Understanding Consumer Experiences and Meanings of AI Shopping Technologies in E-Commerce
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Abstract
The rapid integration of artificial intelligence (AI) into e-commerce has transformed consumer behavior, making trust, personalization, and automation central to modern shopping experiences. Within this context, understanding how consumers interpret and give meaning to their interactions with AI shopping technologies has become an important area of inquiry. Yet, despite growing research, little is known about the subjective and emotional dimensions of these encounters, leaving open the question of how consumers negotiate trust, ambivalence, and resistance in their lived experiences. Here we show that an interpretative phenomenological approach provides unique insights into the deeper meanings consumers attach to AI-driven shopping interactions. Data were collected through semi-structured, in-depth interviews with 12 participants, consisting of experienced e-commerce users aged 20–35, selected using purposive sampling, and analyzed thematically using interpretative phenomenological analysis (IPA). Methodological rigor was ensured through member checking, audit trail documentation, and peer debriefing procedures. The findings revealed four essential themes: trust as the gateway to adoption, emotional ambivalence in the AI encounter, resistance as a form of consumer control, and loyalty through meaningful engagement. These results demonstrate that adoption extends beyond technical efficiency and is shaped by how consumers emotionally and interpretively engage with AI technologies. The study highlights that consumer loyalty emerges when personalization is experienced as authentic and respectful, while resistance reflects an effort to preserve autonomy. These insights enrich theoretical perspectives on AI adoption by uncovering the interpretive structures of consumer experience and provide practical implications for designing human-centered AI systems. Future research may expand this exploration across cultural settings and longitudinally to examine evolving consumer–AI relationships.
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