Four Ways AI Technology Is Helping to Level Up the Real Estate Market

It’s official. Artificial Intelligence (AI) technology is now more widespread than ever before. Across the world, different industries have been taking increasing advantage of AI systems to level up their performance, and the real estate industry has been fast to adapt.

Already we’ve been seeing a growing number of real estate business owners confirming that using AI technology and several branches thereof has helped lower operational costs, while also increasing their revenue.

As a matter of fact, close to half – 49% – of real estate business owners said that AI has brought down operating costs for their firms. More interestingly, 63% have already witnessed growth in their revenue since implementing AI solutions according to McKinsey research.

Even in a challenging market, with widespread economic uncertainty as interest rates keep climbing, both real estate professionals and would-be home buyers are finding long-term beneficial solutions in the use cases of AI technology.

At the consumer end, the real estate industry is largely driven and fueled by the use of AI algorithms, as existing tech infrastructure is helping buyers find the right home and the perfect mortgage.

Already this has proven to be a game-changer, helping companies save time and money, while potential buyers can find the right home based on their specific buying requirements.

However, looking forward, there’s growing potential for AI in the real estate industry, and by contrast to what companies such as Zillow, Compass, and LoanSnap, among others, have already achieved with AI, it looks like we’ve only scratched the surface of how AI can completely revolutionize the property market in the coming decades.

Where AI Technology Is Already Being Used in Real Estate

Rather than completely replace human ingenuity, AI technology has helped to develop a new dynamic marketplace that presents growing opportunities for the entirety of the real estate industry.

For several years, closer to two decades already, Artificial Intelligence, including Machine Learning (ML) and Natural Language Processing (NLP) has enabled real estate firms to better understand buyers’ needs and overall market trends.

Back in 2006, real estate giant Zillow launched an advanced machine learning system that uses AI and neural networks to thoroughly analyze property data including sales transactions, different buyer tax assessments, and important public records.

The program launched by Zillow, which is known as “Zestimate” is a unique valuation model that compiles this information in a matter of minutes, to deliver accurate and on-demand property valuations and useful buyer estimates.

Today, the program tracks the value of over 100 million homes, and instead of having real estate agents constantly update and maintain this information, as valuations change or houses come on or get removed from the market, AI algorithms can now help streamline the entire process more adequately.

Other well-known firms such as Opendoor, RedfinNow, and Offerpad operate similar business models, using AI to collect and store buyer information, retrieve marketwide data, and help potential buyers find an appropriate match.

The rise of instant buyers, or iBuyers, ensures that those active on the property market, can either sell or buy their house, without ever having to interact with a realtor at all. Advanced systems can now help them determine potential offers, and match attractive offers on off-market houses with existing homeowners.

With these systems at their disposal, property companies have had greater opportunities to connect buyers with the right property, and the need for realtors to work through copious amounts of information has now become more streamlined. This gives real estate professionals a better opportunity to improve their overall efficiency.

Instead of lingering on the achievements AI has brought to the real estate industry, we can now look towards new growth opportunities this technology can bring to the frontline.

Development of Smart Contracts

While there are arguments that believe that blockchain technology is perhaps not the technology of the future, the proliferation of smart contracts could empower a completely new generation of efficient automated, and secure transactions in the property business.

With the use of smart contracts, real estate companies can eliminate potential human error, increase their productivity, and create a more secure working ecosystem.

Introducing smart contracts could mean that realtors could set up contracts based on existing standards and buyer data. This would help minimize potential fraudulent activity and establish a chain network through which buyers can view, purchase property and finalize transactions online.

There are however challenges that make the initiation of smart contracts still a seemingly far-off concept in the real estate market. For starters, adequate access to buyer information and data is required beforehand, which can however raise concerns over privacy matters.

Secondly, smart contracts require adequate software infrastructure to set up, which would mean that real estate companies will need to invest in the right tech systems, and further educate employees on how these transactions would work.

Finally, the risk of cyber breaches has become another headwind, as the rise of cyber threats and bad actors can increase transaction volatility.

