#37: James Scott, Research Scientist - Artificial Intelligence, overcoming resistance to change, and tech’s impact on real estate

And you see so many people using the likes of ChatGPT and getting themselves in trouble. I don't know if you saw that lawyer last year that was thrown out of court who, you know, was using six pieces of case law that didn't exist. Yeah. You know what I mean? And that happens because human oversight is the most important aspect of all of this. You need somebody to make sure that the data is coming in reads correctly from a comprehension perspective, but also that the data points themselves are accurate on a round point as well. Because what this is doing is it's taking. Taking words from different parts of the world and putting it together. It's not verifying them. It's not taking it. It's not verifying that it's true. It's not even verifying that the source it's coming from is even true. It's just generating content.

On today's episode, we have lecturer and research scientist at MIT center for Real Estate, James Scott. Steve, this was a fascinating conversation. This is probably the most unique podcast episode we've had. And James, as you can tell by his title, James, is a research scientist, he's a lecturer at mit. Yes, that mit. And we talked about the advancements in technology, artificial intelligence, all these advancements that are having an impact not only in just our, like, everyday world, but specifically in our case, real estate. And I loved his, his, his take on where we're going with, with tech. But he also had, he also had some, like, not even, not really cautionary tales, but he kind of counteracted that with. There's some difficulties with tech and rolling it out to any industry that, that you're in.

Jake. It's like with any technology, with AI or anything new, there's always a resistance to change in an organization. But the critical thing is if you got to get everybody aligned and going the same direction, and if you get a little hiccup in the implementation, you don't give up. You fix it and keep on going. I've seen too many companies where they implement a new technology and at the first sign of an issue, they throw it out. And they should have just kept with it and kept it going. But the team and the company culture is critical with any new technology.

Yeah. And he even addresses that. You got to give it time to settle in and to get full adoption, because these things, their impact comes when it's fully adopted and people start to use it. And so you really can't short circuit it by just giving a short amount of time. But I loved his approach of here's how you get adoption, here's how you get buy in. And one of his points was those who adopt technology early and stick with it are going to be the ones who are successful. And that certainly applies to real estate investing. So let's head west on this episode. Stay tuned as we discuss artificial intelligence overcoming resistance to change and tech's impact on real estate with our guest, James Scott. This episode is brought to you by Skyline Point Capital. If you're anything like me, you're always considering where to invest your money. Stocks, bonds, crypto, a rental home. The list is literally endless. As we've all seen over the past year, the stock market is unstable, the housing market is just weird, and inflation is on the rise. In times like these, the clear place to invest my money is in multifamily real estate, AKA apartment complexes. Here's why. Returns on real estate investments have little to no correlation with the stock market. There's lower volatility, stable income streams, and the tax benefits are insane. And let's not forget that the apartments will typically appreciate in value over time, which means you can walk away with a pretty nice return when the complex is sold in three to five years. Best of all, multifamily investing is passive, so you get all the benefits without the hassle and headache of your typical rental home investment. Getting started has never been easier. Head to skylinepointcapital.com to learn how you can start investing today. Well, James, you come from. You're in Boston now, aren't you?

Yeah, based in Boston.

Okay. How long have you been there? Did you, did you come right from Ireland to Boston?

