Essay Readout: Real Estate’s Hidden AI Revolution by Pete Flint

This is an essay readout using an AI voice clone of NFX general partner, Pete Flint. AI has the potential to smooth out many links in the real estate production chain and create a cascade that will close the productivity gap. This essay reveals what’s on the way and how founders can seize this opportunity. Read the full essay here - https://www.nfx.com/post/ai-revolution-proptech

Episode Transcript

(00:03):
This is Pete Flint, general partner, NFX, asinvestors and Beller, we're optimistic about
the future of AI.
One experiment amongst many, we trained AR amavatars of our voices to read out the essays we
write.
So this is my real voice you're hearing, butThis is now my AI voice.

(00:23):
I've been created by NFX to provide essayreadouts moving forward as you'll hear, I'm
still a pale imitation of the real Pete flint,but I'll get better over time.
And if you have suggestions for me, please letus know This week's article is called Real
Estate's hidden AI revolution released on aneffects.com.
Let's get started.
The icon physically build a home It can't laythe brick, install the light fixtures, or get

(00:46):
your couch up the stairs, but behind thescenes, a number of emerging technologies,
including AI, computer vision and machinelearning are transforming the fragmented
pipeline powering our Beller environment.
Is the answer to a persistent problem in thereal estate and prop tech world?
By the process of buying and selling has vastlyimproved areas like construction, architecture,
project management, and design have lagged.

(01:08):
The result is lopsided advancement and afragmented inefficient ecosystem that that's
about to change.
AI fuel by data will become the base layer thatunlocks efficiency Pete AI has the potential to
spew that many links in the real estateproduction chain and create a cascade that will
close the productivity gap.
This essay reveals what's on the way and howfounders can seize this opportunity.

(01:29):
The lopsided effect PropTech has accelerated ata tremendous pace, but critical parts of it are
lagging where we see advancement.
Companies like Trulia, Zillow, and LoopNetleverage the search paradigm to empower
consumers to become their own property hunters.
The rise of James created best in classsoftware for property management or brokerage
activities since then other companies havesmoothed out the transaction process.

(01:51):
Or introduce new and more accessible pathwaysto homeownership where we see stagnation.
Construction, for example, has been one of theslowest industries to digitize.
The average Morgan project runs about 20 monthsbehind schedule and 98% of projects overshoot
costs or timelines $1.63,000,000,000,000 invalue is lost each year due to construction

(02:12):
inefficiencies.
Consider that you can now conduct most of yourhome search and financing process totally
online and very quickly that if one piece ofconstruction equipment is overbooked, where a
remodeling plan contains a single floor orwhether strikes or skilled labor is
unavailable, then a whole building project canend up months behind.
Because of the interdependent nature of thisindustry, the whole pipeline gets jammed.

(02:35):
This is not a new problem.
The back end to Zillow and CoStar's front endhas been slow to adopt technology and high
capital expenditure in construction and complexlocal regulatory structures that made
digitization hard and seemingly not worth theeffort.
The AI is changing that, and now is the time,while there is a commercial imperative around
driving productivity, there is also a societalimperative The operation of buildings

(02:57):
contributes 30 percent of global final energyconsumption and 26 percent of global energy
related emission The current inefficiencies inour buildings is well recognized as a
contributor to climate change in step withindustries like manufacturing and transport
Morgan this is only likely to become moreimportant with the rise of extreme temperatures
as investors.
We always look at solid timing, and we believethere is a clear economic impetus enabling

(03:21):
technologies and cultural acceptance that aregoing to propel adoption, a productivity
cascade, think of the real estate world like achain, Beller project must move from one link
to the other from site selection toarchitecture to design to pre construction, to
construction, to buying selling to financingproperty management and real estate office
activities.
It's a highly interconnected network, and it isin dire need of streamlining This chain is

(03:44):
composed of third parties who manage each link.
That makes sense.
These are specialized tasks that require domainexpertise but it also creates a system where
any inefficiency within a link can be easilymissed and passed to the next link.
Over time, these problems snowball and lead tomajor delays It can take between 2 -4 months to
complete a plan and permitting process.
1 minute is 4 weeks to purchase a lot, 2 weeksto choose a designer, months to solidify the

(04:09):
plans, a month to choose a contractor, andthat's before the actual construction work even
begins.
That's for a single family house.
For anything else, it's significantly longer.
Pete is where we see opportunity for startups.
Each link along this chain can be optimizedwith AI, creating a productivity cascade along
the whole chain.
First, AI will optimize the individual links ofthe real estate production chain, creating

(04:30):
faster processes with fewer mistakes, Theselinks are primed for AI disruption because many
of them contain large corpuses of visualnumerical or language data, blueprints, zoning
laws, emissions, data.dot.new AI models allowus to tap into these data sources and improve
each process significantly.
This will begin with ai Copilots, but movetowards ai order pilots as models improve and

(04:52):
trust in built.
2nd, this will enable firms to bundle taskstogether that once demanded the resources of an
entire firm, companies will use software toenhance labor productivity, and improve on
cost, efficiency of materials.
3rd bundling of tasks will mean that companiesmanage necessary handoffs at the right time the
choreography of tasks will become dynamic andstreamlined.

