Research on AI in education often remains anthropocentric, separating humans ‘us’ (the knowing and agentive actants) from AI/technology ‘it’ (the object, the liability, or output). This framing simplifies the complexity of human-AI intra-actions and shapes how we understand what it means to be ‘critical’ with AI. Adopting a posthumanist perspective (Barad, 2007; Jones; 2025), this paper rethinks criticality as part of our AI-mediated language learning.

This study draws on a novel digital enthnographic method using multimodal digital portraits with 50 Chinese, Thai and Dutch university students. Using elicitation prompts and follow-up interviews, these digital portraits trace how learners feel, understand and make sense of their intra-actions with AI. Data were analysed through iterative, reflexive coding informed by posthumanist theory, attending to affective, embodied, and discursive dimensions of human–AI intra-actions.

Findings positions criticality in AI intra-actions as the ways in which language learners reconfigure and reshape relations; what happens when learners and AI together reshape the boundaries of what counts as knowing, learning and understanding. For educators, this work reframes critical engagement with AI as an emergent, embodied practice and offers the digital portrait as a pedagogical space for exploring how learners make sense of AI in language learning contexts.