By: Dennis Harrington
From leasing to maintenance, artificial intelligence promises transformation for apartment operators, but industry leaders warn the road ahead requires patience, pilots, and education.
The golden vision that artificial intelligence (AI) expects to deliver by 2030 is breathtaking. Name the multifamily business segment: leasing, resident experience, maintenance, or revenue management. All are likely to be transformed within the next five years.
There’s just one catch. The path to those AI-powered dreams is likely to be challenging.
That’s the takeaway offered by four industry technology leaders well-positioned to know:
- Marcie Williams, chief strategy officer for Bainbridge Cos.;
- Scott Berka, senior managing director of brand and customer experience for Greystar;
- Jordan Kobert, senior managing director of digital technology for Greystar; and
- Kevin Donnelly, executive director and chief advocacy officer of Real Estate Technology and Transformation (RETTC), an affiliate of the National Multifamily Housing Council.
Each expert is extremely bullish on AI’s potential. However, that enthusiasm is tempered with terms like “just scratching the surface,” baby steps,” and “infant stage” to describe the road ahead.
Donnelly cautions, “We’re still at the very early stages of seeing how and where AI will be used. A lot of education has to take place first.”
Bainbridge’s Williams adds, “We’re seeing measurable return on investment on several applications, but we are still exploring use cases and piloting solutions. Integration with legacy systems and change management remain hurdles.”
The rapid rise of AI chatbots offers a preview of coming attractions. In a single year—from 2024 to 2025—the use of an AI applications in multifamily property management surged from 21% to 34% according to a recent survey.
Pilot Power
The march to AI ubiquity should be a measured cadence, advises Greystar’s Berka. “We’re excited by what we see in early pilots. But we’re also patient. We want to make sure any new AI tool is measurably better than the current process and creates a better resident experience before we scale it.” Greystar focuses each pilot on three factors:
- Business outcomes;
- Time savings; and
- Customer satisfaction.
Similarly, Bainbridge goes into their pilot programs with definitive KPIs and timelines, reports Williams. “We select a few properties with diverse portfolios and then examine success metrics (e.g., lead conversion, maintenance response time) with traditional methods, along with feedback from residents and the onsite team. It’s very methodical.”
Education Imperative
RETTC’s Donnelly appreciates the walk-before-you-run approach of industry practitioners. In fact, he believes it’s time for many multifamily owners/operators, technology advisors, and investors to tune out all the consumer hype surrounding ChatGPT and global AI competition and double down on education. “Behind closed doors, many owners and operators admit they don’t understand the fundamentals of AI,” explains Donnelly. “They ask, ‘How does this technology actually work? How should we apply it to our business?’ We’re so early in this.”
He cites the cautionary tales delivered by the continuing public policy debates surrounding data privacy and social media.
“If we want to capitalize on AI for the long term and have it really benefit renters, then we need to start with education,” Donnelly asserts. To that end, the RETTC plans to make an announcement at the OPTECH event in Las Vegas, Nov. 17 to 19, designed to help speed responsible AI development.
Hyper-Personalized
What makes the challenges of early-stage development so worthwhile are the resident benefits it portends. Call the next service phase of AI hyper-personalized, white glove, or platinum-grade. AI will help power even deeper apartment community bonds.
“What excites me the most is the space AI creates for one-to-one human interactions,” observes Greystar’s Kobert. “When we talk to residents, the reason they love their community comes down to personal connections. They feel they’re being cared for, that they belong here.”
Williams echoes the observation. “For Bainbridge, it’s the ability to scale personalization and efficiency simultaneously. AI allows us to deliver boutique-grade service across our portfolio, creating consistency and a high-quality customer experience.”
The Promise of Agentic AI
Donnelly likes to look even further down the road, a day when AI has the back of leasing and frontline staff in ways scarcely imagined today. Welcome to agentic AI.
Agentic AI focuses on autonomous action and decision-making, often using external tools and data to achieve complex outcomes. “It’s the next chapter of AI,” Donnelly predicts.
Greystar’s Berka imagines a day when:
- A resident reports an issue, and AI triages, schedules, and follows up;
- A prospective renter shops across the housing brand network, receives tailored recommendations, and signs a lease without having to research many different sources and sites; and
- On-site teams focus on meaningful human interactions, allowing AI to handle repetitive work.
How should you approach your AI journey? Williams suggests you think small, focus on one pain point, and then test a solution with a pilot. “Involve your team early. Make sure they understand the ‘why,’” she advises.
Donnelly recommends you embrace the technology and not be intimidated by it. “But be clear-eyed by the issues it may pose in a still unsettled regulatory environment. Lean into peer-to-peer exchanges for ideas and advice.”
Berka seconds the collaborative approach. “Don’t go it alone. The best AI results come from pure data and deep partnerships with your property management system and customer relationship management providers.” he offers.