(05:13):
4th, this will enable a foundation which willlead to ongoing digitization of the management
properties to ensure increased operatingefficiency.
These digital tools armed with physical sensingtechnologies will be used to reduce emissions
or operating costs Pete the full streamliningof the building life cycle, the result AI
powered real estate and prop tech platformswill be able to conduct many aspects of the

(05:35):
real estate process under one roof as opposedto the many different systems that are deployed
right now.
It will lead to fewer errors, better results,the closing of the productivity gap and greater
operational efficiency.
This is a change that we've seen most clearlyin software will eventually leak into the
manual associated with real estate throughsensing technologies and robotics.

(05:55):
Examples of AIX Real Estate.
Here are a few examples of where we see realSate powered AI companies initiating the
productivity cascade, AI optimized design,permitting environmental impact, architecture,
the concept and design phase of any buildingproject is a key step in reducing losses down
the line.
It's also one of the best fits for AI in thereal estate Construction Tech Industry, AI

(06:17):
excels a pattern recognition, and optimizationprovided it is trained on high quality
datasets.
In fields like zoning or architecture there arecorpses of work that can be used to train AI
models to act as co pilots to human architectand engineers.
Zoning and permitting codes are enormouslycomplex in the US, and AI can do a great job of
understanding at a base level what is possibleand to speed up the permitting process.

(06:40):
Also, the large and sprawling 2020 tierinflation reduction act puts incentives for
commercial buildings to lower emissions actingas a catalyst for companies to understand their
emissions footprint and improve environmentalefficiency as a result Some companies have
developed AI engines trained on data likezoning laws, demographics, and financial
information to aid with site selection.

(07:01):
Others are trained to reduce climate impact ofbuildings by architectural optimization.
We also see potential in technologies likedigital twins, which allow us to integrate a
variety of data sets from silent sources intoone living replica.
These models will allow us to run Flintscenarios and optimize each piece of the chain
from construction to operation.
Other companies operate further along thechain, NFX Back Tailored, for example, speeds

(07:26):
up the process of multifamily CapEx,renovations, and redevelopment.
Taylor Bird is capable of analyzing all sortsof publicly available visual data.
And without a Pete war, able to turn it intoarchitectural quality as built drawings.
From that designers and architects can setdesign and scope and immediately take those
plans to a marketplace to obtain hard beds,ultimately a month long process becomes a 2

(07:48):
week long process.
That means landlords can fill buildings faster,make more money, and keep buildings in better
condition for tenants.
Predictive analytics plus ai assistive projectmanagement, construction delays, and
mismanagement are large contributors to theproductivity gap We're already seeing AI
powered predictive analytics smooth out thisprocess and identify problems before they

(08:09):
arise.
For example, NFX Backed cruise by core hasdeveloped a field execution platform for
construction James.
The cruise software can automatically creatework schedules lineup crews, and lists tasks
for each person to perform via chat.
Critically, the system is also able to monitorsite health and predict future issues, For
example, the cruise by core AI engine can flagwhen back weather might delay a project when

(08:32):
too many activities are scheduled with the sameequipment at once, or a scheduled subcontractor
has a history of missing deadlines simply bykeeping those trains on the tracks.
The system can save superintendents up to 16hours in their work week, and prevent unforced
errors that impact the future of the project,the digital incumbent advantage, while we are
excited about the emerging opportunities fornew startup encumbered with access to large

(08:55):
amounts of data.
Engineers and distribution hold the initialadvantage.
The large digital residential places and largemortgage origination platform, commercial data
platforms, and construction software tools willbenefit tremendously from these new
technologies.
They have robust databases and distributionalready in place because of this improvements
in AI are likely to make their platformsincrementally better on the front end.

(09:18):
And more efficient behind the scenes.
He will likely see AI led innovationsincorporated into these platforms over the
coming quarters that the keyword here isincremental for B2B startups.
There are still opportunities if you go beyondincremental change and deliver a complete
solution.
There'd be a co pilot, the in order pilot, evenour For example, Celsoft, where capable of
generating an entire personal demand letter,not just a tool to help personal injury lawyers

(09:42):
write those letters faster.
NFX company tailored bird instantly generatesentire as built plants.
These are extremely high value propositionsbecause they truly eliminate the need for
certain processes.
PropTech companies looking to use AR to delivercomplete solutions are likely to gain an
advantage over incumbents who may be looking tograph the AI on to existing services These

(10:02):
companies aren't structured to totally recreatethe workflows they help build.
That said a key challenge for these companiesis having access to all the data in a single
form to fully understand the market, thecustomer needs, and the way that each
constituent works.
These are the key ingredients needed to createthat truly transformative AI autopilot and
deliver that complete solution.
That challenge exists because many traditionalcompanies in the industry have typically

(10:26):
embraced a best in class approach in selectingvendors, bringing onboard a number of partners
and point solutions.
While this made sense at the time, thefragmented data silos inhibit the ability to
deliver new breakthrough product experiencesand customer insights.
This is going to change.
Forward thinking companies are realizing thepower that a single system of record unlocks.
An early example of a company in this space isan FX back radius.

