10 GenAI Use Cases in Real Estate

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Kamil Rogiński

Updated Jun 13, 2024 • 9 min read
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Are you aware of all the ways GenAI can help you run a real estate business? Sales, marketing, customer support, and finance can all benefit from applying AI in their daily operations.

According to McKinsey, GenAI has the potential to completely transform the real estate industry. It could generate between $110 to $180 billion in value in the coming years. Despite this fact, many organizations don’t know yet how to make the most of artificial intelligence.

In today’s piece, I’m going to discuss generative AI use cases in real estate. Hopefully, you’ll be able to implement at least some of them in your business.

10 GenAI use cases for real estate

There are numerous ways in which AI can improve the functioning of businesses involved in property management. Let’s now take a look at a few GenAI use cases in real estate.

1. Generating property descriptions

This is, arguably, the most popular example of AI in real estate. Instead of spending hours on writing descriptions for each property, you ‘feed’ a GenAI tool with all the key information like:

  • location
  • exterior color
  • number of rooms
  • type (residential, commercial)
  • price, etc.

On top of these, you can also indicate the tone of voice, text length, and preferred content format. This helps save both time and money, as generating descriptions for tens or hundreds of properties is no longer a challenge.

That said, there’s also another way to generate descriptions, which doesn’t require writing detailed prompts. We discuss them next.

2. Creating property descriptions from images

Generative AI tools come with computer vision capabilities, i.e., they can analyze photos of the property and create a description based on what it ‘sees’. Things like exterior and interior colors, closest surrounding, and the number of stories above ground will all be taken care of. The real estate professionals only need to provide information that can’t be derived from the image, like year of construction, location, or heating type.

Since artificial intelligence software can describe images so well, it’s hardly surprising that it can also suggest fitting keywords to boost discoverability. You can then use these terms not only in the description, but also in the image “alt text”. This will help potential buyers find your property while running a visual search on Google.

4. Creating AI-powered visualizations

Sometimes seeing an empty apartment simply won’t cut it. Some people need more persuading to decide whether they see themselves living in an apartment/home or not. A real estate agent can use GenAI tools to create property visualizations – they might select modern furniture, cherrywood floors, etc. Seeing how a cold, empty apartment turns into a cozy home can speed up the decision-making process.

Later, this data can be fed back into a model that will be able to predict the type of finishes and furniture that appeals the most to various customer segments. As a result, it will improve the conversion rate from prospect to lease or sale.

5. Generating consistent and engaging social media copy at scale

Another use for AI in real estate is generating social media copy. People look for properties online, this includes both Google search and social media platforms. After preparing your real estate listings, you’ll have to come up with text to promote them across various social channels.

Naturally, the more properties you have, the more posts you’ll have to prepare. This can be time-consuming, unless you use a GenAI tool. It can help you create engaging copy around your real estate. The more details you feed it with, the better the output will be – share who you’re targeting, what tone of voice to use, how long the copy should be, etc.

6. Improving customer support

GenAI also supports real estate companies in day-to-day operations like customer interactions. A chatbot can be trained to answer common questions from potential buyers. If you lease property, then you could also automate work on simple requests from residents, like maintenance. Instead of calling the building administrator and forwarding the tenant’s queries, you could have the AI tool forward it directly to the maintenance team. This way, your customer-facing teams will have more time for other types of tasks.

7. Supporting asset managers in property analysis and operations

Asset managers can use GenAI to collect and analyze property-level data, including sales records, rental prices, property characteristics, and market trends to manage the business more effectively. The data will come in handy during forecasting and budgeting. They can also consider using GenAI in leasing, ESG reporting, capital planning, and risk identification.

8. Helping in acquisitions

When using a GenAI tool connected to the internet, you can also have it assist you in finding properties and land you could acquire or represent as an agent. As it is so good at research and large-scale analytics, acquisition teams can also use it to run financial simulations and assist in creating property development timelines.

9. Finance and accounting

On top of finding and selling properties, running a real estate agency, involves:

  • conducting risk and compliance assessments
  • preparing financial reports
  • forecasting
  • fraud detection, etc.

All of these processes can be streamlined with GenAI. Currently, tasks like invoicing, billing, and payments have already been automated to a degree, but by using AI, you can further optimize and enhance them.

10. Improving relations with real estate investors

I’ve mentioned that GenAI can boost relationships with customers, but the same can be said about investor relations. Not only can it help you with targeting the right investors, but also maintain a good relationship with them.

How so? You can turn to GenAI to create marketing materials, including investor presentations, and use a chatbot to quickly answer all of the investor queries.

Key considerations for implementing GenAI

To fully benefit from AI in real estate, organizations need to have access to IT capabilities that exceed the ‘standard’ tech skillset of companies in the sector. Luckily, this doesn’t mean that they must hire a dozen developers but rather a few engineers and designers who specialize in AI.

Before deciding on any implementations, leaders must consider their customer base and market specifics. A commercial real estate corporation might own and operate thousands of properties worldwide and need solutions that support managing tenant relations.

Meanwhile, a local real estate agency that focuses on residential property sales might only require a chatbot and a description generator to support their support and marketing teams.

To make the most of gen AI, the C-suite has to be prepared to challenge the industry’s current modus operandi and its hierarchies.

As well as accept the fact that they need to add a new technology layer throughout their organizations. Decision-makers have to lead by example if they want to ensure a widespread adoption of AI.

An example of RE and CRE company already leveraging GenAI


To support its clients, JLL has introduced a new AI-powered occupancy management method that helps tenants better analyze office space usage. As shared on their site, they’re helping one of their Fortune 500 clients understand:

  • which parts of the office are under-utilized
  • how many workers come into the office, on average
  • monitor demand for office space like conference rooms.

This is part of JLL’s broader AI-powered Dynamic Occupancy Management platform, which helps building tenants optimize their office space usage and adjust to hybrid work models.

GenAI use cases in real estate – making the most of the latest AI advancements

If you use GenAI correctly, it will help you completely transform your business operations. Creating engaging property listings at scale, automating tenant requests, and boosting real estate acquisitions are just a few ways it supports productivity across the organization.

To make the most of AI, companies from the real estate sector have to create strategies that will help them find a balance between the risks and rewards that using AI-powered tools comes with.

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Kamil Rogiński

Client Partner at Netguru
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