Buying or leasing a new home might seems like a gamble sometimes, but technology is quickly helping to improve the chances of consumers finding their ideal home. Artificial intelligence (AI) is starting to play a role in the real estate industry, offering tools that investors can use to help buyers and sellers maximize their earning potential, especially through machine-learning algorithms

The technology is also helping to match deals with prospective buyers, while also offering a slew of analytical tools to monitor risk assessment and to predict the chances of a loan defaulting based on a consumer’s financial portfolio.

For example, companies such as California-based Opendoor have been making an impact in the industry, raising a whopping $320 million to buy single-family homes with the use of machine-learning algorithms to identify investment opportunities and determine the right price.

The company then puts those properties up for sale on the Internet. Startups such as Leverton and Counselytics are also making a change, selling software that examines lease contracts, compiles data, and makes smart decisions.

Intelligent automation company WorkFusion is selling sophisticated software for companies seeking to optimize their real estate needs with intelligent analytics and by streamlining repetitive work processes.

Let’s now look at different ways artificial intelligence is helping to improve real estate, especially rental properties.

• Top 5 Ways to Boost Home Rentals With Artificial Intelligence
• How AI Can Help Real Estate?
• Will AI Take Over Real Estate?
• How Can We Improve Artificial Intelligence?
• Is Artificial Intelligence in Demand?
• What is AI in Real Estate?
• What Are Some AI Tools for Real Estate Investors?
• Will Real Estate be Automated?
• How Can AI Reduce Costs?
• How is Data Science Used in Real Estate?
• How is Big Data Used in Real Estate?
• Will Technology Take Over Real Estate?

Top 5 Ways to Boost Home Rentals With Artificial Intelligence

The opportunities brought by AI-powered software in the real estate sector are worth pursuing.

1. Improving Lead Generation and Marketing

AI-enabled consumer apps, machine-learning interfaces, and chatbots are already benefiting a lot of eCommerce businesses by collecting customer data and helping with improving lead generation and content marketing.

Read Also: How Artificial Intelligence is changing Marketing

Melanie Sovann, a content marketing specialist at Studicus states that “a chatbot can become an amazing virtual assistant for your clients and a great way to deliver personalized content directly to leads.”

Let’s suppose that you decided to run a social media ad targeting Millennials for a new house listing in an attractive area. You could do it the traditional way and get, say, a Facebook ad to drive traffic to the listing’s page so you could get their views and possibly email addresses.

Or, you could run a Facebook ad, but when a lead clicks on it, they would end up in a Facebook Messenger chat window with a chatbot ready to answer their questions. At that point, you automatically become subscribed to that chatbot’s newsletter, meaning that it will send you content on a regular basis.

An AI-enabled chatbot is able to answer typical questions without any page opt-ins, sales customer support messages, and desperate attempts to get a lead’s contact data.

For example, here are just some of the question ideas that a chatbot can ask a lead:

• What’s your price range?
• What kind of property would you like to buy/rent/sell?
• What’s your location?

On top of that, a real estate chatbot can qualify leads by asking them specific questions and allowing to fill out forms. This customer data could later be used to learn more about the target audience as well as how to follow up.

2. Predict Property Market Value

Since AI has the ability to analyze patterns in vast amounts of data, it can be used to make reasonable predictions of the future value of a property. For example, an AI algorithm can combine current market data from marketplace and CRM as well as consider public information such as transportation network characteristics, crime rates, schools, and buying trends.

The number of property attributes or market data points can exceed tens of thousands, which is definitely a kind of analysis no human analyst or market research is capable of conducting. In fact, this is exactly what Skyline AI’s Or Hiltch was talking about previously in this report.

3. Advanced Property Analysis

AI-powered software can be a solution for improving the ability of a real estate business to provide accurate, comprehensive information about property to clients. Localize is an example of such software, designed to generate the following information:

• The number of sunlight hours that a property gets in a year/month
• The rating and reviews of local schools
• The statistics about the local transportation system
• Updates on the area’s dining scene, entertainment, recreation with notifications about new and upcoming openings
• Parking space availability and prices
• Sound disturbance.

This information would give a real estate agent an excellent opportunity to provide as much useful information to clients as possible, thus getting them more positive reviews and deals.

4. Property Recommendation Based on Customer Preferences

In eCommerce, real-time product recommendation engines are becoming a reality. For example, Amazon recently launched Amazon Personalize, an AI-enabled service that suggests products, customizes funnels, and provides tailored search results based on real-time analysis.

