Inclusive and Critical AI Literacy in Higher Education: From Policy Agendas to Transformative Practice

As AI tools become embedded in higher education, universities are under growing pressure to develop institutional policies, governance frameworks, and regulatory responses. Yet a persistent gap remains between policy intent and pedagogical reality. Strategies adopted at institutional or governmental level - from AI use guidelines to digital competence frameworks - often fail to translate into meaningful changes in teaching, learning, and curriculum design. This Research Topic addresses that gap directly, focusing on how higher education institutions move from AI policy agendas to transformative educational practice.At the centre of this agenda is critical AI literacy: the capacity not only to use AI tools, but to interrogate their assumptions, evaluate their societal implications, and participate in shaping how they are designed and governed. Despite growing policy attention - including the EU AI Act, UNESCO recommendations, and national digital education strategies - the concept remains undertheorized and unevenly implemented. How should critical AI literacy be defined, taught, and assessed across disciplines? What institutional conditions enable or hinder its development? These are questions this Research Topic seeks to advance.We invite empirical, conceptual, and practice-based contributions organised around two interconnected axes:From policy to practice:- Comparative analysis of institutional or national AI governance frameworks and their educational impact- Case studies of how universities translate AI policies into curriculum, pedagogy, and assessment- Barriers and enablers of policy implementation, including disciplinary cultures, infrastructure, and faculty readinessCritical AI literacy in action:- Frameworks for defining and assessing critical AI literacy across disciplines- Inclusive and accessible approaches to AI literacy that address linguistic, cultural, and ability-related diversity- Interdisciplinary perspectives connecting education with law, data science, psychology, and the social sciences- Communities of practice and collaborative models for building AI literacy capacity at scaleWe encourage methodological diversity - design-based research, mixed methods, learning analytics, policy analysis, and participatory or co-design approaches. Work grounded in real institutional contexts, cross-university collaboration, or comparative international research is especially valued.This Research Topic does not seek broad overviews of AI adoption in higher education, nor descriptive surveys of student or faculty attitudes toward AI tools. We welcome contributions that go beyond documenting what is happening to analyse how and why policy translates - or fails to translate - into practice, and what role critical AI literacy plays in that process.By bringing together these perspectives, this Research Topic aims to offer an evidence base that helps universities navigate AI transformation not as a technical upgrade, but as an institutional and pedagogical undertaking grounded in equity, responsibility, and critical engagement. Topic editors: Mari Mar Boillos, Miquel Pérez Torres, AIORA SAMPEDRO ALEGRIA, Dorleta APAOLAZA-LLORENTE Source: https://www.frontiersin.org/research-topics/78674/inclusive-and-critical-ai-literacy-in-higher-education-from-policy-agendas-to-transformative-practice