This is Pete Flint, general partner, NFX, as investors and Beller, we're optimistic about the future of AI. One experiment amongst many, we trained AR am avatars of our voices to read out the essays we write. So this is my real voice you're hearing, but This is now my AI voice. I've been created by NFX to provide essay readouts 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 let us know This week's article is called Real Estate's hidden AI revolution released on an effects.com. Let's get started. The icon physically build a home It can't lay the brick, install the light fixtures, or get your couch up the stairs, but behind the scenes, a number of emerging technologies, including AI, computer vision and machine learning are transforming the fragmented pipeline powering our Beller environment.
Is the answer to a persistent problem in the real estate and prop tech world? By the process of buying and selling has vastly improved areas like construction, architecture, project management, and design have lagged. The result is lopsided advancement and a fragmented inefficient ecosystem that that's about to change.
AI fuel by data will become the base layer that unlocks efficiency Pete AI has the potential to spew that 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. The lopsided effect PropTech has accelerated at a tremendous pace, but critical parts of it are lagging where we see advancement.
Companies like Trulia, Zillow, and LoopNet leverage the search paradigm to empower consumers to become their own property hunters. The rise of James created best in class software for property management or brokerage activities since then other companies have smoothed out the transaction process. Or introduce new and more accessible pathways to homeownership where we see stagnation. Construction, for example, has been one of the slowest industries to digitize.
The average Morgan project runs about 20 months behind schedule and 98% of projects overshoot costs or timelines $1.63,000,000,000,000 in value is lost each year due to construction inefficiencies.
Consider that you can now conduct most of your home search and financing process totally online and very quickly that if one piece of construction equipment is overbooked, where a remodeling plan contains a single floor or whether strikes or skilled labor is unavailable, then a whole building project can end up months behind. Because of the interdependent nature of this industry, the whole pipeline gets jammed. This is not a new problem.
The back end to Zillow and CoStar's front end has been slow to adopt technology and high capital expenditure in construction and complex local regulatory structures that made digitization hard and seemingly not worth the effort.
The AI is changing that, and now is the time, while there is a commercial imperative around driving productivity, there is also a societal imperative The operation of buildings contributes 30 percent of global final energy consumption and 26 percent of global energy related emission The current inefficiencies in our buildings is well recognized as a contributor to climate change in step with industries like manufacturing and transport
Morgan this is only likely to become more important with the rise of extreme temperatures as investors.
We always look at solid timing, and we believe there is a clear economic impetus enabling technologies and cultural acceptance that are going to propel adoption, a productivity cascade, think of the real estate world like a chain, Beller project must move from one link to the other from site selection to architecture to design to pre construction, to construction, to buying selling to financing property management and real estate office activities.
It's a highly interconnected network, and it is in dire need of streamlining This chain is composed of third parties who manage each link. That makes sense. These are specialized tasks that require domain expertise but it also creates a system where any inefficiency within a link can be easily missed and passed to the next link. Over time, these problems snowball and lead to major 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 weeks to choose a designer, months to solidify the plans, a month to choose a contractor, and that'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 optimized with AI, creating a productivity cascade along the whole chain.
First, AI will optimize the individual links of the real estate production chain, creating faster processes with fewer mistakes, These links are primed for AI disruption because many of them contain large corpuses of visual numerical or language data, blueprints, zoning laws, emissions, data.dot.new AI models allow us to tap into these data sources and improve each process significantly. This will begin with ai Copilots, but move towards ai order pilots as models improve and trust in built.
2nd, this will enable firms to bundle tasks together that once demanded the resources of an entire firm, companies will use software to enhance labor productivity, and improve on cost, efficiency of materials. 3rd bundling of tasks will mean that companies manage necessary handoffs at the right time the choreography of tasks will become dynamic and streamlined.
4th, this will enable a foundation which will lead to ongoing digitization of the management properties to ensure increased operating efficiency.
