The fields of artificial intelligence and machine learning have come on in significant strides over the last decade. Technology of this kind has multiple applications across numerous industries – including that of real estate.
This may be surprising to some, as many assume that these innovations generally apply to IT and computing, aerospace and aeronautical engineering and heavy industry for the most part.
In reality, the advances we are witnessing can have a positive impact on almost any sector we can think of. In particular, fields requiring a large amount of data entry, unskilled work or “box-ticking” can be automated and streamlined.
This creates opportunities for “human” employees to be tasked with creative development and detailed thinking, allowing for the significant practical and financial advancement of many companies. Time saved is money saved, after all.
In this article, the specialists at Property Solvers – experts in selling homes fast – will explain the role of AI and machine learning in the property industry, including the opportunities it presents and the challenges it may pose.
Maintenance and Management
One of the toughest logistical issues faced by many real estate and rental companies is the efficient upkeep of properties and the handling of tenancies.
Thanks to AI and machine learning, it is now possible to manage matters of this kind much more easily. Sensors placed at strategic points around properties can analyse energy efficiency, helping property managers to seek out cheaper alternatives.
In a similar way, it is possible for a system to be set up whereby a central office can be automatically notified of errors or maintenance requirements when it comes to appliances or features such as lifts.
AI systems can also be programmed to predict when certain white goods, security hardware or fittings are likely to require inspection or maintenance. This approach will not only keep each property safer but may also save money on more costly repairs further down the line.
Landlord-tenant communications can also be made easier through the application of chatbots or the potential for automated billing as well as repair and maintenance requests. This will improve the time taken to resolve matters as well as landlord-tenant relationships.
One of the major benefits of machine learning in the world of real estate is the ease with which it allows potential customers to find what they are looking for.
For example, systems may now easily analyse which types of properties would best suit prospective buyers based on their previous searches and selections – instead of forcing them to trawl through lists of inappropriate options.
In a similar vein to the matter of landlord-tenant communications mentioned above, correspondence between real estate companies and house hunters can be made far easier too.
Automated chatbots are often used to answer client questions and direct them to the right places on a property website outside of office hours, meaning a reduction in back-and-forth calls and emails and a quicker turnover time.
We’ve already mentioned that AI allows real estate agencies and relevant prospective tenants to find each other more easily. This means that targeting the correct audience when planning a marketing campaign becomes much easier too.
By analysing search data, location factors and other criteria, property companies are now more able than ever to send marketing materials that are relevant to each individual potential client.
This results in direct marketing approaches – such as emails – that match what each house hunter is looking for much more closely than has ever been possible before. Using this approach will mean greater marketing success and a higher number of conversions.
As previously mentioned, AI and machine learning can help property management companies to cut down on energy expenditure and maintenance costs.
By automating methods of communication and marketing approaches, it can also assist in the reduction of man hours and the improvement of a team’s performance by cutting out the more time-consuming, unskilled elements of the workload.
Teams can be smaller and more multifaceted or streamlined as a result, again saving real estate agencies money.
Small Businesses and Independent Landlords
The savings that are made possible by automation may also enable start-ups, SMEs and independent landlords to flourish in the property industry.
Depending on the approach taken, overheads could be reduced, and, thanks to the ease with which AI and machine learning enables the maintenance and management of multiple properties, smaller teams will be able to handle a much larger portfolio than ever before.
Of course, no new development can be completely free of its own unique set of challenges. AI and machine learning are no different, so it’s important to be prepared.
One of the main concerns about AI is the possibility that it will replace certain roles altogether, leading to a downturn in recruitment levels within particular industries.
An opposing argument, however, states that humans within heavily automated industries could take on more detailed or creative roles. With the “grunt work” handled by computers, we could develop our businesses into something we otherwise would never have imagined.
Another challenge may lie in competition. As rival companies invest in more and more sophisticated AI, it’s likely that we will be required to “keep up” in order to compete. This matter may see smaller businesses struggling to afford regular updates and brand new tech quickly enough.
However, the likelihood is that the faster AI and machine learning solutions develop, the easier their components and elements will be to produce and the cheaper they will become. Budgeting for top AI will pay dividends, too. It’s a classic case of spending money to make money.
Of course, we’ll only begin to discover the full potential of AI and machine learning in real estate as this technology continues to develop and be employed.
For now, it’s clear to see that the roles played by automation involve streamlining and expediating processes, taking the stress out of maintenance, easing communications with clients and tenants and enhancing our marketing techniques. Who knows what will be possible in another decade’s time?