AI is changing how rental businesses run, and most of the conversation about it is still stuck on which tool to use. Net Effective: The Rental AI Show goes somewhere else.
Hosted by Jonas Bordo, co-founder of Dwellsy and a 20-year veteran of the real estate space, this weekly series sits down with the owners, operators, proptech leaders, and advisers actually putting AI to work across multifamily and single family rental. They talk about what AI has saved them, where it's flopped, and what they're building next, all in 30 minutes or less.
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Title:Before you make your next decision, ask AI this
"What is it we should be looking at? What is it we should know? What is it we need to do given what's in front of us?"
That's Robert Salwasser on the question AI is forcing real estate owners and operators to ask.
Robert is the founder and president of Income Property Specialists (IPS), where he has spent nearly four decades helping individual investors and family offices manage and grow their real estate portfolios. He co-founded IPS in the mid-1980s after studying economics and law, initially representing Bay Area landlords in property tax appeals and rent control hearings. He also developed an early web-based MLS for income property.
Today, Robert leads IPS with a focus on combining first-class property management with investment profitability and cash flow. He also serves as a Multifamily Venture Partner at Shadow Ventures, sits on the Executive Council for Multi-Housing News, and serves on the Advisory Council for Blueprint.
Robert and Jonas get into a central question for anyone managing or investing in property: what happens when AI can bring together all the information about a building and identify things you did not know to look for?
In this episode
From property management to asset management. Robert explains how IPS is evolving beyond traditional property management into asset management, with AI providing a new ability to bring data together, ask questions, build models, and look for things the team may be missing. For Robert, the opportunity is not simply more technology. It is improving the odds of success for the owners and family offices they serve.
AI is still in kindergarten. Robert describes today's AI as being in "kindergarten or first grade," while pointing to companies such as Palantir as being much further ahead. He believes the real transformation comes when AI can move beyond analysis and start understanding and interpreting information well enough to make decisions. He is interested in what happens when AI, computing power, and robotics develop together.
Why AI could change the way you diagnose a vacancy. A vacant apartment does not necessarily mean the rent is too high. Robert describes how AI could look across rental data, tenant information, maintenance records, and other factors to identify the real reason a unit is sitting vacant. If maintenance is taking six days to complete work orders, for example, lowering the rent may be solving the wrong problem.
The power of seeing the whole picture. Robert sees the greatest opportunity in bringing together information that traditionally sits in separate places. Leasing data, tenant longevity, rents, demographics, employment, maintenance, expenses, and other property information can all contribute to a much more complete picture. The challenge is making sure AI interprets that information correctly and combines it with the experience and judgment of people who understand the business.
Exception management and missed revenue. One of Robert's most compelling examples is AI reviewing leases and rent ledgers to find missed opportunities. If a lease says a tenant has a pet and should be paying a pet fee, but that fee never appears on the ledger, AI can identify the discrepancy. Run that process regularly across thousands of units and small missed items can turn into meaningful improvements in revenue and net operating income.
AI that tells you what needs attention. Robert does not want another report sitting in an inbox. He wants software that monitors the business, identifies something important, and alerts him. He gives the example of tracking an underlying interest rate index and receiving an alert a year in advance when a property's mortgage costs could become a problem. For him, the next step is AI that takes action when it sees something rather than simply producing paperwork.
Why the right question matters more than the data. Robert returns to a lesson from a business class he took years ago: everyone wants data, but the real question is what that data is telling you. Forty years of experience can provide context that a number on a spreadsheet cannot. Robert's concern is that AI may have access to enormous amounts of information without yet understanding the context required to interpret it correctly.
Robots are coming too. The conversation moves beyond software into robotics. Robert sees robots eventually handling repetitive physical tasks such as vacuuming hallways, landscaping, painting, and construction work. He points to Amazon warehouses that can operate without lights because robots are doing the work and argues that the implications for property operations and labor could be enormous.
What AI can uncover that you do not know to look for. For Robert, one of the biggest benefits of AI is discovering things that would otherwise remain hidden. Instead of having people spend hours going through paperwork looking for anomalies and errors, AI can do the initial investigation. The condition is that the data must be good, the system must be trusted, and sensitive information must remain private.
