<p>The integration of AI into education is often framed as a neutral or beneficial response to pressures of efficiency, scalability, and personalisation. In this paper, I challenge that framing by examining how educational AI reshapes teaching as a form of labour. Drawing on Karl Marx’s theory of alienation, I offer a conceptual analysis of how AI mediated systems reorganise pedagogical work in ways that risk estranging teachers from the products of their labour, the labour process itself, their species being, and their relationships with students and colleagues. Rather than treating AI in education as a monolithic phenomenon, I differentiate between generative tools, automated assessment, learning analytics, and administrative systems, showing how each participates differently in processes of standardisation, surveillance, and managerial control. I situate educational AI within wider dynamics of platform capitalism, datafication, and audit culture, arguing that alienation is not an inevitable outcome of technology but a contingent effect of ownership structures, governance arrangements, and institutional imperatives. I conclude by outlining policy, design, and philosophical interventions aimed at reducing alienation, while acknowledging the limits of reform within marketised education systems. In doing so, I reframe AI in education as a political and ethical question about labour, authority, and the purpose of teaching, rather than a purely technical innovation.</p>