Last modified on August 21st, 2023
By Megan Eales Monroe
Artificial intelligence (AI) isn’t necessarily new, but the popularity of newly developed, publicly available AI solutions has skyrocketed over the last year due to advancements in generative AI. Now, almost every industry around the world has started embracing and adopting the power of AI, including property management.
While it’s already clear AI holds enormous potential for property management, there are still plenty of questions around how businesses can best implement AI solutions, and how to navigate brand-new AI territory, especially when it comes to using AI responsibly.
We explore this and more in episode one of season four of The Top Floor podcast, with two property management and AI experts: Cat Allday, AppFolio’s VP of AI, and Peter Lohmann, CEO of RL Property Management.
Tune in to the full episode to hear us discuss ways AI can reduce manual processes, overcome bias, streamline workflows, and help us manage data more efficiently. Plus, we also alleviate the concerns about AI by showing how it can be implemented safely and responsibly
Meet Our Guests:
As the Vice President of the Artificial Intelligence Initiative at AppFolio, Cat Allday is responsible for setting the strategy for how artificial intelligence can best be applied to solving the complex challenges property managers face daily.
In this role, Cat gets most excited when seeing the impact AI has in helping our customers transform their businesses, from improving lead-to-lease conversion to spending time on more meaningful work and making better decisions.
Before joining AppFolio in 2014, Cat held multiple leadership roles at Citrix, where she managed the product development of their collaboration solutions: GoToMeeting, GoToWebinar, GoToTraining, and ShareFile.
When she’s not in the office, Cat enjoys live music, travel, cooking exotic dishes, and enjoying the beautiful Santa Barbara community.
Peter is the CEO & principal broker of RL Property Management, a residential property management company located in Columbus, Ohio. RL manages over 600 units. Peter also owns a small engineering company also located in Columbus, run by his business partner.
Peter received his Bachelor’s in electrical engineering and spent 5 years in the control system engineering industry full-time before founding RL Property Management in 2013. He lives in the Olde Towne East neighborhood of Columbus with his wife, 2 daughters and their dog Oxley.
Megan Eales Monroe: Welcome to The Top Floor, the real estate management podcast that’s dedicated to keeping you one step ahead of industry trends with expert advice and actionable insights. I’m your host, Megan Eales Monroe. Together, we’ll dig deep with today’s property management leaders and industry change-makers to help you unlock new possibilities, transform your day-to-day operations, and grow your business. And, no matter the size or type of portfolio you manage, we’ve got you covered here on The Top Floor.
Whenever new technology is introduced, it holds the potential to change our lives in ways no one ever could have imagined or predicted. For example, it’s only been 16 years since Apple launched the first iPhone, and there are now an estimated 5.25 billion smartphone users worldwide. Or look at Facebook – although it wasn’t the first social media network, it was the first to use social media technology in truly revolutionary ways. As a result, the platform has amassed nearly 3 billion global users in less than 20 years, and was the driving force behind widespread social media adoption.
However, when it comes to the introduction of new technology, artificial intelligence — which is most commonly shortened to AI — is no exception. That’s because in less than one year, it’s clear that rapid advancements in AI technology will change our lives forever. It’s also completely shaking up almost every industry around the world, including property management.
But even with the enormous potential AI poses for property management businesses, there’s still a considerable amount of uncertainty and concern, especially when it comes to responsibly leveraging the technology. That’s why we’re kicking off our first episode of The Top Floor’s fourth season with a deep dive into property management AI.
To help us dig into the exciting, yet complex topic of property management AI, we’re joined by two very special guests. First up is Peter Lohmann.
Peter Lohmann: Well, thanks for having me. I’m excited to be here. So, Peter Lohmann. I’m here in Columbus, Ohio. I own a property management company called RL Property Management. We manage just over 600 doors here in the central Ohio area. It’s a mixture of single-family homes and small apartment buildings.
Separate from all that, I have a little bit of a media business. I guess you could call it that. I have a presence on Twitter. I have a newsletter. I have a podcast called Owner Occupied, where I interview experts in property management. I just love talking property management and sharing a few things that I know or sharing what other people know with a broader audience.
