By 2024, AI technologies have become essential tools in all areas of life, including the real estate sector.

AI in real estate makes managing and selling properties significantly simpler and more effective than before!  AI real estate technology impacts all aspects of the real estate sector: property management, sales, leasing, and more.

How exactly do advanced AI technologies shape the real estate sector? What tools do real estate professionals use to streamline property data operations? Explore case studies on developing AI software solutions and more in our comprehensive guide to AI in real estate!

How Does AI in Real Estate Work?

AI in real estate uses advanced algorithms and machine learning (MI) to sift through large data sets in the real estate sector.

AI technology is reshaping how real estate processes make property valuations more accurate, offering custom recommendations for buyers, and, the greatest pros, simplifying many routine tasks.

How Does AI Integrate with Real Estate? 

Data Gathering and Analytics

AI gathers data: information from property listings, past sales, demographic data, economic trends, and more. Then it analyzes this data to identify patterns and trends that inform decisions.

Real Estate Price Prediction

In complexity with machine learning, it predicts property prices and spot market trends. The prediction is based on location & districts, amenities nearby, planning, market demand, and general condition.

Custom Recommendations

AI customizes its suggestions for buyers, sellers, and real estate investors by learning their specific needs and preferences.
Recommendations are usually based on a buyer’s past preferences or suggest the best pricing strategies to sellers based on the current market.

Efficiency without routine

AI takes over repetitive tasks like scheduling viewings, answering questions, and handling paperwork.
This is a brief explanation with just a few examples of how AI in real estate works. Below, you will find more details, examples, and explanations about each ai integration.

AI’s Impact on Real Estate

Smart AI technology is often used in real estate management and property selling. AI tools help automate processes, analyze large amounts of data, make forecasts, and provide comprehensive analytics. As a result, they help solve various problems related to managing and selling real estate.

Artificial intelligence affects every major industry. However, no sector has more potential for transformative AI changes than real estate.

Let’s explore in detail how AI is reshaping the real estate industry and how it will continue to evolve.

Use Cases of AI in Real Estate industry

AI and Virtual Property Tours

AI has elevated Virtual Tours to a new, much better level. Traditionally, these tours were simple panoramic images or video walkthroughs. Now, with AI, they are more interactive and personalized.

AI customizes virtual tours based on client preferences. It can also provide real-time information, such as material details or upgrade options.

You can also integrate chatbots to answer questions and offer more property details.

AI in Real Estate Financing

AI real estate algorithms can quickly analyze vast amounts of data: credit scores, income history, and debt levels, speeding up pre-approval and application submissions.

AI also automates document verification and fraud detection. AI enhances risk assessment models in underwriting, incorporating a wider range of factors, including non-traditional credit data, to better evaluate a borrower’s creditworthiness.

AI Chatbots

AI chatbots in real estate provide personalized communication and 24/7 Support.

With AI Chatbots, you can:

• Provide instant responses
• Handle inquiries
• Schedule viewings

Predictive Analytics

Predictive analytics helps real estate professionals to get predictions about the future, forecast market trends, price movements, etc, based on previous residential real estate market data.

AI predictive analytics includes the use of:

• Machine learning
• Archival records
• Data mining
• Current and historical statistics
• Free property value estimates

AI-Powered Property Search

AI-powered property search stands out because it learns from user interactions.

How does Artificial Intelligence Property Search work?

By analyzing how users browse and respond during their search, artificial intelligence can determine the effectiveness of the buying experience. It notes whether a purchase was made and if the process was positive or negative. With this information, AI then offers new recommendations, improving the accuracy of property suggestions over time.

This personalized approach helps streamline the search process, increasing the likelihood that property searches will find and purchase properties that meet their needs.

AI Analytics for Property Assessment

AI revolutionized the property assessment process – AI-driven analytics offer high accuracy and efficiency. 

Today, traditional property assessments, which rely on an assessor’s experience and a limited set of local data, are being replaced by sophisticated AI systems!

AI tools can analyze huge data volumes of information at local and global levels.

How Does AI Enhance Property Valuation Work?

AI-based property assessments have advanced algorithms that can sift through large datasets, such as:

• Historical transaction prices
• Current real estate market trends
• Property characteristics
• Socio-economic factors can impact property value. 

AIs process this diverse data far beyond what traditional methods can offer. In just a few moments, you can make accurate and comprehensive assessments.

While traditional valuation methods are often subject to human error or limited by regional knowledge, AI systems analyze both national and global trends.

AI in Property Valuation: Examples

AI analytics for property assessment is already making waves in the real estate industry:

Zillow’s Zestimate uses AI to provide instant property valuations by analyzing public records and user-supplied data. This tool offers homeowners and buyers an accurate estimate of a property’s worth, all in real-time.

