The increasing pervasiveness of Artificial Intelligence (AI) within our daily lives necessitates a deeper understanding of how trust shapes our evolving relationship with technology. This mixed-methods study investigates how edu-cational level, self-perceived ‘tech-savviness’, and emotional responses to tech absence, influences individual reliance on, and trust in, AI. Quantitative analysis reveals that individuals who have been in educational institutions for longer pe-riods (e.g. obtained master’s degrees) demonstrate greater trust in AI, leading to stronger reliance, particularly for recommendations scores. Qualitative analysis uncovers a complex interplay between trust, convenience, task-specific trust, and concerns about autonomy. A striking finding is the prevalence of negative emo-tions, including a sense of "incompleteness," during tech absence, especially among the tech-savvy group. This highlights how reliance can extend beyond functional utility and become psychologically intertwined with trust, potentially impacting self-perception. These findings challenge traditional models of tech-nology adoption and emphasize the need for frameworks that consider the psy-chological dimensions of trust in understanding AI reliance. The interplay be-tween education, trust-based reliance, and psychological factors will be crucial for individual adaptability and resilience in an increasingly AI-driven world.