32) AI’s role in Real Estate

June 30, 2023 admin No Comments

32) AI’s role in Real Estate

Artificial intelligence is generally understood as the ability of computers and machines to handle tasks that require human intelligence.

Machine learning, which is one of the most common applications of AI, involves training machines with large amounts of data to recognize patterns, analyze data, and run forecasts and algorithms.

Artificial intelligence (AI) is poised to revolutionize the commercial real estate industry by transforming the way acquisitions, development, management, advisory, and marketing teams in the industry operate. AI tools are enabling CRE teams to process vast amounts of financial data, automate repetitive tasks, repackage existing content in more palatable formats, and gain valuable insights that can inform strategic decision-making.

One example of this is AVA, an AI-powered commercial real estate valuation platform that empowers smarter, data-driven investing decisions. AVA is the first instant commercial real estate valuation software that determines the accurate value of a commercial property in seconds. This technology accelerates and streamlines the traditional commercial real estate appraisal process by analyzing comparable sales, current market rents and other information to provide an accurate and informed property valuation.

AI tools like AVA are transforming the way commercial real estate is evaluated, purchased and developed by providing faster and more accurate valuations, enabling property owners to maximize the value of their properties by gaining insights into how specific capital improvements might impact the rent roll and total valuation of their building.
There are many AI tools that are relevant to commercial real estate. Some examples include:
– **Silverwork Solutions**: This company uses artificial intelligence to build “cognitive technologies” for the mortgage industry. Its solutions include software robots that complement the work of human employees, enabling automations that can help to deal with repetitive tasks ².

– **Hyro**: This company builds conversational AI that can be used for the real estate industry. Its AI chat and voice interfaces can be available to customers when live agents are not. They’re capable of helping to match customers with properties, schedule viewings, capture and follow up on leads and answer customer questions based on consistently updated information ².

– **Entera**: This company brings its customers a residential real estate investing platform that uses AI to enable automations and intelligent analytics for finding, buying and operating single-family homes ².

AI can be used to evaluate new markets for commercial real estate development by providing powerful tools for forecasting and decision making. For example, investors, agencies, and economists can use AI to predict where the real estate market is headed, hoping to get an edge on the competition and buy at the right price.

Zillow and Redfin currently use AI for their valuation on single family homes.

AI can also help developers remain agile and adapt to shifting markets by providing real-time insight into spend forecasting and budget impacts, early warnings on critical potential incoming project risks across hundreds of data points, and a digital-assist on automatically compiling comprehensive lender and financial partner reporting. This allows developers to leverage their historical project data (coupled with local market benchmarks) to inform project planning, giving them a leg up in change order negotiations and improving vendor procurement with data and automated recommendations that can bend the cost curve on complex projects.

 

Is Skynet becoming self aware?

Not likely. However, research published in McKinsey Quarterly demonstrates that AI and automation are more likely to eliminate specific activities, not entire occupations. Even for positions that are highly automatable, there is more to consider than just how easy it is to program a machine to perform a specific task.
However, the predictive analysis in AI will get better an better as more and more data is available to help with real estate acquisitions and development.

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