One of the biggest risks with any emerging technology is that potential customers will fail to see the improvement opportunity the technology offers. With transformational technologies, the risk is particularly acute, as potential users may struggle to imagine the impact on today's business.
There is a name for this cognitive bias: "Functional Fixedness," which prevents people from seeing an object as having a use beyond its most traditional or expected one. Unsurprisingly, it can have profound effects on tech adoption. When electricity was first introduced, many people saw its purpose as replacing oil lamps with lightbulbs. When computers entered the office, many saw them as expensive typewriters. The list goes on and on.
The "Widget" Mindset
For many operators, the adoption of AI-enabled automation is beginning to look similar. For years, the tech stack has been an accumulation of "widgets"—point solutions that solve familiar, narrowly defined problems. That mindset made sense in the early days of AI adoption. Companies bought digital leasing assistants because such a high proportion of phone calls went unanswered, and AI offered a reliable solution to that perennial problem.
Digital assistants have delivered efficiency to operators, but they have the characteristics of widgets. They are point solutions to a problem with which customers are already familiar. The problem with that thinking is that AI is a technology that does not naturally stay in its lane. Once an AI has mastered the execution of a process, there is little to stop it from improving the process itself and addressing similar, adjacent ones.
We are seeing this play out as multifamily operators change their operating models. As 20for20 has been reporting for the last few years, it is administrative tasks (predominantly associated with assistant community managers) that have been the leading edge of centralization. A previous article in these pages describes the emergence of separate teams specializing in areas like delinquency and retention.
These central teams are organized for an environment where AI handles most of the day-to-day work. As AI has spread across resident interactions—delinquency, renewals, service requests—it has been generating datasets that never existed before. AI chat produces enormous volumes of words, and in those words lie insights that—when harnessed—can unlock new sources of improvement.
A Gold Mine of Insight
The conversations that residents are increasingly having with digital agents create digital records of causality, showing how service quality drives outcomes across processes. With far greater insight into resident sentiment, AI can identify better ways to deliver outcomes even if that means crossing conventional operational silos.
Renewal conversations, for example, don't just speed up decisions; they shed light on resident experience and the extent to which it influences renewal decisions. Renewal conversations tend to be about more than just renewals, as residents share service issues that are long-standing in many cases. When an AI tasked with managing renewal conversations repeatedly notes hesitation related to service issues, its natural reaction is to try to resolve them.
Operators are finding that the renewal process becomes longer and more proactive as the AI seeks to identify issues rather than letting them fester until the renewal offer arrives. That challenges some long-standing habits. Operators often incentivize maintenance teams in part based on retention rates, but proactively addressing service issues a long time before the renewal decision is a different way of planning maintenance.
The Coming, Agentic Era
AI is no respecter of organizational silos. As AI becomes more agentic—i.e., able to propose and even execute decisions on how to improve its own processes without human intervention—such cases will become more common. That is one of the many reasons the continued erosion of multifamily technology categories seems inevitable. Seen in this light, the widget mindset looks increasingly backward.
Agentic AI will change technology substantially. Software traditionally works on the basis that humans design processes and workflows and encode them in the technology's workflows. In the age of agentic AI, the software can and will identify better ways to execute processes. The value is not in replicating existing tasks (like answering the phones), but in improving how those tasks and previously unrelated ones are organized, generating new sources of competitive advantage.
Multifamily technology buyers love a widget, but operators who continue to buy their technology that way will be left behind. The era of the tech widget is drawing to a close. The future lies in self-improving systems—technology that creates intimacy with residents at scale and delivers long-term competitive advantage to those willing to grasp the opportunity.
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