If real estate businesses utilize a self-learning AI algorithm on a listing website, an app or a CRM system, they can teach it to generate recommendations based on customer preferences such as past purchases, views of specific properties, and search filters. As a result, your business will be able to personalize the customer experience and interactions with your digital products.

5. Property Management

Real estate businesses can track rental and property listings, requests for maintenance, tenant applications, and other information with AI software. These results of the tracking can help to identify the most common maintenance issues, tenant characteristics and preferences, price trends in certain areas, and seasonal availability.

How AI Can Help Real Estate?

Here are four ways AI is changing the real estate world:

1. Property Management

AI has a role in property management thanks to its ability to monitor and predict when a home’s maintenance systems need to be replaced. The technology can also keep tabs on rental trends in certain areas and raise tenant rates based on this data once a lease expires.

Other factors can also be examined, such as building automation and expansion analysis to determine potential returns based on metrics that impact rents, expenses and profits in the rental sphere. One such company is Zenplace, which uses AI to streamline processes for tenants, landlords and property managers.

2. Data Analytics

Big data also has an essential role in the real estate industry thanks to the wide arrays of information available about customers and the industries that real estate companies have at their disposal now. Software developers are helping these companies use AI algorithms to analyze data and improve multiple facets of their business, such as targeted marketing, financial and accounting and appraisals.

AI helps to break down a growing index of information regarding variables that could affect the price of a property. The technology can also set income and growth goals through an intelligent robot, which can make adjustments as data changes to help investors reach their financial targets.

3. Predicting Risk Assessment and Loan Defaults

With AI, real estate investors can eliminate much of the risk and guesswork involved in property investments. Smart robots can assess a property and perform a detailed risk analysis report on it, while also predicting how much money an investment could return.

These bots can also predict loan defaults with the purpose of increasing the efficiency of the risk assessment process, pushing borrowers to avoid less profitable ventures and stick to properties that will offer the highest return.

4. Intelligent Search Platforms

About 51% of home buyers began their house-hunting process online, which is why AI is creating intelligent search platforms that could benefit everyone involved. Most of the major search engines are using AI to help users get more data from a basic property search. In the past, brokers, investors, property buyers, and sellers had a limited amount of information at their disposal such as the price and location of a property.

With AI, prospective homeowners and investors can look at ROI, good neighborhoods, and other details. The recent Broker Vs Bot challenge found that a bot was capable of finding better deals for investors and homeowners when compared against three top-tier real estate agents.

Will AI Take Over Real Estate?

Technology implementation in real estate is; however, clearly on an upward trend.

For example, 8 out of 10 commercial real estate businesses now employ a chief data officer to oversee the organization of their data strategy and governance—a large increase from four years ago, when 44% of companies lacked such a role.

Of course, the question that we have to answer is whether AI will replace real estate agents or not.

So far, trends within the industry would indicate that this is not the case. Technology like chatbots, which are regularly thought of as “replacements” for human workers, have been adopted by only a minority of agencies so far.

For those who are concerned about the effects on human workers that AI will have, it’s important to note that AI won’t be taking away people’s jobs as much as it will allow them to work on other tasks that are better suited to human intervention.

Most of the tech adoption as far as real estate goes is aimed towards improving operational processes because they can’t help in areas where humans excel. Selling a house is a very personal experience for a buyer, and the likelihood of AI replacing estate agents altogether is low.

How Can We Improve Artificial Intelligence?

1. A.I Responsibility

This rule may appear blasphemous for many free-market proponents, raised as they are in countries where tobacco groups do not cause cancer, distilleries do not cause alcoholism, guns do not cause school shootings and drug companies do not cause overdoses.

Silicon Valley has understood this, and its go-to excuse when its products cause harm (unemployment, bias, deaths…) is to say that its technologies are value-neutral, and that they are powerless to influence the nature of their implementation. That’s just an easy way out.

Algorithms behaving unexpectedly are now a fact of life, and just as car makers must now be aware of emissions and European companies must protect their customers’ data, tech companies must closely track an algorithm’s behavior as it changes over time and contexts, and when needed, mitigate malicious behavior, lest they face a hefty fine.

2. A.I Honesty

Put simply, a digital intelligence should state that it is a robot. The scope for mischief once robots can pose as humans is simply too large, ranging from scam calls to automated hoaxes, to wait and see what happens.

