<![CDATA[The integration of artificial intelligence (AI) into wearable devices, particularly smartwatches, creates significant potential for delivering highly personalized and intelligent services. Yet, despite their growing adoption, limited research has examined how smart service experiences and perceived trust shape user acceptance of AI-driven smartwatches. This study proposes an extended Technology Acceptance Model (TAM) incorporating smart service experience dimensions (two-way communication, personalized interaction, and user control) and perceived trust to examine their impact on user attitude and continuance intention. Data from 420 AI-based smartwatch users were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This study extends the Technology Acceptance Model (TAM) by integrating experiential constructs—two-way communication, personalized interaction, and user control—and perceived trust to explain continuance intention toward AI-based smartwatches. Results show that smart service experience strongly influences perceived ease of use, usefulness, and trust. While usefulness and ease of use shape attitudes and continuance intention, trust acts as a contextual rather than direct driver. Theoretically, this study positions smart service experience as a key antecedent while elucidating the role of trust. Practically, it underscores the value of AI-enabled personalized features in strengthening user loyalty.]]>
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