AI Transforming the Real Estate Industry: A Data-driven Future
Key Takeaways
- Serial entrepreneur Litan Yahav emphasizes the importance of data and its increasing role in the real estate industry, particularly in commercial real estate.
- While AI is crucial, it is the unique data sets held by companies and the ability to understand and leverage this data that truly drives value.
- The quality and insights gained from a well-curated data set can help investors make better investment decisions, including evaluating real estate assets and identifying reliable General Partners (GPs).
- Although AI and data are transforming the industry, the personal touch and expertise of individuals on the ground remain crucial, especially in areas like construction and property management.
Understanding the Intersection of AI and Real Estate
The real estate business, especially its commercial facet, relies heavily on data. Every transaction revolves around information about assets, market trends, and the performance of GPs, who manage and operate properties. Yet, this data landscape is fragmented, which often necessitates reliance on specific GPs and their track records.
Yahav believes AI emerges as a powerful tool for integrating and structuring this fragmented data. He compares the current state of AI in real estate to the early days of the internet, stating: “I do believe that AI is like the internet. Back in the late ’90s, early 2000s, if you were in a company that wasn’t leveraging the internet, you had no right to exist. And so I think the same is like with AI now.”
Data-Driven Decisions: From Asset Evaluation to Operator Vetting
The use of AI in real estate extends beyond simply collecting data. It helps investors make better-informed decisions by analyzing and extracting insights from this data. Yahav illustrates this with several points:
- Evaluating Assets: Companies like Zillow and CoStar aggregate vast quantities of real estate data, enabling AI models to create benchmarks and price comparisons, assisting investors in gauging whether the price of a property is below or above market.
- Assessing Operators: Beyond the asset itself, Yahav emphasizes the importance of evaluating the GP. “The most important thing is like the horse you’re betting on,” he says. AI can be used to vet operators by analyzing their past performance, track record, investment choices, and communication patterns.
- Market Insights: AI models, fed with data on asset classes, GPs, and specific market geographies, can help investors identify which asset classes haven’t missed distributions, which GPs have consistent track records, and where returns have been most stable.
Beyond AI: The Human Element Remains Essential
Despite the transformative potential of AI and data, Yahav remains grounded, recognizing that human expertise and judgment remain vital, especially for on-the-ground activities. He states, “The last frontier, and I think we’re very far away from that, I think even with the progression of AI, are still the boots on the ground, which is going to be a very unique offering that people have … the technicians, electricians, the HVAC people.”
The Importance of “Soft” Factors and Sentiment
Yahav acknowledges the limitations of data and AI in capturing intangible elements, highlighting a critical aspect of real estate investment: “There’s that soft component to the whole thing that you can’t always glean from the data.” He emphasizes that subjective factors like the character, experience, and relationships of the GPs contribute significantly to a deal’s success.
He reveals that he relies on his gut feeling, combined with the advice of trusted individuals in his network, to evaluate the integrity and credibility of GPs. He prefers to invest with individuals who have a proven track record and whom he has personally met and vetted.
The Future: Data as a Competitive Advantage
Yahav envisions a future where data becomes a crucial differentiator for real estate companies. He believes that companies with unique and well-managed data sets will gain a significant advantage in leveraging AI for value creation and client service.
He cites the example of companies like Zillow, which have amassed vast quantities of user data, enabling them to refine propositions, perfect pricing models, and sell this valuable data to other companies.
Similarly, Yahav’s current venture, Viser, focuses on gathering proprietary data about private markets, particularly by aggregating information about Limited Partners (LPs) and GPs. This data set allows Viser to offer tailored investment advisory and underwriting services to clients.
The Need for a Data-Driven Approach
The insights from the discussion underscore the critical need for a data-driven approach to real estate investing. AI can be leveraged to facilitate faster, more informed decisions, creating efficient market analysis, asset valuation, and risk assessment.
Even though the real estate industry is a people-centric business, the ability to incorporate and interpret data effectively will determine the success of both companies and individual investors. As Yahav concludes, “I think it’s going to be just like the internet. You just have to learn to live with it, leverage it to wherever you think is the future. And obviously, this will create a lot more just like the internet created more jobs. This will create jobs as well.”