<p>Using a framework based on multiple selves, this study investigates how self-cognition influences intelligent algorithm adoption across diverse contexts. With algorithm-based intelligent recommendation reshaping business and society, it’s unclear how contextual difference (public vs. private) defines its adoption. The research shows both collective and personal selves impact the adoption, driven by diverse motivations. The collective self is more influential in public spheres, while the personal self matters more in private settings. Perceived privacy risk impacts the personal self in private contexts, whereas it does not influence the adoption of individuals who prioritize the collective self in public settings. These insights illuminate technology adoption in the digital era and suggest contextual interventions for the effective and ethical deployment of intelligent recommendation algorithm.</p>