years, you have seen each individual commercial real estate shop build out their own software that says, okay, if I wanna know, I'm gonna open an office for scoliosis in Southern California. I wanna know what the foot traffic is, age demographics, where would it make the best sense for me to put this scoliosis practice? And...

The firms have done a really great job of building out those tools. when that doctor does come in and say, hey, I'd like to open my scoliosis practice, they say, well, yeah, so this area right here in Southern California, this neighborhood actually has the highest level of scoliosis diagnoses. It's an aging population. It's mid-60s to 70s, very high foot traffic, and it's low rent. And they can do that cost benefit analysis in

Again, historically, you think about gathering and compiling and then building the models to support your decision making there. I mean, it's a huge undertaking. And it has been. It's been one of the things that has, you the reason that commercial real estate, the people get, you know, in law and all of these, I'm just generalizing. I'll say consulting for simplicity. But, you know, all the reason all these consultants have been getting paid so much is because they have

gone out, found the data, compiled it, built the models, and then they present it to you. That whole first piece of it is done now. Now it's just about presenting it to you. And that's where, even a client that can get in, you know, a client that wants to move somewhere like within the commercial real estate world, they can say, well, you know, I can get on ChatGPT and they, and honestly ChatGPT can get within throwing distance of, know, where like a market rent would be. The problem is,

Luke Tatman (22:08.074) You know that you know, that's fine when you're looking at, know Maybe a 1000 or 2000 square foot space where maybe it's five cents off per square foot So you're paying an extra, you know 200 bucks a month But when you're looking at a million square foot warehouse you want to make sure that your team has the very best data down to the dime because every cent that you're that you're You pay extra say you're paying a square foot on a million square foot lease Well over a 10 year lease you're gonna be paying, you know tens of millions of dollars

So it's really, you know, the data piece, all about how you get it and how you compile it. The, with this technology to your point earlier, it's technology that took two, three, $400,000 to make up just a few years ago, can be made within days, you know, for a couple hundred, a couple thousand dollars. so it's becoming less about the, has the data. It's who has the best data and who can do the best with the information and telling that story. And I think that.

Again, that's the main priority and focus of all these places. But again, that will obviously have substantial ramifications in my industry and many others.

Dalton Anderson (23:17.358) Yeah, I think there's still two things, right? Where there's still the information offering that these consulting groups, real estate firms, whatever law, they still have this information offering. I think the biggest thing that AI potentially does is it allows less resources to be devoted to the input to get maybe a similar, not a like for like output, but similar enough to where it is feasible.

on I would say a smaller deal or a middle market deal, whereas like a massive, you know, $20 million lease deal, it's a little different where it needs to be pretty dang close. But also I think if you had expertise in a certain area, you would be able to dial in a little bit more, whereas you could build these tools to help automate and aggregate data.

Whereas before you'd have to have people going on there, scraping the data, downloading it, formatting it, and then compiling it into this, this pricing model and this foot tracking model that you're talking about. Whereas now if you're savvy enough, you could implement these things with, as you said, a week's worth of work or a couple of weeks. I mean, we're being generous here on the, on the, lack of time, but it's going to take some time to troubleshoot and get it work and flow. And it's going to need some human checks, but

It takes a lot less resources, like fundamentally the information gathering and offering to get to an information offering to the client takes fundamentally less resources to get to where you need to go. If you have the right, I would say knowledge in your industry and you could fact check what these things are creating for you.

Luke Tatman (24:59.37) Yeah, I think it's, you we both have a mutual connection, I think, and he kind of within pseudo real estate world. He's in valuations and, my uncle, who's actually a, you know, he's a great engineer here slash architect within the DC market. And he, the thing that, you know, his struggle is, and specifically in valuations, you know, we downsized our valuations team tremendously.

over the last two years. And to your point, it's like, mean, if you think about something like valuations or engineering, right? They're underwriting, how much is this building worth? Or how much is it going to cost us to build this building? And if we think about it in the layers that we parceled out before, layer one, right? Layer one was Tom, the guy's like, hey, I'm going to figure out how much this building costs pre-internet. Picked up the phone, hey, Bob.

