This conceptual paper aims to examine the rapid adoption of generative AI in public education, arguing that current “readiness” frameworks can mask a transfer of authority from public institutions to private platform firms. It provides a structural framework for understanding digital enclosure, coloniality and educational sovereignty in AI-mediated educational settings.
The paper synthesizes decolonial theory with work on digital enclosure, platform infrastructure, surveillance capitalism, epistemic justice and educational technology. It introduces the “four lanes of coloniality” as a framework for analyzing institutional dependency under vendor-controlled AI adoption.
The paper identifies four lanes through which platform power enters education: infrastructure, classification, epistemology and labor. These lanes operate through vendor dependency, automated surveillance, linguistic bias, epistemic gatekeeping and uncompensated repair labor.
This is a conceptual paper focused on closed-weight, cloud-hosted, vendor-controlled AI systems. Empirical studies should test the framework across different institutions, governance models and AI arrangements.
The paper outlines a minimum sovereignty agenda for institutions adopting AI. This includes stronger procurement rules, audit rights, visible system changes, usable data access, appeal processes, recognition of repair labor and meaningful participation by educators and students.
Reclaiming educational sovereignty is presented as essential for maintaining education as a public good and preventing public learning from becoming a resource frontier for private capital.
By framing AI adoption as a governance and coloniality problem rather than a mere pedagogical shift, the paper offers a four-lane framework and a practical diagnostic for institutional reflection and action.