Megan Eales Monroe: In addition to knowing Peter from his podcast, Owner Occupied, you’ll also recognize our next guest from season 3, episode 2 of The Top Floor: Cat Allday.
Cat Allday: My name is Cat Allday and I’ve been with AppFolio for almost nine years. I lead the AI and product operations organizations in product development. For the last few years, I’ve been really focused on how we develop AI products at AppFolio for our customers.
I’m excited that we’ve been able to build some great products that many of you guys already use today, and that we’re thinking about the future and what this technology is going to allow us to solve for our customers. So my day-to-day is really working with product and engineering teams to make sure that we are focused on these technologies, and also thinking about things that we need to have in place to make sure that we’re developing AI technologies in a safe, responsible way.
Megan Eales Monroe: In addition to being featured on The Top Floor, Cat was also most recently a guest on season 3, episode 3 of Owner Occupied with Peter Lohmann, where they also discussed AppFolio’s innovation roadmap, including AppFolio Realm’s full suite of AI capabilities. We’ll be sure to provide the link to their episode in the show notes, so you can continue the property management AI conversations after this episode.
In the meantime, let’s dive into our conversation with Peter and Cat, to explore what property management AI looks like today, how businesses can responsibly adopt and leverage AI tools and technology, and the surprising ways property management AI can actually help create more ethical outcomes.
Artificial intelligence technology isn’t new, but the entire world has a brand-new interest in it, thanks to rapid advancements in publicly available next generation AI tools like ChatGPT.
However, even though AI is at the forefront of almost every conversation and news headline, there’s still a lot of confusion around the many different types of AI tools and technology available today. And because the term “AI” is typically used as a blanket term for all things artificial intelligence, we asked Cat to start our conversation with a quick AI primer. Because, as she explains, there’s a huge difference between the types of AI that power smart assistants like Alexa and Siri, and the latest AI that’s poised to revolutionize how we live and work.
Cat Allday: AI is a very broad term. If you think about the different types of AI, I’ll start with narrow AI because I think that’s something that we’re all familiar with and may not know it. These are systems that are designed or trained to carry out a very specific task or solve a particular problem. I think the best example of narrow AI are voice assistants like Siri or Alexa. These have been around for a while. So, that’s called narrow AI.
Then you’ll hear a term called AGI or artificial general intelligence. This is the stuff that sci-fi movies portray. This is a hypothetical concept. With AGI, this is intelligence that has the same level as human intellect, is able to reason and think like a human, and is basically capable of common sense. The technology is nowhere near that today, that is still science fiction. But I think those are the extremes. Narrow AI is actually very task-specific, while this AGI is what people fear. That’s the Skynets of the world.
One layer below that is what’s called machine learning. Machine learning is when you have a computer learn from data or experiences, rather than explicitly programming it to do that. So this is where machine learning development is different than traditional software development. And if you think about machine learning, this is where you train the systems on large amounts of data, and it can learn to recognize patterns, and that’s where it can make decisions and make predictions. The best examples are speech recognition, image recognition, and fraud detection. And I think an example that many people will be familiar with is if you upload a photo to a social media site, like Facebook, and it recognizes the people in the photos and starts tagging them, that’s an example of machine learning that I think we’ve all seen.
And then one layer below there is deep learning. This is a form of machine learning that uses what’s called neural networks, which are multiple training models that are training on massive amounts of data. And this is usually when you hear the term “NLP,” or natural language processing. Speech recognition and image recognition, oftentimes those are leveraging these neural networks that are part of deep learning.
And then built on top of that, we’ll get to the real exciting stuff, is generative AI. This is what you’re hearing about in the media today where these technologies leverage deep learning and they’re able to produce text, video, and images based on user-given prompts. The examples are things like ChatGPT. I don’t know if you guys have ever played with DALL·E, which is the image creator that is also an OpenAI product. Then Bard, which is Google’s large language model.
