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.”
