Leveraging data and creating value from it is the new goldmine in the real estate sector. There is much more data available today than there was even just a few years ago. Information such as net effective rents, leasing spreads, lease comps, market demand, and tenant information has now become much more accessible. In addition, alternative datasets from IoT sensors, social media, geospatial information, and satellite imagery are increasingly being used for smart building design and maintenance.
Where large amounts of data are involved, implementing AI can streamline and transform operations. AI has the potential to impact the sector at every level, from development to sales and management of properties. Most seen use cases are:
The use of AI in corporate real estate makes sure that the expensive decisions are data-driven and unbiased. It also augments the current market with different tools which would speed up the process and improve the customer experience.
Challenges Faced by The Real Estate Sector to Leverage AI and Advanced Data Analytics
According to the Morgan Stanley Digitization Index, real estate is the second least digitized industry in the world.
Brillio has partnered with multiple businesses in the real estate industry and helped them reap the benefits of enterprise transformation as per trending industry opportunities.
Our Solution Guiding Principles
By leveraging our solution principles, coupled with our product-centric delivery approach, and pre-built proven frameworks and accelerators, we have been able to build new-age solutions for the industry around some of the most pressing pain points.
AI and Data Analytics for Advanced Property Analysis
AI allows property owners/investors to perform analysis on how they need to invest in their buildings, what they can invest in, and, ultimately, what are their returns.
Marketplace data, CRM, as well as public information such as transportation network characteristics, crime rates, schools, and buying trends, are gathered to get insights on the optimal price for purchase/sale, the ideal time to sell/buy, risk management, and portfolio optimization.
In this case, AI unlocks the possibility to gather and analyze data more efficiently, and find the most unusual property price-influencing factors, hidden non-linear relationships between data and property desirability, and the major sources of risk like asset level, macroeconomics, the regulatory framework, etc.
Data points analyzed for advanced property valuation:
Smarter Real Estate Management
Automation of building operations management process provides an opportunity to lower the operations/maintenance cost.
Data is gathered from various sources including Wi-Fi and IoT sensors, and then analyzed by an AI algorithm and turned into valuable insights. These insights offer machine learning-based controls for HVAC, lighting control, energy management, building maintenance, occupant tracking, acoustic settings to reduce operating costs, enhance the occupant’s experience, and improve workplace productivity.
Automated workflow for operations management:
Spatial analysis using all relevant data provides actionable insights on space optimization for better building planning/remodeling.
Spatial analysis of employee data, teamwise details, footfall vs timings, common area usage, etc. are used to gain insights and optimize the space usage, maximize the existing space value, and minimize the need for extra space.
Major data points for spatial analysis:
AI might seem like a threat to many agents and brokers in the real estate sector but if used in the right way, it can augment their skills and take the whole customer experience to a new level. AI still has many use cases to be explored and the technology is certainly going to grow extensively in the real estate sector.
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