These digital tools armed with physical sensing technologies will be used to reduce emissions or operating costs Pete the full streamlining of the building life cycle, the result AI powered real estate and prop tech platforms will be able to conduct many aspects of the real estate process under one roof as opposed to 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 clearly in software will eventually leak into the manual associated with real estate through sensing technologies and robotics. Examples of AIX Real Estate. Here are a few examples of where we see real Sate powered AI companies initiating the productivity cascade, AI optimized design, permitting environmental impact, architecture, the concept and design phase of any building project is a key step in reducing losses down the line.
It's also one of the best fits for AI in the real estate Construction Tech Industry, AI excels a pattern recognition, and optimization provided it is trained on high quality datasets. In fields like zoning or architecture there are corpses of work that can be used to train AI models to act as co pilots to human architect and engineers.
Zoning and permitting codes are enormously complex in the US, and AI can do a great job of understanding at a base level what is possible and to speed up the permitting process.
Also, the large and sprawling 2020 tier inflation reduction act puts incentives for commercial buildings to lower emissions acting as a catalyst for companies to understand their emissions footprint and improve environmental efficiency as a result Some companies have developed AI engines trained on data like zoning laws, demographics, and financial information to aid with site selection. Others are trained to reduce climate impact of buildings by architectural optimization.
We also see potential in technologies like digital twins, which allow us to integrate a variety of data sets from silent sources into one living replica. These models will allow us to run Flint scenarios and optimize each piece of the chain from construction to operation. Other companies operate further along the chain, NFX Back Tailored, for example, speeds up the process of multifamily CapEx, renovations, and redevelopment.
Taylor Bird is capable of analyzing all sorts of publicly available visual data. And without a Pete war, able to turn it into architectural quality as built drawings. From that designers and architects can set design and scope and immediately take those plans to a marketplace to obtain hard beds, ultimately a month long process becomes a 2 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 project management, construction delays, and mismanagement are large contributors to the productivity gap We're already seeing AI powered predictive analytics smooth out this process and identify problems before they arise. For example, NFX Backed cruise by core has developed a field execution platform for construction James. The cruise software can automatically create work schedules lineup crews, and lists tasks for each person to perform via chat.
Critically, the system is also able to monitor site health and predict future issues, For example, the cruise by core AI engine can flag when back weather might delay a project when too many activities are scheduled with the same equipment at once, or a scheduled subcontractor has a history of missing deadlines simply by keeping those trains on the tracks.
The system can save superintendents up to 16 hours 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 for new startup encumbered with access to large amounts of data. Engineers and distribution hold the initial advantage.
The large digital residential places and large mortgage origination platform, commercial data platforms, and construction software tools will benefit tremendously from these new technologies. They have robust databases and distribution already in place because of this improvements in AI are likely to make their platforms incrementally better on the front end. And more efficient behind the scenes.
He will likely see AI led innovations incorporated into these platforms over the coming quarters that the keyword here is incremental for B2B startups. There are still opportunities if you go beyond incremental change and deliver a complete solution. There'd be a co pilot, the in order pilot, even our For example, Celsoft, where capable of generating an entire personal demand letter, not just a tool to help personal injury lawyers write those letters faster.
NFX company tailored bird instantly generates entire as built plants. These are extremely high value propositions because they truly eliminate the need for certain processes. PropTech companies looking to use AR to deliver complete solutions are likely to gain an advantage over incumbents who may be looking to graph the AI on to existing services These companies aren't structured to totally recreate the workflows they help build.
That said a key challenge for these companies is having access to all the data in a single form to fully understand the market, the customer needs, and the way that each constituent works. These are the key ingredients needed to create that truly transformative AI autopilot and deliver that complete solution.
That challenge exists because many traditional companies in the industry have typically embraced a best in class approach in selecting vendors, bringing onboard a number of partners and point solutions. While this made sense at the time, the fragmented data silos inhibit the ability to deliver new breakthrough product experiences and customer insights. This is going to change. Forward thinking companies are realizing the power that a single system of record unlocks.
An early example of a company in this space is an FX back radius. Radius helps agents source talent, manage transactions, run marketing operations, draft contracts, and manage in house James, behind the scenes, the company has created 1 single source of truth for the entire process. This opens up potential for more power for AI solutions in the future. Data is the lifeblood behind AI experiences.
