Insight
In this episode of Buildings 2.0, Jose speaks with Serge Reda, Co-Founder at AlphaRithm AI and Chair of Fordham REI Technology Committee. They discuss technology and data science within the commercial real estate industry and how using programming tools like Python can help stitch together disparate SaaS applications. They also talk about how early adopters today will set the standards for doing business tomorrow, the need for specialized tools leveraging AI and machine learning, and how the industry can unlock the insights in dormant data sets.
Topics discussed:
- Why technology is the future of the commercial real estate industry, and why its competitive advantage today will become business as usual tomorrow.
- How collecting large data sets across silos and using AI tools to analyze those data sets can bring new insights to the industry.
- Why commercial real estate needs tools like Python to optimize SaaS applications and integration through data manipulation.
- The importance of capital and opportunity in commercial real estate and how technology might disrupt or enhance those opportunities.
- Why a specialized industry needs more specialized tools, and how AI and machine learning models can help.
- How applying data science to construction data can uncover insights on project risks, costs, and opportunities that traditional methods would not reveal.
Serge's Top Quotes:
#1.)
"What I realized is that managing that data was not the typical type of thing that we normally do in real estate, which is work with statistics and spreadsheets and just kind of boil everything down to kind of one number. What I realized is that that was really a data science exercise, and that's what really led me to pursue a path in technology as opposed to traditional real estate." (2:07-2:34)
#2.)
"I strongly believe that while the role of technology in the commercial real estate industry may still be in a nascent state, it certainly is the future of the industry." (2:39)
#3.)
"The early adopters of something, whatever that is, and it may be technology … the competitive advantage that's enjoyed by the early adopters ends up becoming a cost of doing business later on." (7:21)
#4.)
"Regardless of whether or not you've got ten or a hundred SaaS products, they still all collect and contain data that we can then tap into." (34:25)
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