AI and the move toward predictive asset management. Robert is experimenting with simulations and looking at how AI can help owners think further ahead. He wants systems that can monitor factors such as interest rates, rents, and lease terms and show owners where they are likely to stand a year from now. The goal is not perfect prediction. It is getting enough advance warning to make better decisions.
Don't build an expensive AI tech stack just because you can. Robert's advice to people getting started with AI is to learn the technology and become comfortable using it, but avoid chasing every new product. He warns that it is easy to end up with eight different companies doing eight different things, while the owner is simply paying for an increasingly complicated technology stack. Every tool needs to have a clear payoff for the management company or the property owner.
Why Robert is moving from Google to Perplexity. In his personal use of AI, Robert says he is almost done with traditional Google search and has moved toward Perplexity because he likes getting sources with his answers and does not feel he is simply being directed toward paid links. He also uses Claude Pro to test ideas and explore different possibilities. His advice is to be explicit about what you want, ask for reliable sources, and tell the AI not to make things up.
The AI aha moment is getting bigger. Robert says his realization about AI has not been one single breakthrough. Instead, it has grown as he has understood more of what the technology can do. AI is forcing him and the industry to step back and ask better questions about what they should be looking at, what they need to know, and what actions they should take. He sees tools such as Yardi's Virtuoso opening up a future where owners and managers can simply ask questions of the huge amounts of data already sitting inside their property management systems.
Mentioned in this episode
Robert Salwasser · Income Property Specialists (IPS) · Shadow Ventures · Palantir · Claude · Claude Pro · Perplexity · Yardi · Yardi Matrix · Yardi Virtuoso · Dwellsy · Google · Waymo · Amazon · Multifamily · Asset Management · Property Management · AI Agents · Robotics · Rent Control · Net Operating Income (NOI) · Debt Service Coverage Ratio (DSCR)
Net Effective is a conversation with the people running residential rentals about how they are actually using AI. New episodes weekly, about 30 minutes. Subscribe at neteffective.show.
I think AI is kind of in kindergarten or in first grade. And I think the Silicon Valley company, Palantir, they're probably in junior high, high school with what they're doing. But we haven't gone far enough in time, computing power, I guess, along with just learning how the systems work, that when we get into grad school, that's when it's a completely different world. You've got to be very careful about the tech stack you create. And pretty soon you've got eight different companies doing eight different things for you. And the next thing you know, everybody's making money but the owner, because it's just tech stack paid, paid, paid, paid.
SPEAKER_01
That's Robert Sawwasser, founder and president of Income Property Specialists. And I'm Jonas Bordeaux, CEO and co-founder of Dwellzi. This is NetEffective, the Rental AI show. Robert co-founded IPS in the mid-80s. So he's been at this for about 40 years, managing Silicon Valley apartments, self-storage, and commercial properties. He started off representing Bay Area landlords in hundreds of property tax appeals and rent control hearings, and he built one of the early web-based listing platforms for income property. He's been building with technology in this industry a lot longer than most of us. Robert, welcome.
SPEAKER_00
Thank you.
SPEAKER_01
40 years in the middle of Silicon Valley. Tell us about IPS. You've got to be at the center of so many interesting things.
SPEAKER_00
IPS has been evolving over the years. It started with me leaving law school and doing rent control representation for landlords that fell into kind of property tax appeals up and down the state of California. And then my clients, after I raised the rent and reduced their expenses, said, go ahead and manage the thing. So that's off we went. So it's been building over time. We've got kind of a specialization or a focus on multifamily. That's where most of the portfolio is. That's where my heart is with that. My parents had owned a couple of small buildings, and it's just evolved over the years. And what's been interesting has been the technology that has gone alongside us, starting with, you know, I was around before the internet and had a bulletin board service, the income property listing service. And then LoopNet and others came around and put that out of business. And so now we're into the world of AI, which is a completely different animal.
SPEAKER_01
Yeah, it is a completely different animal in so many different ways. It's been fascinating to see how it's transforming property management. Where are you seeing the biggest impact of AI so far in your business?
