Adoption of Artificial Intelligence in Commercial Real Estate : Data Challenges, Transparency and Implications for Property Valuations

Detta är en Master-uppsats från KTH/Fastigheter och byggande

Sammanfattning: Investment decision in the property market is closely connected to property valuation. Thus, accuracy of valuation results and deep analysis of the market is essential. Artificial Intelligence (AI) models have been successfully adopted in different fields and markets. However, the real estate market is typically lagged in time to adapt to these changes. Swedish commercial property market arrangements are characterized by increasing confidentiality of certain data types. As a consequence, the adoption of the AI valuation models in the Swedish commercial property market is slowed down.  This study aims to bridge the gap in existing research by focusing on the market actor’s behavior in relation to market development and exploiting the capabilities inherent in adopting AI models in commercial property valuations.  The qualitative approach based on interviews with experts has been used to achieve the main objective of this study. Results suggest that the AI valuation models used on commercial properties are applied on valuation data and not on real transaction data. Analysis covers different aspects including data challenges and its disclosure, the role of government authorities, market and data perspectives of AI application on property valuations. A framework on AI implication in property valuation in different time horizons presented in this study will help to overcome data challenges and improve transparency of valuation results. This study is beneficial to various actors in the property market, including government authorities, investors, valuers and researchers.

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