January 28, 2022

Artificial Intelligence – Transforming and Redefining the Real Estate Sector

Artificial intelligence (AI) has made its way into a wide variety of markets, for example – healthcare, finance, law, banking, etc. The real estate sector is still seen to have a reluctant attitude towards adopting AI. According to the Morgan Stanley Digitization Index, real estate is the second least digitized industry in the world. However, in recent years, many of the industry participants started to recognize the immense potential of AI and machine learning which have a transformational impact on the home buying and refinancing journey. 

With the rapid pace of digitalization in the world, the number of data sources has seen exponential growth through better data organization. When assessing AI through the lens of business capabilities, it usually supports – automation process, gaining insight through data analysis and engaging with customers. AI can be used to extract every piece of information from user generated content to property price fluctuations which can be tracked, analyzed and turned into a valuable insight. Over 30% of companies utilize AI in some form already. PwC estimates that AI will contribute a whopping $15.7 trillion to the global economy by the end of 2030.

The real estate industry has assimilated technology in a way that has made it more resilient, invincible and given it a new and vibrant dynamism. Technology infusion has made the transactions between the parties efficiently smoother and improved the quality aspects. It has changed real estate in unique ways.

Valuations 

AI’s most prominent feature is the ability to ‘predict’ the future property values. AI is used to anticipate rent and sale price fluctuations or identify the perfect time to sell a property to have an unprecedented competitive advantage. Pricing in real estate makes or breaks the deal. AI collects and processes data points like historical property trends, macro and micro market fluctuations, taxes, crime rate, transportation options, etc. that can be analyzed to make a reasonable prediction of future property valuation. 

For example, Israeli startup Skyline AI uses predictive analysis to accurately assess property value which is done by pooling large data in the industry. Zillow uses AI to partially estimate property value by analyzing photos as machine learning can assess even the most sophisticated interior details that actually sell it to the customers. 

Lead Generation

AI delivers deep learning which is capable of shifting massive data sets to pre-qualify leads and filter out authentic buyers from window shoppers. The technology provides tailor-made residential and commercial offerings to qualified buyers. Moreover, the algorithm can identify what type of property the customer is keen on buying, allowing the agents to deliver the customers’ niche in a cost-effective and transient way. Platforms like Zillow and Redfin have employed this technology coupling such optimizations with chat-boxes and 3D walking tours to enhance the home search experience. This helps the users to streamline properties with AI-powered personalization which identifies user’s preferences and suggests listings accordingly. 

Financial Modeling and Lending

Construction has been known to suffer from budget overrun. For example, the famous Sydney Opera House was built with 1357% or $70 million in over-budget. McKinsey estimated that large construction projects usually exceed 80% of the planned budget. This budget overrun problem has been tackled by AI. Dolex, a California- based startup, solves this problem using robotics, LIDAR imaging, and AI. Autonomous robots capture 3D images of construction sites and then the AI algorithm analyzes data and turns it into insights, which are used by project managers to tackle the ongoing issue. 

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A massive part of the real estate industry is the mortgage lending, which is a data-intensive process. Machine learning offered by AI is accelerating the document review process through optical character recognition (OCR). OCR helps the lenders to automatically read data from borrowers’ documents. Closings can occur faster and with less downside risk to lenders. One major limitation of this technology is that it can accurately pull information only from template-based documents. Manual and repetitive processes, such as financial modeling, can be automated using extraction and classification technology. This allows for more value-added and customer service-oriented activities. 

Savvy Property Management

According to the 2018 JIL Occupancy Benchmarking Report, 30-40% of the office space remains underutilized. This is referred to as ‘silent costs’ as money losses are not visible outright. Extra charges are paid for energy consumption or unused square feet which lead to poorly managed commercial space. This often results in employee dissatisfaction. 

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AI allows companies to address this underutilization by aggregating and analyzing data collected through sources such as Wifi and loT sensors, and offering solutions ranging from rearranging work configuration to energy-saving optimization. Employees can optimize spaces with the help of natural language processing and the AI can identify users’ needs. This can be used to rearrange entire office layouts or adjust every single employee’s workspace, giving employee satisfaction. For instance, IBM has unveiled its AI-powered TRIRIGA solutions to help property management professionals effectively utilize office spaces by using this technology.

Streamlining Documentation

AI is being used for transaction documentation and lease information extraction technologies to identify key terms and clauses. Using a document management system means all documents are tracked, managed and stored digitally.  This creates a digitalized, machine-readable document, clear of errors commonly arising from human data inputting.

The most cumbersome process is the transfer of property ownership because of the risk involved while transferring huge amounts before property delivery or vice versa. AI is expected to transform the transactions by employing smart contract technology to allow fluent negotiations of terms between the parties and implement the self-executing nature of smart contracts. With smart contracts, computer code is set to automatically send money to the seller when the respective land register is detected in the database. The procedure becomes completely automated and the contract executes only when both parties have fulfilled the terms of the agreement. This process eliminates the involvement of third parties and neither party can influence the transactions.

Changing roles of real estate lawyers

Lawyers need to inculcate value-added skills in this revolution of the real estate industry. 

  • Data handling and analysis: In order to customize the experience and to provide the required amenities to the occupiers, property managers rely on data collected. The laws are constantly changing and real estate lawyers play an important role in providing client assistance to balance commercial objectives against data privacy concerns. 
  • Flexible agreements: As occupiers of commercial properties seek flexibility in their space, agreements will change from leases of fixed durations to flexible membership agreements. Real estate lawyers will play a key role in drafting service agreements suited to fulfill the landlord’s commercial objectives. 
  • Tokenization: The biggest change real estate lawyers will face is the effect of tokenization of the real estate industry. Through tokenization, an illiquid asset such as real estate will become liquid, through virtual tokens representing ownership of a property interest. The interest in a property can be of a flexible nature, being anything from ownership of an underlying asset to an income sharing arising from real estate rental. Lawyers will provide comprehensive guidance to help the clients understand and plan for the complex web of factors, which impact real estate tokenization being a highly sophisticated and cutting-edge process.

Conclusion

AI is just one piece of macro transformation in the real estate sector. The potential applications of AI go beyond commercial real estate (CRE). From AI recommendations to VR tours, property buying is not the same anymore. There has been an upsurge in real estate transactions turning to the web and mobile channels, therefore, real estate companies need to be prepared to embrace the technology in order to thrive. 

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