Your PropTech is Evolving: Practical Tips for Navigating An AI-Powered Industry

The size of the real estate AI market has already surpassed $222.65 billion. The tools and tactics landlords are accustomed to are changing right before our eyes. How is AI changing the real estate industry, and if you’re an average rental property owner, what should you be doing in response? We unpack this and more this month on The Breakdown.

Auspicious Momentum for AI in Real Estate

After decades of development and a few years of explosive public awareness, artificial intelligence (AI) has reached its stride in real estate.

A study by Morgan Stanley Research found last year that AI could automate up to 37% of real estate tasks, translating to roughly $34 billion in operating efficiencies by 2030. The tools and companies facilitating these efficiency gains already exist. There are now over 500 companies selling AI-powered tools and services to real estate investors, with more start-ups surfacing every month. Every one of them wants to offer you some kind of time-savings, mass efficiency increase, or fully autonomous experience for your rental business.

Familiar, big-name companies aren’t falling behind, either. Zillow’s AI-powered home search helps buyers search for properties using conversational queries. Realtor’s AI-powered search and Redfin’s AI search do the same. Property management software platforms are also embracing AI, some looking to bring it directly into your rental management experience. AppFolio’s Realm-X, for example, generates marketing descriptions, responds to leasing prospects, and manages your maintenance requests.

But despite the growing number of AI tools being marketed to landlords, not everyone is keen. If you’ve been in real estate for a while, you might be familiar with the industry’s reputation for slow adoption of new tech. There are still plenty of landlords who prefer to do things “old school” and swear by their manual systems. There are those who insist that AI will compromise the face-to-face, relationship-oriented foundation of the industry.

At the same time, this resistance and caution is matched by mounting pressure to be using AI in every possible application—or else risk falling behind your competitors and losing endless potential value.

There’s a grain of truth on both sides. The reluctant landlords likely have an overly simplistic view of what AI is and what it can do for their business. The ambitious ones could do with a healthy dose of skepticism towards some of the newest tools.

In this article, we’ll take a deep dive into the state of real estate AI and its many applications for landlords. We’ll cover:

• AI use cases with the most value for landlords
• First-look data on how Innago users are already using AI
• Practical tips for average rental property owners trying to navigate a newly AI-powered industry

Where AI Makes a Difference

The term ‘artificial intelligence’ is broad in scope. What we mean when we say something is “AI-powered” can vary widely, hence why it’s important to read the fine print for any AI tools you’re thinking about adopting. What exactly is the AI doing? What task was it built to accomplish? Where does that task fall in your workflow, and how will AI streamline it?

One way to think about AI tools for real estate (and other industries) is by focusing on the role the AI is playing in a traditional decision-making workflow. Below, we cover various uses for AI based on where they fall in the decision-making process: descriptive, diagnostic, predictive, prescriptive, and generative.

Descriptive AI: What's Happening

Descriptive AI tools read your data (or external data) and then summarize or describe the key insights back to you. These types of tools are appropriate when you have a large volume of data to work through with the goal of gleaning some important insight or observation (although, they won’t tell you what sort of action to take based on that information—that's still your job). The AI’s output could be in the form of an interactive dashboard, written summary, or other reporting.

Descriptive AI tools for real estate include the following:

Diagnostic AI: Why is This Happening?

Diagnostic AI takes one step further: Rather than just describing what’s happening in a large data set, it explains why. These are primarily analytical use cases that can help real estate investors understand why something’s going wrong in the numbers or where they can improve.

Predictive AI: What Will (Probably) Happen Next?

Predictive AI does exactly what it sounds like: It makes predictions about the future based on historical data or trends. Tools that incorporate predictive AI are especially powerful for investors looking to invest in up-and-coming markets, get ahead of tenant delinquency, or fine-tune their preventative maintenance schedules.

Prescriptive AI: What Should I Do About It?

Prescriptive AI takes predictive AI to its logical next step, giving you recommendations and suggestions about what action you should take based on an insight. A good prescriptive AI tool should transform data into an actionable step to benefit your business.

Generative AI: Do It For Me.

Among many uses, generative AI tools can take action: They create or do something that you can use as a real asset in your rental business. Most generative AI tools are based on familiar models like Open AI’s GPT5.0 or Google’s Gemini 3.

Here are just a few ways AI tools can create, make, or do something useful for your rental business:

This list is really only the beginning. As AI tools mature and models improve, these tools (especially the prescriptive and generative ones) will continue to be put to work in new ways by real estate investors and industry innovators.

Innago Users Chime In

Industry-wide, AI tools of all kinds are already making their mark. However, there is some data showing that AI use is much more common in large multifamily operators than smaller, ‘mom-and-pop' landlords. This is hardly surprising: Larger landlords have more resources to devote to AI tools and more to gain by automating their higher administrative burden.

Since Innago’s userbase leans more towards small- to mid-sized landlords, we wanted to find out how our users compared. In November of 2025, we surveyed about 200 Innago users actively managing portfolios on the platform about whether they use AI, how they use it, and why. Here’s a short summary of what we found:

• 72% of Innago users surveyed were either already using AI in their rental business or planning to do so in the future.
• 49% of full-time landlords surveyed have plans to use AI in the future.
• Short-term and mid-term rental owners were the most AI-forward of all investor types.
• Writing listings and advertisements was the most common use of AI, with 52% of AI-users indicating they use AI for this purpose.
• Increased efficiency was the most cited benefit of AI, with 44% of current AI users reporting to use AI primarily for this benefit. Other common answers included reduced costs (13%), the ability to leverage data (11%), and more informed decision-making (11%).
• The most common blockers for AI use included lack of knowledge, need, trust, personalization, or scale.

