compass has invested over $1 billion in technology that helps the real estate company’s nearly 30,000 agents go from the earliest contact with a potential client to the closing of a deal – all through one technology platform.
“Our mission is to help agents grow their business, make more money, save time and create great experiences for their customers,” says Rory Golod, president of growth and communications at Compass.
Investments from Compass, the country’s largest brokerage by sales volume, include Likely to Sell, an artificial intelligence tool that analyzes prospects and makes recommendations about who might be ready to sell their home soon. The company recently launched Compass AI, a chatbot tool that can help write real estate listings, marketing materials and agent profiles.
Agents can have thousands of contacts at their fingertips, Golod says, and conversation rates are often exceptionally low with traditional marketing tactics like email and social media. But Compass says that since Likely to Sell launched in summer 2020, nearly 8% of recommendations made monthly through its customer relationship management (CRM) tool are listed on the market within 12 months.
“We want to use AI to help an agent say, ‘If I want to reach someone, I want to reach the people who have the greatest propensity to maybe transact,'” Golod says.
According to McKinsey, advances in generative AI could unlock an estimated $180 billion in value Estimates. The industry could certainly benefit from such a shock as US home sales sank to their lowest level in nearly 30 years in 2023 due to high mortgage rates and low inventory, which have made home purchases significantly more expensive. The industry faces significant disruption in commission fees, according to the National Association of Realtors made a deal This could result in home buyers and sellers negotiating lower agent commissions. There is also a big problem in construction because the nation is simple is not building enough new homes to meet demand.
However, there are many complicating factors that make adopting AI in real estate particularly difficult. Experts say there are huge amounts of disorganized data, ranging from leases to contracts, from investment documents to design plans. The construction industry works with extremely thin margins. The average age of a real estate agent is older than that of workers in most industries, and people in the industry are notoriously tech-shy. And due to the very physical nature of the industry, many technological advances are still in their infancy.
“I would say that real estate has historically been a little bit behind when it comes to the use of AI,” says Alex Wolkomir, partner at McKinsey.
Wolkomir says commercial real estate is further along in adopting AI than residential real estate. He believes the industry’s biggest challenge is ensuring its workforce – builders, real estate agents, designers – is properly trained and understands the capabilities of the AI tools provided to them. He is encouraged by the advances in AI development in the industry over the last five years.
“I think a lot of them [generative] In a sense, AI use cases open up new areas that are of great value for real estate,” says Wolkomir.
Yao Morin, chief technology officer at JLL, says one of the challenges facing commercial real estate is the abundance of unstructured data in the form of leases, contracts and invoices. “I believe that in the age of AI, the barrier to using AI will continue to decrease,” says Morin. “And then you ask yourself, ‘If using AI isn’t a competitive advantage, what is?’ The answer is absolutely your data.”
Last year the company revealed JLL GPT, a generative AI model that provides clients with insights based on JLL’s proprietary market research and externally available market data. According to Morin, 20% of JLL’s 103,000 employees use JLL GPT weekly because the technology allows employees to complete repetitive tasks more efficiently.
JLL also uses generative AI to better predict building maintenance needs, explore investment opportunities and implement sustainability initiatives. “When you think about classic AI, there is a higher learning curve required to understand it and trust the results,” says Morin. “But with generative AI, it’s much easier for us to adopt it and let people see the value.”
Startup Higharc has launched a home construction automation platform that aims to make home construction a faster and more cost-effective process.
“We provide data about houses that are being built,” says Marc Minor, CEO of Higharc. “And when I say ‘make data available,’ I mean every part and part of the building and where it goes, when it needs to be built and who is responsible for that part of the building. We control all this information automatically.”
Last month Higharc increased $53 million in Series B fundingalso from the dealer Home Depotthe venture arm of France Schneider Electricand others in the construction, building products and manufacturing industries. Minor says the biggest opportunities lie in both improving the way homes are built and accessing data from dealers and suppliers.
“If you build the right software layer to systematically change housing in terms of how homes are designed, it makes it easier to understand how to leverage the hardware side,” says Minor.
Prologue Founded in 2016, Ventures has invested $250 million in over 45 supply chain and logistics-focused startups, 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 of Prologis Ventures. “But there is just tons of data that could be collected and analyzed [it]Then you would have better insight to make that decision.”
Prologis used as an example TestFit’s AI in order to better assess the feasibility of new storage locations. Information about specific zoning regulations, environmental conditions, transportation options around a site, and workforce can be integrated to improve decision-making. TestFit can also create dozens of project renderings in just an hour and makes suggestions based on previous metrics.
“As a company, we have long been concerned with the question: What information is important for our customers when they make a decision?” asks O’Donnell. “What matters to them as they drive their business, and how can we empower both our employees and our customers to better understand this information?”
Augmenta, on the other hand, automates designs for electrical systems, all the parts and pieces within a building that draw power from one point and deliver it to another. “The process from ideation to a complete, detailed plan is fraught with challenges,” says Francesco Iorio, co-founder and CEO of Augmenta.
The design process, Iorio explains, is extremely complex, because from sketch to parts list to construction, there is a long list of considerations before an actionable construction plan is in place. In his opinion, the biggest advantage of AI is the automation of the pre-construction phase for electrical systems.
“Giving them the opportunity to design at the highest level of detail, with cost and time at the forefront very early in the design phase, allows people to experiment and answer questions that would be costly to answer downstream,” says Iorio.