Revised artificial intelligence device use acceptance (RAIDUA) model: exploring privacy concerns for socially responsible AI deployment and ethical AI leadership

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Abstract
Purpose: This study has proposed a socially responsible approach towards artificial intelligence (AI) deployment and tested a revised AI device use acceptance (RAIDUA)-based conceptual model involving the potential indirect moderating role of consumers’ privacy concerns (PRCO) regarding AI-enabled devices. Design/methodology/approach: The newly introduced RAIDUA model was verified with empirical data gathered from 280 respondents. A partial least square-driven methodology was used in the present study. Further, a simple slope analysis was also performed to assess the PRCO for their plausible moderating role. Findings: Results confirmed a negative moderation impact of consumers’ PRCO in the interaction between perceived usefulness expectancy and consumers’ perceived emotions. Further moderation analysis confirmed that PRCO weakens the positive interaction between emotions and consumers’ expected willingness and/or desire to practically accept the use of AI-enabled devices, whereas there is a positive moderation effect of consumers’ PRCO in the negative interaction between perceived emotions and objection to the practical use of AI-enabled devices. Social implications: This study has proposed AI usefulness expectancy as a socially responsible approach towards ethical AI deployment and tested the RAIDUA model for acceptance and integration of AI-enabled devices. Originality/value: This study uniquely integrates AI usefulness expectancy along with perceived AI PRCO as a moderating factor in the RAIDUA model for AI adoption. Both aspects had been overlooked by frequently used Farooq et al.’s (2017) UTAUT-3, Gursoy et al.’s (2019) AIDUA and Salam et al.’s (2025) unified MOOC utilization model frameworks in AI literature. Therefore, we submit that the RAIDUA model offers a novel and original theoretical contribution in technology integration literature and AI adoption-related body of knowledge.

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