Due to the rise of Chat GPT, public awareness of AI solutions has significantly increased.
And the real estate industry has seen its fair share of technological advancements, including integrating artificial intelligence.
It can potentially revolutionize the buying and selling process of properties, managing properties, analyzing markets, and generating leads.
I wrote today’s article discussing what AI is, six benefits and risks, and 16 use cases to show you how AI can be used in real estate.
What Is AI in Real Estate?
Machines that can learn and perform tasks that usually need human intelligence. This ability can be called artificial intelligence.
It is also called “machine learning”: when a computer learns how to do something without being exactly told what to do.
For example, let’s say you have a computer that can cook.
But only when you tell him from a recipe each step individually. You need to tell it what ingredients to buy, what to do with them, etc. So you have to be there to observe and do a lot of micro-managing.
After a while, you may not see much of a benefit anymore in having to be there and do all the micro-managing. Doing it that way, you could do the cooking as well yourself.
So you give the computer an upgrade, you tell it: “Hey computer, I will cook different receipts now, and you observe.”
Of course, you prepared the computer for that so it can observe you and describe what you are doing in its own words.
While you peel some potatoes, the computer observes and “thinks” by himself: “Alright, the first thing is peeling potatoes. If potatoes are dirty, I have to wash them. If not I can go ahead. If there are some bad parts, I have to cut them out with knife X, etc.”
So the computer does a whole lot of thinking for just one receipt. This is thanks to a new program you wrote, enabling it to observe and learn and program itself.
Now the next time you tell it: “Computer cook me the nice potato receipt XYZ from last time,” you don’t have to stand around the whole time giving it orders for each and every step. It does it alone.
Of course, in the first iterations, it can happen that the computer may have missed when you cooked the potatoes. Its learning program may not have been prepared to take note of the maximum time to cook them.
So when you try the computer “cooked” meal the first time, you realize: “Oh boy, those potatoes are overcooked.”
You now give it feedback as may happen between a married couple sometimes: “You overcooked the potatoes.”
If you do this to your spouse and your marriage has problems, they may not learn to improve the cooking time but tell you to cook them yourself next time.
In contrast, the computer will not file for divorce and may instead ask in return to get input about what overcooked and different cooking times mean, etc.
In short, its program can learn independently and improve over time by the feedback it gets.
In real estate AI (machine learning) can streamline processes, get valuable market insights, and increase overall efficiency (save time).
6 Benefits and 5 Risks of Using AI in Real Estate
The 6 Benefits
1) A better property search:
AI can help buyers and renters find properties that match their preferences, such as location, price, and amenities, more easily and accurately.
For example, an AI-powered real estate platform can recommend homes to potential buyers based on their search history and behavior.
2) More efficient transactions:
With the help of AI, you can automate many repetitive and time-consuming tasks involved in buying or selling a property, such as a document management, property valuation, and mortgage underwriting.
For instance, the startup Opendoor uses AI algorithms to make instant cash offers to homeowners looking to sell their homes (source).
3) Better risk assessment:
AI can boost property analysis and help lenders and insurers evaluate the risk associated with a property more accurately by analyzing various data sources, such as property records, credit scores, and weather patterns.
This can lead to more informed decision-making and reduced risk of losses.
For example, Cape Analytics uses AI to analyze aerial imagery and provide property data to insurers.
4) Enhanced customer experience:
By using AI, you can give your customers a more personalized and interactive experience by using chatbots, virtual assistants, and other tools to answer questions, provide advice, and offer recommendations.
For example, the real estate company Compass offers users an AI-powered video studio to create listing videos (source).
5) Improved property management
Suppose you are a landlord or property manager. In that case, AI can optimize business operations and maintenance by providing real-time data and insights on occupancy, energy usage, maintenance needs, and tenant behavior.
For instance, the startup Zenplace uses AI to automate property inspections and maintenance requests (source).
6) Improved Real Estate Lead Generation
With the help of AI, you can increase your real estate lead quality by analyzing behavior data and predicting which leads are most likely to convert.
For example, through tools you may already use (e.g., Google Analytics), AI can analyze the online behavior patterns of potential clients and help you improve your marketing efforts to increase the likelihood of conversions.
Additionally, AI can automate lead scoring and lead nurturing, allowing agents to focus on more high-touch tasks.
The 5 Risks
1) Biased decision-making:
AI models are only as good as the data they are trained on (remember the potato cooking earlier). This can lead to unfair and discriminatory decision-making.
For example, suppose it is trained on data from predominantly affluent neighborhoods. In that case, it may undervalue properties in lower-income areas, leading to further housing inequality.
2) Not enough human interaction:
AI chatbots handling customer inquiries may not be able to give the same level of personalized service as a human can.
3) Privacy concerns:
Credit scores and employment histories may be collected and analyzed by algorithms.
If AI does this from potential real estate clients’ social media profiles to determine their financial status, it could violate their privacy.
4) Over-reliance on AI:
If real estate pros rely too much on AI, it may lead to a lack of human intuition and decision-making creativity.
This can happen when AI models are always used to automatically generate property valuations.
In that case, real estate agents may become less experienced in assessing the value of properties themselves.
