Artificial Intelligence

This article is the first in a series about artificial intelligence’s applications in the multifamily sector and the risks associated with its use. 

Since the launch of OpenAI’s ChatGPT in late 2022, the use of artificial intelligence has exploded in popularity across multiple industries. 

Multifamily is no exception, though the sector is already familiar with some types of AI applications. The term “artificial intelligence” refers to several different program types separated into two broad categories — generative and predictive. Of the two, generative AI is a relative newcomer and the core of many of the newest tools and programs, including ChatGPT, which was released by San Francisco-based artificial intelligence developer OpenAI.

“Predictive analytics, machine learning and a host of other approaches have been around for a long, long time,” Donald Davidoff, president of D2 Demand Solutions, told Multifamily Dive. “Generative is obviously getting all the rage, all the buzz with OpenAI.”

As it stands today, multifamily operators are not developing their own AI-based technology in-house. Instead, they look to vendors to develop AI-based products, whether they are startups or existing businesses augmenting their offerings. “It's very much the prevailing view in the C-suite right now that [AI is] something that people are looking to their vendors to bring to them,” said Dom Beveridge, principal of Houston, Texas-based consulting firm 20for20.

Here are a few of the ways that multifamily pros are using AI tools to help streamline their operations:

Leasing and operations

Among the most common and longstanding uses of AI in multifamily is the digital leasing assistant. These tools serve as a first point of contact for prospective tenants, answering questions via website chatbots and in some cases through phone calls, conversing up to the point of booking a tour. Examples include EliseAI, which launched in 2017, and LeaseHawk’s ACE platform, which launched in 2020.

Part of the appeal of programs like Elise is the ability to attend to potential renters or other leads at any time, without the need for a human to answer simple questions. “The industry as a whole has always had a weak spot in terms of the percentage of leads that actually get responded to,” Davidoff said. 

These tools are usually working off of a fixed amount of information, depending on the task, according to Davidoff. If it finds that it can’t answer a question, it will contact a human staff member to take over.

Marketing

Chicago-based real estate firm Draper and Kramer makes use of AI across multiple sectors of its business — including marketing. Jim Love, vice president of marketing and brand, makes use of large language models in order to produce social media content. 

“When we have a press release going out, for example, and we want to fire it off to all of our channels, we can say [to the AI], hey, here's the release, can you give us a quick sentence or two on how to share this, some hashtags? And it takes that extra work step out of it, which is great.”

However, Love says that this tool is not a replacement for the work of a public relations firm. “It’s still in its infancy,” Love said. “It gets repetitive and it has to be guided. But it's very helpful. It speeds things up.”

Advanced searching

One application Love is keeping an eye on is the evolution of AI search. Based on a list of requirements a resident has, an AI search could “write the book report,” in Love’s words, for properties that fit their needs. In order to take advantage of that, Love said, marketers should make sure these AI searches know the necessary details about a given property.

“We can inform that through a lot of the tools we already use,” Love said, “making sure that every piece of information that we can put into the robust advertising is there.”

Data analysis

Multifamily properties generate a wealth of information, from utility data to financial statements. For cases where it would be impractical or time-consuming for a human to process that data, AI data analysis can be used to detect patterns or draw conclusions.

While Davidoff hasn’t seen what he considers a “killer app” for multifamily data analysis, he does anticipate applications where something akin to Microsoft’s Power BI, a data processing AI tool, could make an impact on operational efficiency. “This isn’t game-changing, but it’s material,” Davidoff said. “Those are hours I could spend on something else.”

Review management

Houston-based J Turner Research, a multifamily data firm that specializes in online property reviews, has recently branched into artificial intelligence in order to process and consolidate the insights these reviews provide. The firm’s Einstein tool is designed to categorize reviews by their core concerns or topics, such as customer service or cleanliness, and generate automatic responses to those reviews.

“Before we had this tool, I used to actually go in and try to do this by hand for our clients,” said Turner Batdorf, senior strategist at J Turner Research. “I could do about 100 reviews in an hour. Some of our clients were getting upwards of 1,000 to 2,000 reviews per month. We really tell people that this is their chance to know exactly what residents [think] — the why behind their scores.”

This article is the second in a series about artificial intelligence’s applications in the multifamily sector and the risks associated with its use. Click here for the first article.

Artificial intelligence tools have proliferated quickly over the past several years, with products now available to carry out leasing, marketing and data analysis for multifamily companies. 

