AI-Driven Transformation of the Real Estate Industry: A Framework for Property Valuation, Market Forecasting and Intelligent Decision-Making
Year: 2026
Type: article
Abstract: As machine learning (ML), geospatial analytics, and generative AI take the place of manual evaluation and intuition-driven investment, the real estate industry is undergoing a fundamental transformation. Current research limits practical adoption by treating forecasting, valuation, and decision assistance as distinct activities. A five-layer AI system that combines multi-source data intake, feature engineering using spatial and visual signals, an ensemble valuation engine, a temporal market-forecasting module, and an explainable decision-support layer is proposed in this study. We provide a replicable evaluation procedure, formalize each component, and address governance concerns such as privacy, bias, and regulatory compliance. The framework provides researchers and practitioners with a standard architecture for developing transparent, scalable, and auditable AI systems for real estate markets.
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7225783102
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