Artificial intelligence is not only changing digital spaces, it’s also transforming the physical world with real estate applications.
Nowadays, AI is integrating into every part of the real estate industry, from designing structures to listing them for potential buyers.
See how AI is changing how people build, design, buy, and sell homes and buildings.
1. Leasing documentation
Business management consultation firm McKinsey & Company says generative AI can summarize key themes across leases.
These include a real estate property’s monthly rental fees or market forces that could affect leases.
Artificial intelligence can scan across leases that belong to a specific category and generate tables of information.
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For example, it could look up leases with rent prices per square foot below a specific level.
This AI real estate application may seem like a regular search engine’s features. However, AI bots can “read” photos in the photos of new listings.
Often, conventional search functions can only read text you can copy and paste. If the lister didn’t write them down, a real estate website might not feature them.
Real estate marketplaces that use this functionality include Zillow and Trulia.
2. Customer engagement
Real estate companies can deploy generative AI assistants or copilots to facilitate customer interactions.
For example, it could handle simple tenant requests, such as routine maintenance.
It can identify more complex questions and notify a specialist at a property management company.
McKinsey also says gen AI can observe conversations and written responses to improve communication.
For example, it could craft a negotiation transcript during a high-stakes commercial lease negotiation.
Also, the AI tool could coach specialists in avoiding specific terms during discussions.
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Companies that use similar applications include Findigs, which uses gen AI to approve renters quickly and accurately.
Homebot identifies homeowners and buyers who are likely to make a transaction, helping real estate agents find potential buyers.
3. Property visualization
Modern listings often feature pictures of empty units or ones with a stranger’s finishes and furniture. Consequently, customers may struggle to decide whether the unit will fit their needs.
Generative AI solves this issue by visualizing a potential tenant’s dream apartment as it can understand natural language.
For example, the tenant may ask for a chocolate brown color for the furnishings. Then, they could request a cherrywood finish instead, and the AI changes it in seconds.
It also presents e-commerce tie-ins. For instance, the real estate company may tie up with furniture companies listed in Shopee.
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This partnership may enable the real estate firm to offer digital simulations of that furniture in the visualization.
As a result, smaller home accessory companies could gain a new promotion method while the real estate agency earns more.
Alternatively, a real estate company could enable tenants to create 3D recreations of their furnishings.
This method could help tenants design their homes with their existing knick-knacks before moving in.
For example, Home Design AI lets you redesign your home in seconds. Upload a photo of your living space, select a style, and see your place with a new look.
4. Architectural planning
Architects and contractors also benefit from AI real estate applications.
Let’s say an architect wants to design a new store.
They could deploy Internet of Things (IoT) sensors and computer vision algorithms to collect data points.
These include how customers move through a store before purchasing. Then, they could feed this data along with others like customer loyalty and sales into an AI tool.
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The AI program could provide architecture based on actual real-world data to build a store that lets customers navigate it conveniently.
Another example is TestFit, which can make site plans based on parcel data, topography, and interior and exterior requirements.
5. Investment assistance
The traditional real estate investor starts by analyzing large portions of the market with ideal features, such as airport locations and ports.
Then, they narrow down their search by looking at building information from local brokers or digital tools.
Generative AI tools simplify this process by answering questions like, “What are the top 25 warehouses up for sale that I should invest in.”
These programs sort through unstructured data, such as the performance of a company’s existing properties.
As a result, investors save time building their portfolios.
Entera takes this to the next level by validating your investment ideas with real-time market data and facilitating negotiations.