Some of the latest AI products run on generative AI, or models capable of generating new data from an existing dataset, such as OpenAI’s ChatGPT. They are distinct from predictive AI, which has been used in multifamily applications for many years, most visibly in the form of chatbots on leasing websites. 

“Chatbots don't create content from scratch,” Donald Davidoff, president of Littleton, Colorado-based real estate revenue consultancy D2 Demand Solutions, told Multifamily Dive. “They interact with users to provide content and answers from its training set."

However, generative AI is still in its infancy, and far from infallible. Mistakes and falsehoods presented by large language model-type AI — known as “hallucinations” — are a common occurrence, and have even made the news in some high-profile cases. The most recent was on Feb. 20, when a bug in ChatGPT caused it to produce gibberish responses to prompts over the course of one night, according to The Verge.

Properly deploying a generative AI tool means understanding what it can and can’t do. Here are some tips for multifamily pros to consider before taking the leap:

Seeing through the hype

AI and its potential capabilities have generated interest across all industries, and multifamily is no exception. 

However, at its core, generative AI produces its results based on patterns in its data set and is currently poor at performing critical analysis, according to Davidoff. This leaves it vulnerable to incorrect conclusions and biases present in its source data, and makes it prone to producing over-simplified, low-quality or very generic text, according to a research paper by the University of Southern California in Los Angeles.

U.S. companies are struggling to provide their workers with information on how best to use AI-driven products. As many as 71% of workplaces have little to no guidance on how to use AI, or when and where it is most effective, according to a recent Gallagher report.

Dom Beveridge, principal of Houston-based consulting firm 20for20, said that he saw a rush of new AI-based products, companies and technologies at multifamily conferences following the launch of ChatGPT in late 2022. However, by late 2023, this was no longer the case. “There was really nothing on offer that people hadn’t been talking about for most of the year already,” Beveridge told Multifamily Dive. 

For now, anyone looking to purchase or implement a generative AI tool should be aware of the true extent of what it can and cannot do — and in particular what it cannot replace. 

“It seems like everybody, or at least many people who are in AI positions, and vendors, they try to answer questions like AI can be used for everything, AI will replace everything,” Davidoff said. “And I use the analogy — you can use a chisel to unscrew a screw. But you can also cut yourself. If you just use a flathead screwdriver, you won’t cut yourself.”

This, of course, does not preclude the possibility of technological evolution. “I’m not going to get rid of my PR firm [right now] and say OK, [AI] can handle it,” Jim Love, vice president of marketing and brand at Chicago-based real estate firm Draper and Kramer, told Multifamily Dive. “But where is [AI] going? I’m excited to see that, because it’s this next-generation tool.”

Understanding AI’s limits

While ChatGPT is the most widely known large language model-style AI, its open-ended nature does not make it the best choice for most business-oriented tasks. “It could do all sorts of inappropriate things,” Davidoff noted.

In these cases, purpose-built artificial intelligence made to accomplish a particular task, and given a much narrower dataset than broader large language models, are better options. 

“They aren’t the open-ended generative AI like ChatGPT,” Davidoff said, referring to tools more specialized for leasing or marketing. “They're working off of a fixed corpus of information, and they're pretty quick to realize, ‘I can't answer that.’... So you don't see those hallucinating, or at least I've not heard of that happening at all.”

Generative AI tools are best-suited for processing very large amounts of data — terabytes and petabytes. Multifamily data sets operate on a much smaller scale. “We live in a world of small data in multifamily leasing on the operation side,” Davidoff said. “We have megabytes and maybe gigabytes.”

The ‘black box’ problem

Another issue with AI is that the tech is what Davidoff calls a “black box” — it can be difficult to tell why or how it made the decisions that it did, or to reproduce its results. “In places where you have very large data, and you're willing to accept black box answers, AI is spectacular,” he said. “But when you have moderate data or small datasets, and transparency and understanding is key, that's a real challenge.”

Given its status in the industry, the misuse of AI is likely to be common in the near future, according to Chris Snyder, vice president of engineering at San Diego-based property management automation company Zego, which uses AI in its digital payment and expense management products. 

“There will be side effects and discoveries about the misuse of AI,” Snyder told Multifamily Dive. “And some high-profile company will do something that they shouldn't have, and it'll make the news and people will reach broader conclusions from that.”

