281 Integrating AI into Home Builder Marketing - Kathleen Perley Aug 13 2025

Greg Bray: [00:00:00] Hello, everybody, and welcome to today's episode of The Home Builder Digital Marketing Podcast. I'm Greg Bray with Blue Tangerine.

Kevin Weitzel: And I'm Kevin Weitzel with OutHouse.

Greg Bray: And we are excited to have joining us today, Kathleen Perley. Kathleen is the CEO and founder of DemystifAI. Welcome, Kathleen. Thanks for joining us.

Kathleen Perley: Thank you so much for having me. I'm happy to be here.

Greg Bray: Well, Kathleen, for those in our audience who don't know you yet, why don't you give us that quick introduction and background about yourself?

Kathleen Perley: Yeah, so I am actually a linguist turned entrepreneur. I had an agency in the digital [00:01:00] transformation space specific to healthcare, that I had for about 10 years and sold to private equity. And now I am going back to my first love of AI where I am teaching at the Jones Business School at Rice University, as well as advising the deans on AI. So, it's been a whirlwind and a lot of fun, and I some days miss the digital ad agency space almost so much so that I'm actually back in my old offices once again. So, I'm very excited to be here and kind of nerd out on all the world of AI and how that intersects with digital marketing.

Kevin Weitzel: Before we go super nerdy, I need to know for our audience a factoid about you that has nothing to do with work, family, or your industry that you're in.

Kathleen Perley: I am refurbishing a 1972 International Scout. It is purple. It's really fun. So, that's a fun fact. The other one would be home building. I am building an Airbnb in Round Top, Texas, which is [00:02:00] like a small little town, and it's going to be a Beyoncé-themed Airbnb.

Kevin Weitzel: Okay. Number one, I apologize, I don't know who this Beyonce person is or this thing is, but the International Scout, is this a frame-up restoration, like bolt-up, or are we just talking about just making sure that it runs nice and it's painted and?

Kathleen Perley: More of a runs nice. This summer I'm working on, my husband and I are working on doing a whole new wiring harness on it. The engine's original. We fixed some of the rust, the body work, painted it. We're putting in a stereo system. So, we're not doing like a full, full, full restoration, but at least that was the intention initially. I will say as we've gotten like our hands dirty, it's like, well, we should just fix this and that.

Kevin Weitzel: It happens,

Kathleen Perley: It does happen. It is a money pit for sure.

Greg Bray: But purple?

Kathleen Perley: Purple. It's purple. I got the seats reupholstered. I have the original bench in the back, and I got some more classical-looking seats for the front. And I bought fabric in Round Top because it's a big antique area, and it's like [00:03:00] brown leather with like purple inlay, like interesting fabric in the middle.

Kevin Weitzel: And are we talking like lavender or deep purple, color wheel purple, primary colors? What are we talking about?

Kathleen Perley: No, like purple purple. I'll make sure that you guys can get this photo, but let's see if I can find it real quick. Here you go. It's purple purple.

Kevin Weitzel: Whoa, man. All right.

Kathleen Perley: It is purple purple.

Kevin Weitzel: If that's post body work, that's what you would call a 10 or 20 footer. So, where if you really look at the details, it's not a show car, but from 10, 20 feet, it's impressive.

Kathleen Perley: It's a Monet. Looks really good from a distance.

Kevin Weitzel: Yes. I love it. I love it.

Kathleen Perley: We are actually getting custom plates. We're calling it Grimace.

Kevin Weitzel: I love it.

Kathleen Perley: McDonald's character.

Greg Bray: Awesome. Well, Kathleen, tell us a little bit more about DemystifAI and some of the things you've been doing at Rice University, and why AI is such a thing for you now.

Kathleen Perley: I live in Houston, Texas. I come from a long line of oil and gas folks, obviously. So, you can imagine when I decided to study [00:04:00] linguistics in college, the fear that overcame them in terms of like, what are you going to do with a linguistics degree? We wanted you to be an engineer or in finance, like what are you doing? I really loved it, and actually, I got into marketing and advertising as an accident.

