Is AI really going to help you buy or sell your home this year? And if so, how is that actually going to happen?
Such questions, while perhaps a little skeptical, are more than valid in an era in which we hear almost nothing else but how AI will change our lives, take our jobs and do our thinking.
Also, there are a lot of claims about AI, and they haven’t always proven accurate. Another issue is your data privacy and security, so always consider this when using AI tools.
In real estate, AI is already at work behind the scenes, and you may not even know it.
It’s deployed widely by aggregators such as Zillow and Redfin, which now use natural language rather than keywords to help you find a property on their sites. So, it’s now feasible to say: “Give me six properties in X neighborhood that have Y features”, and you’re going to get a data-driven answer.
Photography and images are also changing. Companies such as RoomSketcher can instantly “renovate” a listing photo. An old 1970s kitchen can be restyled to suit your taste in seconds in a virtual world. You don’t have to imagine anything ever again.
Advanced Automated Valuation Models (AVMs) are constantly being refined by AI, which means you can be accurate about a sale price to within 2%-3%.
These models, often powered by CoStar Group’s vast data sets, are integrated into the websites of our leading aggregators. Realtor.com is an aggressive adopter of this technology. It uses real-time market demand, local economic indicators and neighborhood amenities to deliver value estimates to you.
Here are some more examples of AI in real estate that will become increasingly common this year:
Digital declutter – Tools like REimagineHome or Virtual Staging AI can transform a room in seconds. A homeowner can take a photo of a cluttered living room and use AI to digitally declutter it. It will remove toys and mismatched furniture, and replace them with high-end, modern decor tailored to the current neighborhood trends.
Predictive pricing – Tools such as HouseCanary or Quantarium will analyze millions of data points – including real-time local inventory, upcoming neighborhood infrastructure projects, and even school district rankings – to provide a price “confidence score”. As a seller, you’ll be able to price your home with precision to ensure it doesn’t sit on the market.
Remodeling analysis – AI platforms like BidCompare AI will allow you to upload contractor quotes and photos of your home and work out if your planned remodel will actually deliver a return in investment against its estimate of a final sale price.
Lifestyle matching – Tools such as Abodey AI or houseSEEKER will match properties to your lifestyle. You could ask: “Find me a home within a 15-minute walk of a dog park and a highly-rated school, with a kitchen that gets morning sun.” If such a place exists, it should find it.
Predictive pricing – Buyers will often consider the potential capital gain from a prospective home over a five to 10-year period. Tools such as HouseCanary or Stash AI will use local data, including “gentrification signals”, to forecast value growth. This helps buyers avoid buying at the peak in a neighborhood.
Mortgage deals – Securing a loan has become an automated competition. Buyers will increasingly use AI-driven financial assistants inside aggregators like Zillow to act as digital mortgage brokers. These AI agents monitor thousands of lending products in real-time, automatically calculating which loan structures offer the lowest “total cost of ownership”.
Minimising risk – Your bid on a property is a calculation made with your agent. Emerging AI tools can help by analyzing the demand velocity of a listing by tracking the number of people who have viewed the home, how long it’s been active and recent “bid-to-ask” ratios in that specific zip code. An AI will then suggest a “winning offer” price to ensure you stay competitive without over-paying.