To Boston? Moved over here. Look, I mean, don't hate me too much for this, but I actually had a career before moving to the U.S. i was a lawyer for quite a long time. Okay. And then we moved over here in 2015, and I used that opportunity to go back to school because I had a real passion for real estate at the time. I still obviously do. And I came to MIT as a student and it was really there at MIT that I kind of had my eyes opened in a number of different ways to new concepts, new ideas, new thoughts on how things were going to take place. And within that, I came across a couple of really influential people who kind of changed my whole trajectory in life in lots of respects. I'd been very much a corporate kind of based ideology, and that's where I probably saw myself moving to after mit. But I came across three individuals who were really kind of the flagship of real estate technology at MIT at the start of all of this back and that's back in 2015 they were a lady called Andrea Shagu who started a thing called the Real Estate Innovation Lab there. Steve, Steve Wel, who really led prop tech from the very early kind of it's very early inception and has been a thought leader in that the, the entire time within that. And another really incredible individual called Dennis Frenchman who was the head of the center for Real Estate at the time and who was just. I, I often say when I met Dennis, having been a lawyer, he was one of those incredible people who changed my whole outlook of life because I'd probably seen the world in black and white and from, you know, a corporate world. And he allowed me kind of to see in color and I actually use that line with him an awful lot of, because he had such a kind of dramatic influence over, you know, a lot of how I thought about things and how to see things grow and how innovation works. And so through that I joined up with them when they created a thing called the Real Estate Innovation Lab. And I joined there on day one as a researcher. I then became the lead researcher and then over time the Innovation Lab itself kind of faded away and we created something else in which I lead called the Real Estate Transformation Lab. And that's now led by a professor called Professor Cairo Shan who was formerly the, the head of the BPDA here, here in Boston. And what that does is we're sort of a. No, we are a research platform that essentially merges the 40 plus year or 40 odd years of real estate experience and research that's been carried out at the center for Real Estate at MIT with MIT's sort of technological prowess and understanding to allow us to have a research platform to better understand this new wave of digitization that's been taking place across real estate. And within that the bill, I'm more importantly the built environment itself. We I then have wear a number of different hats within mit. So I'm the director of the Real Estate Transformation Lab. I'm a research scientist there and I also teach two classes. I teach a class called Prop Tech Ventures. I teach that alongside Steve Wil and what that is is a new class that we've developed over the last few years to give students a better understanding of the proptech ecosystem and then within that over the course of the semester allow them to build out their own Prop tech concepts and startup ideas within that to kind of, to drive that forward. And then I teach another class called Technological Innovation for the Built Environment and that's more of a case of understanding the general purpose technologies that exist out there and how they're influencing the cities and buildings, you know, going forward in the future. I say general purpose. What I mean by that is the overall concepts of the technology themselves. So if you were to take blockchain, blockchain would be the general purpose technology, but Bitcoin might be the product that's developed out of that particular technology. And you know, looking at all of those and how they're affecting the cities and the buildings within which we live and that's, that's essentially, that's my, my, my. They're all of my day jobs at the minute. That's fascinating. Yeah, it's been a crazy nine years. It's. And you know, each day it's more exciting than the next because one of the, this is kind of a really. I don't say that it's the fun part of all of this. One of the great things that we get to do and we lead within the lab is understanding all of the products, processes and technologies that are out there and always understanding what's coming down the line and giving ourselves that opportunity to kind of not see into the future. We're not futurists in any way, and I don't really believe in that in any way, but understanding kind of to be able to kind of half glimpse around the corner to see the concepts, the ideas, the innovation and the designs that are taking place within the universities, within the labs, within the incubators and to see what's there that can make a difference. It can make a change across the world of real estate technology or prop tech, depending on how you, how you define it.

Did you, did you have a bent towards technology previous to mit and did you come to MIT with that sort of in mind? Like, did you go to MIT just because you wanted to further educate yourself or did you go there specifically for the technology side of real estate?

I went there truthfully with my eyes wide open to real estate and along the line discovered a, not only a passion but a, I'm going to use an Irish term here, a knack for, for it, like a knack for data science as much as anything else that, you know, I hadn't really tapped into since it's my college and you know, reuse that skill set in different ways to, with, with a lot of the research that we carried out and build that out. And I just happened to be in the right place at the right time as much as anything else. And I, I know that sounds a Little bit kind of crazy in the, in today's world where we all, you know, we build out our careers and we have a very clear concept of where we're going. But this world essentially developed in the midst of everything that I was doing. Because, you know, there's a great example of this. Like one of the first things that I did within, you know, one of my first projects, in fact, it was probably the first project we did within the Real Estate Innovation Lab back in 2015 was we assessed and we looked at all of the different real estate technology companies that were out there. We had a fully encompassed list and it was about 70 companies. That's all that existed at the time. Like depending on who you talk to and who, which list you look at, that's anywhere between 12, 15, 18,000 companies now. And so we were there at the very, very start to see this, this trend, you know, this transformation and evolution takes place with, with it within this niche industry, which is proptech, and then the adoption that then happened subsequent to that within the world of the real estate industry itself.