Megan Eales Monroe: So, in reality, although there are many, different types of AI available today, most conversations are actually focused on generative AI, which is a model that “trains” on large sets of data in order to generate new responses, ideas, and content. In addition, and as Cat mentioned, generative AI leverages Natural Language Processing, or NLP, which helps generative AI models make sense of and better process human language. Natural Language Processing is also what helps generative AI engage in human-like ways.
But even as impressive as AI technology is today, Cat explains that many AI platforms developed for general audiences and generic purposes don’t fully meet the unique challenges and needs of property management.
Cat Allday: I’ve spoken to several folks in the industry that are trying to figure out how to use products like ChatGPT in their operations today. They’re trying to figure out, can I use this tool to help me improve my business? And I think that’s a great example of how a new technology can be applied to improve existing processes that you have in a business.
I think tailored solutions that are built specifically for property management are going to be more effective than a generic tool like ChatGPT. We’ve been thinking about, how do we build these AI products to help streamline these processes, and improve the prospect and tenant experience for our customers? For the past few years, we’ve been actually thinking about how to do this in a meaningful, scalable way. We’ve already built a bunch of products that leverage AI technology to help automate those tasks and provide insights. And so, I think the industry is catching up to some of the stuff that we’ve been doing already.
Megan Eales Monroe: Even as AI solutions come to the forefront of property management conversations, the industry’s adoption of AI solutions has mostly been seen among early adopters. However, as Peter explains, there are very real reasons businesses should be exploring property management-specific AI technology, especially considering the enormous benefits that can come with it.
Peter Lohmann: Well, it is an exciting time. It’s really, really, really, really early days. And I feel like folks maybe don’t fully appreciate how early we still are. And people are preemptively writing it off, right? But the way to think about this is the AI you see today is the worst it’s ever going to be. It’s only going to get better from here.
This is a real paradigm shift. But we’re so accustomed to getting work done by clicking a mouse and moving it around, and navigating through screens, and typing on a keyboard, typing numbers into fields, that the idea of getting work done by… this is so cliche, but it’s like your assistant. If you had an executive assistant and you texted that person on your phone, “Hi, I need you to add a late fee to 123 Main Street,” or “Please look up the rent roll for 567 Main Street and email it to me and copy the client…” If you own a management company and you have someone that you can text to get those things done, you know how high leverage that is. You know how high impact that can be for your ability to get things done.
And if you haven’t experienced that, you maybe don’t realize how different that is from actually doing the task yourself by clicking through screens. So this is a time-saver. It allows for fewer mistakes. It allows people to be up to speed faster and get productive within the software, without extensive training, or practice, or experience, because they can just use natural language to interface with the software.
Any efficiency gain in terms of labor time…it’s a labor game, property management. Any time savings translates to labor savings, and labor savings translates to directly to profit, because labor’s our largest expense. So if I can manage 70 units per full-time employee instead of 60, those last 10 units’ management fees is all profit for the business owner. That’s a really big deal in an industry that has historically had low margins, although that has changed in recent days, not for everybody, but for some folks. So that’s exciting.
Megan Eales Monroe: Although Peter is definitely ahead of the AI curve, the real estate management industry, as a whole, is quickly starting to realize the untapped potential AI holds. And it’s doing so at an incredible pace.
In early 2023, AppFolio surveyed property management professionals to better understand their attitudes toward AI. At that time, 40% agreed that artificial intelligence and large language models like ChatGPT could benefit their companies — but 45% were undecided. In addition, 37% said they believed AI would make their roles more efficient — but 47% neither agreed nor disagreed, showing a general lack of consensus about the benefits of AI.
However, over the course of just a few short months, the industry’s sentiment around AI appears to have dramatically shifted. From my own observations at June 2023’s Apartmentalize conference, live audience polls, Q&A sessions, and attendee conversations signaled a significant interest in adopting and implementing AI solutions.
But adopting AI solutions is one thing. Knowing how to apply them is another. Thankfully, Cat Allday was in attendance at Apartmentalize, and here’s her take on how those who are interested in adopting AI today can leverage the technology to start immediately solving some of their most pressing property management pain points.