So, after college, I did a Fulbright on the utilization of phonetics and phonology in second language acquisition. And I moved home, and I had about nine months before my PhD program started. I had a mom from New York, like a true New Yorker, through and through, and she was like, if you live in this house, you have to have a job. And that's why I ended up in marketing and advertising. I fell in love with it because linguistic coding is a lot like computer coding, and so it all started to kind of make sense. And then I started working on schema markups and things of that nature.

And so, now it's like kind of come full circle, which is really fun. And it's funny, my whole family of oil and gas folks, most family dinners talks about, you know, X, Y, Z shale and blah blah, price per barrel. And I was never relevant until like the end of November 2022 [00:05:00] when my dad was like, Have you heard of this ChatGPT? And I was like, this is why my linguistics degree matters, like it kind of comes full circle.

So, now my goal as I work at Rice, I teach a couple of graduate-level courses to the MBA students and I'm helping advise the deans in terms of how they think about academia and how they integrate AI into their organization, not only from a teaching perspective, but their own operations. And it's so fun because as much as I love engineers and coders, I really do think the biggest transformations in AI that we'll see will come from individuals who understand an industry or sector really well, who have enough knowledge of AI that they can see the opportunities where those two worlds converge. And so, my goal is to get people the skills, the literacy, the foundation, remove some of the intimidation, so that they can go and change the world in whatever sector they're in.

Greg Bray: That's awesome. That's powerful stuff. Anytime you use, change the world in a sentence. That's a big deal.

Kathleen Perley: Yeah. [00:06:00] You know, it's funny because, you know, as a serial entrepreneur, of course, like I couldn't just teach, I started another business. And we're focused on AI and investor relations. And it's really interesting, one of our first clients that we're working with, their CEO is a non-native English speaker, so they have a lot of upspeak in some of their earnings calls, which can be construed as confusion or uncertainty and things of that nature. But it's not that he is unsure as a CEO, it's just English isn't his first language. So, how do you remove some of that subconscious bias that's being held by some of the sell-side analysts from that perspective? So, it's fascinating and, you know, that's just one sector. But there's so many different ways that this can be applied.

Greg Bray: Well, you just came out with a book called AI Made Simple. How do we make AI simple? What is it that you were trying to do there to simplify this for everybody?

Kathleen Perley: I think first and foremost, it's just removing the intimidation factor. Every semester when I teach my grad students, most of them are working professionals or even executives, [00:07:00] and they come into my class and they're like, I really want to take this class. And I'll teach the first course, and one of the first things I do is I'll be like, Hey, this is what we're going to do by the end of the class, like this is your capstone project. And they're terrified.

And I usually have four or five students that come up to me that say like, I think I should drop this class because there's no way I could build an AI wrapper. Like, I don't know how to code, I don't know anything. And I'm like, don't drop, stick with me because you don't have to know how to code. And it's those students that end up developing the best and most interesting use cases for those AI wrappers, and it changes their complete trajectory.

I had one student, and this is kind of nerdy, but he worked for Boeing. And he was working on something very simple. He identified a challenge, right? You need to remove the intimidation factor. And the second thing is you need to really think about what are the friction points in your business. And in his business [00:08:00] working at Boeing and the International Space Station, it's about when something breaks.

They call down to Houston, and the first thing they have to do, and they had some acronym, but it basically means like where the F is the manual that somebody wrote 30 years ago about how this system works. And so he said these manuals exist, the people who built this infrastructures are retiring or no longer with us, now's the time to collect all of that knowledge, that tribal knowledge, if you will, and create a chat bot that can be used in space with references to that specific knowledge base so that we don't have to wait for the communication delay between space and Houston, for example. It's a very simple infrastructure, but it really has a profound impact.

