Year: 2025
Type: article
Abstract: This paper evaluates an AI Property Valuation Tool developed for the UAE real estate market, addressing the challenges of market volatility and inefficient traditional valuation methods. Utilizing a mixed-methods approach, the research examines how the integration of multiple large language models (LLMs), vector databases, and real-time data sources revolutionizes property assessment in the region. The tool demonstrates an 80% reduction in valuation time while maintaining accuracy through its innovative three-tiered search approach combining historical and current market data. Performance testing revealed sub-6-second latency for complex queries following optimization measures that improved accuracy by 21%. Despite challenges with data quality and algorithmic optimization, the system represents a significant advancement in property valuation technology. The research concludes with recommendations for enhancing the tool's capabilities through enriched data integration, market-specific prediction models, blockchain verification, and explainable AI frameworks to meet evolving market demands.
Authors: Layla A. A. Sultan, Mona Kaddura
Institutions: Projektträger Jülich, UAE Space Agency
Language: English
Topic: Housing Market and Economics
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4409585477