Thesis Abstract

Abstract
The real estate industry is increasingly turning to Artificial Intelligence (AI) technologies to enhance property valuation and investment decision-making processes. This thesis explores the potential benefits and challenges of utilizing AI in real estate management, specifically focusing on property valuation and investment decision-making. The study delves into how AI algorithms and machine learning models can analyze vast amounts of data to provide more accurate and efficient property valuations, as well as support decision-making processes for real estate investments. The research methodology involves a comprehensive review of existing literature on AI applications in real estate, including property valuation techniques, investment strategies, and risk management. Additionally, primary data will be collected through interviews and surveys with real estate professionals, investors, and AI experts to gain insights into current practices and perceptions regarding AI in real estate management. Chapter One provides an introduction to the research topic, presenting the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter Two presents a thorough literature review on AI technologies, property valuation methods, and investment decision-making in real estate. The chapter explores ten key concepts related to AI applications in real estate management. Chapter Three outlines the research methodology, detailing the research design, data collection methods, sampling techniques, and data analysis procedures. The chapter also discusses ethical considerations and limitations of the research process. Chapter Four presents the findings of the study, analyzing the data collected from interviews, surveys, and literature review. The discussion includes insights on the effectiveness of AI in property valuation and investment decision-making, as well as challenges and opportunities for implementation. The conclusion in Chapter Five summarizes the key findings of the study, highlighting the implications for real estate professionals, investors, and policymakers. The thesis concludes with recommendations for integrating AI technologies into real estate management practices and suggestions for future research directions in this field. Overall, this thesis contributes to the growing body of knowledge on AI applications in real estate management, providing insights into the potential benefits of utilizing AI in property valuation and investment decision-making processes. The findings aim to inform real estate professionals and investors on the opportunities and challenges associated with adopting AI technologies in the industry.

Thesis Overview