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5 ways artificial intelligence is transforming real estate valuation

Author: imi.bg | Uploaded before 3 months

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Real estate valuation is a field that has long relied on experience, subjective judgment, and limited comparative data. However, with the advent of artificial intelligence, this practice is undergoing a profound transformation. Where previously we worked with a few examples and intuition, today we have thousands of data sources, complex computational models, and automated systems that can analyze the value of a property with accuracy down to the last brick. Artificial intelligence is no longer just a buzzword, but a real tool in the world of real estate. Thanks to it, the value of homes, offices and plots of land is now calculated not only by square meters and number of floors, but also by dozens of other factors – from the level of crime in the area, through the availability of public services, to air quality and user comments on social networks. Machine learning allows systems to “learn” from thousands of examples and build increasingly sophisticated models that not only reflect the market, but also predict it. In this context, the assessment is no longer just a snapshot, but a forecast for the future. Systems that use artificial intelligence analyze the market in real time, monitor news, register infrastructure changes and even read the emotional tone of comments and reviews to assess how consumers perceive a given neighborhood. If previously a given property was evaluated against five similar objects, now it is placed in the context of tens of thousands and viewed through the prism of dynamic dependencies. This makes the assessment far more flexible, accurate and devoid of purely human subjectivity. One of the biggest changes is speed. Processes that used to take days and involved visits, meetings, signed protocols and documents can now be automated. The algorithm does everything in seconds: compares, analyzes, evaluates, calculates risk. This is especially important in mass assessments – for example, in the case of a portfolio of a hundred or a thousand properties, or when a quick response is needed for an investment deal. Moreover, the assessment is no longer limited to classic sources. Artificial intelligence draws data from satellite images, drone footage, Google Street View, online listings, public registers, local news, social media. Even details such as the shading of the facade, the type of paving in front of the entrance or the type of window frames can be “seen” by the system and taken into account in the final result. This adds a depth that is almost impossible to achieve with the human eye. Removing the subjective factor is also a serious step forward. Different appraisers often give different prices, sometimes with deviations of over 20%. There are many reasons – different methodology, limited base, personal judgment, even emotions. AI works without bias. It evaluates objectively, based on thousands of parameters, and can offer not one, but several versions of the assessment – for example, in current condition, after renovation, when renting or in a market downturn. This allows for much more informed decisions, both on the part of buyers and on the part of banks, investors and insurers. Machine learning models have another great advantage – they detect dependencies that are difficult to detect with the naked eye. They can predict whether a given neighborhood will develop, whether it is undervalued, or on the contrary – oversaturated. They combine property data with economic indicators, population mobility, even statistics on migration and demographic changes. This way, the assessment acquires not only accuracy, but also strategic value. There are platforms that already offer similar services in real time. The user enters an address and within seconds receives an assessment, growth forecast, investment or rental recommendations. For professionals, this means higher productivity, for end users – more transparency, and for the market as a whole – a new standard of work. The implementation of AI in valuation also changes the attitude towards the process itself. It is no longer a closed service performed by a narrow circle of experts, but accessible and understandable to everyone. This increases trust in valuations, reduces the risk of fraud, optimizes tax procedures and shortens transaction times. In times of unstable markets and dynamic economic conditions, such tools provide the necessary predictability. There are still areas where human expertise remains key – such as properties with legal complications, cultural value or specific restrictions. But even there, AI can assist the process by preparing data, pointing out analogies or detecting risk elements. Instead of competition, we are talking about synergy. This transformation is not a matter of the future – it is already happening. Large banks, international consulting companies and even government institutions are implementing AI-based models in their valuation practices. The advantages are undeniable – lower costs, faster service, more accurate results. For a market like the Bulgarian one, where transparency is still a challenge, such technologies can lead to a real revolution. Most importantly, however, AI is changing not only the way valuation is done, but also the philosophy behind it. From a subjective value based on a limited perspective, it is becoming a dynamic, adaptive, multi-factor model that reflects not only today’s reality, but also the path forward. For everyone involved in the real estate market – this is the new foundation on which decisions are made. And it is stronger when it is backed by algorithms.

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