These data points make it clear that Innago users are not only using AI but are focusing on its most useful applications to increase efficiency.

To view the full results of the survey and read more about Innago users and AI, be sure to check out our 2026 Market Outlook Report, live on Innago Insight.

Practical Tips For an AI-Powered Industry

There is no universal blueprint for AI integration that will accommodate every property owner. An accidental landlord renting out a single inherited home is never going to need expensive AI-powered deal-finding software. Nor is a large, commercial real estate firm going to necessarily need AI to help screen their infrequent tenants.

However, that accidental landlord may find that connecting their tenant with an AI chatbot for maintenance triage could reduce the amount of 3 a.m. maintenance calls they receive, while the commercial firm could find that AI tax software is well worth it to streamline tax season.

While the following tips are broad, take them with a grain of salt nonetheless. The best AI applications of course depend on your business, what the biggest time sinks are for you and your team, and where you want to introduce automation in exchange for more of your time back.

Identify pain points in your team and target AI assistance there

While the hype around AI accelerates, it’s worth remembering that the goal isn’t to simply integrate AI for AI’s sake. Rather, AI should solve some pain point or problem for you and your team. Therefore, it makes sense to start with that problem.

Here are some questions to ask yourself while considering whether any AI applications make sense:

• Which day-to-day tasks take up most of your time?
• Which properties or units are underperforming?
• Where do your metrics (e.g., occupancy rates, cash-on-cash return, NOI) consistently fall below industry standards?
• What is the most stressful part of managing your portfolio?
• What are the least enjoyable parts of managing your portfolio?

Answering these questions can help you narrow down the most effective places to target AI intervention.

Invest time in due diligence—and ask critical questions to anyone providing you an AI tool or service

A tool or software branded as “AI-powered” isn’t necessarily better than what you may already be using just because it’s “AI.” Before investing your time and money into an AI tool, you should not only find out what the tool is and what it’s supposed to do, but also challenge the company or sales rep to demonstrate the value it will provide you.

Ask questions like:

• What does “AI-powered” mean?
• What kind of AI does the tool use or which model is it powered by?
• How often does the tool break?
• Can I see a demonstration of my exact use case or a sample report?
• Do you have any case studies of existing users?
• Can you quantify how this tool will help me?
• Is the tool going to generate me more value than I’m paying you for it, or will it primarily save me time/stress?

A company that has genuinely innovated and is using AI to solve a practical pain point for its target users will have satisfying answers to these questions. A company just trying to sell you on the “AI” point will not.

Prioritize AI that takes action

AI tools that primarily provide you with insights are useful, but these types of tools tend to give you more work, not less. That’s because you’re discovering trends or problems you weren’t previously aware of, and you now have to take action on those results in addition to your usual work.

An AI tool that takes the action it recommends to you—or at least gets the process started—is worth more than one that just tells you about it. Think tenant chatbots that schedule repairs, virtual leasing agents that add tours directly to your calendar, etc.

Put AI to work on your proprietary data

If there’s one truism that really is true in the age of AI, it’s “Everything is data.” Data collected based on someone else’s portfolio can be a good starting place, but it won’t necessarily tell you anything about your rental business.

For example, let’s say you find a study claiming that tenants pay their rent on time three times more often if they pay via ACH bank transfer. That’s an interesting and potentially actionable insight. But you don’t know for sure if this holds true for your tenants. Maybe you rent primarily to senior residents, who are more reliable payers via check or credit card. The much more useful metric would be one based on your own data.

Running a retrospective study to find out if a statistic holds for your portfolio takes time, but what if you used AI to sort through the years of historical data instead? That data is sitting idly on your desktop—you might as well put it to work.

Cultivate a tech stack that maximizes synergy

You don’t have to use every new tool on the market. You don’t have to automate every aspect of your business, either. If it turns out that speaking to prospective renters on the phone generally leads to more tours scheduled (rather than having those applicants talk to an AI chatbot), then that tool no longer makes sense for your business.

The idea is to cherry-pick the tools that work well with others. AI should augment your systems—it doesn’t necessarily need to overhaul them.

Identify and mitigate high-consequence risks that AI may introduce

There are certain AI applications that are inherently riskier than others. For example, tenant screening is highly regulated by both federal and state fair housing laws. Using AI screening software does not exempt you from these legal obligations, nor do these tools necessarily adhere to every state and local nuance. In fact, lawsuits have already been filed over such algorithmic bias.

Generative AI also comes with its risks. If AI is talking directly to your tenants, what considerations should you keep in mind?

If you’re new to AI, it may be worth avoiding tools that may have steep consequences if things go wrong. If you do deploy them, think about what kind of oversight you’ll have and how you can mitigate any risks involved.

Conclusion

In 2023, AI was among the top technologies predicted to most impact real estate over the next three years by the JLL Technologies’ 2023 Global Real Estate Technology Survey. Three years later, it’s clear that this prediction was correct. AI is now everywhere you can see.

Adopting any level of AI will trigger a shift in your operations, no matter the scale of your adoption. You will have to adapt to new mindsets, rethink your workflows, get used to leaning on AI for routine tasks, and—importantly—trust it to do those tasks well, as much trust as can be afforded to these tools. To get the most value out of AI, you may have to let go of some fundamental underlying assumptions about the industry and your role in it. Traditional operating models may not hold as much weight in the future as AI becomes more prevalent.

Reconsidering long-held ways of working is no small task. As you weigh what AI adoption could mean for your business, we hope these practical tips help point toward a direction to start.