Smart home technologies are increasingly powered by artificial intelligence (AI), offering convenience, energy efficiency, and security, but also raising serious concerns around privacy and cybersecurity. This study seeks to explore the factors that affect the adoption of AI-powered smart home devices by extending the Trust in Technology Model (TTM) to incorporate cybersecurity awareness. The objective is to better understand how users’ trust in technology, institutions, and specific devices, combined with their cybersecurity awareness, influences adoption behavior. A quantitative research design was used, and Structural Equation Modeling (SEM) was employed to examine the assumed relationships among the variables. The results confirm that propensity to trust, in general, technology significantly enhances institution-based trust, which in turn positively influences trust in specific technologies. Trust in specific technologies and cybersecurity awareness were both found to strongly increase users’ intention to adopt AI-powered smart home devices. Moreover, users’ intentions showed the strongest effect on deep structure use, highlighting that positive behavioral intention is a key driver of actual, advanced utilization of these technologies. These results highlight the importance of trust-building and awareness initiatives for fostering wider adoption. This research extends the current literature on technology adoption and provides a framework that can help explain the user’s adoption of AI-powered smart home devices. Its originality lies in integrating cybersecurity awareness into the TTM, offering both theoretical contributions and practical implications for policymakers, developers, and marketers.
Alshammari et al. (2025) studied this question.