Lina Salih

Papers

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About

Lina Salih is a rising scholar whose work sits at the critical intersection of artificial intelligence, user trust, and privacy risk. Her research primarily investigates the post-adoption behavior of AI-enabled services, a domain that has been largely overshadowed by studies on initial adoption and behavioral intentions. In her most cited paper, "AI-Enabled Service Continuance: Roles of Trust and Privacy Risk" (2025, 23 citations), Salih makes a significant contribution by developing and validating a model that explains why users continue or discontinue using AI services after the first interaction. By foregrounding the dual roles of trust and privacy risk, she provides a nuanced framework that challenges the prevailing focus on adoption alone. This work is particularly valuable for practitioners and researchers seeking to understand user retention in an era of rapidly proliferating AI tools. Though early in her career, Salih’s focused, high-impact study has already established her as a key voice in the conversation around sustainable AI engagement, offering actionable insights for designing services that foster long-term user confidence.