Cat Allday: I was at NAA and there was a session about some of the big challenges in the property management space, specifically. One of the biggest challenges that I heard was finding and retaining talent, and AI technology is going to make it easier to train those new hires. You’ll have the ability to remove tedious, repetitive work, so the talent on your team is going to be able to focus on more creative and meaningful work. So, you’re going to be able to retain your team longer. I think that’s one opportunity.
The other thing I heard was driving operational excellence. This is another area where AI can help us. If you think about automating work, you can build a more efficient operation with higher quality results, which I think is an important part of understanding how automation can help your business and doing more with less effort and then redeploying your staff to those more strategic areas.
I think that’s a way where we will see operational excellence being powered by AI. And then I think the last thing is, who doesn’t want to make money or more profits? So by improving how fast you can respond to prospects, how fast you can close maintenance tickets, how effectively you manage the relationships with your residents and owners, you can really improve the quality of your lease renewal rates. There are all these things that can be accomplished with AI technology or supported by AI technology. So, those are big opportunities that align with some of the challenges we’re seeing in this space today.
Megan Eales Monroe: As Peter mentioned before, the way most property management organizations are just barely scratching the surface with how they’re leveraging AI technology today. What makes him most excited about property management AI is the ability to instantly surface business-critical insights and connect data in ways that would take even the most experienced teams days to complete.
Peter Lohmann: I find myself wondering questions to which I know the answer lies within our property management software, it’s just that there’s no way to access it. So here’s an example of a question that I think would be really powerful that an AI would truly be the best way to get this data. Here’s what I would type into it, “Please tell me our current lease renewal rate based on the last 90 days and compare that with our lease renewal rate one year ago.” If you own a property management company you know how valuable that would be to have at your fingertips and how difficult that type of data is to get right now, regardless of what property management software you’re using.
Another one might be, “Please tell me what percent of our clients renewed their management agreement over the last year and compare that with the year 2020.” Just the ability to ask questions of data is like a business owner’s dream. And in big businesses, they have whole departments with highly expensive tools. There’s this field called BI, Business Intelligence, where you’re querying the data and building these fancy graphs and charts. And you need a degree in statistics and computer science to be able to produce these reports.
And if we could just query in natural language the software that we’re using every day, I mean, I can think about questions around leasing like, “Please tell me how many showings on average until we have a signed lease. Now, what was that number for last year compared to this year?” Trends, figuring out trends would be another really powerful use case there.
What happens when you start digging into data is it prompts more questions. So let’s say you looked up the lease renewal rate and you found that the lease renewal rate dropped this year compared to last year, meaning more of your tenants were moving out. What are you immediately wondering, “Well, why? Why is that?” And so, you might want to then know something about…has our average rent amount changed? Let me ask about that. Have our scores that we’re getting on our maintenance requests changed? Let me ask about that. Has our response time to communication requests, has that changed? Is that what’s driving tenant dissatisfaction?
I could envision a future where you’re being given recommendations around process and workflow that are going to have an impact across the organization. So rather than just like, “Oh, I’m able to just tell it to add a late fee instead of going to the screen and adding the late fee myself,” that’s an isolated, relatively minor time saving.
But imagine a world where the system could look at your operations as a whole and say something like, “Hey, it looks like you’re adding a lot of late fees on the fifth. How about if we set up a rule for you so that every property with a balance over a hundred dollars at 12:01 AM on the sixth gets a late fee automatically. Would that be helpful?” That’s the type of thing where it starts to become a game-changer for property management company owners.
Megan Eales Monroe: Based on our conversations with Peter and Cat so far, there’s clearly no shortage of big opportunities for AI in property management. But on the flip side, there’s still a lot of unknowns and plenty of concerns. The latest news headlines are rife with all the ways people could misuse and abuse AI’s powerful capabilities. In addition, with governments around the world scrambling to figure out exactly how to regulate the technology and put guardrails in place for its usage, the entire AI landscape can feel a bit like the Wild West right now.
That’s why, as Cat explains, embracing a responsible approach to AI from the start, especially within the property management industry, is crucial.
