How Apartment Operators Are Using AI to Find Lost Revenue and Cut Response Times

For multifamily owners, the most consequential use of agentic AI may not be simply saving staff time. It may be its ability to expose the operational leaks that erode net operating income.

Apartment operators are beginning to use AI agents to identify missed resident charges, accelerate lease audits, respond to prospects after hours and flag cost anomalies before they become larger problems. The result, executives say, is a faster and more direct view into whether a property's performance reflects market conditions or shortcomings in day-to-day execution.

That distinction matters to investors. In a market where revenue growth can be harder to achieve, the ability to recover charges already written into leases, improve leasing follow-up and catch avoidable expenses can have a direct effect on NOI.

From Task List To Operating System

When WinnCompanies began examining agentic AI about a year ago, its task force expected to identify 20 to 30 potential uses. Instead, the group found more than 220, Anne Hollander, the company's vice president of AI and innovation, said this week at Realpage's RealWorld conference in Denver.

For WinnCompanies, which has a 121,000-unit portfolio, the opportunity extended well beyond automating isolated tasks. The company had been spending at least two hours each day analyzing data, Hollander said, before it began using AI agents.

The work required a different approach to data, including models for organizing and managing it, as well as governance around its use. But the technical rollout moved quickly.

After beginning the process on a Tuesday and exchanging about five emails with the Realpage team, WinnCompanies met with the vendor on Friday morning. Within 22 minutes, data was flowing into the company's data lake, Hollander said, and regular data refreshes followed 15 minutes later.

That data now supports functions across the organization, including leasing, maintenance and analytical report writing.

Faster Leasing And Revenue Recovery

At United Apartment Group, the immediate case for an AI-driven platform was tied to leasing activity and staff capacity.

Lori Oden, the company's executive vice president, said United Apartment Group switched to the platform on May 1. The company's prospect-to-lease conversion increased by 8.2%, while the platform saved 1,464 staff hours, largely through after-hours work.

Its AI agents recorded 2,145 interactions, 40% of which occurred after hours. For apartment operators, that is a meaningful measure of where automation can supplement onsite teams without requiring staff to remain available around the clock.

The company also found and recovered thousands of dollars in missing resident charges. That outcome points to a broader investor takeaway: AI's value may be less about replacing people than ensuring that leasing and resident-account processes do not leave contracted revenue uncollected.

Moving Beyond Spreadsheet Management

At Summit Property Management, Chief Operating Officer Char McCurdy said the company had been relying on layers of spreadsheets to manage information across its operations.

AI has shortened that process. The company can now complete full lease audits in 90 minutes, compared with the 1.5 days the work previously required, McCurdy said. That faster review process has helped the company identify resident charges included in leases that it could recover.

The more important benefit, she said, is the ability to bring the most relevant operating metrics forward quickly. Rather than forcing teams to sort through data and debate its meaning, the technology can help clarify whether an issue is rooted in the market or in operations.

For owners and asset managers, that can make a difference in how quickly they respond to a property's performance. A market-driven occupancy or rent challenge calls for one strategy. A problem tied to leasing follow-up, missed charges, maintenance execution or expense oversight calls for another.

A Clearer View Of Property Performance

The value of faster analysis is especially apparent when costs begin to move unexpectedly.

McCurdy said she recently used the technology during an investor meeting to show within minutes that a leak was causing a spike in utility costs. The company was then able to take action quickly.

That example captures the emerging investment case for agentic AI in multifamily operations. The technology is not merely producing more data. Its potential lies in helping operators turn data into a timely explanation of what is happening at a property and what should be done next.