AI in Multifamily – What Operators Are Actually Asking

AI is everywhere—but how are multifamily operators actually using it?

In this episode of The Multifamily Marketers Podcast, hosts Josh Grillo and Caroline Mills break down the findings from Resident360’s AI in Multifamily survey, exploring how owners, operators, and marketers are approaching AI today.

From leasing and marketing to reporting and resident communication, this episode separates the hype from reality and explains where AI is creating value, where human oversight is still essential, and how multifamily teams can start building a practical AI strategy.

You’ll learn:

• What multifamily operators are actually asking about AI today
• Why most companies are still experimenting instead of following a formal AI strategy
• The biggest barriers to adoption: trust, accuracy, and limited time
• Where AI creates the most value—from reporting and analytics to marketing content and leasing workflows
• Which tasks should always include human review
• How AI is changing apartment search through GEO and AI-generated recommendations
• A simple framework for launching your first AI pilot safely and effectively

If you’re interested in seeing our AI Report, you can download it here.

To suggest a topic, get in touch!

For more multifamily marketing help, connect with us at Resident360.

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TRANSCRIPT

Episode 48: AI in Multifamily – What Operators Are Actually Asking

Podcast Co-Hosts: Josh Grillo and Caroline Mills, Resident360

Josh: Welcome back to the Multifamily Marketers Podcast. I’m your host, Josh Grillo, co-founder here at Resident360, and I’m joined by my co-host, Miss Caroline Mills. Caroline, fresh off the Fourth of July weekend, tell me: How crowded was it in Florida?

Caroline: It was a great first Fourth of July in Florida, but it was packed. Everywhere we tried to go was very busy. But we got to see some great fireworks and spend some time out on the water, so it was a great weekend all around.

Josh: You survived, and you look nice and fresh for a Monday morning after the Fourth of July weekend, ready to go. All right. We have some really interesting stuff to share on the show today, and this one is all about AI. I’ll talk more about it as we get into it, but let me tee it up.

Obviously, AI is everywhere, and everyone’s talking about it. But I think a lot of the conversation in multifamily is too vague, too technical, or too vendor-driven. So we asked multifamily operators one simple question. We sent several emails and a survey to our email list, and among the questions, we asked, “What’s your biggest question about AI strategy right now?”

What came back was really interesting; Caroline, I know you thought so, too. People weren’t asking for hacks or specific ChatGPT prompts. They were asking much more practical questions, like: “Does AI actually help leasing? Can we trust it? What can be automated? What still needs a human? Where do we even start?”

A little more context: This report is based on 30 survey responses, so we’re not calling it a massive national benchmark study. We’re treating it as a directional snapshot, because these are real operators: owners, multifamily marketing managers, and property managers. But the patterns were really clear, and the same concerns kept showing up over and over. So Caroline, when you read through the responses in this AI report, what stood out to you first?

Caroline: What stood out to me was that, like you said, the questions were very genuine and very grounded. These operators aren’t asking how to chase the newest AI trend. They’re asking how this actually helps their team, their residents, their prospects, and ultimately their bottom line. That’s an important distinction. The interest is there, but people are cautious because they don’t want to make the leasing or resident experience worse. There’s some concern about making sure the time and money they invest makes sense.

Josh: One of the first big findings from the survey is that only two out of 30 respondents (think about that, two out of 30) said they had a defined AI strategy. At the same time, a lot of operators aren’t starting from zero. Forty-three percent are using a few tools consistently, and 37% have experimented without anything formal. So multifamily isn’t ignoring AI. It’s still very much in trial mode, and probably very vendor-driven, if I had to guess. So Caroline, do you think that’s a problem? Are multifamily operators behind, or are they being appropriately cautious?

Caroline: I think it’s a little of both. You’re a little behind if you’re not testing anything at all, but operators are being smart if they’re cautious about where AI gets used. In multifamily, it’s not like writing a random blog post. If AI gives you the wrong information about pricing, availability, concessions, pet policies, or lease terms, that can create a real operational problem. So I don’t think the goal should be to move fast and automate everything. The goal should be to start testing in the right places with the right guardrails.