SPEAKER_00
Some of my staff members are using it independently. My CEO, he's using it to go ahead and plan his day. So he's got connectors into his Gmail account and calendar and that through Claude Connectors. And he's using it on a daily basis for that. Other staff are starting to learn it and taking on minor projects like that. Company-wide, in terms of what we bring forward for clients, we're starting to move from just the commodity property management firm into asset management. And that means bigger issues, bigger projects, more from an investment side. That means more analysis. And instantly AI brings forward that capability where you can bring data in from all different sides. You can go ahead and ask it questions, and also you just build models for that on what's important. What does AI see that we may be missing? So, in that regard, I've mentioned in the past to others that I think AI is kind of in kindergarten or in first grade, right? And I think the company, the Silicon Valley company, Palantir, they're probably in junior high, high school with what they're doing. All right. But we haven't gone far enough in time, computing power, I guess, along with just learning how the systems work, that when we get into grad school, that's when it's a completely different world. And alongside the AI come robots, and that's going to change the world as well. KP Reddy, that I had worked with at Shadow Ventures and that heard him speak a while back, and he said, You guys think AI is going to change the world. Wait until you hear about robots and what they're going to do. And once the robots start making and repairing robots, it's a whole different world there. So all of this is coming at us in tandem now. So in terms of AI, I've taken a step back and now I'm learning, I'm researching. I'm talking to a little bit of everybody. I'm on LinkedIn pulling models and forms and things, just trying to find out what the capabilities are. I don't want to rush headlong into it because we all know that AI comes with its own issues of trustworthiness. Privacy is an issue, and what data is good and what isn't good. The advantage that I'm hearing with IPS is we've got data going back 30 years on some of the properties because I've been in business that long. And lucky enough the clients have been with us that long as well. So we've got the data, we can see the trends over time, which is crucial and vital, but it's a different world now. And what AI may be looking at is hasn't been trend or put on a trend line. In the last few years, we've seen insurance go through the roof. Property taxes, they're adding more direct assessments onto property tax bills. That kind of came out of nowhere maybe eight, 10 years ago. We're also looking at interest rates, obviously, going up. And we recently had an event that Bay Area, that IPS sponsors, holds an event. It's called the Bay Area Apartment Alliance. We had an economist, gentleman from Derivative Logic dealing with derivatives on setting forward on rising interest rates, how owners protect themselves. And everybody's viewing that interest rates are just going to continue to go up and stay high for a period of time. All sorts of economic reasons behind that. So all of this complexity going on, it's not only tough to keep track of, it's tough to quantify and to pull from when you're looking at the numbers of an apartment building that changes every month. Rents up, rents down, expenses up, expenses up. And then you've got the technology floating around all behind it. Some of it very good, some of it not so very good. And so it just seems like I don't want to say we're in a state of confusion, but we're in a state that there's a lot happening and it's trying to get the chaff from the wheat. What is it that's going to be the best use of this? What's going to be, as you had mentioned, what's most valuable? What's most valuable to the clients, the family offices, um, the people that we work for? What's going to improve their odds of success in owning an apartment building versus others?
SPEAKER_01
Yeah. You know, that complexity that you're noting really resonates with me because I feel like we're at a time of extraordinary complexity. I feel like the business perhaps used to be a little simpler. See if you can get market rents, you know, keep the residents happy, see if you can get them to renew, and everything worked out pretty well. You know, uh watch out for the water. Uh you always have to watch out for the water. Uh but you know, I I do feel like just to be an average performing property manager today, you need to master a level of complexity that's well in excess of anything I've seen in my career to date. Do you think AI can help folks in handling that complexity?
