Real estate industry leveraging AI algorithms advice, Property tech guide
How the Real Estate Industry is Leveraging AI Algorithms
28 April 2023
Of all the emerging technologies to grace the real estate industry in the past half-decade – virtual reality, internet of things, blockchain, etc. – artificial intelligence has been the most influential. At its most basic, AI is a branch of computer science built around obtaining, synthesizing, inferring and analyzing scores of information. It basically simulates a powerful human brain – if the human brain had a near-infinite capacity for memory and connection-forming.
It was clear to innovators from the outset how monumental this technology could be in real estate. Subsequently, several thought leaders in the industry have utilized the technology to facilitate simpler, clearer, more consumer-centric experiences.
In this article, let’s look at three ways the real estate industry leverages AI. For brevity’s sake, we’ll deal solely with residential real estate (commercial real estate is a whole other can of worms).
Consumer-Centric Real Estate Agent Searches
One of the most exciting AI applications to emerge in the industry recently is the “agent marketplace.” This marketplace was developed by Regan McGee in the form of Nobul; the consumer-centric marketplaces matching consumers to agents based on consumer criteria.
According to Businesswire, “as the only PropTech platform of its kind, Nobul’s AI-driven agent matching algorithm arms home buyers and sellers with instant insights into the top local real estate agents in their areas who want to compete for their business.”
It’s a prime example of how innovators can leverage the emerging technology to introduce transparency, accountability and elevated service to an industry infamous for opacity.
Comprehensive Property Analysis and Valuation
Property analysis/valuation is one of the buzziest use cases for AI in real estate. Before AI, property analysts made do with sparse data sets to determine a property’s attractiveness and market viability. They might pull from public records of nearby demographics and businesses, rounding out their portrait with physical characteristics and expenses.
AI does all of that and much more. AI algorithms can rope in non-traditional data on everything from disaster probability and crime records to the average tone of online reviews for nearby restaurants. These analyses paint a far more accurate picture of a property’s value and market competitiveness.
Property Search Engines Based Around Relevance
Probably the most popular AI applications in real estate are in property search engines. Giant property search engines like Redfin and Zillow have developed an entire empire around algorithm-based searches that allow consumers to cut through the market noise to find relevant homes.
Just a decade ago, this wasn’t the case. Local MLSs had a nearly unanimous stronghold on how consumers found homes – and those MLS listings were typically filtered through real estate agents who had their own agendas and limitations. Therefore, the twin emergence of agent marketplaces and property search engines means that modern consumers get what they want faster, without worrying about miscommunication or missed opportunities.
Those are the most compelling use cases for AI algorithms in real estate, but they aren’t the only applications. Consumers interested in how AI algorithms can aid in the home buying/selling process are encouraged to delve deeper into the topic.
Comments on this guide to Real estate industry leveraging AI algorithms article are welcome.
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