And he actually presented it to his boss and got approval to run the project. And the craziest thing is his boss said, and he told me this afterwards, his boss told him, you know, one of the biggest [00:09:00] challenges we have going to Mars is communication delays as it pertains to life's sustaining support systems. If we can figure this out at ISS, that makes us feel that much more confident if we get to Mars, that you don't have a 20-to-30-minute delay getting a message down to Houston and then back up to space if something is going critically wrong. Because those 45 minutes could be life and death, and so it's so cool.

Kevin Weitzel: Apparently, these people don't know that the average attention span is only like three to five seconds anymore. So, a 20-minute delay is not going to cut it if we send a millennial up to Mars.

Kathleen Perley: Oh yeah, that too. Yeah, a hundred percent

Kevin Weitzel: Gen Z will be like, what? 20 minutes? What do I do?

Kathleen Perley: Exactly. Well, and it's just fascinating. The architecture of what he's building and that he built during my class it wasn't complex. It was like, we have these knowledge documentations, we're going to put it here in the secure environment, and we're going to create a chat interface when people ask a question, and we're going to have a split screen, we'll actually pull up the [00:10:00] manual. It was super simple.

Kevin Weitzel: So, you have a manual where you have instantaneous recall of the information that is there, and obviously, AI can probably calculate some of the nuances to even give you solutions that aren't necessarily in the manual.

Kathleen Perley: Yeah, and that's what was interesting. The AI tool that they built could eventually predict failures before they happen, identify better solutions that didn't exist. But what I think he did, which I think is really important, is start small. Have a way for them to access the manual in real time, where it automatically gives the right section and gives them a summary. So much about AI is about building trust with the people utilizing the technology and having some small incremental wins.

It's funny, I talk to a lot of companies across a number of different sectors about this stuff, and they'll say like, well, we had a model doing X, Y, and Z predictive maintenance, and there's this one time it got it wrong. But it's right 99% of the other [00:11:00] times. And I'll be like, how many times have your humans who've predicted maintenance failures gotten it wrong? 20%. And so, there's also this double standard. It's interesting because I think you almost have to like build that trust bridge for a lot of folks in getting there. The book talks about not just the technical side and the legal side and the ethical side as a leader, when you think about your vision of your organization and where it needs to go, but also, more importantly, how you rethink about the people within your organization.

Kevin Weitzel: Let me ask you this. Do you think that the technical aspect of it is definitely something AI can handle, and the human nuances? Like in marketing, when you're talking about marketing, AI can understand and just absorb mega terabytes of data every second and configure it and spit out all the results.

But when it comes down to the nuances of reading a face, reading the body language that somebody has, when you're talking with somebody in a home building model, or when you are sending out an ad campaign, you know, to the socials. You could put out AI content, but if you really want to nail home to a [00:12:00] certain sect of society, I think that you have to almost compartmentalize that human factor and maintain it while still utilizing the AI for its strength. Right?

Kathleen Perley: Yeah. And I will say, like it's interesting that you mentioned like kind of facial and body recognition. There's actually some of the technology that we're using in the IR space is we're looking at vocal bursts, but we're also looking at like body movement and language and identifying the emotions with really good accuracy. So, there is that technology there, and I think so much of what we do as a society, there's science, and then there's the art. The human still has a lot of the art piece of it.

We oftentimes hear this phrase of like, we need to maintain a human in the loop, things of that nature, and I don't really think that's the right way to think about it. Because oftentimes when I hear like, we need to maintain a human in the loop, my head initially goes to like bottlenecks, like this is going to create a human bottleneck. I was on a podcast recently, and I was talking to somebody. He has this term that he uses that I've adopted, which is a human over the loop. [00:13:00] How do you use AI? And you can use the humans as almost like a manager.