SPEAKER_00
Oh, definitely. You know, in years past you'd look at a couple of vacancies and you go, well, let's drop the rent, right? But now that's not necessarily the first thing you want to do. And in our case, because of rent control in the Bayer, it's the last thing we want to do and set the base rent lower, right? And then you're struggling to catch up with the rent. So one of the things AI does, it looks behind that. It goes into the numbers, it goes into the data, and it says, oh, okay, you've got a couple of vacancies. Well, why are they vacant? Is there a common reason that everybody's complaining that the rent's too high? Do you have an unemployment issue going on in the area, right? Well, San Francisco and Silicon Valley doesn't have that. Rents are up. I think I last saw from Yardy Matrix 8% in San Jose, probably 20, 30% in San Francisco. Thank you, AI. But you know, we go up and we go down in the Bay Area too. So, and looking at all of that, what's the main reason? Well, maybe it's not so much the demographic of it. Maybe it's because that your maintenance team is a little slow and forgot to complete a few items. You know, and the number one reason tenants become unhappy is with maintenance on an apartment building. So AI goes in, pulls out. Well, okay, these units have had an average of about six work orders each, and it's taking you six days to complete them. All right, we've got a problem here that just reducing the rent won't solve. We've got an inherent process issue that needs to be fixed. And that's what the advantage that I see AI, it can bring in the total picture of everything. Why I said earlier that Palantir is way far ahead is that when the Biden administration was leaving Afghanistan, they contacted Palantir and said, Help, we need to get Americans quickly out of Kabul. We need to get them out of Afghanistan. Palantir went in and said, fine, I don't know how much money they made, I'm sure it was a nice sum. But they went in and discovered that there were about 120, 150 agencies and organizations that had and were serving Americans in Afghanistan. And so Palantir said, We're going into all your databases, we're going to lump it into ours, we're going to do our magic in that, and we're going to find out who's American, who's not, who should be coming back to the U.S. And then we're going to coordinate the airplanes, the supplies, the fuel, everything in the background with AI. And I think I read at some point Pellenter was so successful that they were applying 75,000 Americans a day out of Afghanistan. They didn't have that much time to do it. But can you imagine just the logistics of having planes land and take off and fuel and have them at the airport and try to have them vetted and going? No kid with a spreadsheet can do that. Right? That's what I see going forward. That when you're looking at leasing, you're pulling in from Craigslist, from Dwellsey, from others. You're talking to your current tenants, you're seeing what the longevity is of your current tenants and what their rent increase is and what they're paying for rent. Maybe you dig into the background. What's the demographic? What's the employment of the individuals that are staying the longest? And all this data comes at you. My concern and why I'm I'm taking it kind of slow is okay, that's data. Am I interpreting it correctly? Is AI interpreting it correctly? Right? Years ago, I had a business class and uh the instructor in front of the room said, You guys are telling me you all want data. You all want data for your businesses. Okay, the number six, there's your data. Now, what are you gonna do with it? What's it telling you, right? Yeah. So so the guys with 40 years experience in that kind of know from knowledge and experience before we had all this technology. No, that may not be what that number six really means. This is what it really is. It's three sets of twos, right? So the concern that I have is we get more AI, the computer is not yet there. It's in kindergarten first grade. When it gets into grad school, it's going to understand and interpret those numbers and make the decisions, right? That's the beauty of technology. That's also the fear of technology, especially in my industry, where already technology can collect your rent. The technology can take a work order and send a vendor out. The technology is not there yet, that when they don't pay, you go ahead through the process, prepare the three-day notices, and send them out to the tenants. We're not there. So I'm I'm looking at this on what are the agentic uses of AI? What's actually the work that's going to produce, not just the analysis? Because I think the analysis will come, but the analysis has got to be augmented with people and backgrounds and knowledge and just asking the right questions.
SPEAKER_01
Yeah, I agree with that. I think foundationally it's such a challenging thing to sort through all the data with the context that is necessary and the gaps in information about properties that exist. There's so much that has not been digitized and may never be digitized. So, in that context, how can you rely on the machine to make good decisions about the data that you've got? But then when it comes to operational activities, how can you get it to help with serving those three-day notices with doing other things along those lines? Where are you seeing it going? If we're in kindergarten or first grade from an analysis standpoint, uh, where do you think we're going to see the next big push?