(10:49):
Radius helps agents source talent, managetransactions, run marketing operations, draft
contracts, and manage in house James, behindthe scenes, the company has created 1 single
source of truth for the entire process.
This opens up potential for more power for AIsolutions in the future.
Data is the lifeblood behind AI experiences.
We expect to see new data platforms as well asincreased attractiveness of verticalized

(11:12):
solutions and ecosystem.
Morgan considerations for founders.
This is still a developing ecosystem, but we'rebeginning to notice several things that
founders should keep in mind as they build inthis field.
Thursday a feature, AI has the potential tooptimize each link at the real estate
production chain, but founders should bewarethinking too small, It can be relatively easy
to build a new AI tool that is immediatelyattractive, but don't stop there.

(11:35):
You need to fully understand the value chainwhen you build a vertical CS solution, you're
thinking about all the different ways to addvalue to a certain workflow.
Maybe you can understand the environmentalimpact interface with customers or help brokers
decide when to follow-up on leads.
Some of these activities hold more inherentvalue than others, their control Flint These
value will control points at the best places tobegin building your company.

(11:58):
They are the need to have.
Control points also typically do more than justsave time but facilitate the transaction.
Any tasks are helpful, but not true controlpoints.
For example, many companies are capable ofanalyzing opens using AI, but is this a wedge
or entry point that opens up the biggestopportunity to scale into a large company,
consider whether you are more likely to begrafted on to an existing service or over time,

(12:21):
if you could begin to expand your own product,you could imagine an upstream AI optimized
design tool creating a carbon reductionworkflow for example, be sure that you're the
bigger idea, not the feature.
This will be a challenge for startups becauseyou need to get to distribution faster than
encumbrance can innovate.
Ultimately, AI will make it possible to bundletogether specialized tasks under one workflow.

(12:42):
It's okay to start with an incredibly valuablefeature don't stay so specialized that you're
bundled away.
Avoid falling into this trap by identifying thetrue control points in your industry and
building around them.
To recognize where 3rd party status holdsvalue, there will be fewer handoffs between
disparate parties and an AI powered real estateindustry but there are still some aspects of
the process where 3rd party status is a featureMorgan bug.

(13:05):
For example, accreditation, property valuationsWe're auditing of all tasks that must be
performed by outside parties.
These are areas that will be harder to graft onto upstream services 3, debt paid for the work
that you do, deliver true value.
Don't just save time.
The killer proposition in the generative AIworld isn't about optimizing efficiency through
time saving automation.

(13:26):
It's about using that maximized efficiency,unlocking value to drive growth, Flint time
saving solutions may not be the best way tomonetize the service.
You could use this technology to create abreakthrough product experience or to monetize
in some downstream activities.
For example, can you incorporate a marketplaceor embedded fintech to capture more value
beyond a simple time saving tool where we seethe most exciting opportunities or AI enables a

(13:49):
breakthrough proposition that enables companiesto participate in the transaction and get paid
for the value they unlock the companies thatstrongly connect the dots between increased
efficiency and growth are in the best positionto succeed.
Through the compliance audit pilot, real estateremains a highly regular industry, there's a
lot of value to be gained in helping peoplenavigate those opportunities, especially by

(14:11):
flagging small administrative mistakes beforethey snowball into bigger problem, Again, this
will begin with co piloting but move towardsorder piloting.
The transition is happening in high stakesindustries.
One of the earliest examples of AI co pilotingfor example, was in radiology.
AI was used to help detect abnormalities inmammograms and increasingly has begun to be

(14:31):
seen as a key player in the future of theradiology field.
Eventually, as trust builds and technologyimproves, it may eventually be seen as
necessary.
That pattern is likely to repeat Wheneverthere's a routine compliance task, that's an
opportunity for the co piloting to autopiloting transition to occur an overlooked
opportunity, AI, in the physical world, We seemany companies pursuing office activities,

(14:53):
creative work, or digital first applications ofAI.
Many incumbent CAI as the newest way to pursueoffice process automation, but our impact on
the physical world is already Pete, and it'sonly going to get more central architecture,
engineering, and construction is one of the topindustries to be impacted by AI in the future
for an April Goldman Sachs report as we'vecovered.

(15:13):
We're seeing it on the software side, but it'shere on the physical side too.
For robotics, sensing, and emergent IoTtechnologies that will be an even largely real
estate and prop tech are an entry point It'sone of the first places we are starting to see
eyes fingerprints in the physical world.
It's an enormous opportunity.
The first step is to close that$1,630,000,000,000 Globe productivity gap.

(15:35):
If you are an early stage founder building astartup at the intersection of real estate and
AI, then come talk to us.
Thanks for listening to this week's essayreadout of Real Estate's hidden AI revolution.
As a reminder, this is still an AI imitation ofPete Flint speaking.
We are having fun experimenting with new tools,but we'd love to hear your feedback Email us

(15:58):
[e-mail], subscribe to the NFX podcaston your favorite listening platform, share with
your network and founder friends, and staytuned for weekly essays and much more.