The Artificial Intelligence (AI) in Real Estate Market is expected to grow at a CAGR of 11.86%, reaching a market size of US$914.970 million in 2030 from US$522.430 million in 2025.
AI in Real Estate means using technology and algorithms in activities like searching for a property, analyzing investments, managing properties, serving customers, and promoting the business. These help to enhance processes, ease decision-making, enhance service delivery, and exploit a property. The search and recommendation system, predictive analytics, and AVM systems are some of the components of AI in real estate. AI systems analyze large pools of real estate data and provide property recommendations to buyers, renters, and real estate investors.
AI systems use different machine learning algorithms to analyze tendencies in the real estate markets, price changes of properties, and potential rents to help investors maximize the use of their rentiers’ assets. AVMs use attributes of properties, information about the markets, and other deals that have occurred before to come up with the property value.
AI systems can conduct and analyze a lot of information, create personal property recommendations, give investment forecasts, and manage customers. Among the various solutions available on the market, Blackshark.ai Roof, an AI-powered brokerage assistant, can assist emerging enterprises in generating new real estate leads and analyzing customers more effectively for potential sales opportunities. This service aims to reach the right recipients at the right time through upselling and cross-selling strategies.
Both ordinary individuals and investors are driving technology integration in the real estate market. The main goal is to help real estate professionals provide a better experience for buyers, sellers, tenants, and investors through more targeted marketing.
The growth of new technologies, such as the application of Artificial Intelligence and the Internet of Things (IoT) in smart buildings, gives room for the utilization of AI in Commercial Real Estate. Smart building systems improve energy-saving, provide a good tenant experience, and enhance safety, thus providing an advantage to landlords and tenants.
Among various products, one is ComeHome, a digital platform that improves the homeownership experience by making it easy for clients to research and purchase residential real estate. It enhances point-of-sale and loan origination processes, allowing companies to better engage with customers and streamline housing transactions. The real estate business is using AI to improve customer experience, marketing efficacy, virtual tours, CRM capabilities, predictive analytics, and operational efficiency, therefore revolutionizing the digital landscape of property management.
AI in the real estate market is segmented based on different deployment models. Cloud-based AI solutions in real estate use internet-based servers to store, process, and analyze data, allowing for scalability, flexibility, and accessibility. They offer real-time data processing, predictive analytics, collaboration features, and resource and service pricing based on subscriptions.
Moreover, On-premise AI solutions, which are implemented directly within an organization's infrastructure, offer improved data protection, privacy, and customization, making them the preferred choice for real estate enterprises with rigorous regulatory constraints, sensitive data, or particular integration requirements.
Real estate transactions require complicated procedures and legal issues. Creating AI systems that can successfully explore and comprehend these intricacies is a problem. Moreover, during the forecast period, the market is also projected to be restrained by cybersecurity concerns and inadequate technical skills. Real estate businesses are still reluctant to adopt the technology due to fears of data safety and privacy.
North America, particularly Silicon Valley, is a hotbed of technical innovation, with major AI firms and startups such as HouseCanary, Zillow, Redfin, and Trulia pushing advances in AI technology for a variety of sectors, including real estate. The North American real estate organizations were among the first to use AI and machine learning technology to improve numerous parts of their operations, including property appraisal, predictive analytics, market analysis, client interaction, and property management. Overall, North America's technological strength and active real estate market make it a crucial participant in adopting and developing artificial intelligence in this industry.
| Report Metric | Details |
|---|---|
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 – 2031 |
| Report Metric | Details |
| AI in the Real Estate Market Size in 2025 | US$522.430 million |
| AI in the Real Estate Market Size in 2030 | US$914.970 million |
| Growth Rate | CAGR of 11.86% |
| Study Period | 2020 to 2030 |
| Historical Data | 2020 to 2023 |
| Base Year | 2025 |
| Forecast Period | 2025 – 2030 |
| Forecast Unit (Value) | USD Million |
| Segmentation |
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| Geographical Segmentation | North America, South America, Europe, Middle East and Africa, Asia Pacific |
| List of Major Companies in AI in the Real Estate Market |
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| Customization Scope | Free report customization with purchase |