Arvind Jat

The rapid growth of Artificial Intelligence tools has profoundly altered students' learning practices, epistemic judgment, cognitive ability, their academic engagement, and even influenced the world at systematic level. Despite widespread use, the conceptualization of AI literacy remains uneven, limiting higher education Institutes from adopting a concrete framework of AI literacy. This study addresses the fragmented conceptualization of AI literacy in the context of higher education learners through a systematic review of 13 recent key publications. Upon analysis, six recurrent aspects were identified: Mechanics, Ethics, Systemic, Psychological, Disciplinary application, and agency. Synthesizing these, this study proposes the HEX-AI literacy framework, an integrative model that captures the multifaceted nature of human-AI engagement. This paper further argues for tiered implications strategy for Institutes in higher education to adopt AI literacy, advocating that Institutes should develop generic, disciplinary, and systemic levels, while ensuring content to be contextual to learner's goals.