SPEAKER_00
I don't know, to be honest with you. You can't tell the future over? No, not yet. Let uh AI do that in about six years. Um I see most of the value in the agentic AI, right? There are already services out there that you could send at your lease agreements and your rent ledger. And we're looking at this as a solution too. And when you get up to the when you're starting to manage thousands of units and you're bringing them in and you've got people coming in and out all the time, not to mention you've got leases that are constantly changing because the state of California and cities and counties and insurance companies and everybody wants to have a hand in the management of an apartment building, and you've got all these changes. So being able to send all your leases to a service and have it come back and go, hey, Robert, on apartment 101, the tenant signed up that they have a pet and you're going to be charging them $50 for a pet fee. We don't see it on your ledger. So the advantage there is missed opportunity. Ah, okay. People make mistakes, they take a look at the lease, they overlook the pet fee. This is a new property coming in for management, and that fee doesn't get paid for a while until somebody stumbles upon it. No, no, no. Run the AI monthly, run it quarterly, whatever you're going to do, it'll find it. That's one of the advantages. That puts us beyond kindergarten. That puts us into the early grades, right? Now it's actually helpful, and now it's actually moving the property forward in terms of revenue, in terms of net operating income. Net operating income is everything right now on an apartment building. You've got debt service coverage ratios that will start to be followed through with AI. It'll look at the note, look at the loan documents, conversation with the lender. What are you expecting on debt service coverage ratio when we go have to go to refinance in the next year or two? And having to watch that number. So all the firepower we can throw at analyzing that and finding where the breakdowns and opportunities are is crucial. It always has been crucial. Now it's more crucial.
SPEAKER_01
Yeah. I think that's fantastic. It's one of my favorite uses of AI just more generally, is that kind of exception management.
SPEAKER_00
Yeah.
SPEAKER_01
If you will, finding that one off, you know, whether it's financial report, uh asking it to look for things you may have missed, that obscure fee, if you will, the debt covenant that could get triggered and nobody saw that coming because nobody looked at that document for a year or two. I love it for contracts. What are the non-standard terms in this contract? It's one of my favorite questions to ask the AI and see what it kicks back. But I think that's a fantastic use case.
SPEAKER_00
Yeah.
SPEAKER_01
Yeah. So you mentioned robotics. What are you hearing about there? What's next on the robotics side? Because I'm talking to a few folks in the industry, I'm seeing AI just finally unlock the mechanics of robotics in a way that we haven't seen before. Is that something you all have experimented with, or is it just conceptually out there?
SPEAKER_00
I'm keeping an eye on it. So the interior hallway buildings, especially those that are carpeted or even those that have been tiled, right? They've got to be cleaned. Roomba is a mini-version of what can actually be used. So we're not spending time with either outside janitorial or with the onsite managers and staff vacuuming. We open a door, let the robot vacuum out, maybe until they learn how to use an elevator or climb stairs, they're going to have one on each floor and it's just going to go in and vacuum and just be an ongoing concern. There are robots now that can go ahead and put up sheetroth, tape, texture, and paint. And there's an example of robots that are actually in use now doing that. And the building owners go, guys, why would I pay this much money to rent these machines? I mean, I can have the guys do it for probably a third of the cost of your robots. Yeah, but you guys don't work 24 hours a day and can work in the dark. And that's it. And robots are coming. I have a good friend of mine whose son is a logistics manager at Amazon, and a number of their warehouses do not have the lights on because there are no people in the warehouses. They're saving all that energy. That's wild. Because the robots are running through and they don't need the light. And that's the type of thing why it could be scary going forward. Landscapers. There's automatic rowers now. They're being used for parks and cemeteries throughout the country. They're just now coming on, but some of those manual tasks in that will have an effect. Everybody says that that analysts and virtual assistants overseas in that, that they will be a real target of AI. Yes, they will, but there's also certain parts of the repetitive skills or repetitive tasks that need to be done that a robot can do. When I say the whole world keeps you ready, man, when the whole world changes, when robots can start to build themselves and repair themselves, then you've just got a totally independent crew there. And they don't even need to learn how to drive. They just grab a Waymo van and drive themselves to the job. Whole new world. Yeah.
SPEAKER_01
No, it's going to be a remarkable point when we get to that. Feels like science fiction at this point, but my understanding is it's not that far off. A lot of that capability is there. I know I see Waymo's out around me all day, every day.
SPEAKER_00
Oh, yeah.
SPEAKER_01
Delivery robots out and about. I see lawn mowing robots uh on my street. I have a you know robot vacuum in my house cleaning things up. Um the new ones can climb stairs, the new home ones. I've been one of those. All right. So that's out there. I don't know if that's out there for commercial applications yet, but uh, you know, a lot of interesting, exciting stuff on that side. So, you know, as you think about the application for real delivery of bottom line value for clients, where do you think it is right now?