Yeah, this is a fascinating conversation and I was excited to have you on because from the outside looking in, I'm kind of tapping back into my pre real estate mindset. Real estate seems like a fairly static industry, if you want to call it that. Like it's land. It is what it is. There's nothing fancy about it. Tech is probably going to have a very minimal impact on it. But now sort of to your point, we are getting into like this time in our lives where tech has an influence on everything.

Right.

Whether it's AI, whether it's, you know, in the real estate you have, like you said, prop technology where it helps property management companies better manage their assets. Where what are areas of like the real. In the real estate world, are you seeing the most potential for progress? Because again, I come from originally saying I don't see how tech can actually have that big of an impact on managing a property or helping investors. Like, so where do you see this thing going?

Well, okay, you've opened up a whole can of worms.

Good.

I nearly did come off my chair a couple of times.

I love it.

Well, let's kind of start at the start. Now I will be fair about this. Like, I mean there are individual real estate is, is a very unique industry and let's kind of take a step back without it in that it's in itself, it's a cyclical business. It has been one of those ones because of that. It's one where you make Hay while the sun shines. So you got to begin there, you got to make money as it happens. The adoption of new concepts and ideas. This is not new. Technology is not new. Within the world of real estate. In that we had the dot com era, there was a number of different companies that came out of that. A lot of them were a little bit gimmicky. So a lot of people were bitten and didn't particularly think that they were great. I have a colleague of mine who is one of the most revered individuals you could meet within, within the confines of mit. And he will say to me on a daily basis, it's all just a bunch of sensors. And that's his entire thesis on this. And we have great debate on this on a regular basis. But that's not true in any sense. The world of real estate tech and or prop tech has evolved so incredibly over the last, we'll call it eight, nine years, primarily due to two particular reasons. One has been the huge advancement in specific technologies and how they've been developed out. And then from that, what you've been able to curate and use those technologies for within the business. It's not just property management, it's not just asset management, it's not just construction technology which is kind of developed out into its own niche in itself. It's not just design, it's not just financial analysis. All of these things have seen incredible advancements with different areas of technology. For me, primarily the one that has really focused, has driven that. And I know it's a little bit of cliche this week because we're about a year into this incredible media bonanza when it comes to artificial intelligence, but AI has been the driving force in an awful lot of those aspects. Not that specifically to ChatGPT and the large language model sets which have kind of developed out of generative AI, but the other evolution that's been going on actually, which began in the 1950s in essentially natural language processing and image recognition systems, in predictive analytics, all of these things have really helped facilitate and drive numerous technologies that are out there. You coincide that with the incredible amount of money that has just gone into this industry over the last eight, nine years. Like, I mean, if you look back into it, when we started, there was maybe a billion dollars been kind of been put into this and the question of whether or not it was actually really real estate tech or not was always a great debate. And that were those numbers 100% to a point. Like, I mean, in, you know, 2022, where we're getting maybe $30 billion invested into this industry every year at this moment in time. There has been a, definitely a comeback in that, but that's due to a number of different factors. Technology has had a, has had a comeback in the last 18 months. VC has had a comeback in the last 18 months. And so you know that probably we've seen definitely a, certainly a curtailment on the amount of money that's flowed into the system. But coinciding with that, because of the likes of something like a kind of a major black swan event like Covid, the adoption of new technologies within the realms of industry has been incredibly increased. Like I would, I'm using anecdotal evidence here, but it's ones that you, you'll often hear is that we probably moved five years forward in the space of about 18 months when it created on an adoption curve, because people were, hold on, there's another way of doing this. I can't do it from home. Can I do it remotely? What's out there in the marketplace? So the appetite for new concepts and ideas completely changed in that space of time. And then from that, we now have incredible advancements within the likes of something like AI, specifically gen AI for a lot of people, because that's the cool new concept that everybody's seeing. And they're kind of trying to work out how this is all going to change numerous different aspects. But that coincides not just with the large language model sets which you're seeing when you use something like chatgpt and the words that are generated from that, but even design concepts like me for, for buildings, the floor plate concepts within that, like in the orientation concepts that come with that. I mean, this, this is, there's, there's incredible efficiency and there's an incredible kind of level of understanding that that's, that's coinciding with this. And we're really only at the tip of the iceberg.

Yeah.