We expect to see new data platforms as well as increased attractiveness of verticalized solutions and ecosystem. Morgan considerations for founders. This is still a developing ecosystem, but we're beginning to notice several things that founders should keep in mind as they build in this field.
Thursday a feature, AI has the potential to optimize each link at the real estate production chain, but founders should beware thinking too small, It can be relatively easy to build a new AI tool that is immediately attractive, but don't stop there. You need to fully understand the value chain when you build a vertical CS solution, you're thinking about all the different ways to add value to a certain workflow.
Maybe you can understand the environmental impact interface with customers or help brokers decide when to follow-up on leads. Some of these activities hold more inherent value than others, their control Flint These value will control points at the best places to begin building your company. They are the need to have. Control points also typically do more than just save time but facilitate the transaction. Any tasks are helpful, but not true control points.
For example, many companies are capable of analyzing opens using AI, but is this a wedge or entry point that opens up the biggest opportunity to scale into a large company, consider whether you are more likely to be grafted on to an existing service or over time, if you could begin to expand your own product, you could imagine an upstream AI optimized design tool creating a carbon reduction workflow for example, be sure that you're the bigger idea, not the feature.
This will be a challenge for startups because you need to get to distribution faster than encumbrance can innovate. Ultimately, AI will make it possible to bundle together specialized tasks under one workflow. It's okay to start with an incredibly valuable feature don't stay so specialized that you're bundled away. Avoid falling into this trap by identifying the true control points in your industry and building around them.
To recognize where 3rd party status holds value, there will be fewer handoffs between disparate parties and an AI powered real estate industry but there are still some aspects of the process where 3rd party status is a feature Morgan bug. For example, accreditation, property valuations We're auditing of all tasks that must be performed by outside parties. These are areas that will be harder to graft on to 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 AI world isn't about optimizing efficiency through time saving automation. It's about using that maximized efficiency, unlocking value to drive growth, Flint time saving solutions may not be the best way to monetize the service. You could use this technology to create a breakthrough product experience or to monetize in some downstream activities.
For example, can you incorporate a marketplace or embedded fintech to capture more value beyond a simple time saving tool where we see the most exciting opportunities or AI enables a breakthrough proposition that enables companies to participate in the transaction and get paid for the value they unlock the companies that strongly connect the dots between increased efficiency and growth are in the best position to succeed.
Through the compliance audit pilot, real estate remains a highly regular industry, there's a lot of value to be gained in helping people navigate those opportunities, especially by flagging small administrative mistakes before they snowball into bigger problem, Again, this will begin with co piloting but move towards order piloting. The transition is happening in high stakes industries. One of the earliest examples of AI co piloting for example, was in radiology.
AI was used to help detect abnormalities in mammograms and increasingly has begun to be seen as a key player in the future of the radiology field. Eventually, as trust builds and technology improves, it may eventually be seen as necessary.
That pattern is likely to repeat Whenever there's a routine compliance task, that's an opportunity for the co piloting to auto piloting transition to occur an overlooked opportunity, AI, in the physical world, We see many companies pursuing office activities, creative work, or digital first applications of AI.
Many incumbent CAI as the newest way to pursue office process automation, but our impact on the physical world is already Pete, and it's only going to get more central architecture, engineering, and construction is one of the top industries to be impacted by AI in the future for an April Goldman Sachs report as we've covered. We're seeing it on the software side, but it's here on the physical side too.
For robotics, sensing, and emergent IoT technologies that will be an even largely real estate and prop tech are an entry point It's one 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. If you are an early stage founder building a startup at the intersection of real estate and AI, then come talk to us.
Thanks for listening to this week's essay readout of Real Estate's hidden AI revolution. As a reminder, this is still an AI imitation of Pete Flint speaking. We are having fun experimenting with new tools, but we'd love to hear your feedback Email us acuityd@nfx.com, subscribe to the NFX podcast on your favorite listening platform, share with your network and founder friends, and stay tuned for weekly essays and much more.