Josh: I think that’s really the key. A strategy doesn’t mean a 40-page AI playbook nobody will read. It means answering a few basic questions. Caroline, what do you think those basic questions are?

Caroline: I’d say five of them. What are we allowed to use AI for? Which tools are approved? What information should never go into AI? What needs human review? And how are we measuring whether it actually helped? Those five questions alone would put a lot of teams ahead of where they are today.

Josh: So the gap isn’t awareness. Everybody knows AI matters. The gap is operational clarity.

One of the most important findings in the report is that the biggest barrier wasn’t cost. Using ChatGPT or Claude at the paid tiers runs around $20 a month unless you buy a bigger plan. Only 4% cited cost as the main barrier. The biggest concern, Caroline, was quality and accuracy, cited by 40% of respondents, and another 32% said they simply don’t have time to figure it out. That tells me operators aren’t saying AI is too expensive. They’re saying, “I don’t know if I can trust it, and I don’t have time to babysit it.” So where does bad AI output create the most risk for a property?

Caroline: I think the biggest risk is anywhere the information needs to be exact or is sensitive. Like we talked about, that could be pricing, availability, lease terms, concessions, pet policies, or fees. Be very careful with fair housing–sensitive language, and with resident complaints or maintenance emergencies. Those aren’t places where you want AI guessing. There’s also brand risk. If AI writes generic content, your property starts sounding like every other property in a competitive market, and that can be a problem.

Josh: Right. We don’t need more apartment copy that says, as we’ve talked about many times, “Modern living meets everyday convenience.”

Caroline: Exactly.

Josh: Ugh. We should send that phrase back where it came from. So how should operators think about human review?

Caroline: Human review should be non-negotiable for anything customer-facing, especially early on. That includes leasing responses, resident communication, website copy, ad copy, review responses, renewal messaging, and any pricing-related recommendations. AI can draft those for you, and it can summarize and organize, but you still want a human making the final judgment call.

Josh: So the answer to the trust problem isn’t avoiding AI. It’s designing workflows where AI helps with the repetitive work, but humans still control the decisions and, more importantly, the customer and resident experience.

Okay, one thing that surprised me was where operators said they wanted AI’s help most. The top answer was reporting and analytics, at 73%. Maybe no surprise there, because we know AI, especially Claude Cowork, works really well for reporting and analytics. Marketing content and copywriting came in second at 63%, and we know ChatGPT does a great job writing copy. Then competitive analysis and pricing at 50%, leasing and prospect communication at 47%, resident communication also at 47%, and operations and maintenance workflows at 40%. Caroline, were you surprised that reporting and analytics beat out content?

Caroline: A little, but it makes sense, because teams are drowning in data. We hear it all the time. They have website traffic, ILS leads, ad performance, cost per lead, tours, applications, occupancy, pricing, whatever it may be, plus ownership reports on top of that. The problem isn’t that teams don’t have data. It’s turning all of it into a clear story, and that takes time. AI can help answer what changed, why it might have changed, and what we should look at next.

Josh: So what’s a practical example of AI helping with reporting?

Caroline: A team could use AI to draft a weekly performance summary. For example, maybe traffic was up but lead volume was flat, cost per lead increased, tours dropped, and occupancy stayed the same. AI can help organize that into a narrative: Here’s what changed, here are the possible reasons, here are the questions the team should ask, and here are the recommended next steps. You still need a human to validate it, but it can save a lot of time.

Josh: That’s a super important point. AI isn’t just a copywriting tool. It can be a thinking partner and a strategy partner for reporting, if you give it good inputs. That’s the big “if.” You have to give it great inputs. So Caroline, on the content side, where is AI actually helpful?

Caroline: In first drafts, repurposing content, writing variations, email subject lines, ad copy tests, social captions, and turning one idea into multiple formats. But the first draft shouldn’t be your final draft. AI content needs brand voice, property details, audience context, and editing. Otherwise, like we said, everything starts to sound the same.

