Compass has invested more than $1 billion in technology that helps the real estate company’s nearly 30,000 agents move from contacting prospects to closing deals, all through one technology platform.
“Our job is to help agents grow their business, make more money, save time, and deliver great experiences to their clients,” said Rory Golod, President of Growth and Communications at Compass. says Mr.
The investment by Compass, the nation’s largest brokerage by sales volume, includes Likely to Sell, an artificial intelligence tool that analyzes prospective buyers and recommends those likely to be ready to sell a home quickly. . Most recently, the company announced his Compass AI, a chatbot tool that helps create property listings, marketing materials, and agent profiles.
Gorod says agents have thousands of contacts at their fingertips, but traditional marketing tactics like email and social media often have very low conversation rates. However, since Likely to Sell was launched in summer 2020, nearly 8% of recommendations provided monthly through CRM (customer relationship management) tools have been listed on the marketplace within 12 months, according to Compass. .
“We want to use AI to enable agents to say, ‘If I’m going to reach out to someone, I want to reach out to the person who is probably most likely to make a deal,’” Gorod says.
McKinsey estimates that advances in generative AI will unlock $180 billion in value. The industry will certainly benefit from such a shock, as U.S. home sales will fall to their lowest level in nearly 30 years in 2023 due to high mortgage rates and inventory shortages that are making home purchases significantly more expensive. There is a possibility of receiving. The industry is expected to experience major commission disruption after the National Association of Realtors struck a deal that could force home buyers and sellers to negotiate lower commissions. There are also big problems with construction. That’s because the country isn’t building enough new housing to meet demand.
However, there are a number of complicating factors that make AI implementation particularly difficult in the real estate sector. Experts say there is a huge amount of unorganized data, from leases to contracts, investment documents to design plans. Construction takes place on very thin margins. The average age of real estate agents is older than employees in most industries, and employees in this industry are notoriously tech-phobic. And because of the highly physical nature of the industry, many technology advances are still in a relatively early stage.
“Historically, I would say real estate has always been a little bit behind the curve in terms of the use of AI,” said Alex Walcomia, a partner at McKinsey & Co.
Walcomia said commercial real estate is more advanced than residential when it comes to implementing AI. He said the biggest challenge facing the industry is ensuring that employees such as construction workers, real estate agents and designers are properly trained and understand the capabilities of the AI tools they are given. thinking. He is encouraged by the industry’s forward momentum in his AI journey over the past five years.
“I’m thinking a lot [generative] The use cases for AI are like opening up new areas of great value for real estate,” says Wolkomir.
Yao Molin, chief technology officer at JLL, says one of the challenges facing commercial real estate is the presence of large amounts of unstructured data in the form of leases, contracts and invoices. . “In this age of AI, we believe that the barriers to using AI will continue to be lower,” Morin said. “And you ask yourself, ‘If using AI isn’t a competitive advantage, then what is?’ The answer is definitely your data.”
Last year, the company launched JLL GPT, a generative AI model that provides insights to customers based on JLL’s own market research and externally available market data. According to Morin, 20% of JLL’s 103,000 employees use JLL GPT on a weekly basis. This is because the technology allows staff to perform repetitive tasks more efficiently.
JLL is also using generative AI to better predict building maintenance needs, explore investment opportunities, and implement sustainability initiatives. “If you think about classical AI, there is a longer learning curve before you can understand it and trust the results,” Morin says. “But with generative AI, it becomes much easier to implement and people can see the value.”
Startup Higharc has launched a home construction automation platform aimed at turning home construction into a faster and more affordable process.
“What we’re doing is making data available about the homes that are going to be built,” says Marc Mine, CEO of Higharc. “And when I say ‘make data available,’ I mean every piece and section of the building, where it belongs, when it needs to be built, who is responsible for that part of the building. We’re managing all that information automatically.”
Hyark raised $53 million in Series B funding last month. The funding includes funding from other companies in the construction, building products and manufacturing industries, including retailer Home Depot and the venture arm of France’s Schneider Electric. Miner says the biggest potential lies in both improving the way homes are built and accessing data from sellers and suppliers.
“From a home design perspective, if you build the right software layers to systematically change the home, it becomes easier to understand how to leverage the hardware side,” Miner says.
Founded in 2016, Prologis Ventures has invested $250 million in more than 45 startups focused on supply chain and logistics, including AI-enabled companies such as TestFit, Altana AI, and Logiwa.
“People have always used their intuition to make real estate decisions,” says Will O’Donnell, managing partner at Prologis Ventures. “However, there is a huge amount of data, and if we can collect and analyze it, [it]That way you will have better insight to make that decision. ”
As an example, Prologis uses TestFit’s AI to better determine the feasibility of new warehouse sites. Information about specific zoning regulations, environmental conditions, transportation around your site, and workforce can be integrated to improve decision-making. TestFit can also generate dozens of project renderings in just an hour and makes recommendations based on historical metrics.
“One of the things we spend a lot of time on as a company is what information is important to our customers when they are making decisions,” O’Donnell asks. “What is important to them as they drive their business forward, and how can we help both employees and customers better understand that information?”
Augmenta, on the other hand, automates the design of electrical systems, all the parts and components in a building that receive electricity from one point and deliver it to another. “The process of taking an idea to a complete and detailed plan is full of challenges,” says Francesco Iorio, co-founder and CEO of Augmenta.
According to Iorio, the design process is very complex. That’s because from sketch to list of parts to construction, there’s a long list of considerations before coming up with a viable construction plan. The biggest benefit of AI, he says, is the ability to automate the pre-construction stages of electrical systems.
“By being able to design at the highest level of detail, while prioritizing cost and time very early in the design stage, people can experiment and answer questions that are costly to answer downstream. You can,” says Iorio.
