Trust in AI has a price

Transcript:

Amy Gromowski:

Businesses should be using AI to empower them. Let AI handle the heavy lifing of data processing, for example, and humans can provide the final verification, the context, the empathetic customer service.

Maiclaire Bolton Smith:

Welcome to Beyond the Buildings by Cotality. I am your host Maiclaire Bolton Smith, and I'm just as curious as you are about everything that happens in the property industry. On this podcast, we satisfy our collective curiosity, explore questions from every angle, and look beyond the obvious. With every conversation, we illuminate what is possible. Artificial intelligence is no longer a novelty. It's a core part of the home buying journey. In fact, three quarters of buyers now assume AI is working behind the scenes, touching everything from property searches to mortgage quotes. That's according to our new report, AI and Housing 2026. That same report reveals a startling paradox. While adoption is high, trust has fallen off a cliff. So what's causing this trust deficit? To help us understand what home buyers are now demanding from housing ai, we have totalities head of Data Science, Amy Gromowski on the show. Amy, welcome back to Beyond the Buildings.

Amy Gromowski:

Hi Maiclaire. I always love to be here.

Allie Barefoot:

Before we get too far in this episode, here's a friendly reminder about how to see what's coming up next in the property market. To make it easy, we curate the latest insight and analysis for you online, find us using the handle @Cotality on all of our social media channels. But now let's get back to the show.

Maiclaire Bolton Smith:

Okay. Well, you and I have talked AI a lot in the last couple of years, so I'm excited to dive into this one because AI is everywhere now, not just in housing, but today we specifically want to talk about housing, but our new report shows that trust is actually retreating. So what's driving this new disconnect that people are no longer trusting AI?

Amy Gromowski:

Yeah, that's a big question, isn't it? Our report shows that while home buyers assume AI is part of the process, their trust in it is surprisingly low. I agree. So the data points to a few key drivers of the disconnect. First, there's a significant fear of unverified information. So our survey found that 64% of home buyers are concerned that AI is just recycling unverified data. So that's number one. Number two, there's just a massive verification burden. So a staggering 68% of people feel the need to double check AI provided information. So they're getting information, they're assuming AI is underneath it, but they feel they need to double check it. So when you have to verify everything, you're not really saving time or effort,

Maiclaire Bolton Smith:

Which

Amy Gromowski:

Erodes the trust in the tool. And then finally, we just as people are less forgiving of machines, we're less forgiving of ai. So we found that 70% of buyers would lose trust in a website after significant AI error compared to 60% for similar error from a real estate agent. So that's the trust gap, and it's really at the heart of the disconnect.

Maiclaire Bolton Smith:

That trust gap is really interesting because I mean, I think it says a lot about human nature that you're more inclined to forgive or be okay with a mistake that a human might make, but we expect so much from machines and we expect AI to, well, I guess we kind of expect it to not be perfect. We don't trust it. But you would think that AI and machines are designed to not make mistakes, whereas humans, we're all human, we're allowed to make mistakes. So why do you think that gap exists?

Amy Gromowski:

So when it comes to ai, if AI is powering a set of transactions, for example, and there's an error, we're assuming that error is prolific versus a human, it's going to be that specific situation or transaction that you're in. So that's one human error versus AI error just could be confounding. And if it got it wrong this one time, we know it's a system behind whatever it is that we're doing. So how many other times are they getting it wrong? I think that's a big part of it that so our data shows that 30% of people are more tolerant of a human mistake while 17% are more tolerant of an AI mistake. I think that's interesting.

Maiclaire Bolton Smith:

Very,

Amy Gromowski:

And the gap exists I think for a few reasons, one that I just talked about. But first, really there's a black box problem. So with a human expert, we can ask them why and they'll explain their reasoning. With many AI systems, that's not always possible. So it can feel very opaque and therefore untrustworthy. Another reason is just this perception of accountability. So we can hold humans accountable for their mistakes, but who do we hold accountable

For an AI error? Is it the developer? Is it the data provider? There's ambiguity there that makes people uneasy. Who am I going to go to when I need to understand or have a conversation around air? And then lastly, we've talked about this before you and I, but the home buying process is deeply personal and it's a very high stakes decision. So people want empathy and they want nuanced understanding of their situation that we feel that only a human expert can really provide. And that's especially true when it comes to our family safety or when it comes to our financial security.

Maiclaire Bolton Smith:

Right there. Yeah, definitely. And really, I mean, I think the way of the future is it's a combination of the two that AI is part of the process, and I think you've actually found that people are willing to pay extra to have a human double check what AI is telling them. So I guess how is that desire for this human verification, how is that actually helping businesses right now? I mean, I think it's proving that AI is not going to take all the jobs away. The people are still needed, but how is it helping businesses?

Amy Gromowski:

Right. This is a fascinating finding, isn't it?