Josh: I think the opportunity isn’t just producing more content faster. It’s doing the repetitive parts faster so the team can spend more time on strategy, accuracy, and the big one: differen… differenti… I can’t even say the word.

Caroline: Differentiation.

Josh: Differentiation. How you’re different. Oh my gosh, I couldn’t get that one out. That was a tough one. All right, let’s jump into the leasing side. A lot of the open-ended questions came back to leasing. One person asked, “Does AI actually help or hurt leasing?” Another asked, “What can be automated versus what needs a human touch?” And one response said, “AI does not compare to humans. It is not analytical and does not have a sixth sense.”

I thought that one was pretty interesting. I actually kind of agree. AI doesn’t have a sixth sense, but I don’t think it needs to. So Caroline, let’s answer that big question directly: Does AI help or hurt leasing?

Caroline: It depends on how it’s used. AI helps when it handles speed, consistency, and repetitive follow-up. It can help with initial responses, tour scheduling, confirmation emails, reminders, and post-tour follow-up, all the things we think about day to day. But it can hurt when it replaces human moments: renewals, escalated complaints, emotional conversations, pricing expectations, and nuanced objections. Anything that requires empathy and full knowledge of the resident and what’s happening at the time, you want a human handling those touchpoints.

Josh: So AI should handle volume, and humans should handle relationships.

Caroline: Exactly. I think that’s the simplest way to say it. The best use of AI isn’t to remove the leasing team. It’s to give the leasing team more time for the conversations that actually need them.

Josh: So what does a good AI-to-human handoff look like to you?

Caroline: It needs to be thought out, clean, and useful. AI should summarize who the prospect is, what they’re looking for, what questions they asked, what objections came up, and what needs to happen next. The leasing agent shouldn’t have to dig through a messy transcript. The handoff should make them better prepared.

Josh: So the best operators aren’t choosing between AI and people. They’re designing workflows where AI handles the busywork and humans handle the trust-building.

One of the most interesting forward-looking questions was this: “How can we make sure our communities and brands are accurately represented and surfaced in AI-generated summaries, recommendations, and discovery moments?” That’s a huge question, because the renter search is changing. We’ve talked about this over and over on this podcast. A renter may not just search “apartments in Austin” on Google. They might ask an AI tool, “Find me a pet-friendly apartment near restaurants, with good reviews, under this budget, and with a short commute to work.” The question is: Will your property show up in those AI-generated results, and will it show up accurately? So Caroline, what should apartment marketers do now to prepare for AI-driven search?

Caroline: We hear this all the time; I have these conversations weekly with different clients. You need to make your property information clear, consistent, and easy to understand. That means strong website content, accurate floor plan information, updated amenities, and neighborhood content. Make sure your local SEO is handled and your Google Business Profile is accurate; we’ve talked about that a lot here. Reviews and clear brand positioning matter, too. AI tools pull from all available information, so if yours is generic, outdated, or especially inconsistent, AI might not represent you correctly, or might not pull you in at all.

Josh: So is this the next evolution of SEO?

Caroline: It is, but it’s bigger than traditional SEO. It’s not just about ranking for a keyword. It’s about whether AI systems can understand, trust, and recommend your property. Specificity matters, which we talk about a lot with our clients. Reviews matter, local context matters, and clear website content matters. Generic property marketing is going to become even less effective.

Josh: So the big takeaway is that the future of search rewards clarity. If your property’s story is vague, AI isn’t going to magically make it compelling. It may just summarize the same generic story faster.

All right, if an operator is listening and doesn’t have an AI strategy yet, the question becomes: Where do they start? The report recommends starting with the highest-volume, most repetitive communication in the operation, usually initial prospect follow-up, and piloting it on one property before rolling it out portfolio-wide. Caroline, what would you say is a good first AI pilot?

Caroline: Pick one property, one workflow, and one goal. Good first pilots could be prospect follow-up, tour scheduling, weekly reporting summaries, content repurposing, or resident messaging drafts. Don’t start with the most sensitive workflow, and don’t start with a full portfolio rollout. Start somewhere measurable, where you can see whether it’s making a difference, and definitely somewhere low-risk.