SPEAKER_00
From a bigger picture, I see it's bringing forward things that you don't ordinarily see. You don't know what you don't know. Now we need to know what's discovered and found for us. We don't need guys going through lots and lots of paperwork looking for the anomalies, looking for the errors. Let the computer do it. And as long as the computer is properly trained and the numbers are good and it's verified and it's trusted, and we've got assurance that what they're finding is truly private and not teaching for others, but it's not being shared, that's where the value really is, is what are the opportunities we're missing, and also the ability to start to predict forward and to deal with that with technology more and more. So I've been dipping my toes in into simulations and other things with apartment buildings. We know, you know, for example, we know where what interest rates you're going to do, right? For the most part. You have a note, it says, look, in year three, you're going to adjust to whatever this index is, plus a margin on top of that, right? Right now, I've got a number of properties that are going from 3% to 6%, 7% in mortgages. The numbers can be huge. I want to know a year in advance. I want to be able to see that and have the software track that underlying index and go, Robert, we've got a problem here. And I don't need it to just print out a report. I need it to alert me. That's a computer taking action when it sees something. And I have a conversation with vendors all the time. Don't just give me paperwork. Just tell me what I need to know, right? Send me an email. Don't make me go click click click all through your program. So in this case, the next step is to take a look at this. And here in the Bay Area, you know, you really can't give a rent increase except every 12 months with all the rent control or even the limitations on a on a 12-month lease. So you know a year in advance what your rent's going to be with pretty good certainty. You know, in San Jose, you're probably going to ask for the 5% increase this time next year on somebody that moved in now, because if rents are going up 8%, we're limited to 5%. You better believe we're going to ask for the 5%, provided maintenance and everything else is doing their job and everything's fine. So that's the next step is taking a look at what you've got now and going, okay, well, a year from now, this is the position we may be in. Now it's not going to be perfect. You're not going to be able to predict the interest rates well, but there's a fundamental shift going on in the treasury and the U.S. debt and government and that that makes lowering rents. No one's telling me that we're going to be at three and four percent mortgages again anytime soon.
unknown
Right?
SPEAKER_00
Yeah, I don't know that we'll we'll ever see that again in our lifetimes. True. Yeah. So that's what the potential, that's what I'm studying, that's what I'm looking for right now. Dipping toes into AI, yes, taking classes on Claude. My CEO and I, Clay, we took a class from Kingo on Claude. We started with one version, and six weeks later we were already on the first or second version after that. It was moving that quickly to do that. So just a whole new world.
SPEAKER_01
Oh, yeah, a whole new world. So, where do you recommend people start if they're just exploring AI for the first time? I know there's a lot of property management folks out there for whom it's a brand new concept. They may be listening to this and hearing about it for the very first time. Where would you recommend they start?
SPEAKER_00
They just got to get comfortable with it. They've got to accept it. And they've got to learn as much as they can and be careful signing up for every new shiny thing that comes along. I'm the worst one. I I go instantly to a bright, shiny object, right? I'm the one that yells squirrel and runs across the street, right? I'm I'm that that guy. Okay. So I have learned over the years, try not to be that guy, because the problem that you get with all of this is a new industry, as a new service coming at us, too. And real estate's very strong on coming in into AI now. You've got to be very careful about the tech stack you create. And pretty soon you've got eight different companies doing eight different things for you. And the next thing you know, everybody's making money but the owner, because it's just tech stack paid, paid, paid, paid going up like that. So you just you've got to be aware of that. And you've got to be aware of what the payback is either to the management company or to the owner. Yeah.
SPEAKER_01
Out of curiosity, any owners you're seeing out there who are really pushing the envelope on AI?
SPEAKER_00
From the standpoint of their properties, actually, no, I don't. They're aware of it. I'm sure they're using it in their profession. I'm sure they're using it personally and taking on that software, but not from an apartment standpoint. That's what we're for. That makes sense.
SPEAKER_01
That makes sense. So you mentioned uh the personal side for them. What about for you? How are you using uh AI in your personal life?
