Artificial intelligence has transformed higher education by improving academic efficiency and delivering personalized learning experiences; yet, it raises concerns about data security and algorithmic bias. This study explores how undergraduate and graduate students in journalism, media, and communication perceive AI-driven educational systems, focusing on data privacy, ethical challenges, and algorithmic inequalities. We gathered insights through semi-structured interviews with students of varying academic abilities, using a phenomenological approach, and thematic analysis. Findings reveal limited awareness of data management processes, fears of misuse, and concerns about AI biased feedback. The study emphasises the need for greater transparency, inclusive AI development, and educational initiatives to address these ethical issues. By amplifying student perspectives, it contributes to the conversation on ethical AI practices, offering actionable recommendations for policymakers, educators, and developers to promote trust, equity, and accountability in AI-integrated education.