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How to Use AI in Real Estate Industry

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Artificial intelligence is reshaping numerous industries today, so the role of AI in real estate can’t be overlooked. Many people don’t fully understand how many business processes are automated, data analyzed, and features are implemented in real estate software using AI technologies. If you don’t want to stay behind competitors and succeed in the modern real estate market, you need to learn how to leverage AI-powered solutions. So, let’s talk about what does AI mean in real estate, the most common artificial intelligence use cases, and how to avoid challenges and ensure that your company benefits from AI in real estate.

What is artificial intelligence?

Artificial intelligence (AI) is a general term for the field of computer science that is focused on developing an accurate simulation of human intelligence. AI includes several subfields, including machine learning (ML), deep learning, and natural language processing (NLP), and computer vision. All of these enable machines to understand and respond to human language, learn from and make predictions based on data, and interpret visual information. Due to these capabilities, today, AI software can perform tasks that previously required human input, such as creating texts and visual media, decision-making, and problem-solving.

Artificial intelligence has impacted numerous industries in recent years. But what is the role of AI in real estate? Let’s find out!

Role of artificial intelligence in the real estate industry

The significance of AI for real estate operations can’t be overstated. Artificial intelligence is actively integrated in several key areas today:

  • Property valuation. Traditional valuation methods rely too heavily on limited data and human perception, which can sometimes lead to inconsistencies and inaccuracies. AI for real estate agents or investors can easily analyze diverse datasets, such as previous sales data, property metrics, neighborhood analysis, and overall economic trends. Advanced AI models continuously learn and improve,  ensuring up-to-date valuations, and can even predict market trends and slight market fluctuations, enabling real estate companies to create dynamic pricing strategies and reduce risks.
  • Predictive analytics. AI applications enable real estate professionals to anticipate future industry trends and make data-driven decisions. Artificial intelligence enables investors to strategically plan their investments based on future price movements and demand patterns. Also, by integrating machine learning in real estate solutions, investors can identify properties with high potential for growth based on such factors as location, neighborhood infrastructural developments, and demographic shifts. Finally, property managers and homeowners can predict tenant needs and preferences with AI models, improving satisfaction and retention rates.
  • Property management. Artificial intelligence can make the process of managing residential, industrial, and commercial properties more efficient and streamlined. AI integrations allow property managers to automate numerous routine tasks and customer support, quickly process maintenance requests or even predict issues using smart sensors, and reduce costs by optimizing energy usage. These functionalities make property management software even more crucial for the modern real estate industry.
  • Personalization of customer experience. AI algorithms can track and analyze customers’ search history, previous actions, and preferences. Based on this data, AI-powered real estate platforms can offer clients tailored property recommendations that are better for conversion rates and customer satisfaction. Also, implementing conversational AI in real estate apps can help you provide 24/7 customer support with chatbots and virtual assistants. These tools can instantly answer clients’ queries, schedule viewings, and even offer properties based on previous interactions.
  • Fraud detection. Real estate deals usually involve large sums of money, so risks of fraud activities are high. Artificial intelligence and machine learning models can quickly identify unusual patterns and behaviors, such as anomalies in payment methods, transactions, or user profiles. AI apps can instantly alert stakeholders when anything suspicious is occurring.
  • IoT integrations and smart homes. Internet of Things (IoT) devices are the foundation of smart home environments. AI integration can make these devices even more convenient and efficient. Artificial intelligence can optimize smart devices by analyzing user behaviors and energy consumption patterns. Plus, AI-powered IoT systems provide real-time monitoring and control capabilities, allowing to manage properties remotely with a smartphone app and receiving alerts about unusual activities.

To develop custom AI real estate solutions, find a reliable tech partner. Among the most acclaimed product development companies with real estate expertise are SAP SE, Clockwise Software, Vention, Fingent, and Curotec. To choose the right service provider for real estate AI software development, you need to know what your app’s key features are. Let’s talk about the most common use cases of artificial intelligence in real estate to provide some examples.

AI use cases in real estate

If you are still wondering how AI can be used in real estate, let’s take a look at some of the most prominent use cases impacted by artificial intelligence.

