The request for AI education in schools has led to basic programming classes, robotics clubs and technology courses as the main responses. These methods show good intentions, yet they confuse learning about AI technology with actual AI literacy. The paper establishes that AI literacy exists beyond being a subject and digital tools and computer science departments cannot handle its implementation. The capability exists as a cross-disciplinary learning skill which helps students understand AI systems while questioning them and working with them in academic and social and civic environments. The paper defines AI literacy through four essential domains: (a) Critical AI Reasoning for understanding AI system classification, prediction and information generation processes; (b) Digital Ethics and Data Agency for handling consent, privacy issues, surveillance and bias problems; (c) Human–AI Collaboration for determining AI usage, intervention points and effective teamwork with AI systems; and (d) Applied AI Across the Curriculum for teaching AI throughout languages, arts, sciences, humanities and vocational subjects, instead of treating it as a standalone technical subject. The paper provides classroom examples, teacher-ready implementation ideas, and a K–12 progression model that moves from AI awareness in early years to critical and creative collaboration in upper secondary. Instead of asking schools to produce AI engineers, the model prepares students to become informed, responsible participants in AI-shaped societies. The conclusion offers concrete steps for school leaders and teacher teams who need to act now, without waiting for perfect infrastructure or specialist staff.
Constantine Andoniou (Wed,) studied this question.