Artificial intelligence is already reshaping apartment maintenance, but multifamily operators are approaching it cautiously. They’re using the technology first to analyze inspection data, improve reporting and support decisions, rather than expecting software to outright replace technicians, experts told Multifamily Dive.
At Greystar, for instance, AI is being applied through a closed-source enterprise platform across several maintenance functions. The company uses the technology to analyze inspection and compliance data for trends and to create internal tools and communications that help teams work more efficiently, according to Richard Regitano, Greystar’s managing director of maintenance, facilities and engineering.
“One of its most valuable applications is synthesizing inspection data so field teams and company leaders can move more quickly from information to action,” said Regitano. “We’re still in the early stages of integrating AI into maintenance operations, but we’re seeing forward progress every day.”
CAPREIT sees potential across an even broader portion of the maintenance lifecycle. The firm believes AI could use camera data during apartment inspections, validate the age and expected service life of appliances, track warranties and service requests and support predictive spending.
“AI in maintenance operations offers one of the largest and most straightforward uses of AI,” said Savas Karas, CAPREIT’s chief technology and transformation officer. “AI can be a valuable tool in the maintenance lifecycle.”
Other operators are still determining where to begin. RPM Living has started exploring platforms that could improve reporting, provide stronger operational insights and give leaders better visibility into real-time maintenance activity, but it has yet to select or implement a system, according to Cerwin Thompson, the company’s vice president of facilities.
Operators seek proof before scaling
For now, the business case for AI remains a work in progress. Greystar has asked field and regional teams to submit ideas and best practices that can help identify where AI could have the greatest impact.
That measured approach is especially important across a portfolio as large and varied as Greystar’s, Regitano said. AI brings real costs and a learning curve, so the company is testing applications that provide clear value and remaining flexible when the technology does not yet fit.
RPM is taking a similar approach during its evaluation.
“It’s definitely not a small investment, but we see it as an important opportunity to improve the way we work and support our teams,” Thompson said. “If the right solution helps us do that, it’s an investment we’re willing to make because delivering a great experience for our clients and residents remains our top priority.”
At CAPREIT, calculating a return remains difficult because operators do not yet have enough data, Karas said. Training and data collection will be essential, as will ensuring the information feeding an AI platform meets the company’s standards.
“As we collect data and compare it to our operational goals, I am confident AI will have a positive return on investment,” Karas said.
A multiplier, not a replacement
Although AI may help companies operate more efficiently, most operators are not deploying it as a headcount-reduction strategy.
For instance, Greystar views AI as “an addition and a multiplier, not a replacement,” Regitano said. Its near-term value lies in giving employees better information and tools so they can make faster, smarter decisions.
RPM likewise expects technicians to remain indispensable at the property level. The company hopes AI will eventually remove repetitive paperwork and streamline administrative work, but Thompson emphasized the limits of the technology.
“AI is a great tool, but it’s not a replacement for a maintenance team member,” Thompson said. “At the end of the day, AI can’t complete repairs or turn an apartment.”
Predictive maintenance is the next frontier
The next major opportunity is moving from analyzing current conditions to anticipating problems.
Greystar is working toward analysis and modeling across its service history so AI can identify recurring themes, flag likely equipment failures before residents are affected and give frontline workers more detailed recommendations. The company is also exploring the use of robotics and AI vision for inspections and hazard analysis.
CAPREIT’s interest in appliance life cycles, warranty tracking and predictive spending points in the same direction. RPM’s immediate wish is more basic: technology that can reliably reduce paperwork without creating new burdens for maintenance teams.
The differing approaches suggest that AI adoption in apartment maintenance will likely be incremental. Operators want better data and faster decisions, but they are still testing where the technology produces measurable value and where human judgment and hands-on expertise remain essential.
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