SPEAKER_00
Well, I'm just about done with Google in terms of search. I I've pushed the move over to perplexity. And perplexity, what I like is that it gives you the sources. And there's no when you ask for you know a suggestion, you don't get links to Amazon, you don't get links to everybody else that have paid to send you links, right? You just get the data. And then along to what I'm learning and what I'm using it more, like Claude, using Claude Pro, that subscription base, is using it just to test ideas. What do you think if I do this? What about this? What about that? And then you just have to make sure you tell it. Don't make stuff up. Don't tell me I'm handsome just because you want to please me, right? Just give me what you know, what you can source and see, and go to reliable sources and give me the list of that. So you've got to be very specific in the prompts of what you tell it because it doesn't know the background conversation going on in your head. You've got to be very explicit in that. And that's a different way to interact with a computer and just asking questions.
SPEAKER_01
Yeah, it's so funny. I think we're also conditioned to the very short, brief search without context at Google. And then most of the work comes after you get the result. Whereas now you need to put more work into the beginning, into the prompt, in order to get the right result at the back end, right? You have to be able to give it the context so it can give you a proper result. Google, you want data? Six. Good luck with that. Yeah. Yeah. Yeah. It is fascinating to watch people move away from traditional search. It's going to be very interesting to see how that affects Google in the long run. Because that's such a huge last number I saw, they had something like 93% share of the search market. So what happens if the search market shrinks materially and it becomes an AI-based experience for us?
SPEAKER_00
Yeah. Well, I think I was reading that Google spent like $10 million for the data from Spirit Airlines when they went into bankruptcy. And they claim they're not getting any personal data, they're not getting card report points or anything else. They're just looking at the data of how people move around and what they do and all of that, but they're adding it to their body of knowledge. And that's interesting.
SPEAKER_01
Yeah, it's kind of you go back to the core of where they started, which was indexing, right? That's still a pretty relevant need, even more so in the AI world. So you know, if you have all of that context, what can you do with it, right? That's certainly never going to bet against those guys. Uh smart folks uh with tons of resources. Uh so I guess one last quick question for you. What was your aha moment with AI?
SPEAKER_00
Good question, Jonas. I think it's just becoming a bigger aha over time to see what it can be used for and the capabilities of it. But really, when I first started to look at it probably last year or so, it was interesting, it was unique. You know, everybody was saying you can't trust it, it'll tell you what you want to hear and so on. But as it's developed, it's just starting to take a step back. And it's forcing me, it's forcing us in my business, us in the industry to take a step back and go, what is it we should be looking at? What is it we should know? What is it we need to do given what's in front of us? Right. It's no longer you, well, it's always still you don't know what you don't know, but now you quickly have to find that out and take a look at it. Like when you look at a vacancy rate that's going up, the first thing you don't go to is maintenance work orders and see, well, how long are the maintenance work orders taking? Are they completing the job and are they nice to the residents, right? The tax. No, I mean, that's something that's brought forward from an asset management side with further contemplation, with further digging into the numbers, that now the AI will bring that forward. And just the industry going forward, Yardis Virtuoso coming out, I guess, have released it to some beta players. So I think it's coming out in September. And that's just doing like Claude has type your question in. Among the portfolio, which tenants are under eviction? Which tenants have the most money? Are my utility bills going up or down? What are the properties that have a spike in water cost? Is there a leak and all of that capability? And as the technology also develops, the monitoring of leaks and usage and all that, it's just bringing more data into the fold that brings forward probably new ways to take action.
SPEAKER_01
No, that's exciting. Things like Yardi's Virtuoso are incredibly exciting because there's so much data in those systems, and it's been so hard to extract historically, so hard to get to the right information uh in those systems. And so being able to interact with it in a much more intuitive way, I think is going to really blow some things wide open for property managers and owners alike.
SPEAKER_00
Yep.
SPEAKER_01
Yep.
SPEAKER_00
So if you ask what guys new to AI need to know, they need to quickly get up to speed. They need to understand it and start to use it, if nothing else.
SPEAKER_01
Well, Robert, this has been such a pleasure. Thank you so much for coming on the podcast. Really appreciate you.
SPEAKER_00
Thank you, Jonas. Appreciate the invitation.
SPEAKER_01
That's NetEffective. New episodes weekly. If you're running rentals and figuring out AI, hit like, subscribe, follow, or whatever your app makes you do to get more of the show. And if you'd like to come on as a guest or subscribe to the weekly updates, go to neteffective.show. I'm Jonas Bordeaux. Thanks for listening.