However, while this may breed uncertainty about the technology, Snyder believes the industry will overcome its hesitancy, given the trends of the past. “‘Mobile’ was a buzzword, so was ‘cloud,’” said Snyder. “AI is going to go from a buzzword to a commodity.”

Dive Brief:

• JLL rolled out a proprietary large language model, JLL GPT, to its more than 103,000-member workforce last week. The company’s technology division, JLLT, developed the generative AI capabilities specifically for the commercial real estate industry and is looking to offer the tech to clients in the future. 
• The tool features a conversational interface, allowing users to ask natural language questions similar to other popular models. The decision to build versus partner or buy was motivated by the need for security as well as to have a model trained on commercial real estate data, said Yao Morin, JLLT CTO.   
• “For us in JLL and commercial real estate in general, we really need to be the expert,” Morin said. “There are a lot of data and information that is not available to the general public that we wanted to capture and leverage through the GPT technology and offer to our employees.”  

Dive Insight:

As employees familiarize themselves with the model, JLL is monitoring usage and the number of unique visitors coming in. 

In the first 48 hours following the rollout, more than 11,000 employees used the model, the company told CIO Dive. 

JLL Technologies developed a proprietary LLM to generate relevant information for employees and turn data into insights by fine-tuning it with internal commercial real estate information along with other external data sources. The goal is to augment, not serve as a replacement for employees. 

After initial tests yielded success, the company felt comfortable forgoing gradual deployment.

“It has been overwhelmingly very positive,” Morin said. “We decided to roll it out to the entire JLL because we feel like we have tested it and we really have a lot of confidence in what we have built.”

The company chose not to share certain details related to the development of the technology due to the “highly competitive” nature of AI in the commercial real estate landscape. 

JLL operates in more than 80 countries around the world and brings in annual revenue of $20.9 billion. Before JLL GPT, the company used AI to improve building efficiency, generate 3D leasing visuals, calculate sustainability risks and power investment leads. 

One in five of all JLL Capital Markets opportunities globally was enabled by its AI-powered platform in Q1 2023, according to the company. 

The company expects JLL GPT to initially assist employees with transforming space utilization dashboards into conversations, augmenting client feedback and expediting workplace planning strategies. In the future, the company expects the tool to help with data mining for automated facility management, price modeling and predictions for investors and matchmaking for leasing transactions.

One use case already identified by a JLL employee was using the tool to sift through a lengthy lease agreement to determine whether employees can bring a dog to the office, reducing the length of the task from hours or days to seconds. 

“We will continue to have demos and instructions that help create and explain use cases for our employees,” Morin said. “We also have been evolving our products and we are going to add new features.”

As teams update the model, they will lean on user feedback, Morin said. 

“We are going to continue to evolve JLL GPT so that it gets to the right place for our employees,” Morin said. “Just like any software rollout, you have to go through that phase.”

The company also has more than 40 innovations related to generative AI in development or in beta.

Relying on artificial intelligence to free up site-level personnel — or even replace them — isn’t a new idea in the apartment industry. On the contrary, it has been going on for a while.

Although the concept isn’t new, AI is still relatively new to some operators. Count Phoenix-based MEB Management Services among that group. After adopting Elise AI in early 2022, the apartment operator has seen substantial gains, saving more than 3,000 employee hours and filling in the labor gaps that resulted from the COVID-19 pandemic. The virtual leasing assistant platform does things like provide 24/7 services and coordinate tours for new residents.

Although AI has saved man hours, Denise Trentacosta, senior asset director of MEB, is adamant that the company — which has almost 24,000 properties across Texas, Arizona, New Mexico and Tennessee — is not using the software, which integrates with websites and apps to answer emails, texts, phone calls and chats, to replace jobs.

New software is only one focus for Trentacosta, who supports eight workforce communities in Tucson, Arizona. Here, she talks with Multifamily Dive about technology, the Arizona market and inflation.

This interview has been edited for brevity and clarity.

MULTIFAMILY DIVE: I know technology is a focus for you. What programs intrigue you?

DENISE TRENTACOSTA: Technology that has intrigued me and a number of my peers personally is user-friendly tech and tech that will integrate seamlessly with our property management software. 

We want to leverage technology to improve and increase human encounters coming out of COVID. We've got a segment of the populace that found a way to do things remotely and is happy doing it remotely. We want to support those folks. But for those who prefer to talk to us and look us in the face, we want to enrich those engagements. 

How does that affect on-site staffing?

