AI and the residential real estate ecosystem
Most of the recent excitement over Artificial Intelligence has centered on generative AI, or more specifically, the ability of a chat bot to generate informed responses to complex inputs. While AI’s capabilities have an obvious potential for automatically generating property descriptions and marketing content, improving ad targeting, and managing customer service responses, AI will play a much broader role across the residential real estate ecosystem.
First, let’s establish some absolutes:
- AI won’t replace real estate agents
- AI won’t negate the need for agents to be marketing savvy
The promise of AI is made possible primarily by the advancement of Learning Models, which can be trained by analyzing vast amounts of information to learn how to compile very targeted, comprehensive answers and to deliver relevant insights to even the most detailed queries. The application of AI, however, will bring about many new changes, efficiencies, and opportunities across the housing industry.
How home buyers will benefit from AI
Searching for a home has evolved. The process is consistently and incrementally being enhanced on online listing sites. According to the National Association of REALTORS®, 41% of home buyers begin their searches for homes online, while 93% utilize online searches in their home buying endeavors. AI promises to make this process simpler, more personal, and more efficient.
AI will enable search features allowing a user to input images of homes or features that interest them, creating a highly customized experience. Voice search will also simplify their ability to find homes with the exact features or feel they are looking for.
Similarly, AI Learning Models that increasingly learn a home buyer’s most detailed preferences will be able to find and automatically promote properties that better match their aspirations for a specific home. These models can even detect subconscious leanings, interests, inclinations. Homes that match preferences can be virtually staged to further reflect design preferences–allowing a client to visualize any home in the way they would imagine living in it.
How home sellers will benefit from AI
Learning Models can also describe who would most likely buy a home. While we’ve seen buy-side tools evolve, AI promises to take the marketing of a home to a new level of detail. Modeling might reflect how listings should be physically and virtually staged, even as far as the colorways and art on the walls. These models can quickly stage a home in many decorating styles and then select the style that is best matched to a buyer.
Learning Models can already recommend repairs and renovations that will most benefit the home selling process, even estimating how specific repairs will affect expected days on market for that home.
How homeowners will benefit from AI
For most homeowners in the U.S., their home is their largest and most important financial investment. AI will help homeowners get the most out of the entire homeownership journey. AI will make recommendations on energy savings, home maintenance, and the most financially attractive remodeling options. Tools that allow “what if” scenarios can predict the market value and detailed costs of a renovation project—putting a homeowner in an informed, confident position to more effectively negotiate with a contractor.
How lending will benefit from AI
AI is already active in lending—delivering on its early promises of faster, more data-driven decisions, underpinned by better risk prediction. The obvious benefit of almost instantaneous credit decisions is the compressing of closing cycles, making the buying and selling of homes easier on everyone.
One area I hope to see addressed is in FICO scores. They are broken and take many potential homeowners out of the market completely. They overly punish consumers with small mistakes in their pasts while undervaluing their current and future credit worthiness. AI promises to generate better credit models that more fairly qualify consumers—including making precise recommendations on how to get qualified.
To address our persisting inequity challenges, we need new models to help both the underbanked and unbanked find paths to home ownership.
This brings us to the issue that 25% of US adults are underbanked (must regularly use alternative forms of financing) while another 10% are unbanked (have no traditional checking or savings account)—and it gets much worse when looking at Black, Hispanic, and other people of color. We need an entirely new set of AI-driven models to help underbanked consumers become homeowners.
How real estate agents will benefit from AI
“How much is this home worth?” remains the first and central question in most every transaction. AI promises to provide better tools for REALTORS® so that they can confidently assume the role of authority on their markets as well as individual properties. CMAs that utilize AI will more precisely account for the market timing of offer acceptance and the closing of comparable properties, while more and more nuances between properties will be accounted for.
Valuation models that use AI will also become more predictive—correlating non-real estate data and other economic information toward identifying how markets will behave going forward.
Learning Models can also analyze the other listing or buying agents and provide insights on their negotiating tendencies—providing guidance that allows you to secure the best deal for your client.
A very tech-forward Miami brokerage uses Learning Models to determine the negotiating savvy of listing agents. By analyzing the past transactions of any listing agent, they can provide their own buyer agents the best strategies for negotiating better deals.
This, of course, can be extended to improving an Agent’s own performance. Learning Models can capture the smallest behaviors and tendencies that translate to higher productivity and financial success. No one wants their every move to be tracked—but much like an athlete benefits greatly from scrutinizing their training and game performances, REALTORS® can improve their own execution and outcomes by way of analyzing their daily behaviors.
AI is revolutionizing professional athlete training, as well as mental and health fitness apps. AI is equally capable of optimizing performance in real estate and lending.
AI and its form of image analysis, when applied to an uploaded picture, will improve inspections and repairs—making them faster, more efficient, and cost effective. A picture of a crack in a foundation taken by a REALTOR® will be enough to provide a risk analysis along with a detailed remedy.
How investors will benefit from AI
Investors will increasingly lean on AI’s Learning Models to optimize their portfolios and increasingly find future opportunities before they materialize.
AI modeling can make predictions about the impact on local housing served by urban transportation projects—which point to both the development opportunities as well as social and economic impacts of such projects. Similar impacts can be modeled for new parks, schools, new employers, and even popular retail projects such as a new neighborhood Whole Foods store.
Atlanta’s new Beltline is transforming neighborhoods and changing Atlanta’s suburbs—in both positive and challenging ways. Applying models to better predict the social and economic impact of these projects will be an important tool for investors, real estate professionals, and city planners.
How our society will be impacted from AI
AI has a trust problem, and it should. It’s only as good as the data it’s trained on and the means by which we apply it to solve problems. Time will tell how we manage the promises and challenges of AI as both are plentiful.
As the American automobile was introduced to our nation, many feared it would lead to an uncontrolled sexual revolution as couples escaped the watchful eyes of parents monitoring porch swings. To accommodate these public concerns, Henry Ford redesigned the back seat of the Model T in hopes the car would not contribute to widespread moral decay.
As with any other significant tech innovation—the automobile, television, the internet, smart phones, and social media—AI opens up new worlds of expression, learning, entertainment, education, and opportunities, while also presenting us with significant social and ethical challenges. The power of AI presents us with much more complex and serious concerns than prior innovations.
Embrace AI to your advantage…but be ever diligent in recognizing its challenges.
To learn more about AI-powered home valuation and predictive analytics tools, contact Plunk.
David Bluhm has spent the past three decades starting and growing technology companies. In a variety of founder, director and senior operational roles, Bluhm has been involved in over 20 start-ups that have achieved a combined “high water” equity value of over $36 billion, including 2 IPOs and 7 company acquisitions—four of which valued over $100M. Bluhm is co-founder and president of Plunk, an advanced analytics company revolutionizing the way homeowners, home experts, and investors value and invest in residential real estate—through the power of AI, Machine Learning, and image analysis.