And, you know, there's a, there's a great, you know, for a lot of people listening to this, they'll have, especially ones who are familiar with technology, they'll often understand the concept that is the Gartner hype cycle. And this is this kind of S curve that whereby, you know, new technologies are, you know, that when they come into play, they go along this very kind of steep curve going up to a point of. It's called the inception trigger, to a point called the peak of inflated expectations. And we're at that moment in time where this new technology can do no wrong. It's going to change the world. And everything is going to, it's, everything is going to be based off this technology. And this happens all the time. We see it all the time. Like remember, you know, five or six years ago, Blockchain was going to do this. Yep. All right, you know, you know, autonomous vehicles were going to do this. Numerous aspects of AI have been going to do this for a number of years. And then what happens is through time and understanding and regulation and investment, we, that, that, that, that peak slowly falls down into a slope of disillusionment or, sorry, a trough of disillusionment whereby you kind of start to realize this has limitations, it's not going to be adopted the way we thought, but we start then figuring it out and then it goes into the slope of enlightenment where we, through that figuring out phases where we embrace the technology, it fits into it from a commercial level, we use products with it, and then it slowly rolls out into this kind of plateau of productivity where we embrace it all the time. We don't even realize it's a new technology anymore. And that's kind of the general point. I'm sorry, going back to my point with this, with Gen AI, we're really at that point of inflated expectations and we're trying to figure out this can do so much and we're trying to figure out how we're going to make it all capable. And there's a number of people that will suggest that we're about to, that's about to taper off. And then there are a number of people that say we're only getting started because the more, you know, with the embracement of data, the data collection that's out there, which is the, the foundation stone for a lot of technologies. And we're only getting started with how to embrace this, utilize it, create the efficiency and there's just so much more to give. And you know, that's, you know, that's been showcased in a number of, you know, stock portfolios. When you look at the AI, how AI is going to change number of different aspects of business and how it's going to be embraced. But for me, AI has been at the forefront of our, our understanding and our, our research. Because it's not today or yesterday that AI has come about. You know, this is a concept that's been around. I think 1956 is the first kind of concept where AI was, was kind of given its formal title by a group of incredibly brilliant people at the Dartmouth Conferences where they tried to figure this out. And through not having the Computational capabilities, not having the data storage facilities kind of ran into a lot of brick walls for a long time. But then in around the early 2000s, with the evolution of data storage capabilities, the advancements of GPUs and other kind of really great, insightful people building on this, AI has, has, has, is the, is the cornerstone of, of numerous different products that are out there that can really change how different aspects of the business work. And you don't, you don't even need to pigeonhole it into, you know, property management or asset management or development or construction or any brokerage. Any different aspect of real estate. AI is affecting and is going to continually change how all of these different aspects of the business, you know, kind of orchestrate themselves going forward.

Hey, James.

Excuse me.

In the business, with our investors and the properties we own, in the last 18 months, acquisition activity has virtually come to a screeching halt due to the higher interest rates and the problem with bridge debt and trying to be a better operator. What we see right now as asset managers and with our property managers, everybody's looking for that magic bullet to help improve efficiencies. We can't hire the right people to be the property manager. All these things and on the forefront about every meeting, weekly meeting or monthly meeting, we're talking about, how do we utilize AI to help us during this time to make our properties as the most efficient we can using technology? That's all I hear is how can we use technology to make it more efficient, less human intervention, and provide a better service? Can you elaborate on that, what that looks like, where you see this as going, and how investment companies owning property can utilize AI to have that competitive edge.

I love how you put all that because it's, you know, it showcases so many different things that we all know we just sometimes forget about. You know, the evolution of technology always comes in a moment of like, we'll call it in a moment of change. Going back to my original saying, like, I mean, make hay while the sun shines. Like, when the market's up, nobody wants to talk about technology. It's just, get the deal done, get it done as fast as you can. Now we're in this moment of change, you know, I mean, where people are not doing okay. How do we increase efficiency? How do we make that happen? I, I read something about this AI thing that's, you know, you push a magic button and everything just, you know, it's going to just work wonders.

Occupancy goes down, it's going to change.