Bob's lumber, how you doing? Listen, how much, how much is lumber going for today? That's how much. All right. If I bought a million, how much would it be? All right. Punch in your calculator. Okay, great. Click. Thank you. Internet comes along. All right. Now we have a website. Bob's lumber has a website that tells me how much I get a little calculator and that's it. The thing about AI is now that AI can pull from 10 Bob's lumber websites, you know, if it's connected properly. and you just think about all the different moving components of, you know, these basically valuations and engineering.

These are all like super complex, like learn skills. But as people, there are AI companies coming out every day specifically solving for one problem. So there's an AI company that comes out tomorrow that says, we are going to be the best aggregate of lumber data on the entire internet. We'll get all the lumber companies, we'll put it in here. That's great. mean, that's the phase that we're in. People are making millions of dollars off of consolidating all the lumber pricing onto a website that's scrubbing the internet using an AI.

And I think that it's, you know, it's interesting because like these, we are, we're, know, people are building the machines now where a lot of this stuff that's kind of specialized like valuations or engineering. don't think that it's at that point yet where those, you know, are really the models haven't been built yet, but we're right on the precipice of it. think is, you know, kind of the current location that we're at. I don't even remember what your question was, but I,

Dalton Anderson (27:22.626) No, no, I, I agree a hundred percent with everything you said. And I love the, your analogy of Bob's lumber, maybe just to provide an example. Cause if you're listening to this, you're like, no way, that's not how it works. That's crazy. An example from myself without getting too civic about what we were doing, but basically we had a vendor that was offering a service of aggregation of data, like reviews or different things, criminal reports on a location when we're writing insurance, not used for pricing or anything, but

would enable us to have a better understanding of the type of risk that this property potentially be and whether or not we're comfortable and we had the right appetite. Instead of paying the vendor, we are able to use these AI companies to scrape the data off the internet where you could scrape the Yelp reviews, the Google reviews, these other things. Whereas it's important unstructured data doesn't necessarily move the needle in evaluations or change materially.

how you would price the property, but it might change your underwriting decision on whether or not this company or this property is the right fit for this portfolio. might not be our standard portfolio, it might be our at risk or challenge portfolio or however you wanna deviate out. to do that, previously you'd have to have bodies at the problem and it would.

it would just be a manual process and you'd have to do it every time. Someone would have to go in there, type in the address of the location, scrape all the reviews and of those reviews, we don't really care about all those reviews. Really it's, we care about some reviews that are at problem, like crime or other things like, you know, the property manager is taking care of the property, they have leaks and it's been taking weeks or, you know, there's pests, et cetera. And so you can really use AI to just, hey, like,

look for these problem reviews or these problem primer reports in this area and the proximity of this location. it helps it helps immensely instead of paying a vendor to do it. You can bring that in-house or make a solution at a fraction of the cost that it would have taken before.

Luke Tatman (29:35.498) Yeah. Yeah. think it's, I mean, it's good to contextualize it for the listener. Um, and I do think it's just, you know, to kind of bring together everything that, you know, we've said yet far, it's just, there are so many industries that are going to be so affected and like everyone thinks that they're kind of untouchable, but it's like even your real world solution, it's like the industry and real estate are two of the largest, you know, driving industries within the United States. And even those right there, it's like,

Those are two massive support functions for both of those businesses and they can be automated in a lot of ways. I mean, we look at where we've gone from two years ago to now. It's been incredible. It's been almost unimaginable. And with the upcoming developments and quantum computing and just the flow of development and just the basic GPT models, it's like, think we'll be very surprised when we should get back together, maybe one or two years from now look back and say, wow.

We were really wrong or really right, but you know, we'll see.

Dalton Anderson (30:37.509) Yeah, we'll see. We'll see when these nuclear power plants get turned on and we'll really start powering these models with everything we got. We'll see what happens. I'm sure it's going to be more interesting than less interesting for sure. And I think it's relming on the outcome of correct versus incorrect, but yeah, I'm a delusional optimist. So we'll see how it goes. Speaking of this AI providing value and disruption to various industries.