I can think back to earlier in my career, and the fear coming from tech and, specifically, artificial intelligence was that it was going to be used to replace our on-site office team. And that's not the goal. The focus is to alleviate some of the mundane tasks, to meet those people that just want to do things from a distance and to find a way to support people no matter what time of day it is. 

We can also give back time to our on-site folks to talk so they can talk to people that want to talk to them and not be inundated with some of those other things. 

The biggest goal for us with tech is making sure that it is a smart use of our energy and our resources and that it is of value. It’s not just the conversion ratio and how many calls AI is taking in a day. But the less tangible things — the experience for our team members and the experience for our residents as well.

Have you seen any softening in apartment demand in Arizona?

We definitely have seen a moderation in some of our sub-markets. We've seen what might even be described as a slight softening of rent growth. It's not huge but a plateau. 

We’re taking a pulse from our various crystal balls to understand if we think this moderation is coming in the fourth quarter, which is very typical in Arizona and other major markets across the country. People just want to get in and get settled where they are through the end of the year. And then we see things pick up again in the mid-first quarter. So, we're seeing a moderating typical of what we have experienced in years past.

How are inflation and gas prices affecting your residents?

Gas prices are hitting everyone. They're hitting our residents, which in many cases are also my team members. Our folks enjoy living in the communities that they manage. Those gas prices are impacting the way that they go about life.

We see more grocery delivery trucks than before. Spending $7.99 or $10 to have the groceries delivered to them may not have been a value before, but they're seeing the value now because they don't have to drive to the grocery store multiple times. 

Does that shared experience help team members relate to residents?

We try to draw this line between residents and team members. But when you're talking about workforce housing, they are the same. These are the same folks that are feeling these impacts. When given the opportunity, our team members are ready and willing to have an empathetic chat with our residents. They understand that our residents are feeling the pinch. 

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The business of running a property generates a wealth of information, including maintenance history, utilities payments and leasing performance. 

On its own, this information can be daunting. However, when paired with a business intelligence framework, data can be analyzed in illuminating ways.

For instance, a property management report may not make trends in lease-up obvious. However, if the data in that report is laid over a map of the property, it may be easier for managers to see if one part of the property is not performing as well as another, in an example given by Houston-based multifamily technology consulting firm 20for20 in its recent white paper.

Dom Beveridge, principal of 20for20, sees lots of opportunities for the use of big data in the multifamily industry. 

“I tend to be of the view that everything can be characterized in data,” Beveridge told Multifamily Dive. “And if it can't, at the moment, it's not because it's impossible, it's because we didn't figure out how to do it yet.”

Here, Beveridge talks with Multifamily Dive about how to implement business intelligence systems, findings from his company’s white paper and the potential of artificial intelligence integration.

Note: This interview has been edited for brevity and clarity.

MULTIFAMILY DIVE: How do you define business intelligence?

DOM BEVERIDGE: Business intelligence is a type of application that organizes data and allows you to get value from it. It's different from things like reporting, which just pulls data into a format and produces it for you. 

Business intelligence gathers and stores data in a way that allows you to go and retrieve it to perform whatever kind of analysis that you want.

What are some of the best ways to encourage BI adoption among property companies?

The first order of business for any company that wants to be successful at this is, don't view it the same way that you view rolling out other technology. This isn't like rolling out a payment system or a CRM, because it involves data that sort of transcends everything across your business.

You need a pretty far-sighted view of the kinds of things you want people to be able to do in your company. Which means that it's the job of the technology and business leaders to think about, how do we build the foundation? Is there a product that we can go by externally?

The alternative, if the company's doing well, is to go custom build your own thing. Lots of companies have done that, particularly larger companies. But you basically have to think about, from an enterprise perspective, how do I build this foundation that is going to gather every piece of data from every system that I could be interested in analyzing data from? How do I organize that in one place? How do I make it easy for people to access that data? What tools do I need to build? 

And that's where you've probably heard people talk about things like dashboards. If on the one hand, I'm building this foundational thing that organizes my data, the other thing that I have to do is say, what things do we want to improve about marketing? 

You're sort of marrying this very personalized effort of putting in front of people exactly the data that they need to get things done, which requires that you do this very companywide thing of organizing where all of your data is kept. So that everything has whatever data it needs to support whatever analysis people do.

What are some of the best sorts of applications to start with?

