The role of artificial intelligence (AI) in real estate has been expanding at a rapid pace, and has managed to transform varied aspects of the industry. Among other things, AI is widely used for property management today. As Kanat Sultanbekov says, by leveraging AI tools property managers are able to improve efficiency, streamline operations, as well as elevate the overall tenant experience.
Kanat Sultanbekov briefly discusses a few major uses of AI in property management
Traditionally, property valuation processes relied on time consuming manual processes that were subjective and prone to human error. This process is today made a lot more efficient with the help of AI and machine learning (ML) models. AI powered algorithms and ML models leverage vast amounts of historical and current data to perform property valuation. AI systems take data points like comparable property sales, market trends and location attributions into account to provide accurate and objective valuations to property managers.
Automating the valuation process saves a good deal of time and effort for property management companies, as there would be no need to manually research comparable sales or spend hours crunching numbers. AI based property valuation also does away with the element of subjectivity from the process While factors like personal opinions, emotions and human biases can influence traditional valuations, AI algorithms analyze data objectively and provide an impartial assessment of a property’s value. These insights can be used for determining rental rates, evaluating potential investment opportunities as well as fixing the selling price of a property.
Tenant experience and satisfaction are vital to competent property management. AI can be used in many ways to improve tenant experience. AI powered chatbots, for instance, can be used to answer tenant queries in real time, and deliver instant responses to their questions and concerns. The use of AI-powered property management software has also become commonplace today. It helps personalize tenant experiences by analyzing tenant data and preferences.
As per Kanat Sultanbekov, ensuring properties are well-maintained and all maintenance issues are addressed promptly is among the vital responsibilities of property managers. Traditional maintenance practices usually depended on reactive approaches, where repairs were made after an issue arises. On the other hand, with the use of AI and predictive maintenance technologies, property managers are able to adopt a proactive and streamlined approach to maintenance operations.
Predictive maintenance typically makes use of AI and ML to analyze data from sensors and Internet of Things (IoT) devices installed in buildings. Such sensors continuously monitor various aspects, like energy consumption, humidity and temperature. By collecting and analyzing this real-time data, predictive maintenance technologies can identify patterns and anomalies, and predict potential equipment failures or maintenance needs before they occur.
Implementing predictive maintenance has many benefits, like lowering tenant complaints and minimizing disruptions, optimizing budget and resource allocation, and improving the efficiency of maintenance tasks. It can also help enhance the lifespan of building systems and equipment.
It is vital to understand that while predictive maintenance is a valuable tool, it doesn’t entirely eliminate the need for manual routine inspections. Regular inspections, coupled with predictive maintenance, help create a comprehensive maintenance strategy.