Redfin leverages machine learning models to deliver precise home value estimates, processing thousands of data points.

AI can also be used in the mortgage lending process. Banks and financial institutions are integrating AI analytics to assess property values quickly and efficiently.

Overall, AI analytics reduce the risk of over- or undervaluing properties, help streamline lending decisions, and improve customer satisfaction.

AI-driven Property Management: How it Works?

One more real estate business where AI is important is smart property management.

AI in property management can be used for:

• Automating routine and time-consuming tasks
• Handling tenant inquiries
• Managing lease renewals
• Processing payments
• Optimizing real estate transactions
• Reshaping day-to-day management operations

Automation of Daily Operations

AI can streamline everyday tasks. For instance, AI in Real Estate can manage tenant communications by automatically triaging and responding to inquiries based on urgency. Lease renewals and payment reminders can be completely automated, minimizing the need for manual involvement.

AI-Powered Maintenance Optimization

A significant advantage of AI in property management is its capacity to enhance maintenance processes.

AI-based systems can prioritize maintenance requests according to urgency and automatically schedule appointments with service providers. In addition, AI is making great strides in building energy management. Smart algorithms can analyze usage patterns and weather forecasts to optimize heating, cooling, and lighting systems, helping reduce energy consumption and costs.

AI in Customer Service

AI in can significantly improve customer service across the real estate industry. Over the past few years, AI-powered chatbots and virtual assistants have become must-have tools for responding to real-time customer and real estate agent inquiries.

Case: AI in Predicting Client Preferences

Another example of AI and Real Estate roles is predicting client preferences. AI-driven systems can analyze customer behavior, preferences, and search histories to generate personalized property recommendations. 

For instance, if a potential buyer consistently looks at properties with large windows, three bathrooms, and a big garden in certain neighborhoods, the AI system flags similar homes for real estate agents to recommend. This not only streamlines the buying process but also increases customer satisfaction by offering more personalized service.

Integrating AI into real estate platforms helps to meet client’s needs more efficiently and improve overall customer experiences, making the entire process smoother and more rewarding.

AI in Real Estate Marketing

One of the key areas where artificial intelligence excels in real estate marketing is its ability to analyze vast amounts of data: browsing habits, engagement metrics, past purchases, etc.

By leveraging this data, AI can create highly targeted marketing campaigns that precisely match a client’s preferences, such as location, price range, and property features, without spending hours sorting through listings or MLS databases manually. The result is a higher likelihood of client engagement and response, benefiting both the client and the agent.

AI-powered marketing tools can segment audiences with incredible accuracy, ensuring that marketing messages are tailored to different groups based on their unique interests. This level of personalization increase customer experience. Ultimately, it leads to a better return on investment across all marketing activities.

For real estate business owners, AI is also valuable in refining investment and revenue models. AI provides real-time insights into which areas of the market are likely to generate the best returns.

By automating the data analysis and personalization process, AI allows building stronger client relationships, knowing that their marketing efforts are optimized for success.

How to Develop Real Estate Software with AI?

Developing AI-powered real estate software can take different paths, depending on your business objectives. There are two main options:

Option 1: Developing AI Software from the Ground Up

If you want to highlight AI features as your product’s main selling point, begin by clearly defining the scope of AI functionalities you want to integrate. Identify which AI real estate solutions will deliver the most value to your users. These could include automated property valuations, AI-enhanced customer interactions, or predictive analytics for market trends.

Option 2: Integrating AI into Existing Platforms

The development approach will differ if you already have an application or web platform and wish to integrate it with AI capabilities. Integration involves assessing your current technology stack and determining the most efficient way to incorporate AI without disrupting existing operations.

We will provide you with a step-by-step guide on how to develop unique AI Real Estate Software.

4 Stages to Develop AI-Powered Real Estate Software

The development process is divided into four key stages: Discovery, UI/UX Design, Development, and Release & Post-Support.

#1: Discovery Stage

Project Kickoff

We conduct an in-depth business analysis and product discovery to determine which AI functionalities are essential to achieving your business goals. We also decide on possible integrations with existing systems.

Tech Architecture Libraries & Frameworks

Once we define the scope of work, we move to the Tech Architecture Libraries & Frameworks step. At this point, we clearly understand the features and scope of work.

User Flow

User Flow involves laying out the basic project structure. Our UX/UI design team will draft the initial design based on the selected features.

#2: UI/UX Design Stage

Our design team conducts in-depth competitive research during this stage to make your future product visually attractive, intuitive, and effective.

User Flow Creation

The design team maps out how users navigate the software to provide a logical and seamless experience.