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  • AI-powered search and recommendations. AI for realtors and property managers can significantly enhance search and recommendation systems by analyzing customer preferences, search history, and behaviors within a platform. Providing properties that better match client needs help them to find a suitable option faster. Also, NLP capabilities enable real estate apps to understand more complex queries and improve search functionalities with more refined filters.
  • Administrative tasks’ automation. One of the most common use cases of AI in real estate is automation and streamlining of numerous administrative tasks. Automated AI functions often include documentation management, scheduling management, sending reminders, real estate data entry, and data analysis. All of these can significantly enhance the efficiency of day-to-day operations and free up employees’ time for strategic thinking and more creative tasks.
  • Market analysis and investment insights. Accurate market analysis requires hours of research and analyzing at least hundreds of data points. It used to lead to inaccuracies that impacted companies’ investments and marketing strategies. With real estate artificial intelligence software, businesses and individual investors can now leverage machine learning models and advanced analytics tools. AI platforms can quickly analyze historical data and current market conditions, evaluate numerous factors that influence risks of investments, including market volatility and property metrics, and even suggest portfolio optimization.
  • Energy management and sustainability. Modern businesses need to put emphasis on green energy and carbon footprint reduction to appeal to audiences that share the same values. Using artificial intelligence for real estate solutions, property management companies can control lighting, heating, and air conditioning systems based on tenants’ occupancy patterns and weather forecasts, reducing not only energy consumption but also costs. AI models can also offer insights into improving sustainability and energy-saving techniques. By using machine learning, artificial intelligence property management systems can predict future energy needs and adjust building systems to ensure optimized energy usage without sacrificing tenants’ comfort.
  • Tenant screening and risk assessment. Property management involves a lot of risks with the main one being the likelihood of tenant defaults and problematic behavior. Artificial intelligence for real estate can assess credit scores, rental histories, employment records, and social media profiles to provide comprehensive analysis of tenants’ reliability. Also, property managers can automate background checks to reduce workload and ensure thorough screening of potential tenants.
  • Predictive maintenance. Managing residential, industrial, or commercial real estate requires constantly ensuring that properties remain in optimal conditions. Artificial intelligence can help to anticipate and address issues before they even arise by automatically monitoring IoT sensors, scheduling maintenance based on equipment usage and patterns, and efficiently allocating maintenance resources.
  • Optimization of marketing strategy. Machine learning models can track and analyze the performance of marketing campaigns and provide valuable insights for allocating resources more effectively in the future. Also, generative AI can be used to generate personalized content, such as emails or advertisements, that resonates with specific audience segments. In the highly competitive real estate market, companies that implement AI-based tools can gain a competitive advantage and reach wider audiences.

If you ever wondered how to use AI in real estate, we hope that we provided a lot of use cases. But implementing artificial intelligence in business processes can come with some potential setbacks and limitations that you can overcome if you are prepared.

Challenges of using AI in real estate

AI applications in real estate offer numerous advantages but also can pose some challenges. Let’s talk about key considerations and how you can succeed in integrating AI.

  • Privacy and security. Real estate operations always involve a lot of personal information, and implementing AI in real estate software raises significant privacy and security concerns. AI models require access to vast datasets that include personal and financial information, so it is crucial to ensure that this data is handled in compliance with data protection regulations, protect infrastructure from breaches and unauthorized access, and get explicit user consent to avoid legal issues and reputational damage.
  • Data quality. AI software development effectiveness heavily depends on the quality of datasets. Errors in data entry, outdated information, or incomplete datasets can easily lead to inaccurate predictions and compromised reliability of AI models. It is important to constantly validate datasets, ensure comprehensive information collection, and standardize data collection from various sources to avoid issues. 
  • Integration with existing software. A lot of real estate companies still use legacy systems or outdated software, and integrating artificial intelligence can become a real challenge. If you lack the necessary tech expertise in your team, hire AI specialists with proven experience in real estate software development. They will help you to ensure that AI systems work seamlessly with existing software, even if it will require significant modifications or a complete overhaul.
  • Cost and resource limitations. AI adoption often comes with significant upfront investments. Maintenance and updates of AI systems also require continuous investments and skilled personnel. Smaller real estate firms may struggle with this spending, but with many APIs for integration and open-source models, they will still be able to benefit from artificial intelligence.
  • AI bias and ethical concerns. Artificial intelligence is still evolving and AI systems can sometimes provide inaccurate and discriminatory outcomes due to corrupt data and technical issues. In the real estate industry AI bias may affect decisions related to property valuation, investment predictions, and tenant screening. Real estate companies need to detect and mitigate AI bias early on and fine-tune AI systems to avoid these problems in the future.


Now that you know what AI is in real estate and how it revolutionized the industry, it is difficult to ignore technology’s advantages and potential. In the competitive real estate market, companies need to constantly look for new ways to enrich user experience, improve marketing, and enhance business operations. Artificial intelligence is not just a trend that will go away, so to stay competitive, you need to implement AI in your real estate software, even if it comes with some challenges and setbacks.  With a reliable tech partner and understanding of use cases, you will be able to benefit from AI significantly.

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