• It’s the answer to a persistent problem in the real estate and proptech world. While 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. (View Highlight)
  • Where we see stagnation: Construction, for example, has been one of the slowest industries to digitize. The average mega-project runs about 20 months behind schedule, and 98 percent of projects overshoot costs or timelines. $1.63 Trillion in value is lost each year due to construction inefficiencies. (View Highlight)
  • Consider that you can now conduct most of your home search and financing process totally online and very quickly. But if one piece of construction equipment is overbooked, or a remodeling plan contains a single flaw, or weather strikes, or skilled labor is unavailable, then a whole building project can end up months behind. Because of the interdependent nature of this industry (it’s all centered around a core asset – the buildings where we live, work and play or the infrastructure that supports them) the whole pipeline gets jammed. (View Highlight)
  • While there is a commercial imperative around driving productivity, there is also a societal imperative. The operation of buildings contributes 30% of global final energy consumption, and 26 percent of global energy-related emissions. The current inefficiencies in our buildings is well recognized as a contributor to climate change, in step with industries like manufacturing and transport. And this is only likely to become more important with the rise of extreme temperatures. (View Highlight)
  • Think of the real estate world like a chain. Every project must move from one link to the other. From site selection to architecture to design to preconstruction, to construction, to buying/selling, to financing, property management, and real estate office activities. (View Highlight)
  • It can take between 2-4 months to complete a plan and permitting process. 1-4 weeks (if all goes perfectly) 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. (View Highlight)
  • 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…new AI models allow us to tap into these data sources and improve each process significantly. (View Highlight)
  • Second: 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. (View Highlight)
  • Third: Bundling of tasks will mean that companies manage necessary handoffs at the right time. The choreography of tasks will become dynamic, and streamlined. (View Highlight)
  • Fourth: This will enable a foundation which will lead to ongoing digitization of the management of properties to ensure increased operating efficiency. These digital tools, armed with physical sensing technologies, will be used to reduce emissions, or operating costs, completing the full streamlining of the building life cycle. (View Highlight)
  • The result: AI-powered real estate and proptech 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. (Some companies are already doing this). (View Highlight)
  • AI excels at 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 architects, 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 2022 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. (View Highlight)
  • Other companies operate further along the chain. NFX-backed Tailorbird, for example, speeds up the process of multi-family capex, renovations, and redevelopment. TailorBird is capable of analyzing all sorts of publicly available visual data, and without a site walk, able to turn it into architectural quality as-built drawings. From there, designers and architects can set design and scope, and immediately take those plans to a marketplace to obtain hard bids. (View Highlight)
  • For example, NFX-backed Crews by Core has developed a field execution platform for construction teams. The crews software can automatically create work schedules, line up crews, and list tasks for each person to perform via chat. Critically, the system is also able to monitor site health and predict future issues. (View Highlight)
  • The large digital residential marketplaces (e.g. Trulia, Zillow) and large mortgage origination platforms, commercial data platforms and construction software tools (who are not asleep at the wheel) 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. You will likely see AI led innovations incorporated into these platforms over the coming quarters. (View Highlight)
  • That challenge exists because many traditional companies in the industry have typically embraced a “best in class” approach in selecting vendors bringing on board 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. (View Highlight)
  • AI has the potential to optimize each link of 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. (View Highlight)
  • Many tasks are helpful, but not true control points. For example, many companies are capable of analyzing floorplans using AI, but is this a wedge or entry point that opens up the biggest opportunity to scale into a large company? (View Highlight)
  • There will be fewer handoffs between disparate parties in an AI-powered real estate industry. But there are still some aspects of the process where 3rd party status is a feature, not a bug. (View Highlight)
  • For example: accreditation, property valuations, or auditing are all tasks that must be performed by outside parties. These are areas that will be harder to graft on to upstream services. (View Highlight)
  • The killer proposition in the generative AI world isn’t about maximizing efficiency through time saving automation. It’s about using that maximized efficiency – unlocking value to drive growth. (View Highlight)
  • 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 (in some cases, better than trained radiologists), 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. (View Highlight)