Luke Tatman (30:42.122) Thank

Dalton Anderson (31:07.247) What do you think the core value proposition is besides relationships, like a human interaction when AI becomes better at sourcing deals, underwriting, providing predictive analytics on forecasting of these geographic locations? Like here in the future, think the foot tracks is this, but I think with these other developments, like we've got these local developments that are coming up that each have.

800 single-family homes or multifamily homes or apartment buildings. And so it predicts the traffic to increase and the valuations to change, et cetera, et When it was able to contextualize all these moving parts that typically would reflect a real world model. What do you think is the real value proposition in the future? Like five years from now, 10 years from now, when these things really get built out besides the relationship piece.

Luke Tatman (31:56.308) Yeah, mean, think, well, it's funny you said, mean, you know, where the argument I've made, I think holistically right now has been fairly reflective of, you know, the, you know, the world of law, finance, consulting, all of those, think have been fairly applicable to, know, what I'm talking about, broadly speaking, of course. But I think the one thing about real estate is it really commercial real estate specifically is it is all about deal origination. That's it. And, you know,

There are people that my old boss would pick up and call every week. He'd called him a hundred times before and never, you know, was able to convince him to sell. And there's another bunch of other guys that have called a hundred times before. It's not so much. It's sales. Can you convince your person to sell? Can you convince someone to buy it? And that's it. mean, it is the value we bring even at the end of the day, really is can we provide value to you?

and enhance your life through whatever means you're looking to enhance it through. So if your fund is looking to make a substantial return, then we just have to, and this is where it's like, we've now gone from having just the broker in on the pitch with the marketing person who can talk about the marketing brochure to now we actually have kind of taken a different approach. We have the broker come in, who's the salesperson in traditional sense, but then we also have our analysts come in. So our data analysts.

because they are the ones that are able to compile the actual story and make the justifications. And so I think it's, again, as the playing field is becoming leveled by everyone having very similar data, I think the value proposition, no matter what, stays the same because it's rooted in that one singular thing, which is sales, people, relationships. The means in which we get to that, I think, is different. But again, those people that are utilizing this in an entrepreneurial spirit,

and saying, well, actually, yeah, I can leverage AI to tell a way better story. I can leverage AI to get you way better data. We can get a larger data set. The people that are utilizing this correctly, I think, you know, will just excel immensely in these next couple of years. So to answer your question, think the value proposition stays the same. It's just kind of a different field that you're playing in, you know, to get to that point.

Dalton Anderson (34:20.687) The sausage is made slightly different in the future, but it's still a sausage.

Luke Tatman (34:25.354) That's exactly right. Same old sauce.

Dalton Anderson (34:26.801) Are you seeing these firms pop up? Have you seen anything that has popped up recently that looks promising?

Luke Tatman (34:34.762) In terms of like for AI.

Dalton Anderson (34:40.699) like an AI based or AI, let's phrase it this way, an AI native real estate firm.

Luke Tatman (34:47.978) It's funny you say that actually. I wish I had the article in front of me. There's one that is looking to replicate some AI capabilities or real estate capabilities with AI out in Las Vegas. It was about two and a half months ago. They are trying to redefine commercial real estate and they received a severed pig's head in the mail with a note that said, don't you dare try changing commercial real estate because...

You know, we, this was built on the backs of, know, yada, yada, yada. It's just like the old unions, you know, back when the industrial revolution came around, right? It's like, it is, it's a classic strong arm of like, don't you, you're not going to change this. so while there aren't specifically, you know, companies right now that I would identify as, you know, promising, there are steps being made both from the big shops and from small shops. Just, I mean, there's, there's a.

company called Henry AI, they are a, I'll just use them as an example, they make OMs, which are like a big part of our business, it's an offering memorandum. And that's just when we take a property to market, it just gives investors and buyers just an overview of everything about the property. And now that company is specific on that one component of our business, they make those automatically now. And so it's, you know,

You could, could a, and I think the goal is obviously for shops like CBRE, JLL, ours, the goal is to come together. and yeah, I guess the goal is to come together and make, probably make some of those, a lot of those tools in house. but you know, now we're in the space race. We'll see who is the first, who can get to that point of making it make economical sense, while delivering at the level of service that people are comfortable with. it's.

