Outlook for Artificial Intelligence in Real Estate: Startups Will Create the Future of Proptech

Agya Ventures

PR99578

 

SAN FRANCISCO, Feb. 16, 2023 /PRNewswire=KYODO JBN/ --

 

Agya Ventures (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=3281858006&u=https%3A%2F%2Fwww.agyaventures.com%2F&a=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.

 

Logo - https://mma.prnewswire.com/media/1878586/Agya_Logo.jpg

 

"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.

 

    1. 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 (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=1395405999&u=https%3A%2F%2Fwww.nar.realtor%2Fnar-doj-settlement%2Fmultiple-listing-service-mls-what-is-it&a=MLS

)

       providers, and provides more robust results for buyers and renters

       presents a significant opportunity.

 

    2. 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.

 

    3. Mortgage marketplaces and underwriting: The single-family mortgage

       market is estimated to be >$13 Tn (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=116630444&u=https%3A%2F%2Fwww.bankingstrategist.com%2Fmortgage-finance-sector&a=%3E%2413+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.

 

    4. 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 (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=3297307397&u=https%3A%2F%2Fwww.ibisworld.com%2Findustry-statistics%2Fmarket-size%2Fhomeowners-insurance-united-states%2F&a=%24125+Bn%2B+market

).

 

    5. Construction estimation, bids and materials: The world is going to add 2

       Tn square feet of real estate by 2060 (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=2347699888&u=https%3A%2F%2Fwww.gatesnotes.com%2FEnergy%2FBuildings-are-good-for-people-and-bad-for-the-climate%23%3A%7E%3Atext%3DAs%2520the%2520global%2520population%2520rises%2Cfor%2520the%2520next%252040%2520years.&a=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.

 

    6. Sustainable construction: The built world accounts for 40% of global

       greenhouse emissions (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=1312161470&u=https%3A%2F%2Fwww.weforum.org%2Fagenda%2F2022%2F11%2Fhow-we-can-decarbonize-the-real-estate-sector%2F%23%3A%7E%3Atext%3DReal%2520estate%2520drives%2520approximately%252040%2Cin%2520the%2520real%2520estate%2520sector.&a=40%25+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.

 

    1. 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.

 

    2. 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 (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=2922636007&u=https%3A%2F%2Flayoffs.fyi%2F&a=10%2C000+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 (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=2922636007&u=https%3A%2F%2Flayoffs.fyi%2F&a=10%2C000+people

), 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 (

https://c212.net/c/link/?t=0&l=en&o=3784681-1&h=1443073535&u=https%3A%2F%2Ftechcrunch.com%2F2023%2F02%2F07%2Fgenerative-ai-is-building-the-foundation-of-proptechs-next-wave%2F&a=This+report

) was originally published in TechCrunch

 

CONTACT: Agency Esta, Yael Gewant, yael@agencyesta.com

 

SOURCE  Agya Ventures

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