Disruptor Daily: Which Challenges Faces AI Adoption In Real Estate? 6 Experts Share Their Insights

There’s a bevy of trends shaping AI’s use in the real estate sector. Unfortunately, not all of those trends are positive, as there are significant challenges to AI adoption in any industry. These industry insiders pinpointed the greatest hurdles to widespread AI adoption in the real estate sector. Here’s what they said:

  1. Grant Cardone, Real Estate Investor and CEO of Cardone Capital – “The user is the number one challenge to any new technology. The already successful agent, broker, leasing agent or investor will also resist the adoption of new technology.”
  2. Attila Toth, founder and CEO of – “Many-many years of doing things the same way. Traditional infrastructure industries, like real estate, have been shaped to a much lesser extent by high technology than other industries. This is mostly due to the fact that for a long time the primary source of innovation has been project finance, material science, and good old process improvement. To embrace AI, leaders in real estate need a mindset shift as to what the next source of disruptive innovation will be. The new generation of industry leaders must understand the transformative opportunities inherent in data and predictive analytics. All that said, the next generation of leaders doesn’t emerge overnight…especially not in a very traditional industry.”
  3. Jasjeet Thind, Vice President, AI and Analytics at Zillow – “It’s likely the same challenge faced by any firm looking to deploy AI solutions, regardless of industry – a shortage of talent. We simply cannot recruit data science professionals fast enough to keep pace with innovation.I’d encourage anyone interested in tackling a variety interesting problems – personalization, semantic search, conversational AI, home valuation, natural language processing, natural language understanding, computer vision, ranking and relevance, document understanding and classification, multi-arm bandits and UX optimization algorithms, and a host of other areas within analytics, AI and machine learning – to visit”
  4. Daniel Cozza, Chief Product Officer of Building Engines – “Despite the explosion of technology, real estate can be wary of change.Forward-looking firms like Beacon Capital Partners experiment with new technology to differentiate and drive efficiency. They may try AI-based approaches in select properties to assess the benefits before rolling them out across the portfolio.One concern about AI is managing personal information. It’s critical to choose technology that is SOC II and GDPR compliant, with strong privacy policies.

    Finally, some fear a robotic-like experience in customer service, but one of the benefits of an AI chatbot, for example, is that it becomes more human and more personal over time.”

  5. David Lee, Chief Operating Officer at Kastling Group – “To increase market efficiency, there has to be more data, and data is a touchy subject. There is a lot of public data available that could be deemed sensitive in aggregation. The sharing of this data could also be unethical especially without knowledge and/or consent.”
  6. Mark Choey, co-founder of Climb Real Estate and founder of Climb Labs – “Finding that intersection of a practical problem to solve that has lots of data to train a computer on is the number 1 challenge to AI’s adoption in real estate. AI is, simply put, a branch of computer science where computer algorithms can learn from data. However, you need a lot of high-quality data to be able to train an AI to have meaningful results.For example, home valuations are one such example of an application where you have a lot of data out there (e.g., all the home data plus sales in the US over a long period of time) and the problem is useful enough to solve (e.g., accurate home valuations).”


Original article contributed by: Disruptor Daily 

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