Again, it's so funny because things are moving so fast that there really is no definitive answer.

Dalton Anderson (36:47.665) Yeah, just the uncertainty. It's almost like a suspenseful show, but you're you're part of the show. You're the lead actor and then you're also the observer at the same time. It's a bit odd, you know.

Luke Tatman (37:00.362) Yeah, you're looking around and you're like, what is going to happen next? You know, I think that's one of the weird parts of becoming an adult during these times is that like, you know, everyone, you know, kind of reached the conclusion historically like, oh, we're just all children that grew up and no one really knows anything. We're all just kind of figuring out as we go along. But even more specifically now, it's like people that have been working in IT for, you know, 20 years, people at other companies, you people within the industry that have been working in IT for 20, 30, 40 years.

They know almost just as much as the entrepreneurial people we're talking about like myself who have been studying this stuff because it's evolved so fast since the first chat tpt model came out that the playing field has been leveled. So it's like no one knows what's going on. Anyone that tells you that knows where we're going or what's going on, they are lying to you because we're all in the same boat.

Dalton Anderson (37:52.7) Yeah, it's funny you say that. I was talking about it earlier. I went on a run today and talking with some buddies and kind of came up in conversation, but I basically referenced like for our generation, this is potentially the thing that you could make it big on, right? Like we're too young. We're too young for a really Bitcoin. Like maybe you could throw some money in Bitcoin, like if you had some, but you're not, you're not a young professional where you've got

you know, 20 grand to throw at a problem with Bitcoin like back in high school or something. The housing crash or too young for that. And so all these things where you can make a lucrative outcome are these, these just like massive opportunities you were just too young for. But this is the one opportunity currently for the generation that we have where you could really, if you go all in and really study it,

add it to your craft, provide value to these large organizations, create an organization. That's where you can really add value to society and also enable yourself to be financially compensated for it.

Luke Tatman (39:04.01) Yeah, I think so. mean, a friend of mine and I have, you know, we've talked about, you know, some business ideas over the past, you know, 10 years and the barrier to entry has been that $200,000 check to build out tech and, you know, actually implement some of this stuff. And right now is the gold rush. You know, if you're going to go consolidate Tom's lumber pricing, you know, if you see hiccups in your world, it's exactly what I talked about in the game. You see a problem.

It doesn't even have to be a problem with your company or your job specifically. You see a problem with your industry? Go find a way to make those apps or make that website or make, you know, use AI to get to the finish line because there will be, you know, going forward two to three years of just a gold rush of people just making companies. I a lot of them will fail, but a lot of them will succeed. And I think that, you know, people need to be creative and be entrepreneurs now more than ever, because this is...

This is quite possibly could be one of the last times that there's gonna be any semblance of entrepreneurial spirit. So take advantage of that while you can.

Dalton Anderson (40:12.933) the gold rush and then there's the great consolidation that we'll all hear about. Yeah. Yeah. So today in this, I think it's a great place to close it out. Today's episode, talked about at risk jobs, shifting the thought process of AI influence from individuals to institutions and then how AI is reaching over.

Luke Tatman (40:16.958) The great consolidation, yes. Put the chip in your head and there you go.

Dalton Anderson (40:39.749) the aisle to the old guard, potentially these industries like real estate, insurance, other financial services and law.

That being said, loved having you on the show, Luke, super knowledgeable about various topics and provided a lot of anecdotal and empirical information on just where are we at and how we feeling and what are you seeing? Is there any way that people could get in touch with you or anything that you want to share with the listeners before we drop off?

Luke Tatman (41:13.194) Yeah, you know, I have I'll make sure that Dalton has my My information that he can put at the bottom of the episode So if anyone wants to get in touch, you can find me on LinkedIn at Luke Tappman That's probably the just way to reach out and then I'll make sure to give him the information as well But thank you for having me. It's been a it's been a pleasure and I Will see what we'll see we're out on the next episode in a couple of years

Dalton Anderson (41:36.762) Yeah, man. Before we close out, I do this every episode. I just say wherever you are in this world, good morning, good afternoon, good evening. Have a great day. Thank you for listening and see you next week. Bye.

Luke Tatman (41:52.83) Thanks.