Smart Property Management Solutions

Managing and maintaining multiple rental properties requires a large team of professionals that understands the challenging aspects of real estate management, and how to handle an array of different tasks at the same time.

Up until now, a majority of real estate management firms have used outdated structures that oversee the management, maintenance, and communication of rental properties. Not only does this require a large team of managers, but it also requires countless working hours to effectively deliver services to tenants.

Instead of relying on traditional solutions, property management companies are now rather looking at how Artificial Intelligence can manage different tasks, without these ever overlapping, while at the same time delivering the same amount of output, if not more, as compared to a larger team.

With the right systems in place, companies can now thoroughly streamline their management operations, by keeping up-to-date records on the tenants, financial accounting, and maintenance requests.

This not only improves day-to-day activities, but also helps to streamline the process of resolving tenant requests for maintenance, managing building security features and upgrades, and keeping better track of renter records such as lease agreements and any additional documentation.

Instead of compartmentalizing each rental property, companies can now use cloud-based technology infrastructure to help better analyze and improve their in-house operations. Property managers have on-demand access to tenant records, and building information and can provide more up-to-date information once it’s been requested.

Data-Based Forecasting Models

Anticipating market fluctuations and predicting future outcomes requires a rather forward-looking approach. What’s more, delivering up-to-date accurate predictions tends to be extremely difficult considering ongoing economic headwinds and market-related trends.

In recent years, however, there have been changes throughout the property market, where companies can now predict future outcomes based on historical data. Using AI to understand how market trends fluctuate over time enables businesses in the industry to establish forecasting models that consider a range of factors.

Using predictive models means that software systems can analyze data sets more accurately, understand how future trends will change based on consumer buying trends, and simultaneously analyze several different market segments.

There’s also a better opportunity to identify possible risk factors, based on economic data. Using algorithms to pinpoint areas of volatility and opportunity, ensures that property firms have a better understanding of how they can position themselves within their market.

Not only will the outcomes of these models be valuable to real estate professionals, but it also allows buyers and investors to sufficiently analyze how they can maximize their return on investment (ROI), reduce their risk exposure, and more effectively analyze how prices could fluctuate in different economic scenarios.

These forecasting models are key components that can help predict what the future of real estate will look like, and also create a better opportunity for property firms to align themselves with changing market trends and economic behavior.

Improved Content and Digital Marketing Strategies

Not only can Artificial Intelligence help predict future market trends and create forecasting models for buyers and investors, but there’s a growing opportunity for it to help shape the way property companies market to audiences, especially active would-be buyers.

Already we see how other industries have leveraged AI to develop and deploy marketing strategies that can provide consumers with customized content, and deliver more relevant messaging to buyers.

Traditional models required realtors to obtain contact information of prospective buyers, using cold-calling methods or emailing tactics to reach out to those active within the real estate sphere.

While these methods have worked until recently, advanced technology could enable companies to take a better and more forward-thinking approach to how they can effectively engage with their prospective audiences.

Putting the right message in front of the right people requires an endless amount of data that stretches beyond traditional market spheres. Implementing more sophisticated technology means that property companies can now better understand what buyers are looking for before they have even come in direct contact with them.

Companies can now integrate chatbot software into their marketing efforts, which will help paint a better picture of what clients are looking for.

Other features such as online search engine analytics could give real estate marketing teams a better understanding of where they can meet their clients online through digital navigational tools.

Teams can now formulate content based on clients’ needs, rather than using unreliable methods that don’t necessarily meet users’ demands, or effectively communicate the right message.

The Future of AI and Real Estate

While artificial technology is continuously developing, real estate professionals will need to become more adaptable to these sorts of systems to ensure they can appropriately deliver effective forecasting models and online communication.

Already, it’s possible to see how AI can help transform the future of real estate within a precarious marketplace. Driven by precarious conditions, using AI not only helps to bridge the gap between primitive models and future trends, but it enabled real estate professionals to better understand the future of different market segments, adjust their strategies, and deliver more valuable insight to clients.