# Goal Gap

This Perspective argues that generative AI should not be understood as just another teaching tool for efficiency and personalization, but as an active, persistent, generalist, and increasingly autonomous cognitive artefact and 'epistemic infrastructure' that restructures schools' cognitive ecologies by redistributing epistemic labour and consolidating feedback, assessment, explanation, content generation, and tutoring within a single interface; on this basis the authors identify two enduring misalignments, a pedagogical gap between learning sciences and AI design and a goal gap between measurable performance and developmental aims, both reflecting logics of efficiency, standardization, and control already embedded in existing educational systems, which GenAI does not introduce but risks en

This Perspective argues that generative AI should not be understood as just another teaching tool for efficiency and personalization, but as an active, persistent, generalist, and increasingly autonomous cognitive artefact and 'epistemic infrastructure' that restructures schools' cognitive ecologies by redistributing epistemic labour and consolidating feedback, assessment, explanation, content generation, and tutoring within a single interface; on this basis the authors identify two enduring misalignments, a pedagogical gap between learning sciences and AI design and a goal gap between measurable performance and developmental aims, both reflecting logics of efficiency, standardization, and control already embedded in existing educational systems, which GenAI does not introduce but risks en