Think about digital marketing and advertising. As a former CEO in an ad agency, I'll tell you this: the one thing I loved was doing advanced segmentation, implementing CDPs, and personalization, and I loved that stuff. And we would talk about AB testing and having different ads for different ad segments and different audiences. So, for example, for primary care, the mom got a different ad than the young professional, than the working dad, right? All different messaging, all different experiences.

But what ended up happening, we'd have these really great ideas, but we'd only implement maybe one of them, like a general and then a one alt, because the clients didn't have the budget and it took a lot of time because it was all, most of it was manually done. With AI, we had the opportunity to finally follow through on some of those promises of like true AB testing and personalization that many marketing agencies have talked about for [00:14:00] years.

Greg Bray: Kathleen, as you say that, we run into the, that sounds overwhelming issue again, because you're just talking about that simplifying, that removing the barrier, almost the fear of, wow, that sounds amazing, but it feels like a lot of work. It feels hard. I don't know what to do next. How do we help people kind of take an idea and then move toward that, oh, we can do it, or what is that piece to get them over that fear, if you will.?

Kathleen Perley: I get oftentimes asked, and I'm sure Rice doesn't love this because I teach an executive education course, so they get paid when people sign for my courses. But I also tell the people, the best way to get over that fear and intimidation is just try it. Like, get your hands dirty every day. Everything that you do invite AI to the party and just see if it works or not. Start experimenting. That's the best way to learn.

On that example, my first step would be I'm going to do a deep research within either Gemini or OpenAI and have it do [00:15:00] an understanding of my customer base segments, upload some data that I have from my own CRM system or my own database, and say, can you help me identify the four most critical customer segments and what personalizations make sense, and then have it do a deep research article. And then I would take one campaign or one touch point in the process and say, okay, now let's version this piece out and let's see what the results tell us, right?

I think it gets really scary when you think of everything in broad strokes. Start breaking it down into the steps or the tasks. It's just like you do in dev work, right? You t-shirt size things, you break out the features, you backlog them. It's that same process with AI. If you think of it as we're going to personalize every single aspect of our journey for all of our different customers, that's really overwhelming. So, just say, okay, what are the top five, and let's take one touch point and let's personalize that and see what happens.

Greg Bray: In my experience [00:16:00] so far, I've talked to, especially builders and their marketing folks, how are you using AI? What are you doing with it? Things like that. We see a lot of individuals doing individual things.

Kathleen Perley: Yeah.

Greg Bray: What you're talking about is a much more process-driven, much more strategic oriented, and pulling in things together. Who should own something like that at the company? How do we kind of make sure that that's being driven at the right level?

Kathleen Perley: So, it's interesting, it's why I wrote that book, AI Made Simple Results Made Real because there's so many times I would talk to companies and their executive leadership team would say, Who do I need to hire to like take care of this AI thing to turn on the switch? And I'm like, no, no, no. You need to understand this. Because as an executive and as a CEO or wherever you sit in that executive board, part of your role in the organization is really outlining the vision for the organization, and if you don't have the understanding of where AI is going to transform your business [00:17:00] and can think about it strategically, you're going to end up with a lot of individuals doing one-off things all over the place. Some that actually move you towards the vision that you want to accomplish, some maybe not. And it's not that you don't allow them to do some of their own experimentation, but really looking at the aspects of your organization and having that lens. So, it should happen at the executive level.

And then you should really think about it in terms of what's already going on? What are some of the key challenges that you have today, or friction points, and where are the biggest opportunities? And then quantify them. If I fix this by making this assumption that AI can do Y, what does the output look like in terms of value creation, in terms of time saved and therefore costs saved, in terms of new revenue generated, things of that nature? PWC just came out with some research that organizations that have adopted AI are seeing their average revenue per FTE has tripled. But you need somebody from the [00:18:00] top that makes sure that you're not chasing shiny objects and you're thinking about it through the lens of your business first.