Maiclaire Bolton Smith:

Is, yeah. The fact

Amy Gromowski:

That 44% of buyers are willing to pay a fee for human verification of AI is a huge opportunity for businesses. You're right. It highlights that the value isn't just in the AI itself, but in trustworthy application of AI. So this is a winning formula for the human-in-the-loop model. And we talk about that, right? The human in the loop is really important. So instead of replacing human experts, businesses should be using AI to empower them, let AI handle the heavy lifting of data processing, for example. And humans can provide the final verification, the context, the empathetic customer service. So it really should be a best of both worlds model

Maiclaire Bolton Smith:

And

Amy Gromowski:

Not only build trust with AI and with human, but create a premium service. That's what businesses should be thinking about, a premium service for customers,

Maiclaire Bolton Smith:

And

Amy Gromowski:

They're willing to pay for it.

Maiclaire Bolton Smith:

And it's great to have data like this to actually show that and to show. Do you think though we'll ever see a tipping point where people will get to that point that they will ultimately trust AI more than they trust people?

Amy Gromowski:

I do. I think we'll get there, but it'll be a gradual process. We have to build our trust, we have to build our comfort over time. It's not going to happen overnight. And it will require a system that's built on transparency and reliability, and that takes time. It takes time to feel that, to build trust with the information you're getting through transparency and also through consistent use of ai and seeing that we can trust it from a reliability perspective for people to trust without manual verification, they'll need to see that consistent track record of accuracy, especially in these high stakes decisions.

Maiclaire Bolton Smith:

Yeah, it'll be really interesting to see how, I mean, it's taken us a long time to get to this stage with ai, so it'll show how it'll continue to evolve in time. I think one other thing that was really interesting in the findings that you had, Amy, was that surprisingly, the younger tech savvy buyers are actually the biggest AI skeptics. So I think some people might think the Gen Z, the new generation that are moving into the home buying phase, they've grown up with technology their entire lives. You and I have talked about this before, your children are in this group and they've always had technology, but it's that group that are the most biggest skeptics. Why do you think that is?

Amy Gromowski:

Yeah, I've given this a lot of thought. I find this really interesting as well. And if you think about it, I do think it makes sense, right? So younger generations, they are digital native, they've grown up, you just mentioned like we've talked about with really AI at their fingertips. It is interesting. My 16 year old, even though for us, it's only been a small period of time for him with Chat GPT coming out three, four years ago now, he can't really remember a time before that, which is interesting because the complexity of the work he needed to do looked different. And as the complexity of his work has grown, he's had AI as this tool, kind of like the calculator. So he doesn't really even remember a time without it. So they are digital natives and they've grown up with this technology, but they're not really passive consumers of it. They're more sophisticated users. Therefore, I think they understand that algorithms have biases and that data can be flawed. So their skepticism, I don't think is a rejection of ai. I think it's a demand for better ai. Their expectations are higher. That's really how I interpret that. So I think that's right, while older generations, older generations are more likely to use AI tools, but they're also more likely to question. So their demand for transparency is really a sign of their engagement and their desire for more equitable and trustworthy AI future.

Maiclaire Bolton Smith:

Yeah, no, it's so interesting. Well, I guess too, when we look at AI influencing expenditures, things like setting mortgage rates, buyers are asking for the industries to slow down a little bit on that. So can we talk a little bit about that hesitancy that you've uncovered with this report as well? This is fascinating data.

Amy Gromowski:

It does show that there's a significant level of discomfort with AI's role in financial decisions. So just a couple of stats on that, right? Nearly half of the buyers, 49% said that AI driven fluctuation in rates would make them feel insecure about their financial stability. And 46% find automated AI valuations without prior approval to be unacceptable. So

I think this hesitancy is really rooted in a fear of losing control. And again, back to lack of transparency. They need transparency. It's a major financial decision, and it's about their stability and it's about their family's future and wellbeing. So this has a profound impact on people's lives. If AI can change a mortgage rate on a home's valuation without a clear explanation, that's definitely introduces a lot of instability and potential unfairness. At least the perception of that is definitely understandable. So I think we all need to be very aware and cautious as an industry around this dynamic and ensure that when AI is used in financial context, it's done so with full transparency and really clear avenues of recourse and review. Where's the human in the loop on that?

Maiclaire Bolton Smith:

And that theme of transparency is a big one here that I'm hearing over and over here, Amy, and I guess people want to understand what is happening under the cover, what's happening behind the scenes. So what do you think good AI transparency actually looks like?

Amy Gromowski:

Yeah, transparency really has several layers to it. So the first layer is disclosure. We know that 37% of people from our survey believe AI labels should be required. People have the right to know when they're interacting with ai. So for example, in our appraisal space where for appraiser software, we have a great chat bot that's available 24 hours a day to appraisers to ask questions. And we, we've received very good feedback around this chat bot not having to wait to call and talk to human, but it's very clear disclosure that you are engaging with AI and there's inability to talk to human and put your questions in the queue, which comes to another aspect of which is human in the loop. We want to be users of ai, want to know that there is a human that they can talk to to appeal AI's decision, right? And that there's a human being on the other side overseeing it.

Maiclaire Bolton Smith:

Another

Amy Gromowski:

Aspect is explainability.

