Is artificial intelligence a farm tractor or a spreadsheet? Jevon’s Paradox is the idea that when technological advancements make a resource more efficient, instead of society consuming the same amount of that resource more efficiently, the price goes down and consumption of that resource goes up. When the spreadsheet was invented, instead of the accounting industry getting decimated (i.e. replaced by more efficient use of resources), accounting and other spreadsheet-based jobs went up. Contrast that with when the farm tractor was invented, the farm tractor eventually replaced all horses on farms, making horses obsolete. For more on this, see this blog post by Derek Thompson.
Applying this framework to today, will AI replace knowledge-economy jobs, rendering them obsolete? Or, will it make employees in those roles more efficient, resulting in increased consumption, and eventually create more opportunities? Recent signs seem to indicate that job displacement is starting to happen, especially among early-career workers. However, it’s still early days and we probably won’t know the definitive answer for several years or more. Even without knowing the outcome, it makes sense to assess the risk now and prepare for the possibility that AI is a farm tractor.
Assessing Real Estate Industry Risk
- The real estate industry (most referring to commercial real estate investing) has Medium risk of disruption from AI. When compared to other investment areas, it is Higher risk than venture capital, but is Lower risk than public equities.
- Real estate is a less efficient market than some other markets, since it is still very relationship-based and fragmented, with market data segmented by thousands of local submarkets.
- A lot of real estate activity still happens offline, which makes it harder for AI to disrupt it. While some new service providers have made efforts to bring real estate activity online, it has been a slow process. Local brokers still control a lot, especially on larger deals, which require an element of trust.
- Compared to real estate, other markets that have Low risk of AI disruption include private equity and venture capital. Private equity often focuses on buying a business and improving operations or business strategies. These activities involve both managing people and high-level reasoning, making them hard for AI to replicate. Venture capital involves startup companies, where information is often scarce, people are a big driver of success, and companies often change strategies. These elements all make it difficult for AI to replicate.
- Markets that have High risk of AI disruption include public equities and fixed income. In these markets, information is mostly public and standardized, is universally available to many participants all over, and human psychology can often be a disadvantage.
Real Estate Role-Specific Risk
- Most at Risk – Roles that focus on repetitive, rules-based tasks: standard financial modeling, gathering comps, assembling investment memos or slide decks, underwriting loans, servicing loans, and performing appraisals. We’d caveat this by saying that current LLMs are pretty bad at financial modeling at this stage and struggle to understand spreadsheet relationships.
- Least at Risk – Investor relations and capital raising roles, since there’s a big human component; asset management of properties that are more operationally intensive; investment strategy roles, since they require more reasoning, lateral thinking, and judgement; loan origination, since it is sales and relationship-focused; real estate development, since it requires building physical real estate and overseeing a lot of external parties.
- Moderate Risk – Asset management of less operationally-intensive properties (i.e. freestanding retail properties or industrial properties with few tenants); real estate brokerage, since it involves relationships (note that some of this is migrating online); deal leads, since running deals requires project management and overseeing other people; debt capital markets, since it is somewhat relationship-based.
What Steps Can You Take?
- Get closer to the real estate – real estate operations is an important role, which when done well results in increased revenue, reduced expenses, and improved cash flow. Real estate operations is largely an “offline” role that cannot easily be automated with AI applications.
- Develop softer skills – whether it’s building relationships with investors, negotiating deal terms, building a culture of teamwork, or exhibiting leadership skills
- Use AI tools to enhance process for routine tasks – become an AI expert within your team and leverage tools to enhance your output with the same amount of time
- Go beyond return and focus on risk – return is the number that comes out of the model, but more important is risk-adjusted return. Risk is harder to quantify and requires more human judgement, which is something that is not easily replaced by AI. Try to focus on assessing risks and thinking through all the possible and probable outcomes in an investment deal.
- Think strategically – step back and engage in higher-level thinking. Start by asking yourself why are things the way they are? Is there a better way to approach the goal? Are you targeting the right goal in the first place? Are there lessons from other areas of your life that are applicable? Can you connect the dots?
- Focus on niche strategies – the most liquid parts of commercial real estate (i.e. core multifamily and industrial) are the most efficient and will be more easily replaced by AI. Niche strategies, such as student-housing, certain development, or distressed/workout situations) will take longer to get replaced.
Below is a list of popular real estate tools that are useful in various parts of the investment process. Some are more AI-focused than others. If you haven’t already, it would be a good idea to get familiar with some of these tools and find out if they can make you more efficient in your role.
Deal Sourcing Tools
- LoopNet – Largest commercial real estate marketplace in the U.S covering all asset classes and metros; integrated with Costar for enhanced market data
- Crexi – Centralized online marketplace with access to a vast inventory, including for sale, lease, and auction properties
- Reonomy – Commercial real estate data and analytics platform that provides access to extensive property records, owner contact information, transaction history, debt data, and predictive analytics. It is best for sourcing deals off-market, but is not as good for general market research.
Deal Analysis Tools
- Microsoft Copilot for Excel – AI-powered assistant for various Microsoft apps, including Excel. At this point it is best for basic financial modeling or simple data analysis, though it is less useful for complex financial modeling.
- Google Sheets with Gemini – Similar to Microsoft Copilot, Google Sheets is useful for simple modeling and data analysis at this point, but will continue to improve over time and be able to handle more complex tasks.
- Keyway – Commercial real estate technology platform that leverages artificial intelligence for investment analysis, document management, and workflow automation; performs fast, precise rent comps, market surveys, underwriting, and due diligence, helping investors spot opportunities and optimize pricing strategies, especially for multifamily.
Deal Research Tools
- CompStak – Specializes in lease comps and granular transaction data, making it useful for appraisers, underwriters, and analysts
- Costar – Offers broader coverage, deeper market analytics, more advanced property comps, and a larger listing ecosystem – including tenant leads and lease data; also provides industry-leading submarket research reports.
- Placer.ai – Location intelligence and analytics platform focused on providing real-time foot traffic data, consumer behavior insights, and in-depth demographic analysis for retail stores, shopping centers, and office buildings
- Axiometrics – Commercial real estate data and analytics company specializing in apartment and multifamily market intelligence, including comprehensive market data and forecasting.
- REIS – Comprehensive CRE market data and trend analytics, with strong coverage of multifamily and office markets
- Realpage – Property management software and data analytics solutions for the multifamily, commercial, single-family, and vacation rental markets.
- Trepp – Leading provider of data, analytics, and technology solutions primarily focused on the structured finance, commercial real estate (CRE), and banking markets.
Closing Thoughts
While ChatGPT was launched in November 2022, just three short years ago, it feels like we have lived through a full AI revolution since then. Many startups and incumbents have invested significant amounts of capital into AI, vying for a piece of the next wave of economic growth. While business application of AI still remains somewhat limited, there are also early signs that AI is impacting employment in certain areas, especially at more junior levels. Thus, it makes sense for all of us to figure out how we can adapt to this new age of AI. Whether it is focusing on more “human” skills, or becoming power users of various AI tools, now is a good time to rethink your career strategy in the age of AI.
Looking to learn more? Check out our various professional resources! Whether you have yet to break into the industry or are just starting out in a new role, we have everything you need. All you need to bring is your effort!
Thanks for reading!
Getting value from our free materials? Consider supporting us on Patreon 