Cat Allday: I think you’ll hear terms like ethical AI, responsible, trustworthy. I think they’re all interchangeable. But the goal of ethical or responsible AI is really to address risk and challenges that could be associated with AI, like biases, privacy concerns, societal impacts. Responsible AI is really the development and deployment of AI in a way that aligns with ethical principles and values, and it ensures that the technology is designed, implemented, and used in a way that respects the rights of people, that promotes fairness, transparency, and accountability. And so, I think it’s an important thing for us to be focused on.
I would say most big tech companies have a responsible AI position or framework in place. If you think about these large regulatory organizations, like the National Institute of Standards and Technology, the European Union, they have already developed guidelines for responsible AI, and not only do they ensure that AI tech is used in a way that provides the best possible outcomes for people and society, but they’re also helping those companies comply with, and I think it’s fair to say, forthcoming regulations.
There will be regulations on this technology, and so it’s important for companies to be ahead of that so that they’re building the products responsibly today. And then when those regulations are defined, they’ll be in compliance, or it’ll be very easy for them to comply because they’ve already built this good foundation.
If you’re working with a vendor or a partner, you should be able to ask them, what is your stance on responsible AI? What are your policies and your practices? Companies should be able to share that. Then, do they adhere to a set of standards? Like I shared, the National Institute for Standards and Technology have a framework for responsible AI. Do they follow and adhere to those standards? Make sure that they have a process for ensuring that their AI development is following those ethical principles. I think any company who’s in this space needs to be thinking about how they’re building responsible AI.
Our responsible AI values, our framework for us when we’re developing our AI products are fairness, reliability, privacy and security, transparency, and accountability. We use these values to ensure that our AI products are developed in a way that protects our customers, and the data that they entrust us with. We have an assessment process. So we have these values that frame the way we think about development. Then we have an internal assessment process that, before we can write one line of code that uses AI, we’ve gone through this assessment to think about what problems we’re trying to solve, considerations to make sure that we follow these values, and then there’s a regular review process to make sure that, as things change, that our technologies are still following these values.
Peter Lohmann: As an industry, let’s lean into this and try to control the conversation and the framing of this tool within our industry. These things are coming. I’m telling you that right now. And so, if we don’t get ahead of this, we’re going to get steamrolled by legislation that we’re not going to like and articles in newspapers that we’re not going to like. So I think this is one of those times when we have an opportunity to step up as an industry and update our code of ethics, or adopt a set of ethical guidelines, or whatever it is that we need to do.
Megan Eales Monroe: Although many conversations around AI in the news today are concerned with potentially negative outcomes, we wanted to know if the opposite could also be true. By building property management AI systems committed to fairness, resistant to misuse, and by implementing strict quality control measures, could AI technology actually result in better outcomes?
Cat Allday: With any new technology, there’s always risk and benefits. I think that’s what we’re seeing in the media today. I think the media oftentimes will talk about doom and gloom, and that overshadows some of the really powerful benefits that AI can bring to businesses, as well as to society.
So I think AI and technology in general can help you with consistency in decision-making and even make you more compliant. Humans make subjective decisions and that’s where the potential for ethical issues come in. If you have two team members and they’re presented with the exact same situation, it’s very likely that they might make very different decisions. And so, one chooses to do something while the other does not, and now you have the potential for this inconsistent outcome.
I think where AI can help is in standardizing the repeatable processes and ensuring that privacy and security are part of those processes. If you think about consistency in decision making, I think AI can actually sometimes help you because you’re removing some of that subjective nature.
I think another example is in providing levels of service to your residents and consistent levels of service. Let’s say you have some residents who are primarily Spanish speaking. There are lots of translation capabilities in AI, and you might actually be able to support and serve that customer or that resident faster because you’ve added an AI component that can help you translate. And so that’s an example where you might not think about your normal behavior as creating any kind of variation in service level, but it might, because if you don’t understand what the resident’s saying, you might not respond as fast to a particular service issue that might be going on. So, that’s where I think technology can actually assist in creating this kind of consistent customer service experience.