The industry follows this very odd adoption pattern. Companies typically go as far as they can without implementing it. They're just using the reports that you get from their applications. But it's very, very limited in what it can tell you. 

That’s because the thing that I want to know about my business is different from the things that other people want to know about their businesses. So when you're using a pre-canned set of reports that somebody else designed, it's frequently not reporting the thing that adds value to you. 

So they'll go and buy a business intelligence product off the shelf. That works for a while, but they always outgrow it. If you're trying to be a data-driven organization, the stuff that you buy off the shelf from your PMS vendor is never good enough, ultimately. And what people tend to do is to go and design their own data model, or they do it with things like Microsoft tools. 

Designing a data model is a really big undertaking. Then you have to build it, then you have to deal with all the integrations into the platform, and so on. So it's very costly in both time and money, but then you have a really good capability at the end of it. 

What are some ways in which AI can be included in these models?

The thing that you always have to be cautious about in multifamily is that because we have 12-month leases, the number of pieces of data that a property generates is really small. And what you find with AI is, it's extremely good at dealing with really big problems.

We don't have particularly big data problems in multifamily. They're mostly quite small. AI is good at looking at a really large set of data and saying, “Well, these things tend to correlate with people that renew and these things tend to correlate with people that don't.”

It has the potential to find things out that you otherwise wouldn't. And so that potentially gives you the opportunity to get better at predicting who is going to renew and who isn't. And that makes your business more predictable, which is potentially a useful thing in managing your business. 

The jury is very much out on whether AI is going to give you a better answer to those questions than many of the [tools] that we're already familiar with. Those are some of the things that people are working on, how much better it is and how much value that improvement adds. That's far from settled right now.”

Chicago-based Daniel Management Group oversees a range of property types, from urban to suburban and large communities to smaller buildings. 

The firm, which manages apartments throughout Chicago and Wisconsin, is seeing a rising desire among tenants for more space, making townhomes and single-family rentals soar in popularity. 

Communities with private garages and entrances are getting a lot of interest as renters seek privacy along with the maintenance-free lifestyle of apartments, according to DMG president and founder Roger Daniel. As the spring leasing season approaches, Daniel expects residents to be drawn to properties that can deliver on these trends.

“Our staff is engaged with residents and potential residents to have a thorough understanding of trends, desired amenities and market demands,” he said.

Here, Daniel talks with Multifamily Dive about other trends in his markets, the rise of artificial intelligence and challenges for the new year.

This interview has been edited for brevity and clarity.

MULTIFAMILY DIVE: What are you seeing in terms of trends in your markets? What do renters want this year?

ROGER DANIEL: Throughout our portfolio, we are seeing several key trends. First off, there is increasing rental demand in the suburbs. We are seeing this demand driven by either residents who are downsizing or young families and couples leaving the city. 

These renters are searching for suburban-specific amenities including green space and more outdoor areas with grills and fire pits. 

Also, we are seeing demand for spacious units with private entrances and garages that allow renters to feel like they have a single-family home, but with all the benefits of maintenance-free apartment living.

Other trends we’re experiencing are a growing demand for package delivery, storage and the ability for tenants to enter their apartments through an app on their phone or a key fob.

What types of technology do you rely on to provide your management services?

Technology has become integral for property management for efficiency for us and ease of use for our residents. DMG residents depend on an online portal for all their rental needs, including payment, work orders and any communication to property management.

Additionally, we are integrating virtual tours into the leasing process. The digital walkthroughs allow potential residents to get a sense and view of the property and unit quickly and efficiently.

Lastly, on the management side, we leverage artificial intelligence technology to detect and combat fraud and manage residents’ renter insurance. This allows us to focus our time on engaging and serving the residents.

What are some ways you plan to use AI? 

DMG is looking to integrate AI into its leasing process. For example, AI could be the initial contact for leasing prospects.  We are currently using AI to help screen potential residents to ensure they are not applying fraudulently. We look forward to continuing to find ways to use AI this year.   

Is electric car charging important for your properties?

EV chargers are becoming a staple for all new properties we manage. As electric cars are increasing in popularity, we recommend that properties offer the charging if the ROI is there.

What are some of the biggest challenges you face in this new year?

As we enter the new year, there are new challenges. AI is an universal disrupter and that is also the case in multifamily property management. We are focused on looking for ways we can integrate AI into our day-to-day operation to help DMG execute more efficiently and allow us to continue to deliver our unyielding attention to detail and a professional, service-minded management style.