The State of AI in Property Management Report: Explore the Paradigm Shift in Property Management
Artificial intelligence (AI), while still in its infancy, is steadily becoming essential in today’s business world. Although there are some uncertainties, business leaders and teams are eager to harness AI to drive growth and optimize operations. To explore how the property management industry is adapting to this technological revolution, AppFolio conducted over 20 hours of interviews with property management professionals, compiling their insights into the State of AI in Property Management Report. Here are some key takeaways.
Communications Is the Top Use-Case for Now
Expanding on earlier AppFolio research that found resident communication to be the most common use case of AI in property management today, interviewees for the State of AI in Property Management Report discussed how the technology is already leaving its mark on leasing operations. As one interviewee explained:
“I can’t answer every single email and every single phone call, and I hate having to check my emails and voicemail every 30 minutes.”
According to one interview participant, AI-powered leasing assistants “work 24/7, through the holidays, and never get sick.” The result?
Beyond leasing, generative AI tools such as ChatGPT and AppFolio Realm-X can produce professional emails and other forms of written communication instantly. The technology is also a game changer in its ability to help break language barriers. For example:
Data Analysis and Data Entry in the Blink of an Eye
AI can analyze data — identifying trends, discrepancies, and patterns — in seconds, offering insights that humans might overlook or take hours to discover. One participant uses AI to project profitability based on credit score requirements:
When it comes to large-scale manual bookkeeping, many interviewees are excited about AI’s ability to process invoices. One interview participant said:
Or if you’re part of a vertically integrated property and investment management operation, AI can give back hours of your life by aggregating, normalizing, and visualizing large amounts of property and asset management data.
AI Empowers, Not Replaces, Property Management Employees
While concerns about AI-driven job displacement are valid, the professionals we interviewed remain optimistic. They believe that in an industry reliant on customer service, human property managers will always be essential. One interviewee noted:
Rather than replacing employees, AI is expected to change roles and responsibilities for the better. Future property managers will be able to focus on less stressful, more impactful work. In fact, in a recent AppFolio interview, Zack Kass, Futurist and former Head of Go-To-Market for OpenAI — the company behind ChatGPT — commented:
Addressing Early Concerns
In these early stages of AI adoption, some challenges and concerns need attention. Continuing human oversight and establishing best practices for AI implementation and use are crucial. Here are a few tips for integrating AI into your business:
Understand that AI is intended to supplement your work but not replace your judgment and expertise.
Always confirm the accuracy and reliability of outputs.
Use AI within the context of all other existing policies, laws, and regulations.
Create, distribute, and enforce an AI policy that covers your organization.
The State of AI in Property Management Report provides a detailed view of the current status of AI adoption in the real estate and property management industry, a look at the latest AI technologies and how they are being applied, and much more. We invite you to check out the full report here.
For more ways to fine-tune your AI strategy, download our free guide below.
Frequently Asked Questions
How Are Property Managers Using AI to Automate Rent Collection and Reduce Delinquency?
Property managers use AI to send timely payment reminders, flag accounts at risk of late payment, and handle routine follow-up before it reaches team members. The result is fewer manual touchpoints and faster resolution on outstanding balances.
As a result, residents can hear from you sooner, and your team spends less time chasing payments and more time on the work that actually requires them.
What Are the Most Common AI Use Cases in Property Management Today?
Resident communication is the most common use case for AI in property management right now. AppFolio research and over 20 hours of interviews with property management professionals confirm it: resident messaging leads adoption.
Beyond communication, operators are applying AI to:
Leasing: AI leasing assistants respond to prospect inquiries 24/7, capturing every lead, even through holidays and after hours.
Data analysis: AI identifies trends, discrepancies, and patterns in seconds, surfacing insights that would take hours to find manually.
Bookkeeping: AI interprets and processes invoices at scale, cutting manual data entry even for firms handling tens of thousands of invoices.
Language translation: AI helps English-speaking managers communicate clearly with Spanish-speaking residents, for example.