Drawing once again an example from the organic world, manufacturers put Ethyl Mercaptan in normally odorless natural gas to notice a catastrophe before it’s too late. A.I should be held to the same standard. When the machines cross the “general intelligence” threshold, they may choose how they want to sound and act, but this is yet a long way away.

3. A.I Transparency

Any human can explain, with varying degrees of accuracy, why he or she performed certain actions. A.I should be expected to do the same, if not more given the superiority of their processing power.

There ought to be no place in this world for black boxes making intrinsically vital decisions: the technology was created to avoid just this. Without this rule, the first two cannot stand as no honesty or responsibility can be expected from a system that is not understood, and which may not understand itself.

In the face of limited technology and a plethora of potential uses, the benefits of A.I clearly outweigh the risks. This is however no reason not to have a conversation about its implementation before the robots start doing the talking for us.

Because of the technological limits mentioned above, machines simply can’t understand the world, as well as humans, do. This however does not mean that ethical issues shouldn’t be addressed when we assume they can, and let them make decisions accordingly.

Is Artificial Intelligence in Demand?

AI is going to power medicine, robotics, engineering, space, military activities, and marketing in a large way. And need I tell you about the organizations that are on the lookout for the smartest professionals with AI skills?

Well, Amazon, Facebook, Uber, Intel, Samsung, IBM, Accenture, Google, Adobe, Microsoft and others are only the leading ones. There are a host of others around you because they are naturally tuned in to the fact that as many as 31% of organizations around the world are likely to use AI in the current year.

So where do we get started? Well, AI and analytics make a great team. Analytics, with the help of relevant data, is designed to analyze the ever-increasing amount of data that organizations have access to. More and more organizations are realizing the importance of analytics in their organizations to achieve competitive advantage and effectiveness.

To do this better and to achieve the business objectives in a highly effective manner organizations are executing AI along with analytics in their routine jobs. This combination of power helps process data quicker and easier to extract insights on a real-time basis. So a clear understanding of analytics is what paves way for AI adoption. Because it is only an organization’s strong analytic capabilities that will help it to leverage AI more effectively.

What is AI in Real Estate?

It’s important to take a look at the ways in which artificial intelligence and machine learning are impacting the real estate industry. In truth, nearly every aspect of the real estate sector has been touched by AI solutions over the past few years. To give you a clear picture of the ways in which AI is impacting your typical real estate transaction, here are a few examples.

It’s helping agents with lead generation

Most agents know they’re bound to receive plenty of website visitors and potential leads who aren’t serious. After all, at this point, it’s a common pastime to visit a site like Zillow (NASDAQ: Z) (NASDAQ: ZG) and dream of owning a multimillion-dollar property.

However, instead of the agent having to sift through all their leads to identify those with the most potential of becoming a real buyer in the near future, deep learning allows artificial intelligence to be able to qualify leads accordingly.

Other sites use natural language processing (NLP) technology to help specialty agents zero in on their ideal clients. For example, an agent who specializes in the luxury market can use this real estate technology to prequalify their leads so they don’t waste time tracking down potential buyers who can’t afford their listings.

It’s transforming the home search process

Ever since listings first became searchable online, technology has played a role in helping buyers streamline their home search. While nearly every home search tool allows real estate agents and prospective buyers to narrow a home search by a list of criteria like the number of bedrooms and bathrooms or location, often, this method still leaves everyone with too many options to choose from.

That’s where the AI algorithm comes into play. Many of today’s home search tools can use those search criteria to identify the user’s preferences and select properties based on those findings. Most algorithms can then offer alternative listings that might be a good match and place the best-fitting listings at the top of the user’s search results.

It’s streamlining transactions

On the back end of the transaction, artificial intelligence can also make it easier for the Realtor to run their real estate business. For instance, many customer relationship management (CRM) systems utilize machine learning for things like auto-fillable data and generating automatic reports.

Not only does this cut down on the amount of time a real estate agent needs to spend in front of the computer doing office tasks, but by taking the human element out of data entry, it helps reduce the number of errors overall.

It’s making property valuation easier

Additionally, one of the major features of AI that real estate agents are coming to rely on is its ability to “predict” the future. Namely, this comes in handy when trying to assess property values and rental values. In this instance, an AI application’s automated valuation model might gather data about public records, transportation options, area crime rate statistics, and school district ratings in order to generate an analysis of a particular property’s value.