Kevin Weitzel: Alright, let's take this from the top. Take a company that has a board. I'm all for getting rid of the top. I do this from a financial standpoint. I can't stand that in the United States, we have people making hundreds and hundreds of times what an average worker makes. It's disgusting. That set aside, if you can punch in all the parameters into AI, and you can have a board that says, here's our goals, here's our factors, here's our hurdles, here's our, you know, financial limitations, yada yada, yada, here's our throughput potential, if you could make data decisions like that, why not just let AI do that for you instead of paying an exorbitant, bloated paycheck to a CEO?

Kathleen Perley: As a former CEO, I think it depends. It's science and it's art. There's one way to think about AI implementation, and it's saying, here's what we do today. Let's integrate AI and be 10 times faster at it and add revenue to bottom line. [00:19:00] Not that there's anything wrong with that. That's what a lot of the businesses are doing. And that's honestly, when I work with companies, typically what I tell them to start with, because it's easier mentally before you have to make the next leap, which is the most important leap.

With the capabilities of AI, what can your business do different that you weren't able to achieve before? Is it a new segment? Is it a whole new way of rethinking that industry? I really think you need to have the nuance of experience and the art side of an understanding of your industry to be able to identify those things. And the companies that are able to say and do, completely reshift how they think about their business, how they serve their customer base. So, it's not about doing more with less. It's about how do we do more with more. So, shifting that mindset, those are the companies who are going to be leading the pack in five years.

Kevin Weitzel: In full disclosure, I was playing devil's advocate there for our listening audience. So, playing [00:20:00] devil's advocate again, I'm going to ask a two-part question. I have personally changed all of my appliances to Energy Star. I have switched out every possible light bulb in my house to LED. So, we're talking about an 80% savings in efficiency. My electric bill has not changed. So, that said, as we implement this AI that is supposed to make things more profitable, more efficient, why is it that we are just paying the same amount of money and just shifting it to another player in the game?

Kathleen Perley: Twofold. Well, one, because a lot of organizations aren't implementing AI correctly. It's the hodgepodge lack of strategic vision in terms of how AI is implemented that starts from the top. They're either bringing in AI consultants and throwing everything at the wind because it's not a software rollout. So many companies are treating this like an SAP rollout. It's not, it really isn't. I don't consider myself a consultant. I talk to businesses. I hate consultants, so I can't classify myself as one. And I probably shouldn't say [00:21:00] that out loud, because a lot of my students and a lot of my peers are consultants, but I prefer AI consultants, right?

Because I worked with clients all the time, and they'd bring in another consultant, and they would try to come in and tell you like how to do your business, and like that they knew more about your business or your customer base or your segments, and they never did. And so, they would come and they would spew and you would get like a beautiful 200-page deck of stuff that you either A, already knew, or B, things that you were like, Hey, that's great, but there's X, Y, and Z, and from a legal campaign, like we can't do that. Right? There's like all those types of things, and so I think a lot of the reason why we're not seeing the return is because it's not being done right or well.

Greg Bray: Kathleen, if we can pivot just a little bit down a couple of layers, because we're talking about leadership and owning it and everything else, but we got folks listening today going, that's all fine and good, but I don't control that. I want to get better with what I can do. So, where are some of the places that the people in the marketing team that are [00:22:00] just responsible for cranking out the content and figuring out how to use it, where are some of the places that they should be focused to get a better, impact and use from the AI tools?

Kathleen Perley: Start by thinking about where are the friction points in your day-to-day right now. As somebody who's done a couple of construction products and home builds, we built our house in Houston. Now I'm building the Beyoncé-themed Airbnb. Right. One thing I always valued from my builders is like weekly updates. I know those are time-consuming but use AI. Have the super that's on the job do a voice memo that automatically gets uploaded in Slack or a Teams message that then translates into, here's where everything is, and sends it to the customer. Find where the pain points are, figure out what the customer values, try to see if there's convergence on those things, and just start playing around with it.

