When pondering artificial intelligence (AI), real estate might not immediately spring to mind. Traditionally considered a slow-to-innovate industry, real estate transactions have largely remained rooted in traditional methods, with brokers and independent landlords dominating the scene, while real estate investment trusts (REITs) hold sway.
However, mirroring trends in other sectors, the real estate realm is now welcoming the transformative potential of AI, impacting both commercial and residential segments.
An illustrative infographic demonstrates five instances of AI integration within the real estate domain.
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Any field rich in data proves ripe for AI integration, and real estate is no exception. Historically, property valuations and estimates relied heavily on neighborhood comparisons and human assessments. Yet, increasingly, AI-powered algorithms are assuming responsibility for generating these estimates.
Furthermore, generative AI now contributes to crafting three-dimensional property models. Such models enable prospective buyers to virtually explore properties using everyday devices like smartphones and tablets. This technology gained traction during the pandemic, facilitating property viewings while minimizing physical interactions.
Additionally, AI finds application in smart home devices, such as thermostats, lighting systems, cameras, and monitoring devices. These devices keep landlords abreast of any issues requiring attention, such as plumbing leaks.
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This exploration of AI in real estate delves into the transformative impact of this new technology and provides examples of its deployment within the industry.
Understanding Artificial Intelligence:
AI encompasses computer and machine capabilities to undertake tasks typically requiring human intelligence. Machine learning, a prevalent AI application, entails training machines with extensive datasets to identify patterns, analyze data, and execute forecasts and algorithms.
Supervised Machine Learning:
A subset of machine learning where algorithms learn from labeled datasets, encompassing input and desired output.
This application finds widespread use in real estate.
AI in Real Estate: Five Use Cases
- Predictive Analytics:
Arguably the most prevalent and practical AI application in real estate, predictive analytics underpins property value estimates. Platforms like Zillow leverage AI for “Zestimates” and personalized recommendations, among other features. Investors and agencies employ AI-driven forecasting to anticipate market trends, gaining a competitive edge. - 3D Modeling:
Visual representations assume heightened significance in real estate, with AI-powered digital twins allowing users to digitally explore spaces. Companies like Matterport create 3D virtual property tours, facilitating remote viewings and cost savings for all stakeholders. - Smart Home Devices:
Property technology (proptech) devices, including smart doorbells and thermostats, aid remote property monitoring. AI enhances user customization, cost savings, and maintenance efficiency. - AI in Property Management:
AI streamlines tenant screening, rent collection, and maintenance scheduling. Chatbots assist in customer interactions, while automation optimizes workflow management and analytics. - Mortgages:
AI facilitates mortgage underwriting, fraud detection, and loan servicing. Lenders like Rocket Companies offer near-instant mortgage approvals through AI-driven processes.
Will AI Revolutionize Real Estate?
While real estate traditionally evolves slowly, AI’s impact is evident across predictive analytics, property valuation, smart home technologies, mortgages, and beyond. As AI capabilities mature, its role in real estate is poised to expand further.
Investors eyeing AI exposure may consider AI stocks or ETFs, or explore real estate investing opportunities intertwined with AI advancements. As more real estate entities embrace AI, the industry’s landscape is set for further transformation.
