The real estate sector, like many others, is slowly but surely adapting to the “data-focused” world and making progress in defining use cases for testing artificial intelligence in this field. Indeed, with AI infiltrating every industry, it makes perfect sense to explore what new technology like machine learning can contribute to real estate management. Already, a number of use cases have emerged, showing promise in multiple areas that can improve a company’s position in the market.
When it comes to large properties like corporate office buildings, real estate maintenance costs can take up a sufficient part of the budget. According to the 2018 JIL Occupancy Benchmarking Report, 30-40% of office space remains underutilized. This is typically referred to as ‘silent costs’ as money losses are not visible outright.
IBM has recently unveiled its AI-powered TRIRIGA solution to help real estate management professionals effectively utilize office space. TRIRIGA gathers data from various sources including Wi-Fi and IoT sensors, which is then analyzed by an AI algorithm and turned into valuable insights. This can potentially help enterprises to make better decisions about managing their working spaces.
Another AI-focused company, Gridium, specializes in energy saving and property resource optimization. Machine learning algorithms automatically analyze weather data and detect suspicious spikes in energy use patterns to warn property managers. This enables building operators to react to issues on time and decrease operational costs. LinkedIn has managed to save about US $ 100,000 in operational costs at the company’s headquarters annually using Gridium’s technology.
One of the most prominent features of AI is its ability to ‘predict’ the future. Since AI has the ability to analyze patterns in vast amounts of data, it can be used to make reasonable predictions of the future value of a property. For example, Israeli startup Skyline AI uses predictive analysis to accurately assess property value. Utilizing over 130 different sources of data and analyzing over 10,000 features of each property, Skyline’s prediction accuracy is in the higher percentiles.
Real estate businesses can benefit from using AI in many important ways. At this point, AI is just scratching the surface of the real estate sector, but it’s reasonable to assume that highly effective algorithms can bring immense benefits to buyers and sellers both.
Credits : Akhil Handa,Pankaj Tadas