The AI Turn in Higher Education: From Labour Market to Employment Challenges

Abstract

In the contemporary educational landscape, Artificial Intelligence (AI) emerges as both a catalyst for innovation and a potential source of inequality (Boriati e D’Ambrosio, 2025). This study investigates the relationship between the use of AI tools and the processes of studying, writing, and producing knowledge among university students. Grounded in a socio-educational framework, the research aims to explore whether AI functions as an inclusive technology that democratises access to learning, or whether it reinforces existing educational divides and social inequalities (Warschauer, 2004; Couldry e Mejias, 2019; van Dijk, 2020). These perspectives enable a multidimensional understanding of how AI uses intersect with cultural capital, digital competence, and educational-labour opportunity (Archer, 2007; Livingstone, 2009). Preliminary reflections suggest that the integration of AI in education cannot be understood merely in technological terms but must be situated within institutional and social contexts that either promote or limit inclusion. The capacity of AI to enhance learning depends on students’ access to resources, institutional support, and the development of critical digital literacies (DigComp 3.0). Universities and schools are thus called to act not only as sites of technological adoption but also as spaces for the social negotiation of digital responsibility and epistemic justice (Facer e Selwyn, 2021). In conclusion, AI should be viewed not merely as a neutral tool but as a social artifact embedded in power relations (Foucault, 1980; Castells, 1996; Feenberg, 1999), capable of both expanding and constraining educational inclusion. The challenge for educators and policymakers lies in transforming AI from a potential driver of inequality into an instrument of democratic learning and social empowerment.