Megan Eales Monroe: In addition to creating a more consistent resident experience, Peter also sees how using property management AI can help make the entire property management system function more responsible, by removing subjective decision-making from some processes.
Peter Lohmann: AI is a tool and it’s an incredibly powerful tool that gives you unbelievable leverage. And so, it seems to me that we should bake into that system, because we have the ability here for a bias towards good, towards positivity. The other thing that comes up for me for some reason here is the fact that we as property managers are fiduciaries for the property owners. Now, I’m speaking as a third-party property manager here. The property owners who have hired us to manage these homes and apartments, we are bound by law, at least here in Ohio and in many other states, to act in their best interest.
Megan Eales Monroe: Whether your property management is using it or not, AI is here to stay, and its adoption is only projected to increase as the technology continues to evolve. Also, the longer you wait to implement property management-specific AI systems across your teams, you may be losing out on the opportunity to elevate your business insights, achieve productivity gains, and increase efficiency across your entire business.
So, how do you get your team ready to embrace this next phase of AI? Here’s Peter and Cat with their final thoughts around today’s conversations.
Peter Lohmann: I would say be open-minded. And just as you are evaluating any new technology or new software for your business, this is really no different. I can see that property management company owners may be tempted to either write off the segment entirely or to adopt every single thing that has the word AI in it immediately. And neither of those is correct, is what my intuition says. My intuition says that there’s going to be some best-in-class solutions that use AI to help deliver results for their customers. And that’s what I would want to be looking for and what I will be looking for as a property management company owner.
To my peers who may be nervous about it, quite frankly, I’m not going to sit here and say you shouldn’t be nervous, because this is new. And I’m not from the future. I don’t know where this is going to go. But I think technology, we have all seen if you look back 20-30 years in the industry, I’ve been professionally in the industry for 10 years only and I’ve seen the changes that have come just in that time. I think it’s safe to say that technology’s been a net positive on the whole. And I don’t see why AI specifically would be any different. The industry will adapt and absorb this tool the way we have others.
Cat Allday: You know it’s interesting. We think about these big technology adoption curves. So mobile phones. Who thought that they would be able to walk around with a computer in their pocket? And I love the story about Blackberry. I was a Blackberry user. I loved my keyboard. I never thought I would use a phone without a keyboard after having my Blackberry. And if you think about how fast iPhone disrupted Blackberry, and they were a $10 billion company at the time that iPhone was introduced, who would’ve thought that a device without a keyboard would have the kind of penetration it did as fast as it did? That is an example of a disruption.
And I think that AI is going to have that kind of disruption in our industry as well as in across technology. So, I guess the question is, do we want to be Apple or do we want to be Blackberry? From a technology standpoint, I definitely want to be Apple. If we think about it from a property management point of view, don’t you want to be thinking about how you’re going to be leveraging this kind of technology to drive your business forward and eclipse your competitors?
I think this is a good opportunity for those forward-looking businesses to think about how they can harness this technology to their benefit.
Megan Eales Monroe: Thanks to the rapid advancement in g-generative AI, every industry — including property management — is about to undergo a brand-new wave of digital transformation. Property management teams that adopt AI now have an opportunity to transform the way work is done, for the better. That includes elevating business-critical insights, achieving productivity gains, increasing efficiencies, and outperforming competitors, so you have more time to focus on what matters: growing and scaling your property management business.
We’d like to thank Peter Lohmann and Cat Allday for joining us today. To continue the conversation around property management AI, tune into their interview on Owner Occupied. Also, to see what industry-leading property management AI can do for you, visit appfolio.com/ai to learn more about AppFolio Realm, our full suite of AI capabilities.
Thank you for joining us on this episode of The Top Floor, brought to you by AppFolio. If you enjoyed the conversation, let us know by leaving a review wherever you listen to this podcast — we’d love to hear your feedback. Also, make sure you’re subscribed to The Top Floor podcast to get notified as soon as our next episode goes live. Until then, we’ll continue the conversation around all things real estate and association management on the Industry Insights section of our website: appfolio.com/industry-insights. We’ll see you there.