On the one hand, this version of desktop appraisals has been particularly useful in the era of the coronavirus pandemic. However, beyond that, it will likely continue to prove to be a useful tool for real estate agents when they’re tasked with generating comparative market analysis, as well as with investors when they’re deciding whether to add new properties to their portfolios.

It’s changing the way we approach lending

Lastly, machine learning has also had an impact on the mortgage industry. As any real estate agent or investor knows, the underwriting process involves pouring over any collected paperwork to determine whether to lend to the prospective borrower.

However, the process of desktop underwriting uses AI technology to read those documents and make an initial determination before the documentation is handed over to the underwriters. While desktop underwriting doesn’t always replace the human element of this process entirely, it does help speed it up significantly.

What Are Some AI Tools for Real Estate Investors?

After reviewing more about how AI works and its benefits, the next step is to learn about some recommendations. With that in mind, we’ve curated a list of some of the best AI programs available to you as a real estate investor to give you a sense of which ones might be the best fit for you and your business.

1. Skyline AI

For those in the commercial real estate industry, Skyline AI collects data points from a variety of sources and analyzes past transactions to help you get a sense of which neighborhoods are up-and-coming and which are heading for a potential downturn.

By analyzing property owner behavior, this tool can also help commercial real estate investors find distressed properties, off-market deals, and opportunities for value creation.

2. Proportunity

Proportunity offers a similar service for those in the residential real estate industry. Operating in 50 markets, this tool gathers property value data, crime rates, transportation data, and school district ratings to fuel its automated valuation model and predict which properties and neighborhoods will give you the highest returns.

3. Enodo

Those in the multifamily market should turn to Enodo. Its machine learning capabilities can help you calculate market rents, find comparable properties, and identify lucrative investment opportunities. For those considering doing renovations, it can also help you estimate the future value of any added amenities.

4. Beyond Pricing

Meanwhile, those within the vacation rental industry may benefit from using Beyond Pricing. This tool compares data from a variety of sources, including Airbnb and VRBO, to help you find the best pricing for your vacation rental.

5. Lofty AI

Like Proportunity, Lofty AI claims to help you identify the best investment opportunities in 40-plus markets. This tool is geared toward out-of-state investors and uses deep learning as well as alternative data points to predict early signs of gentrification.

Will Real Estate be Automated?

While automation does seem to be creeping into most aspects of our lives, and hurting many industry workers, it will never be a problem for the busy world of real estate.

Unless we make leaps and bounds in artificial intelligence, you won’t be seeing any robots or other forms of automation buying or selling real estate. Here are three reasons why:

Human Intuition

When a person comes to you to help them buy a home, they will likely have a long list of details they want and need from their ideal home. With modern technology, you could easily find a home that matched their list completely.

For example, say the client is looking for a home with three bedrooms, a den, and a kitchen with an island already installed. The software could likely find you a hundred homes in the area that meet these specifications, but it will never know which one is right for your client.

Any worthwhile real estate agent can see past what their clients think they want and can read what they really want.

Reasoning

Thanks to technology, the sheer amount of data available to businesses is staggering. However, all of that data is meaningless without someone who knows what it means and can follow the trends with their buyers and sellers.

Technology can create charts and spreadsheets full of useful data, but what do those figures mean to your client? Without someone to translate the data, all of it is essentially useless.

Alternatively, technology is best suited to work in tandem with real estate agents. A modern agent will access an IDX real estate website via CRM to maximize lead generation and customer satisfaction.

Empathy

Buying or selling a home is usually one of the biggest moments of a person’s life. Your clients want someone who has experience handling something so emotionally impactful to their lives.

An automated service has never had to stress about finding the right home, struggle through a failing economy or lose sleep about the future of their family. Empathy is the function and emotion that connects us and makes us truly human.

In today’s busy market, most homes have many offers on them, which means that someone has to lose—and it may be your client. As an agent, it’s your job to assure them that you’ll find them the right home and comfort them through a discouraging time.

There are no algorithms to explain the underlying message behind your client’s body language. It may be able to detect changes in mood, but technology can never understand the full story.

How Can AI Reduce Costs?

The right prospect of AI is to provide actionable insights in massive amounts of unstructured data. This definitely impacts the cost of doing business. AI is involved in process automation and codifying business logic. As a result, the probability of a human error will be reduced significantly. Artificial intelligence improves the overall efficiency and can help to minimize the mistakes.

