Why AI Could Be a Property Manager’s New Best Friend
Experts weigh in on three major areas where AI can help in operations.
As AI technology continues to evolve, property managers are finding new ways to add it to their toolboxes, in both a figurative and literal sense.
According to McKinsey & Co.’s State of AI in 2025 survey, 88 percent of 1,491 respondents across the globe have adopted the technology in some capacity, and 64 percent say that the technology is driving innovation.
In the multifamily industry, generative AI has become an essential feature in enhancing the resident experience and making the lives of property managers easier. Whether they’re chatbots that liaise with current renters and prospects or GPTs that scan and analyze documents, there are plenty of ways to implement AI for resident use and innovation.
But how can stakeholders determine which uses of AI are optimal for them?
Step one is to decide is what you want AI to accomplish and then ensure that team members are on board for implementation, suggests Yatina Katunga, an emerging technology analyst at Cushman & Wakefield.
“People used to think you could use AI very broadly,” she told Multi-Housing News. “When you do this, there are problems with accuracy. There are so many models now that you need to understand exactly what you are trying to achieve because, as we’ve found, AI is not one-size-fits-all.”
Katunga identifies lease management and property maintenance as two areas where AI adoption can make significant impact. Property managers are already seeing results when using AI for these purposes.
Leasing made easier
Leading industry executives view AI as an additional tool for key property management tasks, rather than as a replacement. At RKW Residential, property tour requests have increased 9.2 percent since the company started using the technology to help identify leads.
“AI allowed us to expand our coverage and improve our speed of response, which allows our teams to focus on the high-value, relationship-driven parts of their job,” reported Kevin Owens, the company’s president of property management.
Draper and Kramer uses an AI chatbot at a similar stage in the leasing process, automating responses to common prospect questions about such topics as rent, amenities and pet policies. This allows leasing teams to focus on personalized interactions with qualified leads.
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“It acts as a level of prequalification, since prospective residents are easily able to get information that helps them decide if a property is—or isn’t—a fit for them,” noted Tim Kramer, the firm’s vice president & director of operations.
Using technology to field these questions frees up time for leasing teams to spend on other tasks. Cushman & Wakefield also uses AI to scan lease documents in order to identify key clauses and anomalies.
AI is beneficial for property tours, as well. The technology provides the prospect with an initial opportunity to learn about a community. Then it can help schedule the tour, follow up and help provide links, as Marquette Management President Jim Cunningham pointed out. That’s allowed team members to utilize their time for other tasks, such as building relationships with residents and handling other requests.
Streamlined work orders
Property managers are increasingly turning to AI to streamline the work order process, thus reducing delays and easing the strain on maintenance teams. Resident requests that don’t go through properly create headaches for residents and the management team alike. RKW is exploring ways for the technology to help balance workloads and accelerate completion times for work orders, which can even be submitted after hours and distributed to technicians immediately. According to Owens, this ensures that “the right people are doing the right things.”
While the initiative is still in early development, Owens predicts that it will become essential to RKW’s maintenance operations. “We believe that over time, we’ll be able to implement something where work orders come in, and based on the skill set of the team, those assignments will be automatic,” he said.
Marquette is also exploring how AI can help residents request work orders and diagnose issues. By gathering detailed information, AI can provide maintenance staff with background before they start a job. Sometimes it can resolve a problem without dispatching a technician.
Kramer suggested a chatbot that enables residents to start by reporting an issue. In theory, the company could have “(an) AI attendant in place to provide a first response on basic maintenance requests and answering questions on things where, theoretically, the resident could troubleshoot or resolve the issue on their own,” he said.
This approach can help residents fix minor issues themselves—reducing wait times along the ways—while freeing maintenance technicians to prioritize more complex or urgent repairs.
Becoming more proactive via AI
An emerging feature of AI in multifamily operations is predictive technology models. AI systems are becoming more proactive as they analyze sensor data, asset usage and work order history. That identifies issues before they are detected by staff or felt by residents.
When used to submit work orders and identify problems in a portfolio, the model can learn to signal a current operating problem or a potential issue. That raises the intriguing question of how predictive maintenance will shift the focus from reactive to proactive ways of keeping up with equipment and avoiding system failures.
Predictive models can calculate the life expectancy of HVAC and other systems, which can prolong their usage and help cut maintenance costs. Additional benefits could include less downtime, more efficient vendor deployment and improved resident satisfaction.
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Other industries have benefited from using AI to monitor systems, identify trends and detect early signs of failure. The most effective approach is repairing or replacing components only when needed, rather than relying on predetermined replacement cycles that can drive up expenses, Kramer advises.
“Due to the wear and tear involved in taking apart and inspecting a component, performing maintenance proactively on a periodic, arbitrary schedule can sometimes ultimately lead to more maintenance than if we were able to predict exactly when service is necessary,” he commented.
This shift allows property managers and maintenance teams to stay ahead of potential problems in a more cost-effective way that doesn’t always require retrofitting entire systems.
“I think that’s going to be the game changer,” said Owens. “It’s in the early stages, but when we can predict what work may be needed and can handle it, we will be able to be more efficient and avoid getting into an emergency situation.”