One of the interesting things I tell my students, because there's a lot of conversation about the job market and you know, a lot of students who are, you know, spending a lot of money to get the MBA are like panicked [00:23:00] when they're in my class because we talk about some of the efficiency gains and the transitions in terms of how people are thinking about jobs. I tell them one thing, which is research has shown that individuals who have AI skills, and I'm not talking coding skills, I'm just talking about knowing how to use the tools are 70% more likely to get hired than somebody with no AI skills, and even somebody who has more actual industry relevant experience.

PWC, also in that same report that I mentioned earlier, they're getting about a 56% premium in terms of wages and comp than those who aren't. So, I would say lean in, put the hat of your CEO on, put the hat of the visionary of your organization, and try to think about how are they measured in terms of success? Where can you find the convergence in terms of things that you can do and lean into it? Offer to be part of the council, the AI council offer to do some pilots, experiments. [00:24:00]

I mean, it's so funny, so many of my students, through my courses at Rice, I teach two of them, they end up leading the AI initiative at their organizations because they know more than anyone else in the company. Not because of they took six weeks, but because they leaned into it. And during the two six-week courses I teach, they can't be intimidated. They're like thrown into it. And once you're thrown into it and you realize it's not as scary or as hard as it sounds, they are really able to move the needle.

Greg Bray: Awesome. So, I got, a couple of quicker questions. Define for folks who aren't familiar with it, deep research. You mentioned that before but I think that's an area that not everybody who's just that casual ChatGPT user really understands what's possible there.

Kathleen Perley: Deep research is a game changer. All of the AI tools have some version of it. I'll talk in terms of Chat GPT because that's typically the most utilized tool. So, when you write a prompt, you'll see like there's a couple of icons or tools that you can access. There's one that looks like a [00:25:00] telescope, that is deep research. So, you click that, and then you write your prompt. So, you can say, help me do a SWOT analysis of the home builder industry in Atlanta and another city, focusing on these four topics.

What it'll do is I'll ask you some follow-up questions, and then it takes a little bit of time. So, it's not as immediate as some of your standard prompts, maybe like 10, 13 minutes. What it does is it does research. It actually goes out to the web and identifies 30, 40 sources and then writes a summary paper that typically is like 10 to 12 pages long with tables and charts, and it's all sourced. And so, it's basically like what you would hire a consultant or a researcher to do. It's incredible.

 The thing that I love the most about it, when you go to the sources and you read them, you're like, I would've never found that article. No matter how many times I searched or how many times I revised my search, or even I went three pages deep, I probably would've never found that [00:26:00] source, and that source is actually really helpful. So, you as a plus user, so if you're paying chat GBT $20 a month, you get I think maybe 10. I don't know it off the top of my head, but you get so many deep research articles a month, and they're amazing. Before you use those, because they're very valuable, ask ChatGPT, Hey, I want to use a deep research. Here's what I want to do. Can you help me refine a prompt to use for deep research?

Greg Bray: All right, so Kathleen, now let's flip that question on its head. Let's say that a prospective home buyer using deep research to research homes in the area or something like that, and I, as the builder, want to be one of the sources that's being cited, what do I need to be doing on my website to be showing up there?

Kathleen Perley: I'm so glad you asked that question. I think within the last 24 hours, OpenAI has released an update where if you're a business or you're selling a certain product or service, you can actually upload information to ChatGPT so that you are listed in [00:27:00] there as a resource. I can send you the link, Greg, after this, so that you have it and your listeners can find it. It's kind of stealth. Not a lot of people know about it yet, but they're basically creating their index. So, just like you would submit a site map to Google, this is what you would do to ensure that you're getting shown on search generative experiences like ChatGPT. They're trying to create an operating system, and so they're now creating a way for people to upload their own content.

