AI-enabled smart home technologies and residential property price premiums in Malaysia: a hedonic pricing analysis

Purpose This study investigates the influence of artificial intelligence (AI)-enabled smart-home technologies on residential property prices in Malaysia using an extended hedonic pricing framework. Specifically, it examines whether the integration of AI-based features, including smart security systems, automated energy management and intelligent home-control technologies, contributes to measurable housing price premiums. Design/methodology/approach Using a cross-sectional dataset of 300 residential properties (229 in regression analysis), this study employs an extended hedonic pricing model and multiple regression analysis to evaluate the influence of structural, technological and locational attributes on residential property values. In addition, subgroup comparisons across smart-home technology levels are conducted to examine variations in the pricing effects of AI-enabled smart-home features across different housing submarkets. Findings The results show that AI adoption is positively correlated with property prices (ß = 0.154, p = 0.002–0.003 for both regression models presented in Tables 12 and 13), indicating that smart-home technology is reflected in property prices in Malaysia. Depending on specification (Table 12: R2 = 0.310; Table 13: R2 = 0.212), the models explain between 21.2% and 31.0% of the variation in property prices. Further results indicate that AI security systems do command a measurable price premium for homes, and that size and other structural attributes remain key determinants of property prices. The negative relationship between distance to the central business district and property price remains significant, indicating the importance of location. Research limitations/implications The study is limited by the cross-sectional design, the focus on a subset of AI-enabled technologies, and the restriction to the Malaysian market. Future research should investigate this relationship further by using longitudinal data, broader measures of technology, and cross-country comparisons. Practical implications The findings show that investors, developers, and financial institutions value digital housing features, encouraging the use of smart technology in residential property investment and valuation in Malaysia and elsewhere. Originality/value This study offers empirical evidence from an evolving market on the pricing/value effects of AI-enabled housing attributes while contributing to the growing literature on technology-driven value creation in real estate markets.