Faculty AI literacy in higher education systems: a systematic review and future-adaptive framework

Amidst the evolution of AI beyond Large Language Models (LLMs), higher education requires literacy frameworks resilient to rapid technological obsolescence. This PRISMA-based systematic review synthesized 27 empirical studies to construct a future-adaptive faculty AI literacy framework. By anchoring 39 indicators across six dimensions within Boyer’s scholarship model, the study reframes AI literacy as a systemic pillar of digital academic professionalism. Moving beyond transient tool-centric skills, the framework prioritizes enduring meta-competencies, specifically algorithmic logic and critical reasoning, as the primary mechanisms to safeguard digital agency and prevent algorithmic alienation. The findings advocate for a paradigm shift from perception-based to performance-based assessment, operationalized through the proposed Artificial Intelligence Literacy Scale for Faculty (AILSF). This study provides a testable, evidence-based model of adaptive professionalism, ensuring faculty leadership evolves alongside emerging autonomous systems while preserving human-centered academic integrity.