Our company and we're going to have efficiency and it's going to be fantastic and it's going to be wonderful. And you hear like, this is not, you know, this is not an unusual conversation. This is happens in every real estate company. It doesn't matter whether you're, you know, 2,000 people or you're, you're a five man team. And again, you know, you, you read especially you read what you see in the media and you kind of go, okay, well there's a magic button here that, that's not how it works. All right. And not only that like me, but, but it's understanding its capabilities is kind of the first step. What can this do? Where can I drive the efficiencies within my business? Looking at the, looking at the bottlenecks within my business, what's taking up the time of the people within the office? Is it scheduling calls for, you know, to showcase the, you know, leasing units? Is it, you know, calling people back with, with, with. We'll call it triage for, on, on maintenance requests? Is it, you know, what, where is the difficulty within my business that taking up a lot of the people's time and it's not really helping them go out and really make money with the time that they have while they're working for me or within the business and then understanding what product is available to kind of alleviate those bottlenecks that you have within your business. And there are numerous. But here's the issue with, not issue, but here's the thing that people kind of sometimes don't realize at the start of this journey. There are numerous different products out there which can be very hard to kind of figure out. As I said, we're now looking at, you know, 18,000 different concepts out there and with the money that will be pushed into AI specifically that one, then into real estate specifically, there are going to be more startups with that. It's so hard to figure out which companies are going to be here in two years time as well as everything else. But in understanding how your business works, how it operates is a great start. Understanding the capabilities of what can be done with these is a huge element as well. It's not a case that there's a button that you press and it links all of your data seamlessly into this particular product and it spits out and tells you what to do, which happens with so many people and they're so disappointed. All right. Because I'm touching about 15 different topics here, so I'm going to miss bits. But just come back to me as I'm rambling here, but an awful lot of the products out there, they need to be sustained, they need to be, you know, and they need to be really managed in a really capable way. And there's a great example of this that everybody seems to understand a little bit better, which is Salesforce. You know, Salesforce requires people to enter data on a daily basis or a weekly basis in order for you to garner that insight that creates the value within the team or the office. Most real estate products required that data input as well, be it from an external source or from internally as well. And when you don't have buy in from the people within the company, they're not entering the data. And so what happens is a situation that the products can sometimes look like they don't really work that well, but it's not the case, they're not been used in the right way. And you have to figure that out. You have to get buy in from your entire team. When you, when you take on a lot of these concepts and these ideas as well, you then have to understand your data migration systems as well. Can we use the data that's already there? How does that seamlessly, does it seamlessly fit with the new product that we want to get? And then where are we going to extract the value? Because there are so many people out there working with consultants and with different teams to extract data. The concept that we all know and love within the business world, which is a return on investment with these things, I'm trying to get that. And that's a very, very difficult thing to prove and very difficult thing to understand. And you know, with a lot of times you're going to find an answer that's not really going to sit with a lot of people, but you know yourself. I'm going to use an example here that gets me in trouble all the time because I shouldn't tell people this because I tell it at different events. But here's the level of efficiency. There's an incredible class at MIT and I gave this, I sold a story actually at a YPO conference recently where one of the students, I sat down and was having a meeting with them and I was asking them how their week was going because I knew at that time there was midterms were just on and I knew that there's a couple of deliverables that they have to do and it's a really stressful week. I asked them, how you doing? And they go, fine. What do you mean you're fine? This is the hardest week of the Year, you shouldn't be fine. I was curious what's going on? And they said, yeah, fine. I said, do you not have your midterms yet? Midterms were good. And I do not have deliverable in this particular subject, which I know is extremely hard and extremely difficult. It's one of those ones that Requires at least 15 hours of time every week. And it's a course that's based off real estate legal documents and they have to assess two 300 page legal documents and then derive answers from questions they're given and it takes up at least a good portion of their week. And I said, what about that? And they go, well, it's fine. I said, how is it fine? And they go, what I do is I copy and paste the 300 page legal document into chat GPT and I ask it, you know, I mean, what are the most important issues with this contract? And it spits out the answers. And five of the six answers of the questions I have, I'm given. And then I need to finesse probably the last one. The whole thing takes me about 20 minutes.

Oh my God.

