It’s a new year, and one in which things will continue to move quickly in multifamily technology. We’re kicking it off with a brand new study in an area that will dominate our thoughts and plans this year and beyond.
Today, we’re releasing a new paper titled “Automation: The Real Story of AI in Multifamily.“ The paper reflects something I’ve been noticing over the past 18 months: the adoption cycle for AI in multifamily is changing. What we once thought of as technology for handling rote tasks—like answering leasing calls—is spreading into many areas of what we traditionally consider property management. And in different and surprising ways.
Time to stop thinking about “AI”
We’ve all experienced AI hype. A glance around the trade show floor at the recent RETTC OPTECH would reveal AI in most technologies. It is clearly part of any technology’s narrative to potential investors. But for those of us interested in how it might change multifamily operations, it’s getting less and less helpful to think about “AI” as a tech category. It’s better to think more clearly about the real sources of value that the tech is helping operators exploit.
In the case of operational AI applications—i.e., those that are involved in tasks that traditionally fall under property management—the source of value is automation.
That’s an important difference for a couple of reasons. First, an increasing number of activities are being automated. And second, automation is moving beyond rote tasks and into the domain of decision-making. That is the trend that will have the greatest impact on how we run multifamily real estate, and based on this latest research, it is already starting to change some multifamily organizations.
A confluence of innovations
Several important factors have emerged over the past 18 months that have changed the adoption cycle for automation. One is the increasing maturity and adoption of voice AI in multifamily service delivery. This was a clear finding from the 2025 edition of the 20for20 annual survey: operators saw several clear use cases where voice agents are better than text-based ones, and believed that the technology is now ready to be customer-facing.
That adoption trend appears to have accelerated over the past year - this latest research draws on real-life examples of operators who have radically transformed prospect and resident communication.
The other interesting trend is the rapid adoption of delinquency management. For most of the history of AI in multifamily, AI has primarily focused on leasing, where it has proven an excellent solution to the problem of answering the phones and nurturing prospects to book a tour.
On the surface, delinquency looks similar: reminding someone to pay rent doesn’t seem so different from prompting someone to book a tour. But there is a critical difference: leasing conversations end once the prospect makes their decision. Delinquency, by contrast, is a recurring, monthly process that involves existing residents. That changes a lot about adoption.
Once operators see that AI-driven delinquency interactions work well and deliver better outcomes than fully human-based processes, there is a natural pull to change other parts of the operation (think service, renewals, maintenance, etc.) as well. That pattern of adoption is becoming clear, and it is reflected in the stories in this new research.
Change is coming!
These trends have important implications for the future of property management work, though not quite in the ways many of us expected when the AI conversation first began. A frequent theme on this blog is how multifamily operators tend to look for technologies that solve problems with which they are already familiar (the “widget” mindset). For many, this consigns AI to rote tasks like phone-answering and lead-nurturing.
What is more exciting is that as AI-enabled automation spreads, organizations become more knowledgeable about their properties and their residents, which opens up new possibilities for what automation can do.
Because so many resident interactions are now digital, and because we retain far richer information about what customers want and how they feel, AI is increasingly able to recommend—and in some cases enact—decisions that lead to better resident outcomes and, ultimately, stronger performance.
That enables us to understand more, act more nimbly, and rethink what we mean by “repetitive” or “routine” work. Ultimately, this shift is already changing organizations and even how people think about software itself.
That is the substance of an important new study for 2026 that takes stock of the most significant technology trend right now. Download your free copy today, and, as always, please find me with your feedback. This will be the biggest operations and technology conversation for 2026 and beyond!
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