Understanding the role of privacy issues in AIoT device adoption within smart homes: an integrated model of privacy calculus and technology acceptance

Purpose The proliferation of Artificial Intelligence of Things (AIoT) devices has introduced notable privacy concerns, influencing user adoption and trust. This study integrates privacy calculus theory with the technology acceptance model to analyze how privacy risk perception affects users’ intentions to adopt and continue using AIoT devices. Design/methodology/approach A research model was developed and validated using data from 313 AIoT users. Findings indicate that perceived usefulness and ease of use significantly enhance users’ trust in AIoT devices. Additionally, prior privacy experiences and privacy knowledge amplify users’ privacy concerns. Findings Privacy risk perception and concerns reduce trust in AIoT devices but do not significantly deter continued usage intentions, highlighting a “privacy paradox” where functionality and convenience outweigh privacy concerns. Future research is encouraged to examine user attitudes across diverse demographics and controlled settings to gain deeper insights into privacy perceptions and behaviors toward AIoT. Originality/value These findings contribute to a comprehensive understanding of AIoT adoption dynamics and offer practical implications for designing privacy-conscious AIoT applications.