Agya Ventures, a venture capital firm focused on real estate tech, blockchain, AI and sustainability, proclaims the emergence of artificial intelligence (AI) will cut through material use cases in real estate tech from search and listings to mortgages, construction, and sustainability.
“AI presents a generational opportunity in real estate,” said Kunal Lunawat, co-founder and managing partner of Agya Ventures. “Real estate is a $50+ Tn asset class, and one of the key drivers of the global economy. There is a significant opportunity for real estate tech entrepreneurs, because of the scale of the opportunity, and the moment of time we find ourselves in.”
The Opportunity in Real Estate Tech
Some of the most valuable companies in the early years of the real estate tech cycle created significant stakeholder value across these sub-sectors in real estate tech listed below – all of that will be in play with AI in the future.
- Residential search and listings: Google’s first real threat to its Search product could come through Bing’s integration with ChatGPT. That said, both Search and Bing are not tailormade for real estate, which in part, explains why Zillow, Redfin, and StreetEasy have become valuable businesses. A machine learning (ML) enabled search and listings engine that leverages large language models, integrates with MLS providers, and provides more robust results for buyers and renters presents a significant opportunity.
- Real estate brokerages: We believe real estate will always need the consultative hand of brokers – they are invaluable and cannot be replaced when an individual or family is making the largest financial decision of their lives in buying a home. Yet, a number of services provided by brokers and brokerages can be automated in a similarly personalized and consultative manner. Enter AI-powered chatbots that power real estate brokerages of the future.
- Mortgage marketplaces and underwriting: The single-family mortgage market is estimated to be >$13 Tn in the United States alone. Mortgage search and underwriting have gotten better over the years but there’s room for much more. For one, the industry stands out for its abject lack of personalization. AI has the ability to create and work off infinite customer personas, providing more robust search and underwriting solutions.
- Renters and homeowners’ insurance: Landlords and mortgage lenders typically mandate renters/buyers to get an insurance policy before moving into an apartment/home. Unlike real estate brokerages, where the agent’s role is critical, it is our belief that AI can completely automate the insurance layer, especially as it relates to renters’ and homeowners’ insurance policies. These products are relatively cheaper and not as complex, and ML-tooled bots can improve the customer journey: from acquisition and underwriting to policy administration and claims management. Companies like Lemonade have given a glimpse of what’s possible with Maya AI but we have only gotten started in this $125 Bn+ market.
- Construction estimation, bids and materials: The world is going to add 2 Tn square feet of real estate by 2060 – the equivalent of adding 1 New York City every month for the next 37 years! Pause for a moment and think about the amount of data the construction industry will generate over the next few years – and now consider the existing BIM and BOM models and current paper/spreadsheet-based estimation and bidding tools, and their technical sophistication. We are not going to replace general contractors at the job site but it’s amiss to say that general contractors that don’t partner with AI companies to leverage their own data will be at a competitive disadvantage in the years to come.
- Sustainable construction: The built world accounts for 40% of global greenhouse emissions, and with 2 trillion square feet of additional real estate coming up, the number does not look any better. Part of the problem in solving emissions from the built world is that there’s only as much we can do with existing real estate – emissions that have been already operationalized in the environment. The more effective solution is to embed sustainability at the point of inception of the project, when a building is still in its design stages. Layering AI in an architect’s workflow to determine emissions outcomes across scenarios, and subsequently make recommendations triaging cost, zoning and sustainability is going to be critical in how the built world interacts with climate change.
Moment in Time
“Considering the significant opportunity set for real estate and AI today, we distinctly believe startups are better positioned to build new companies in the space, compared to legacy real estate technology companies looking to add AI to their existing product mix,” Lunawat said.
The AI revolution will birth two categories of companies, as defined by entrepreneur and author Elad Gil.
- De novo applications built on top of large language models by startups that don’t exist today but will thrive in the years to come. Ex: an AI-enabled new real estate search platform with a distinct UI/UX.
- Incumbent products that add AI/machine learning tooling to remain competitive in the market and retain distribution. Ex: Zillow injects AI into its search feed but largely retains its product functionality.
When it comes to real estate tech, it is crucial to juxtapose Gil’s distinction with how 2022 panned out for incumbents in the industry. Layoffs abounded in real estate tech last year – close to 10,000 people were let go in 2022, up 300% from 2021, as companies sought to preserve burn and refocus on their core offerings. An index of 17 publicly listed real estate technology companies was down >80% from their peak valuation, many of them having gone public via SPACs in the recent past.
“At a time when several incumbents in real estate tech continue to battle challenging micro and macro conditions, it is tough to envision how existing players can effectively adapt AI in a meaningful fashion this year,” Lunawat said. “Our analysis indicates that mature companies are looking to play defense and preserve their core offering, ruling out any robust embrace of AI in their existing products.”
This, in turn, creates a unique and urgent window for startups to build ground-up de novo applications for real estate with AI at its core. The technology is not perfect but is growing at a breakneck speed. ChatGPT 4.0 is expected to launch this year and will open yet another paradigm in AI. We have entered an era where programming moves from imperative to declarative code, expediting product cycles and feedback loops in an unprecedented fashion. In all of this, the opportunity set for entrepreneurs in real estate tech across search, listings, mortgage, insurance, construction, and sustainability stands out as a generational one.
This report was originally published in TechCrunch