Wireframes Creation

At this step, designers develop the basic structure of the software pages, providing a clear blueprint of the user interface.

Design System Creation

We establish a consistent design language for the software that includes colors, typography, and component styles.

UI Design

Our designers work on creating the visual elements of the software.

User Testing

This step is crucial, as only after testing with real users can you gather feedback to make necessary adjustments to the design.

We aim to optimize the project timeline to synchronize the design and development stages when possible. Optimization allows for faster iterations and ensures that design enhancements are quickly integrated during the development process.

#3: Development Stage

Our development team works on both the Back-End and Front-End development. The main goal at the development stage is to ensure that all AI features are seamlessly integrated and function as intended.

Back-End Development

We build the server-side architecture that supports AI functionalities.

Front-End Development

We develop a user-facing side, making the AI features accessible and intuitive for users.

AI Feature Integration

Special attention is given to incorporating AI-driven solutions.

Feature Testing

At this stage, we test whether all AI features and other functionalities work smoothly and meet performance expectations.

Bug Fixing

Any bugs that we found during testing are promptly addressed

Readiness Check

A final evaluation is performed to confirm that the software is fully operational and meets all quality standards.

#4: Release & Post-Support Stage

After successfully releasing your AI-powered real estate software, we provide post-release support to ensure everything operates smoothly. Our post-support services include:

• Complimentary Bug Fixes: We offer free bug fixes for one month after the project’s release to address any unexpected issues promptly.
• Hourly Support: For additional needs, we provide ongoing hourly support to assist with any further adjustments, updates, or enhancements required.

Challenges and Considerations in Development 

When developing AI-powered real estate software, you may face some challenges and considerations. Let’s briefly consider these challenges:

Data Privacy

AI systems rely on vast amounts of data, but a significant portion of this data may be sensitive.

How to ensure user information is protected?

It is essential to make sure that all data is handled securely and in compliance with privacy regulations, such as GDPR or CCPA. This will help protect confidential information.

Potential Bias in AI Algorithms

Even artificial intelligence algorithms cannot work perfectly. Sometimes, AI algorithms can inherit biases from the data they are trained on, leading to skewed or unfair outcomes.

How to prevent this?

Make sure that your AI models are trained on diverse datasets to minimize bias and produce fairer results.

Integration with Existing Systems

Another potential challenge is integrating AI into existing systems. Incorporating AI into established platforms can be complex and requires careful planning to ensure AI real estate features are smoothly integrated without disrupting current workflows or systems.

How to prevent this?

Thoroughly assessing the compatibility between AI tools and existing technologies is a must for a seamless integration process.

Addressing these potential issues in the early stages of development will help you successfully integrate artificial intelligence into your software.

The Future of AI in Real Estate

In 2022, the real estate industry’s investment in generative AI technologies was around USD 351.9 million. In 2032 it’s projected to jump to about USD 1,047 million. This growth translates to an average yearly increase of 11.52%.

• North America bringing in over 41% of the total market revenue in 2022.
• The services sector within generative AI is set to see significant expansion.
• Cloud-based systems were especially popular, capturing 60% of the revenue in 2022.
• Among all groups, real estate agents are likely to experience the fastest growth rate over the decade.

Source: Precedence Research 

The Most Common Examples of AI in Real Estate Solutions

Property Management Apps
AI-powered property management apps make the processes more automated. AI helps with rent collection, tenant screening, maintenance requests, documentation, and other real estate tasks. 

Property Valuation
Property Valuation AI tools can analyze a vast amount of info. They are helpful for real estate companies, commercial real estate businesses, property owners, and other real estate-related users.

Predictive Analytics
Analytics data provide accurate property valuations, user behaviors, future price trends, and more important information. 

Market Trend Analysis
AI-powered market trend analysis tools provide insights into property price trends, demand, supply levels, etc. Market Trend Analysis is a great feature that helps businesses stay competitive and make timely decisions based on current market conditions.

Smart Building Management
AI solutions for smart building management help real estate professionals optimize energy use, enhance security, and improve occupancy management.

Customer Experience
AI greatly enhances the customer experience by offering intelligent property recommendations based on market demands and previous user experience.

Virtual Tours
Potential buyers can explore properties remotely through AR tools. The lack of need to commute makes Virtual Tours more than a must-have!

Develop Your AI-Powered Real Estate Software with RewiSoft

At RewiSoft, we’ve been building real estate solutions since 2019.

Based on 15+ completed Real Estate projects, we know how to use AI to create top-quality software that meets the highest standards in the market.

You can trust us to develop your AI-powered real estate software, and you’ll receive a cutting-edge solution that drives results.