Artificial intelligence (AI) is making its mark on every industry and the real estate market is no different. As more AI solutions present themselves, experts say using AI solutions in property management should be done with clarity and intent.
"While real estate is fundamentally about people, it's always been powered by data – and now, that's being further enhanced and managed by AI," says Carla Hinson, vice president, North America Solution & Innovation for MRI Software, a real estate technology company.
Hinson notes that as property owners attempt to fulfill the promise of AI in their business, realizing success right away requires understanding how AI can help and implementing it in a strategic fashion.
AI is Changing Property Management
Data analytics and market trends have always been a cornerstone of the residential real estate market, but for property managers, AI is becoming a gamechanger. Hinson says AI can identify patterns in resident lifecycle data to predict renewal likelihood or potential delinquency risk. It can also improve operational prioritization and flag patterns indicating systemic issues, further enabling proactive capital planning.
Hinson says AI can effectively analyze key areas including:
● anticipating resident turnover before lease expiration;
● identifying operational cost inefficiencies across properties; and
● improving leasing velocity through better lead scoring and response timing.
As AI helps to improve retention and service reliability, even small gains in occupancy can equal palpable financial impacts.
"AI enhances decision-making in residential real estate by connecting two critical layers: resident behavior and operational performance, which lead to better financial results," Hinson says.
Implementing AI Solutions with Intent
When introducing AI solutions, Hinson advises property owners to do so with clarity and frame it as a multiplier – not as a replacement for people. Emphasizing its ability to streamline reports, processes, and workflows, AI can actually increase time and efficiency for both managers and tenants.
Also, she recommends piloting AI in a clear, "high-friction" area to help build engagement and trust among stakeholders, noting that multiple AI initiatives at once can create "change fatigue." From there, testing and feedback can occur, adjustments can be made as needed, and as teams see AI improving resident satisfaction and easing workload, adoption becomes organic.
"AI is a tool to enhance service and decision-making, not remove the human element that defines property management."
Scaling AI Solutions Across Portfolios
While Hinson is a fan of "start small, prove value," she recognizes that owners will eventually look to scale AI across portfolios. To do so, the process(es) must achieve operational maturity and data consistency.
She says it's also important to find "regional alignment" that takes into account regulatory environments and demand drivers; governance and accountability, including compliance with housing rules; and training and change management to assist managers in using AI insights in their daily decisions.
"The goal isn't to automate every property. It's to replicate proven use cases across similar asset classes with discipline and clarity," says Hinson.
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