Maiclaire Bolton Smith:

It's

Amy Gromowski:

Not enough to say AI made a decision. It also needs to explain why it made that decision. A great example of that is in our mortgage space, we have a fraud risk score, and it's a pretty sophisticated pattern recognition based on a lot of different data on flagging where applications may have fraudulent information. There are just aspects to it that have some odd patterns

In order to give the user of that fraud report. Why was this flagged? We're always giving like, here are the things that triggered this to become a high risk application that should be reviewed. Again, a human in the loop. It's not saying decline this application. It's just saying you may want to take a look at it. So we get back to the human in the loop and there's explainability in terms of giving the mortgage underwriter some insight into what is going into a high risk score. That would be another great example. And then the third aspect to transparency is really providing access to the data and giving insight into where the data is coming from.

Allie Barefoot:

The

Amy Gromowski:

Survey found that 64% of buyers are concerned that AI is just recycling unverified information. We do this all the time in terms of some of the AI we use is helping appraisers or real estate agents navigate forms. They can use AI and talk to the application to help them get to the right part of the form. We're using image extraction information to populate, auto-populate, and give some time saving in property characteristics and measurements. But there's always this ability, again, to the human in the loop for the appraiser to flag something that maybe has an error. There's that feedback loop that comes back in to flag that. But I would say our underlying property characteristics is multi-source. There's very complex algorithms behind that to verify that information. And we're always serving up that information with full transparency on where it's coming from, the confidence that we have in the accuracy of it because of so many different assets that we have. And then again, the human in the loop to be able to override that as they verify the information that is coming up and that information coming back into our systems

Maiclaire Bolton Smith:

In

Amy Gromowski:

A self-healing, self cleansing way. So I know that was a lot of detail, but those are the aspects that are really important and Cotality just fully embraces each and every one of those.

Maiclaire Bolton Smith:

Yeah, that's great.

Allie Barefoot:

It's that time again, Cotality just dropped new numbers about what's happening in the housing market. Here's what you need to know. The traditional leap from renting to home ownership is fracturing. While US home prices have climbed a staggering 135% over the last 15 years. Skyrocketing rental costs are locking aspiring buyers out of the market entirely. Today, rent consumes 39% of the average renter's budget, which is eight percentage points higher than what homeowners pay towards housing. And that's even after rent prices jumped 30% over the last five years alone. And despite the media spotlight on large Wall Street institutions, it's actually small mom and pop investors who are driving the shift. Landlords with fewer than 10 properties bought 20% more homes than they offloaded last year. Even more significant, 40% of these small scale investors hold their properties for a decade or more, allowing them to influence rental rates long-term because price margins are tight for small time landlords, systemic hurdles like high interest rates and rising home insurance premiums are passed directly to tenants. And unfortunately, even when those costs stabilize, the savings are rarely passed back to the renter, leaving them priced into place. To explore the data behind the investor footprint in your local market, go to Cotality.com/insights and that's a sip. See you next time.

Maiclaire Bolton Smith:

Well, Amy, you've been here enough to know that I like to finish these podcasts with, pull out that crystal ball of yours, and really what we're saying now is trust has become a product. So what's the number one thing that companies need to be thinking about right now to win that trust?

Amy Gromowski:

I would say to tie back to what I just said, embrace the human in the loop model.

The data from our survey is overwhelmingly clear on this point. People are not ready for fully automated home buying experience. They want the power of ai, but they want it combined with the expertise, empathy, accountability of a human professional, a human professional who is trained to do what they're doing. And there's a lot of human professionals throughout that end-to-end value chain of finding, buying and ensuring a home. So I really think the winners are companies that don't just try to replace the humans with ai, but companies that make the human experts the superhero, right? We talk about what AI should make the human experts the superhero, and I think those are the companies that win.

Maiclaire Bolton Smith:

Well, Amy, this has been so interesting. Thank you so much for joining me today on Beyond the Buildings by Cotality.

Amy Gromowski:

Thank you Maiclaire.

Maiclaire Bolton Smith:

Well, I know you'll be back again soon, so thank you for listening. I hope you've enjoyed our latest episode. Please remember to leave us a review and let us know your thoughts and subscribe wherever you get your podcast to be notified when new episodes are released. And thanks to the team for helping bring this podcast to life producer Jesse Devons, editor and sound engineer, Romeo Roman, our fact guru, Allie Barefoot and Social media duo, Sarah Buck and Mikala Brooks. Tune in next time for another conversation that illuminates the ideas that will define the future.

Allie Barefoot:

You still there? Well, thanks for sticking around. Are you curious to learn more about our guest today? Amy Gromowski is the Head of Data Science at Cotality, leading teams of data scientists and machine learning scientists in developing artificial intelligence and machine learning solutions, including computer vision and generative AI for property related solutions in the real estate, mortgage and insurance markets. Over the course of her career, Amy has held various AI related roles, including data scientist, client, executive analytics, product manager, and most recently as a leader of AI slash ML business development. With 25 years of experience, Amy enjoys working with C-Suite leaders on AI slash ML strategy, technology leaders, product leaders, and clients to innovate in the property ecosystem.

‍