Real estate is a complex sector involving many different stakeholders, functions, objectives and challenges. Anyone who has tried renting a property will know the experience is not always straight forward, and things only become more challenging when the goal is to build a new building. Fortunately, the sector is rapidly evolving as technology finds new ways to transform the various areas and improve the experience and value for everyone involved.

Real estate is a part of all our lives, so it’s useful to understand some of the way that AI is changing it for the better. Let's have a look at a few examples of AI in real estate.

Guide smart investment in real estate

Investing in real estate is a big decision requiring careful consideration of many different factors. People new to the real estate game and making their first purchase or even second investment are often overwhelmed with the amount of information to be processed and the number of small decisions that must be made.

AI can help strip complexity from this process by analysing the available data on a property and creating a clear picture of the opportunity with regards to features such as energy efficiency, safety of an area, recent property purchases in the area, the sales price and even using trend data and data on local investment and development to predict future valuation.

Predict property sales value

The valuation of a property is based on several factors, such as the size and location of a property, number of rooms and bathrooms, recency of renovation and proximity to amenities. However, a luxury, exceptional or unconventional homes which defy the market norms. This creates a challenge of how to objectively value the property to avoid over or under-valuation.

The ability of AI to detect patterns could be the key to this challenge. By working with historical data of luxury and premium properties with similar characteristics, agents can accurately gauge a fair selling price.

Property recommendation based on customer preferences

Many customers spend hours trawling property websites online and entire weekends visiting properties that don’t fit their needs. Combined with a hyper-competitive market that sees great properties sold days after they go on the market, it can be very difficult to find and buy the right property. This also creates a challenge for real estate agents who may invest time and energy coordinating viewings with prospective buyers for a property that doesn’t fit their needs.

Recommendation engines are a powerful tool that can help overcome this challenge. By analysing prospective buyers desired specifications (e.g., location, cost, size etc.) agents can personalize property recommendations but also highlight the criteria the property matches that demonstrates it’s a good fit. This helps reduce the search burden on customers, helps them find the right property and can help estate agents to increase their sales.

Enable smarter real estate management

Estate agents have a highly demanding job and must deal with multiple enquiring, such as rental and property listings, tenant enquiries, maintenance, sales and much more. In addition, agents are challenged to constantly stay connected and provide insight into rental and sales trends across a large geographic area. AI can assist with automating many of the highly repetitive and manual but nonetheless critical tasks that agents are meant to perform, such as automating appointment setting, managing maintenance requests and even providing market intelligence by identifying trends across a certain geographic area.

Streamline document processing and due diligence

Real estate agents, and sometimes other stakeholders such as banks and lawyers, are required to complet