Exploring the Relationship between AI Competency and Professional Identity in Language Education: A Mixed-methods Study

The integration of artifi cial intelligence (AI) in education is increasingly prevalent; however, the implications of AI competency forprofessional identity remain underexplored. Building on Sociocultural Theory and Possible Selves Theory, this convergent mixed-methods study examines the relationship between AI competency and instructor characteristics with professional identity among 111Turkish EFL instructors. Validated scales measuring AI competency and professional identity were administered alongside semi-structured interviews with 12 participants. Quantitative analyses revealed that AI competency signifi cantly predicts professionalidentity (β = .295, p = .002). Prior AI exposure markedly diff erentiated competency levels, while age and teaching experience had nosignifi cant eff ect. Qualitative fi ndings identifi ed three identity trajectories (strengthening, neutrality, and questioning) shaped by beliefs,emotions, institutional support, and instructional experience. We propose a novel interpretive mapping of these trajectories onto thehoped-for, expected, and feared dimensions of professional self-representation, off ering a theoretically parsimonious lens forunderstanding why instructors with equivalent AI competency levels exhibit divergent identity responses. The study highlights theimportance of professional development that goes beyond technical training to include guided, refl ective, and emotionally resonantexploration connecting AI skills with pedagogical values and ethical awareness.