This is a, this is a project that would normally have taken any student somewhere in the region of 10 to 12 hours and they're now doing it in 20 minutes. And you're kind of going to yourself. That's the level of efficiency that can be extracted when you utilize this technology really well. Now, couple of caveats. You still need to read your answer, you still need to curate it, that it reads and makes sense. And there's a human oversight element to all of this. And you see so many people using the likes of ChatGPT and getting themselves in trouble. I don't know if you saw that lawyer last year that was thrown out of court who was using six pieces of case law that didn't exist. Yeah, you know what I mean? And that happens because human oversight is the most important aspect of all of this. You need somebody to make sure that the data is coming in reads correctly from a comprehension perspective, but also that the data points themselves are accurate and are on point as well. Because what this is doing is it's taking words from different parts of the world and putting it together. It's not verifying them, it's not taking it, it's not verifying that it's true. It's not even verifying that the source it's coming from is even true. It's just generating content. And once. But once you realize that the content is essentially there and you can curate that to you Know, with a little bit of understanding and knowledge and expertise, the efficiency just, it just rolls and it's so fast. And you know, when you, when you take an example like that, you realize, like, if you're not using this correctly, you're essentially standing at the traffic lights on a bicycle and your competitor is pulling up in a Porsche. And that's, that's the level of efficiency that's created with something like this. And you kind of have to embrace that and start to understand and educate yourself. Okay, where are the bottlenecks? Where can I create greater efficiency? What are the products that can achieve this? And let's see how we can roll with, you know, roll this out as best we can.

Okay, so, James, as we wrap up, I want to ask you one last question. Tech, especially in real estate, has just been growing in leaps and bounds over the past few years. And even said, you know, back through Covid, we kind of jumped ahead in the schedule about maybe five years. What advancements do you see tech having in the real estate space over the next one to, let's say, three years, that are going to have massive, massive impact on real estate and real estate investing?

The obvious one has to be generative AI, and that's in a number of different capacities. But there are ones, and I'll touch on a few other ones as well. I just want to, because I know the media kind of focuses on that an awful lot. But there are a couple of products out there in the marketplace that when you see the generative reporting capabilities that it adds into the data extraction kind of value that it brings to the end user, you realize how, how much of a game changer this, this is going to kind of bring to the marketplace. Now you could, you know, the likes of artificial assistance, the, the use of, you know, chatbots, and I know, you know, Jake Ruto made chatbots earlier on, but chatbots, they kind of have a bad name in certain respects as well because they, they, let's be fair about it. We've all had frustration with chatbots as an end user over the course of time, but there's a reality to how these things work now. They're far more humanistic, they're far more capable, and they're far more capable of sinking into other aspects of, of your, of your network. So for, for scheduling purposes, for maintenance purposes. But there's a couple of companies out there that are using this really, really well. I hate pulling kind of names out of the, you know, because I think it's a little bit unfair, but there's a company that, you know, I think you just should have a look at. I think they're doing incredible work on Marker M A R K E R R and just to see how they demo their, their understanding of their product because they have this incredible insight into, you know, kind of forecasting rent bottles and with, with that. But it's the Gen AI piece that's just spectacular for how they, how they put together the reporting mechanism. Because you know yourself, you've used a number of, I'm sure, real estate products out there and for a lot of the end users in the real estate world, they, you know, they see all these magical graphs, they see all these kind of, you know, fantastic equations that are running in the background. They see the code even running in the background sometimes and they go, oh yeah, this is brilliant, this is cool. But they don't actually understand what's in front of them, you know, and that, that's a really important part that people sometimes forget. Like, I mean, you know, a lot of the people are, you know, they're property managers, they're facility managers. They're just kind of going, what's this? You know, I mean it's, it's a little bit convoluted for them. What they've done is they've really done a fantastic piece of work with Gen AI to showcase, to take all the information that's on its dashboard and put it and generate a report from that information. Very discernible. So like it's literally two pages and you kind of go, this is all I need. And this really. And it really, really works. And that's something that's really interesting as well. Real estate itself, you know, you go into different aspects of this, like, I mean, blockchain. I know we joked about it earlier saying like the peak of inflated expectation, it really hasn't taken off the way it has. But smart contracts, which is an element of a blockchain, are we going to see an evolution of that becoming a much stronger element of a real estate transaction? I firmly believe we are. You know, it's really going to kind of delve into that in a much bigger way. It's going to take time. A little bit like the same way as Docusign, you know, it took time for Docusign for us to embrace that. Now it's kind of standard practice. But for a long time people were kind of not doing this. This isn't work for me. You know, it just, it just didn't sit well with them more than anything else. And now, now It's a case of why didn't you send me a docuSign? It's so much easier. Yeah. All right. It beats. It beats a PDF, doesn't it? You know, everybody trying to, you know, print it off, look for printer signs and scan it back in. All right. And then it becomes part of the process. And that's when a lot of these things are going to happen. You know, we'll think that, you know, we're just going to not engage with them, kind of be scared of them, worried about them, and then suddenly it's just going to become part of the process and we're not even going to think it's even technology anymore. Yep. So AI, I think the advancement AI is going to be the real driving one. We're definitely going to see a huge amount, I think, a drive in construction tech. I know it's not necessarily what a lot of reader or the listeners are kind of big into, but the advancements in 3D printing, the advancements in modular prefabrication, they're an essential component of the business because construction and development has just got so expensive. It's not just about the financing of buying the site and making that work. Supply chain issues, material issues. It's so expensive even to build these days with the way things are. So we need advancements in that from so many levels, from an affordability standpoint for. To make kind of these things work and that, you know, we need to drive that, embrace that and take that on and figure out where the roadblocks are that are kind of causing the issues with driving and those new, those new elements of construction into the system. Because, you know, I joke about this all the time. Like, I mean, if you look at a construction site back in 1986 and you look at one now, right, Bar the foreman with an iPad in his hand, what's the difference? Yeah, right. It kills me. It's just so wrong. It's so ripe for change and innovation and it needs it. Right. And I'm not trying to get into a situation about jobs or I'm a big believer that technology and innovation helps jobs and it drives jobs more than more than. It reduces labor. So, yeah, you know, I'm a big believer in that as well. So. But I think all those areas are going to see real change in the next, you know, two to two to five years. To the point that in five years time, we won't even recognize that these are their changes. They're just part of the system. Part of how.