Simplifies Market & Customer Insights

AI is efficient in playing an enormous role when it comes to analysing the market and your customer’s data. Ambitious startups are exploring new opportunities and new solutions for their business growth. Predictive analysis helps start-ups in cost reduction on maintenance.

On regular quality checks with AI-based systems also optimize marketing strategies and bring down marketing expenditures. It can also proof to be most effective marketing tool for your business by eliminating unlikely customers from the list of potential customers.

Active Process Automation

In the last few decades, various automation tools are being innovated as per the business requirement. The focus is to transform the business process agile. In this new era startups and enterprises are taking advantage of the rise of AI in automation.

A Smart AI algorithm is helping the leaders in predicting the astonishing outcomes. Industries like retail, hospitality, financial and others run huge process automation that works 24 hours without a break. In that case, AI is proactive to maintain such a process effectively. It helps to increase the chances of conversion.

Well-organized Sales Process

These days’ sales teams are using AI to get to know more about the customers better. Businesses in offering tailored solutions using AI to ask few questions to their buyers & based on their preferences. An innovative and more effective approach is implemented when it comes to marketing for your business.

The focus is to increase the chances of conversions while understanding in-depth. Therefore, AI is helpful in crafting a sales pitch that can reach the right customer at the right time on the right platform. Sales process is all about offering the best fit as per the client’s/customer’s preference.

Personalized Customer Experience

Utilizing Artificial intelligence allows a business to offer a more personalized experience to potential customers. AI-driven processes are beneficial in operating multitask for businesses in various verticals. On the basis of AI-enabled analyze business functionalities can be more efficient.

Identifying the vast patterns of data allows the business to handle the whole process. It can help companies to engage their customers in a real and impactful way. An AI-driven application can help businesses to provide personalized services to the right customers with the right content at the right time.

How is Data Science Used in Real Estate?

In terms of the real estate sector, in America the use of data science is at a point where it is very developed. Real estate companies are investing in property matching online software, which can determine if a property is a good match in terms of investment for each customer.

Models that allow this have been developed by using a variety of public data and market information such as prices per square metre on past transactions, number of bedrooms and the quality of the neighbourhood.

This provides clients with much wider parameters than could be provided by a single estate agent and allows the estate agent to offer greater accuracy in their information, for by example, giving clients accurate house prices instead of estimations.

Zillow, an American real estate company, has developed a ‘Zestimate’ prediction, which predicts what the value of a property currently on sale will be anytime for one to ten years from now.

The success of data science in real estate is however dependent on the quality of the data and how it can be accessed. The volume available is huge, sources are multiple and not always in line with one another. A huge amount of data sits in paper files or PDF documents, so it’s not easy to access it even though very relevant.

A key challenge during these first stages of data science in real estate is therefore understanding how to structure and qualify data in order to eliminate non-relevant or unreliable sources and focus on dependable data that is available for use.

In the near future, data science will have an important role to play, as it will be able to not only improve a business strategy but also improve the way and quality of our lives. Data science which works in tandem with Artificial Intelligence (AI) will be able to analyse behaviour, interests and preferences in order to propose the ideal apartment for each client.

This will mean that clients interested in a property will be able to visit it on their smartphone, projecting themselves into what it would be like to live there, by eliminating a wall or changing the colours for example.

Users installed within a building will also benefit from a greater understanding of data. The IoT is becoming more and more necessary and used in AI within the real estate sector.

Sensors that record temperature, air, equipment condition allow for responsive environments which adapt to user’s habits and behavior. Data will thus have a direct impact on the chosen place of residence and investment criteria and will increasingly influence buying and selling habits.

How is Big Data Used in Real Estate?

Before big data, many of the decisions made in real estate were mostly based on gut feel and first impressions. Now, data analysis is one of the main factors in today’s decision-making process.

Real estate service providers who are focused on delivering bespoke, customer-centric property solutions typically have satisfied customers. Insights from their data can be used to help better meet the needs of their existing customers, the real estate owners, and be used to position themselves as the real estate partner of choice for prospective customers.

The internet has made searching for property – to buy or rent – an online exercise, with big data being enabled by many apps, websites and online forums. According to a study by the National Association of Realtors, 51% of home buyers found their property online in the last year.

The data revolution makes finding data on proximity, real-time traffic estimations, noise levels, areas of late night activity, restaurants, parks, outdoor activities and customer reviews easy to find, and eliminates some of the typical buyer confusion.