It's funny because you're like, why would they do that? It's so like selfless of them in a way. They're smart. They're running up to issues with data, like publicly available data that they can use to improve the models. So, if you're uploading content that might be behind a firewall or some information that's not publicly available, because you're talking about your products and you want to sell them, it gives them more information that they can then train the models on. Which you're okay with because that's what you want to, you want to show up in experiences within ChatGPT.

Greg Bray: Next one. Give us one prompting tip that you feel would help people with their prompts. Or two, if [00:28:00] you can't narrow it to one.

Kathleen Perley: I can't do one. Two.

Kevin Weitzel: One was tough. Two, piece of cake.

Kathleen Perley: Piece of cake. So, for example, I want to test an email subject headline. I'll say, generate 15 email subject headlines for this newsletter that I've attached. But before you generate this, next, I want you to produce the subject headline, the rationale as to why you think it's a good subject headline, before you start the next one, and use that as a process. Because these models, these large language models, what they're doing is predicting words, and the more words and the more that they write out the rationale in that process, they tend to get better. So, if you have it, do that process of, Hey, draft this, and then provide your rationale before you give me the next one, you end up getting a lot better results.

Once I get those 15, I'll be like, okay, now review those 15, develop a chart, pro/con each, and then give me five better ones. And that typically gives [00:29:00] me the best ones. So, don't be afraid to like, push the models a bit and have it judge its own work. It really does. And having it explained why the pros and cons of each and the rationale, and when you ask to develop five better ones, it really takes all of those insights to really kind of push the needle further.

Greg Bray: I think the takeaway there is it's learning as it goes, so you don't always get the best answer to the first question.

Kathleen Perley: Exactly.

Greg Bray: And we're used to, in a search environment, expecting I asked a question, I got the answer, I'm done. And in this case, that's not really how these work. Am I understanding that right?

Kathleen Perley: Exactly. And then the other prompting tip that I will tell you is tell the model that your job depends on this. As a good Irish Catholic girl, like it's got a little bit of Catholic guilt, and if you lay it in there, you do end up getting better responses. And now I'm sure my model at some point is like everything that you put in here, your job depends on it being perfect, but it surprisingly does make an impact.

Greg Bray: Chat [00:30:00] GPT responds to stress. There we go.

Kathleen Perley: Yes, exactly. It has guilt.

Greg Bray: Well, Kathleen, thank you so much for spending time with us today. Do you have any last thoughts or words of advice you wanted to leave before we wrap up?

Kathleen Perley: I would say lean into it. Explore, watch YouTube videos. I'm going to plug the book. Buy the book. It's really, I think, a great stepping stone. My 75-year-old father read it and is now turning into an AI wiz, so it's accessible to all, which is really important. You know, have fun. Don't be afraid to fail and explore, and ask the right questions.

Greg Bray: Name of the book and where people can get it one more time.

Kathleen Perley: Yeah. So, it's AI Made Simple. Results Made Real: A Guide for Executives Partnering With the Future, and you can get it on Amazon.

Greg Bray: Awesome. Well, Kathleen, if somebody wants to, uh, reach out and connect with you, what's the best way for them to get in touch and learn more?

Kathleen Perley: LinkedIn would be probably the easiest and best way, and you'll also get access to I published a weekly newsletter. My students forced me to do this one, actually. My first section of students, I had about 90 students, [00:31:00] they were graduating, and they were like, how am I going to stay up to date on AI? What am I going to do? They're like, can you please start a newsletter? Because we started every week with kind of what was going on in the space. And so, they're like, what are we going to do? And so, I have that newsletter that my students still read and share to this day, and it's free. So, feel free to use that as well.

Greg Bray: Awesome. Well, thanks again, Kathleen, for spending time with us, and thank you, everybody, for listening today to The Home Builder Digital Marketing Podcast. I'm Greg Bray with Blue Tangerine.

Kevin Weitzel: And I'm Kevin Weitzel with OutHouse. Thank you.

Kathleen Perley: Thank you guys. [00:32:00]