Yeah, it's almost as, almost as if we, we've always had it.

Yeah. Yeah.

Well, that's brilliant. James, I want to thank you for joining us on the podcast today. If people want to get a hold of you, if they want to find you, look you up, where can they, where can they search you out?

Sure. I mean, I have a, I have an open door policy where I work. I mean, so it's just people calling to me or getting in touch with me at any time. But you can always just email me at jr scottit.edu.

I love it. Well, now you're gonna have people showing up at your office expecting an open door.

It's my day. I mean, that's, that's. To be honest with you, I wouldn't change it for the world because the insights you get from people, the questions you get from people, that's that, that here's another part that I have to have to talk about when it comes to innovation and technology. And I just going to go back a little bit about this. All right. I remember when we first started looking at AI, one of the first things that people like this back in 2015, people said, oh yeah, this is going to change how brokerage is done. This is the end of the broker. The end of the broker. We're getting rid of the broker. All right. And you know, kind of people love that because, you know, the broker, you know, the expensive part of the transaction. Everybody, right?

Yeah.

But there's a reality to this as well. I mean, all of these technologies have enhanced the broker's capabilities that the broker is actually in a stronger position now than they probably were, you know, I mean, 10 years ago. And you know, there was a couple of studies done that said that, you know, broker was 90% chance that in the next 20 years that they would, they would be gone. We're not seeing that at all. Brokers, human contact and human relationships are such an integral part of real estate. The relationship element and the human oversight. When you're using AI to verify different elements, that's people, people. You know, there's a lot of worry that, you know, a lot of jobs will be lost. Jobs will be lost in certain areas where they're probably redundant, but they will be created in new areas. Yeah. And the humanistic, the human element of, of embracing these technologies to, to, to extract the value and the efficiency is, is a huge part of that. And real estate is still a people business. No matter if you're a broker, a property manager, an asset manager and finance, it's still about the network and the connection that people have by, by coming together, building out ideas, seeing what works, seeing what doesn't, and driving everything that they do forward in a number of different ways. So, you know, that kind of is why I have the open door policy, because that's what this is all about.

Well, James, thanks again for joining us. And for all of you listening, thank you for tuning into another episode of Heading West. And we will see you again next week.

Bye, guys. Great to meet you.

Thanks, James.