GenAI and the purposes of education: educators’ perceptions through Biesta’s model of qualification, socialisation, and subjectification

The integration of generative artificial intelligence into education calls for rethinking how knowledge is produced and taught in increasingly algorithmic environments. Using Biesta’s framework of qualification, socialisation, and subjectification, this study offers an epistemological reading of educators’ perceptions in higher and adult education. We analyse 115 open-ended survey responses from Italy (65) and the UK (50) collected within the ASEM Hub (RN3) initiative. Across both contexts, early adoption concentrates on qualification, while effects related to socialisation and subjectification are rarer and more ambivalent. UK respondents – supported by institutional guidance and training – show greater confidence but also concern for integrity and workload. Italian participants highlight fragmented support, ethical caution, and risks to professional agency and students’ independent judgement. Meaningful GenAI integration requires rituals of verification – traceability, evidence, and public justifiability – that preserve disciplinary norms and learners’ ownership of judgement. The study situates efficiency gains within a broader educational responsibility: ensuring AI-assisted work remains accountable to communities of inquiry and sustains, rather than displaces, socialisation and subjectification.