5) Security risks:
Data breaches potentially exposing sensitive information can always happen, with or without ai. However, since AI is still in its infancy, other types of cyber attacks are possible with it. They are called “AI attacks” and work a bit differently.
For example, this article mentions that “an AI attack can transform a stop sign into a green light in the eyes of a self-driving car by simply placing a few pieces of tape on the stop sign itself”
16 AI Use Cases in Real Estate
To better understand AI in real estate and its use cases, let me explain it through an analogy.
As a buyer’s agent, you may try to find the perfect home for a client. You have to sift through hundreds of listings to find properties that meet their needs.
This process can be time-consuming; even then, you may miss out on properties that would be a great fit.
Now, imagine if you had an AI-powered tool that could search through all those listings and identify the ones that match your client’s needs in a matter of minutes.
That’s the power of AI in real estate and one real estate business use case in increasing efficiency and saving you time.
There are four areas of real estate where AI finds various use cases: lead generation (real estate marketing in general), property management, predictive analysis, market analysis, and ai for customer experience.
Let’s look at these use cases in more detail with some examples. You may remember some of the above benefits.
1) AI Use Cases in Real Estate Lead Generation
Virtual tours:
Using AI-powered virtual reality and augmented reality tools to enable potential buyers to tour a property without ever leaving their home can boost lead conversion rates and save you time.
However, this use case may be more useful for international buyers or those looking to relocate to a new area than potential buyers living closer to the particular property.
Image recognition:
A great property description with a decent sales copy can increase your lead conversion rates. However, they can be pretty time-consuming to create.
To save you time, in this use case, AI algorithms can analyze property photos to identify specific features such as the number of rooms, the type of flooring, and the style of the kitchen.
This information can generate more accurate and persuasive property descriptions and thus convert potential buyers better.
Chatbots:
As partially discussed in a past article, AI-powered chatbots can help you be faster and more responsive regarding answering common questions from potential buyers, tenants, or seller leads.
They can save you time and be used to schedule appointments, provide personalized recommendations, and do follow-ups.
Analyzing the Needs and Wants of Your Target Audience:
In past articles, I covered the importance of real estate targeting and finding your ideal real estate client for better quality leads.
And AI can also help you with that (e.g., Chat GPT).
With a decently engineered prompt, you can analyze large amounts of text from social media posts, forums, and online reviews to learn more about your target audience’s preferences and sentiments.
You can improve and tailor your marketing message based on the collected and interpreted information.
Predictive lead scoring:
Some CRMs (my article) offer this AI feature in their software solutions. You can use AI to identify patterns and characteristics common among past clients and current leads to having it calculate which one is likely to convert in the future.
This can also free up time since you can focus your lead nurturing efforts on the few leads and past clients that are worth the effort.
2) AI Use Cases in Property Management With AI
Predictive maintenance:
AI can predict when maintenance is required based on data from various installed sensors on a property.
Property managers will save time and money with it since issues will be detected early before major damages occur.
Tenant screening:
As discussed above, AI can help property owners, landlords, and managers evaluate tenant applications. It can be done on factors such as employment status, credit history, and criminal records.
Rent prediction:
AI can also analyze trends in a particular rental market. This helps property managers adapt their pricing strategy accordingly, maximize profits, and reduce the risk of vacancies.
Energy management:
To reduce energy costs and promote sustainability in their respective real estate niche, property managers can use AI to analyze energy consumption patterns and identify where there is room for improvement.
Chatbots:
No more 3:00 am calls because of issues with toilets. An AI-powered chatbot can help tenants with routine inquiries and maintenance requests.
3) AI Use Cases in Real Estate Market Analysis
Predictive analytics and demand forecasting:
AI can use multiple market data sources such as demographic data, historical property prices, and market trends to predict (making a high-odds guess) market behavior in the future.
This data can be used to find potential investment opportunities or to know which real estate niche you should start focusing on.
Property valuation:
While it can be risky if you over-rely on it, you can use AI to analyze property features and compare them to recent sales data.
This helps the AI to estimate the value of a property accurately.
Depending on the AI model, it may use a combination of various property valuation methods (e.g., cost-based, comparison, income capitalization).
Property Search:
If you use AI to enhance property search engines or even on your own real estate website you can provide the following:
- Personalized recommendations based on a user’s search history and preferences.
- Making it easier for potential buyers to find the right property.
- Thus increasing your lead conversion rates.
4) AI Use Cases in Real Estate Transaction Management
Contract Analysis:
When I had my international real estate referral business, the legal parts were not my favorite parts (some may like it, though).
With AI, you can have it extract data from contracts to ensure they are accurate and identify any potential issues or risks.
Fraud Detection:
This use case may be something an escrow service company could implement.
You can use AI to analyze transaction data and identify any potential fraudulent activities or suspicious behavior, helping to prevent financial loss or getting into a money laundering scheme.
Transaction Monitoring:
I’ve been there, and you probably are too. Real estate transactions can cause inefficient communication overhead because you want to keep all involved parties updated.
AI can also help save some time with this communication by monitoring transaction progress and providing automated updates to all parties involved. This helps streamline the process and reduce delays.
Escrow service companies, real estate transaction management services, or document management companies could also implement this type of AI.
This article has been reviewed by our editorial team. It has been approved for publication in accordance with our editorial policy.
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