Recognizing methodological applications and challenges of artificial intelligence in real estate valuations

Artificial intelligence (AI) is transforming the real estate sector by offering innovative tools for analyzing complex data and improving valuation accuracy. Technologies such as machine learning and deep learning are becoming increasingly prevalent in real estate valuation practices, opening up new possibilities and supporting more informed strategic decision-making. This study presents a literature review on the application of AI in property valuation, based on 67 articles published between 1993 and 2024. The aim is to explore the major research trends, methods employed, and challenges encountered in this field. The results reveal a significant surge in academic interest in recent years, coupled with the adoption of sophisticated techniques such as neural networks and big data-based analysis. Geographically, the US, China, and Europe are emerging as major contributors to this field of research. Studies focus on integrating economic, demographic, and geospatial data to improve estimates and enhance understanding of market dynamics. However, significant challenges remain, such as model transparency, data quality, and the applicability of technologies in emerging markets. This review provides a clear overview of current practices and future prospects, offering valuable insights to optimize real estate valuations in an ever-changing global environment.