AI In Property Valuation

AI In Property Valuation

Real Estate Valuation is based on multiple criteria like location, area, brand, accessibility and finer details of the property. However, major deciding criteria continue to be budget, location and the brand. When it comes to commercial real estate, the process, in essence, remains the same. This process involves a substantial amount of data collection and evaluation. Given the vast amounts of data involved, application of AI has changed the face of property valuation making the process easier, faster and more accurate. Multiple firms have shown a keen interest in incorporating this technology to their advantage while deciding about the present and future of their investments.  

Benefits of AI in property valuation:

Understanding the various factors such as employment growth, demographics, topography, rental rates, vacancy & occupancy rates is a complex process. Collating, calculating and analysing various variables becomes that much easier with AI, rendering the old tedious methods relatively redundant. Apart from that, the inclusion of AI into the valuation process serves several benefits to the commercial real estate sector.


Many tech startups have developed algorithms that can sieve through a variety of listing services, curate and accurately match investors to their requirements for a suitable property.  For example, Geo Phy incorporates satellite images and using AI, provides a precise valuation of a property. Proportunity is another firm that can accurately forecast expected price fluctuations in a particular locality.


These AI platforms have aided the CRE industry to provide clear, quick and precise information to its investors and customers. The exact data regarding return on investments (ROI) as well as price fluctuations expected in a location are a couple of factors that can help improve cost efficiency and speed up execution of transactions.  


Today, with technology becoming more accessible, updation of property valuation in a single portfolio barely takes a few minutes. This has led to a dynamic and enhanced portfolio management system.


AI tools have been quite successful in bridging the gap between need and requirement -thus making it a very personalised experience. Another instance, where both the customer and investor are treated with the highest priority, promoting satisfaction and trust.

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