Metacognitive AI literacy: going beyond the AI skills gap agenda

While use of artificial intelligence (AI) proliferates across educational, professional, and civic domains, conventional AI literacy frameworks remain anchored in functional skills acquisition and fail to address the fundamental epistemological challenges posed by probabilistic, opaque algorithmic systems. This article argues that AI literacy must be reconceptualised as a metacognitive social practice that transcends individual competencies to encompass collective capacity for critical engagement with AI design, deployment, and governance. We examine how the probabilistic nature and epistemic opacity of contemporary AI systems – particularly large language models – render traditional rule-based digital literacy paradigms obsolete. Drawing on case studies from higher education institutions and the Nordic financial sector, we illustrate how participatory co-design processes and experimental pedagogical spaces can cultivate metacognitive awareness and democratic agency in AI-mediated environments. Our analysis reveals that efficacious AI literacy development requires institutional transformation: universities must evolve beyond skills transmission to become sites of collective intelligence where learners interrogate algorithmic power structures and mobilise alternative AI futures. Framing AI literacy as a critical social practice positions higher education as essential infrastructure for civic resilience, demanding fundamental reconfiguration of university missions, governance structures, and pedagogical approaches to anchor AI literacy as a public good rather than a private asset.