Top 10 Uses of AI in Multifamily

We turned to experts to find out how artificial intelligence is reshaping the rental sector.

Multifamily is and has been, no doubt, long dependent on people-driven processes. Given a problem, the industry has invariably appeared more comfortable “throwing humans at a process than throwing technology tools at it,” observed John D’Angelo, real estate solutions leader & managing director at Deloitte.

AI House Shutterstock_1660696504 Today, this opens considerable opportunities when it comes to eliminating mundane, rule-based tasks. In turn, this leaves humans freer to tackle the reasoning behind actions, while bots can take over the repetitive, workaday chores. Artificial Intelligence will enable this tectonic shift, D’Angelo reasoned.
 
AI is going to impact all asset classes and all elements of the real estate process. It won’t be one application creating efficiency, but myriad advances in machine learning, deep learning, natural language processing, image recognition, autonomous devices and generative AI, said James Scott, director of the Real Estate Transformation Lab at the MIT Center for Real Estate in Cambridge, Mass. “And it is only set to become significantly more important as the technology evolves and is adopted,” he added.

Multi-Housing News talked to industry experts on how AI will soon—and is already—being used in multifamily. Here are the top 10 ways for the industry to implement AI right now.

1. Streamlining the makeready process

One multifamily company studied the individual steps required to get an apartment ready to be rented again, recalled D’Angelo. Using analytics to determine where the process slowed, the company realized obtaining stoves or refrigerators often took longer than needed.

“It caused them to look at other places to gain inventory,” he said. “They cited some really meaningful reductions in time and cost in the makeready process. If you shave days or costs off the process, it pretty quickly pays for itself in hiring the data analytics and process rigor.”

2. Promoting to prospects

Chicago-based Draper and Kramer is using machine learning in its marketing efforts to gain a larger audience, personalize messaging and improve marketing efficiency, reported Jim Love, vice president of marketing and brand.

“We can see all the behavioral data and buying signals on prospects,” Love said.

“Everything they click on and scroll down to is scored. The higher the score, the more AI is going to target ads for that person. It cuts down on costs because it’s taking less time and money in ad placement to find out what prospects are showing buying signals.”

3. Revenue management

AI will power the next generation of revenue management systems, which will have the potential to be much more powerful than current solutions, said Tess Gruenstein, senior vice president of acquisitions and portfolio management for Bailard.

“It should drive results to the topline,” she added. “There are some early applications doing revenue management …. It’s kind of seamless from the operator’s perspective.”

4. Writing copy

When managers wanted to promote a just-concluded community event on their property’s website, they had to generate short copy and photo captions about the event themselves. Draper and Kramer found generative AI can assume that task.

“The property manager has so much to do,” Love said. “The generative AI can write a nice clean piece of copy about what the event entailed from just a few prompts.”

5. Generating alt text

Alternative text assists in making websites accessible, including for people with disabilities. That’s what makes AI’s ability to create alt text the favorite AI tool of Nomo Nagaoaka, Yardi RentCafé project manager.  For example, a blind renter needs a description of every image.

“Most times that’s easily missed, and we want to avoid that because we want websites accessible to everyone,” he added. “When clients upload images, we have a tool that automatically generates alternative text to describe the images. That appears with the image, on the side, automatically. It saves a lot of time for the staff.”

6. Promoting proactive maintenance

AI can anticipate when repairs or replacement may be needed before an appliance actually breaks down, Gruenstein said. For instance, the technology can predict when an AC unit isn’t working to full capacity and requires replacement.

“It can take care of issues in advance, so you don’t have to do costly repairs and maintenance at odd hours, inconveniencing the residents,” she said.

  

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7. Gaining leasing efficiencies

Mundane, repetitive steps have long defined leasing. AI tools such as chatbots can assume those tasks, from setting up prospect appointments and tours to following up.

“In multifamily, the processes are voluminous and pretty consistent,” D’Angelo said. “Chatbots in leasing are not a new application. But the chatbots have gotten so much better. Buying them in the software makes them so much more accessible.”

Eric Brody, managing partner for New York City-based early-stage proptech investment fund ANAX Ventures, agreed leasing is a natural for AI. “What do you need from my license? Do I need a W2?” he asked. “Ninety-five percent of interactions you need could be automatic by using language models to drive the prospect through the funnel.”

8. Speeding underwriting, transactions

Manually extracting and compiling data and sorting large volumes of information made underwriting tedious and error-prone. AI can rapidly analyze data and historical trends to gain a better sense of the markets and individual property performance.

The result, said Dan Kodzi, CEO of Miami real estate developer Royal Palm Cos., is “more accurate predictions for the future, allowing for more efficient capital allocation and portfolio diversification.”

9. Empowering digital twins

Combining computer automated design with sensors and IoT devices, digital twins can more accurately depict a project, delivering multiple benefits, Kodzi said.

The gathered data can produce predictive insights across property management and project development, pinpointing opportunities for substantial energy savings over buildings’ lives. It can even predict what amenities residents will actually use, helping developers gain a better grasp of resident wants and needs.

10. Helping multifamily sellers, investors

For multifamily property sellers, AI can more efficiently create customized marketing campaigns targeting acquisition-minded investors, Kodzi said. In turn, multifamily investors can conduct AI-enabled searches of properties falling within given parameters, size up properties’ levels of risk and anticipate value over time, he added.

AI is too powerful a tool to dismiss, Love concluded.

“It should be embraced today before all the things in test become mainstream. If you start using it next year, you’ll already be behind. It’s advancing so rapidly that it will be mainstream faster than imagined.”

Source: Multi-Housing News