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Machine learning offers enormous opportunities to all areas of the real estate market, writes Vian Chinner, CEO of Xineoh.

Much discussed as a revolutionary technology of the future, Artificial Intelligence (AI) is already having an impact in the present, reshaping the way work is carried out across a range of industries, from manufacturing to customer service.

One of the niche arenas where its impact has not yet been significant is the real estate market, but this is also set to change.

In the past, a buyer using a realtor would have outlined some basic factors – price, room requirements and area – to the agent, who would then interpose their own interpretation of those parameters and show the resulting properties. This very process has been carried online, in perhaps a slightly more inconvenient experience to the user. When using a realtor, the user gets at least some curation of the results. When using a property portal, however, a user has to click through every property fitting the search parameters.

The situation is further complicated by the fact that a property search will usually last a couple of months, during which time the searcher, using a portal, will have to click through the same list of perhaps hundreds of properties and perform the same curation over and over again.

The advantage of viewing properties online is that potential buyers enjoy the freedom of looking at multiple listings undisturbed. AI recommender systems have already proven their worth in enabling users of sites with a large amounts of content – like Amazon and Netflix – to make quick, high quality decisions. The time has now arrived to give home buyers the same seamless experience.

AI has proven in other industries that it can accurately identify the core of what a user is interested in, including being able to predict a user’s personality, to a higher accuracy than their own mothers. AI is able to pick up latent variables in a home listing that may be hard for humans to express. People sometimes describe it as a home ‘talking to them’ or not.

This will also automatically improve the user experience in the realm of having to repeat the search over and over again, across a longer period of time. An algorithm would be able to take into account how recent a listing is and alert the user if something new that is likely of interest, comes onto the market.

While such an example, where the users are effectively property hunting without using an agent, seems to suggest that AI will actually negatively impact on estate agents, the opposite is, in fact, true. From a real estate agent’s point of view, AI can actually be an asset, rather than a threat, as it can add tangible knowledge to their collective insights and improve the real estate agent’s core capabilities to serve their clients. In other words, cognitive computing should enable agents to be better professionals and make better recommendations to their clients.

Remember that the selling of property is still very much a game where the ‘human touch’ is required. Most people like the idea of dealing with another human being, rather than a faceless AI. So, while machine learning may impact this space in the near future in terms of its ability to automate repetitive functions and assist buyers in finding the properties they are most likely to be interested in, it will merely be an assistant to real estate agents, rather than a replacement.

The other side of the property market game is that of commercial property management, and this is an area that is sadly under-serviced by technology at present. Moreover, it is quite possibly the area of the industry that could most benefit from AI.

It is worth noting that in the commercial property market, the median vacancy time is far longer than for residential properties. By capturing a broader dataset of information about the individual or organisation seeking commercial real estate, better recommendations for property can be made.

At the same time, machine learning could be used to develop a corporate occupier profile that might include information about their industry sector, competitors, revenue trends, or profitability, enabling the algorithm to more effectively predict the odds of a tenant seeing out the term of their contract within a commercial property. Such knowledge could assist in significantly reducing the vacancy rate, meaning the growth yield would increase, positively impacting on this sector of the market.

It is clear then that AI is likely to have a profound impact upon the property sector in the near future, in building management, commercial property rental and in the residential real estate market.

However, estate agents need not fear that machines will replace them in this space. There are some things a living, breathing real estate professional can do that a machine simply cannot. And for all the other areas, AI will only serve as a tool to improve agent productivity, make their lives easier and ensure their workflow is more efficient. Ultimately, AI will give estate agents the gift of time, which will enable them to spend even more energy doing what they do best – closing deals.