Realtors, investors, and homebuyers now have access to data that is a click away, which empowers them to make smarter investment decisions, with data analysis making accurate predictions about risk and market trends. Big data is transforming the real estate industry into a well-calculated game of information. Benefits include:

1. Risks mitigation. Predictive analytics helps reduce risk when it comes to real estate investments, and realtors and buyers now have access to critical information about a property with few unknowns.
2. Simple (and fast) evaluations. Realtors use property evaluations to set the price of their properties, and home buyers and investors use them to put forward offers. Financial institutions rely on them to calculate loans and minimise losses. Big data has the ability to make appraisals based on years of market data, making it a tool for buyers and sellers alike. Coupled with viewing the property, it offers a way to make accurate appraisals.
3. Realtors understand customers’ needs better. Predictive analytics provided by big data helps real estate agents better understand what their customers want, and helps them respond with personal offers based on the data.
4. Improvement in marketing strategy. Realtors can move on current consumer trends faster, and more accurately.
5. Using big data with social media. Many advertisers utilise social media sites for their useful marketing data due to their high use by the valuable 18- to 35-year-old demographic. It’s easy to target your key audience by region, age, gender, interests, and preferences for optimal engagement.
6. A new level of insurance services. Insurance companies that cater to home insurance also use big data to analyse optimal insurance offerings for customers and geographic regions.

Will Technology Take Over Real Estate?

From digital open houses to Artificial Intelligence (AI) platforms to bitcoin cryptocurrency, new technologies are taking over the real estate industry by storm and accelerating the pace of business.

With tech-savvy Millennials and Generation Y representing the largest group of homebuyers, it is important to power up your career by staying on top of these swiftly evolving trends and learning how new tech can work for you.

Over 70% of customers look for homes online and more than half of house tours are booked through a website. Now more than ever, keeping up with the latest tech can help you differentiate yourself from your competition. Learn how to leverage the real estate tech revolution with these three emerging trends:

1. Artificial Intelligence can be an intimidating and even threatening idea to some. Science fiction has conditioned us to view it as something that will ultimately overpower human intelligence and bring about our demise. But, today’s AI solutions do not dream of electric sheep yet, and are used to meet a growing need for convenience and efficiency.

Real estate AI platforms can range from robots giving house tours to immersive virtual tours offered from the comfort of your client’s couch. Beyond its consumer-centric approach, AI can streamline processes for agents by automating repetitive tasks, like answering questions in real-time with chatbots, and use predictive analytics to sift through large amounts of data to target hot leads.

2. Virtual Reality (VR) and Augmented Reality (AR) offer a unique try-before-you-buy model in real estate. Thanks to aerial footage obtained from drones and 3D technology, your clients can now “step into” a space and have an immersive virtual experience while you assist another client.

Agents may soon no longer need to spend time and money staging a space, because clients are able to personalize it with virtual furniture. Many international investors already use VR before considering a real estate purchase, and this trend will increase as the VR experience becomes more immersive and sophisticated.

Allowing your clients to evaluate a space will help speed up their decision-making process and is more likely to put you in touch with an interested buyer.

3. Blockchain Technology. While Blockchain Technology is still in its infancy, it has already demonstrated its vast potential with the recent use of bitcoin currency in luxury real estate sales. Bitcoin, a digital cryptocurrency created by blockchain technology, is essentially a decentralized electronic money used for transactions worldwide.

The appeal of this peer-to-peer currency is that it is borderless, not controlled by a monetary authority and has created a wave of new digital wealth valued at about $200 billion — in less than a decade.

Read Also: Podcast: The Voice of Marketing and Earn Opportunity

Despite bitcoin’s potential tax implications and tech bubble “feel”, sellers are willing to accept the currency for large-scale projects fueling speculations that bitcoins may be revolutionizing the financial sector next.

It is important for real estate professionals to adjust to these technological advances and diversify their strategies, as new tech will continue to accelerate the pace of business. Consumers will increasingly seek centralized experiences that integrate all facets of a real estate transaction.

One way you can diversify your strategy is by offering an AHS® Home Warranty along with your listing. This can help save your clients’ time and reassure them that their budget is protected from unexpected covered breakdowns.

Final Words

These days, it seems like artificial intelligence and machine learning programs are growing smarter by the day. While there’s no telling where technology will take us in the future, one thing we know for sure is that this technology can be used right now to help real estate agents and investors.

With that in mind, use this post as your guide to AI in real estate. Armed with this knowledge, you should be able to bring your real estate business to the next level.