Josh: So what would a 30-day test look like?

Caroline: First, define the workflow. Let’s use weekly marketing reporting as an example. Then define the goal: Why are we doing this? Maybe you want to reduce reporting time, improve clarity, or make recommendations easier to understand. Then use an approved tool. Keep a human in the loop, and track whether it saved time, improved quality, or helped the team make better decisions. At the end of 30 days, decide: Do we keep it, improve it, expand it, or stop?

Josh: And just so everyone’s aware, everybody has to be bought in. If you’re rolling this out, you need full team support and company buy-in, not one person trying it on their own without anyone else knowing. That’s what you don’t want. We see it now: so many people in a company dabbling in their own AI tools. That’s where you can run into trouble with AI governance, like data privacy and fabricated information. We know how much of what comes out of ChatGPT is true and how much isn’t. And there’s what’s called shadow AI, where lots of people at your company are using different AI tools, but there’s no common ground: no shared tool, no compliance, no agreed way of doing things. So my question to you, Caroline: What should teams avoid?

Caroline: There are a few things. Don’t put resident personal information into AI. You don’t want rent rolls, financial reports, lease documents, or private ownership reports going into free public AI tools, or anything confidential. You also don’t want to automate anything customer-facing without good review. The goal is to make AI safe enough to use, not scary enough to avoid.

Josh: So the operators falling behind aren’t necessarily the ones choosing the wrong AI platform. They’re the ones not testing anything at all. The takeaway from this report, for us, is pretty clear. Multifamily operators are interested in AI, but they’re cautious, as they should be, and honestly, that caution makes a lot of sense. Only two of the 30 operators we heard from have a defined AI strategy, but many are experimenting. The industry isn’t ignoring AI. It’s trying to figure out where AI actually belongs.

We mentioned that AI can help with reporting, marketing content, leasing follow-up, resident communication, competitive analysis, and operations. But, guys, it still needs human review. It still needs data guardrails and brand oversight. And it definitely shouldn’t replace the relationship-building that actually drives your leasing, your renewals, and your resident satisfaction.

Caroline: And if you’re overwhelmed, don’t start with the technology. Start with a problem. Where is your leasing team losing time? Where are prospects falling through the cracks? Where is reporting taking too long? Where is communication inconsistent? That’s where AI can help you first.

Josh: So start small: one property, one workflow, one approved tool (and I’ll stress approved), one clear goal, and human review. Then measure where it actually helped. Because I think the real risk isn’t picking the wrong AI tool. The real risk is doing nothing while other teams get faster, cleaner, and more efficient.

We’re doing this right now at Resident360. One of the big things we decided several months ago was which tool we’d use as a company. Everybody needs to use the same tool and share the same prompts we create for the things we do. So that’s going to be a wrap for today’s show. Caroline, any final thoughts?

Caroline: It’s great information, and it’s very interesting to see the takeaways. We put together a really great report in a good format. We all clearly have the interest. It’s just a matter of how we use AI and how we see it change and take shape.

Josh: Absolutely. If you’d like a copy of the AI report we created, again, it’s a small study with 30 respondents, but we put it together in a pretty cool report with the questions and answers.

Caroline: Yeah.

Josh: I think it came out great, and it gives everybody a really good sense of how people are thinking. I remember saying this to Caroline and our marketing manager, Natalie: “You know what would be really interesting? If we run this survey again a year from now and see how the answers have changed.” I guarantee they’ll be completely different a year from now.

Caroline: Yeah.

Josh: So if you’re interested, we’ll link the report, a PDF that’s several pages long, in the show notes for this podcast. Go to resident360.com, click Resources, then Podcasts, and find episode 48. It’ll be in the show notes there, and you can download it and see everything for yourself. With that, that’s a wrap. We’ll be back next week with another episode. We appreciate everybody listening today. Caroline, enjoy that nice summer sunshine in Florida, and I’ll see you next week.