How Can Property Managers Use AI to Improve Resident Satisfaction and Retention?
AI improves resident satisfaction by resolving requests faster and keeping communication consistent. Residents heard faster are residents who renew.
When an AI assistant answers an inquiry at 11 PM or a maintenance issue gets routed the moment it's logged, the resident experience stops feeling arduous. As one property management professional put it, building better lives for residents is something most operators want. Faster service calls, quicker application feedback, and clearer information all contribute to the kind of experience that makes a resident stay.
What Role Does AI Play in Optimizing Net Operating Income (NOI) and Revenue Performance?
AI supports revenue performance by turning operational data into decisions you can act on. It analyzes large volumes of property and financial data in seconds, surfacing patterns that inform pricing, occupancy, and risk decisions.
One property management professional used AI to model profitability scenarios, specifically. That kind of "what would've happened?" analysis, run in seconds rather than hours, helps operators make sound financial decisions and protect asset value.
How Is AI Transforming Maintenance Operations, and Can It Become a Revenue Driver?
AI transforms maintenance by routing requests automatically and resolving routine issues before they hit your desk.
This kind of accelerated maintenance resolution protects two things operators care about: resident satisfaction and asset value. Unresolved requests are a common reason residents leave, so resolving them quickly supports retention. Paired with resident services delivered through the platform, maintenance shifts from a cost center to a source of measurable value for the business.
What Leasing Metrics Should Property Managers Track to Maximize Occupancy and Renewal Rates?
Track lead capture rate, response time, days vacant, and renewal rate. These four tell you whether your leasing process is working before occupancy numbers confirm it.
AI leasing assistants improve the first two directly by responding to every inquiry, 24/7, so no lead slips through. Renewals matter just as much: they start earlier than most operators think, often 90 days before lease end. Watching response time and days vacant alongside renewal rate gives you an early read on occupancy and where to focus your team's attention.
How Can Property Management Companies Grow Their Portfolio Without Adding Team Members Proportionally?
Companies grow without proportional hiring by directing routine work to AI agents operating under human monitoring and supervision. The daily volume that used to require another hire gets handled automatically.
As one interviewee noted, property management is a customer service business, so people remain essential. The shift isn't fewer people, it's people doing higher-value work. Roles change for the better: team members move off repetitive tasks and onto the relationship and growth work that requires them.
What's the Difference Between AI-Native Property Management Software and Platforms With Add-On AI Features?
AI-native software is built with AI embedded in the architecture from the ground up. Add-on AI is layered onto a legacy system that was designed for task execution, so it only speeds up the old way of working.
The difference comes down to context. AI-native architecture gives the system an operational model of your business, along with the specific context of a given property, so it can act accurately across your operation. Add-on AI operates without that context, which limits it to narrow, incremental improvements. The underlying architecture determines what the system can and can't do.
What Should Property Managers Consider When Evaluating AI-Powered Property Management Software?
Focus on whether the software changes how your day actually works, not just how many features it lists. The question that matters is whether it handles the routine so your team can focus on what requires them.
Consider these factors:
Context: Does the AI understand your data and processes, or does it operate on generic defaults?
Human oversight: Do AI agents run under human monitoring and supervision?
Unified data: Does everything connect in one system, or will you still juggle disparate tools and double entry?
Accuracy: Can you confirm the reliability of AI outputs before acting on them?
Governance: Are compliance checks and role-based permissions built in?
What Are the Biggest Concerns Property Managers Have About Adopting AI, and How Are They Addressing Them?
The most common concerns are job displacement, output accuracy, and compliance. Property managers are addressing them with human oversight and clear internal policies.
The professionals interviewed by AppFolio stayed optimistic about jobs: in a customer service industry, people make the difference, and AI changes roles rather than eliminating them. For accuracy and compliance, operators are applying four practices:
Treat AI as support for your judgment and expertise, not a replacement for it.
Confirm the accuracy and reliability of outputs before acting.
Use AI within existing policies, laws, and regulations.
Create, distribute, and enforce an AI policy across your organization.