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What is the Impact of Artificial Intelligence on the Real Estate Industry

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The real estate industry is one of the many industries being disrupted by artificial intelligence (AI). From chatbots to predictive analytics, AI is changing the way real estate agents do business. Here's a look at how AI is impacting the real estate industry and what agents need to do to stay ahead of the curve.

What is AI?

Artificial intelligence sounds futuristic, no doubt influenced by popular culture. Yet true AI, the kind we have now, isn’t nearly as advanced as to be able to do any of the things you see R2-D2 do in the latest Star Wars movie. Instead, today’s AI is all about using advanced machine learning algorithms to process massive amounts of data as quickly as possible, identifying trends that could otherwise go unnoticed. 

Because AI makes use of massive amounts of data it’s not just good at identifying trends – it’s also adept at predicting future ones based on the information it’s provided. In fact, the larger the data set, the better modern AI performs – with enough information at its disposal, a machine learning algorithm can provide incredible insights.

What is the real estate industry?

The real estate industry is, of course, the business of buying, selling, and investing in property. Real estate agents, brokers, investors, house flippers, construction companies, and property maintenance companies all fall under the real estate umbrella, either directly or tangentially.

How can AI be used in the real estate industry?

Because there are so many different facets of the real estate industry, AI can be leveraged in dozens of different ways. A few examples include how real estate agents can use AI-assisted tools to build client relationships or how investors can use predictive analysis to help make determinations on the profitability of a property. The possibilities might not be limitless, but they’re highly promising.

The Impact of AI on the Real Estate Industry

So what, exactly, are the different ways that AI can impact the real estate industry for the better? Let’s take a closer look below at four of the primary ways.

The Use of Virtual Assistants

The more automation you can build into your processes, the better – but this automation must be reliable. Otherwise, it’s not going to help you if it’s only going to deliver inaccurate or inconsistent results. This means that automating certain processes, especially those in client relationship management, needs to be done in ways that actually helps you build those relationships more efficiently.

The rise of so-called “virtual assistants” is emblematic of what AI can do for real estate professionals. A virtual assistant can automate tasks such as sending emails to your marketing list on a regular basis, for example. Other good ways to use AI-enabled assistance include an automated calculation tool that buyers, sellers, and agents alike can use, with the data the tool relies on being pulled from a large machine learning database.

The Use of Predictive Analytics

Identifying trends and then predicting the impact that those new trends will have on the real estate market is a major selling point for artificial intelligence. Machine learning and analysis can parse massive amounts of data in a fraction of the time that people can, identifying both issues and opportunities before they arise. 

AI-enabled predictive analytics can even be leveraged to create opportunities for greener real estate. HVAC systems, for example, make up 45 percent of energy usage in commercial buildings. 30 percent of that energy is wasted, but machine learning can be used to identify where waste is happening. This allows more targeted approaches to minimizing that waste, which reduces maintenance costs incurred by real estate investors.

The Use of Chatbots

A step up from a simple menu on a website, a chatbot is an interactive tool that allows site users to ask questions in real English and get accurate responses back. Programming a chatbot through traditional methods requires massive investments in time and resources, and the results are less than stellar – it’s obvious to anyone using a traditional chatbot that we’re a far way off from useful interactivity.

Yet artificial intelligence increases the use of chatbots to near-human levels of interaction. Using machine learning, chatbots have access to massive amounts of data on the kinds of questions people tend to ask, allowing it to find better answers that are more helpful and less like talking to a robot. Using a chatbot in this way is hugely advantageous for real estate professionals looking to streamline their sales and marketing funnels effectively.

The Use of Augmented Reality and Virtual Reality

If the coronavirus pandemic has taught us anything, it’s that the ability to continue to live our lives during such times is dependent on strong remote business tools. Virtual reality and augmented reality are part of that, as you can leverage VR/AR tools to conduct business remotely and efficiently – and the processing power of artificial intelligence helps make these capabilities a possibility.

In the world of real estate, being able to show properties virtually during the pandemic was a major boon. While nothing will replace truly walking through a property, having an interactive VR experience from across town – or across the country – where someone can explore the interior of a property without having to set foot inside it kept the real estate industry afloat during those tumultuous times.

Conclusion

New technologies always have the potential to disrupt the status quo. Embracing these new technologies from the outset is often the one factor that dictates long-term success, and this concept applies to the real estate industry just as it does to any other. AI and machine learning is just another step in the right direction for any real estate professional who wishes to see their business thrive.

Ben Shepardson

Ben Shepardson is a Realty Biz News Contributing Writer and has a long track record of success in online marketing and web development. While pursuing a bachelor’s degree in Computer Information Systems, he worked doing enterprise-level SEO and started an online business offering web development services to small business customers.

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