Authors: Amir Shabbir Patel, Sahil AA Khan, Dhairya Suryawanshi, Rohan Karchuli
Abstract: The real estate industry is currently experiencing a rapid digital transformation, largely fueled by the integration of artificial intelligence (AI) technologies. Among the most promising applications is the use of AI-powered recommendation systems, which aim to redefine how buyers, sellers, and agents interact with property platforms. These intelligent systems are designed to analyze large volumes of property data and user preferences, offering highly personalized recommendations that improve the overall user experience. By leveraging data-driven insights, AI has the potential to simplify property discovery, reduce the complexity of decision-making, and enhance overall market efficiency. This study explores the implementation of different AI models, including machine learning algorithms, deep learning techniques, and natural language processing (NLP), within the context of real estate platforms. We evaluate their ability to process structured and unstructured data such as location, price, amenities, and even user reviews or natural language queries. A prototype recommendation system was developed and tested using real user behavioral data, including browsing history, clicks, and saved properties. The case-based experiment demonstrated that AI- enabled recommendations not only improved engagement but also significantly reduced search time, making the property- hunting process more efficient and user-centric. In addition to the technical benefits, this paper also examines the broader challenges and ethical considerations associated with AI adoption in real estate. Issues such as data privacy, algorithmic bias, and transparency in recommendations are highlighted as key areas that require careful attention. Furthermore, the study identifies opportunities for future research, such as integrating predictive analytics for market trends, enhancing trust through explainable AI, and expanding personalization by considering emotional and lifestyle factors. By addressing these challenges and advancing the current models, AI-driven recommendation systems can play a transformative role in shaping the future of the real estate industry. [4].
