Manhattan, NY CREW New York co-hosted a breakfast panel with the CCIM Institute to hear from industry leaders about technology throughout CRE and the impact of artificial intelligence (AI). Moderated by Zach Aarons of MetaProp, the panel included Aviva Fink from Reonomy, Francesca Loftus from hOM, and Janine Yorio of Compound.
The discussion opened with a general overview of AI, provided by Zach Aarons. Aarons is an early-stage PropTech investor in the U.S., having funded more than 60 startups in the space as an individual as well as 40 startups through MetaProp NYC’s venture capital funds.
Aarons explained that AI replicates “thinking‚“ behavior, as simple as Google finding a kid-friendly hotel in Portugal or as complicated as facial recognition from photos. Through machine learning, technology becomes able to make predictions and anticipate patterns based on past data i.e., Netflix cataloging viewers’ preferences as they select programs to watch and suggesting similar shows. Aarons said, “The last thing we need is an unintelligent robot that rules over us.” The panel chimed in with examples of how AI intersects with real estate technology (prop tech).
Loftus noted the use of computers that respond to guests with automated answers. She stated that machine learning is great for mapping scheduling preferences or figuring out staffing needs, though a large volume of data needs to be compiled for deep learning to work. Loftus co-founded hOM at the end of 2013. At first, hOM was providing wellness instructors to amenity managers and pivoted into being a full community management solution when they saw how many buildings couldn’t afford an amenity manager or couldn’t dedicate ample square footage to built-in amenities but had underutilized lounges or temporary vacancies that could be activated with programming.
Fink outlined the difference between deep learning and machine learning and how a program can be trained to recognize custom data patterns. She offered the example of a company classification system to show relationships between companies like LinkedIn - and people. Reonomy uses third-party data sources but analyzes this data in-house with their trading set models. They track the evolution of data on properties by date stamping changes, with the goal of creating a new version of all the property data available saved in one place.
Yorio noted that, while computers are good at mathematical data and can be trained to understand and map changes, they can’t yet completely replace the human element. For example, if a kitchen in a unit is out of date, a person will recognize this immediately, but a computer has to be painstakingly trained to understand these slight visual differences by creating a valuation model and tweaking it by a human evaluating the machine’s answers. More highly skilled people are needed to develop AI, but it will certainly be able to replace people for some applications. She mentioned that drones are now the most important new tools in real estate, teasing her male counterparts by saying that, “As long as real estate is run by men, they’ll embrace any way to use toys in everyday work.” Yorio has more than two decades of real estate investment experience. She was previously head of real estate development for Andre Balazs’ Standard hotels and before that was a portfolio manager at real estate private equity firm NorthStar Capital, where she worked on hundreds of investments from origination to exit, five of which culminated in IPOs, including four publicly-listed REITs.
To close out the morning, the panelists shared what jobs they thought would be eliminated by AI. These were their answers:
- Francesca Loftus: Property Managers;
- Janine Yorio: Title Closers;
- Aviva Fink: Originators;
- Zach Aarons: Property Technology Venture Capitalists.
Although their answers varied, they showed that AI has a wide berth of possible applications.
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