Generative AI as a Conditional Job Resource: Examining ELT Teacher Well-being and Critical AI Literacy through the JD-R Model

Abstract

The English Language Teaching (ELT) profession faces a systemic crisis of well-being characterized by high rates of burnout and administrative intensification. While Generative AI (GenAI) offers the technological affordance to automate monotonous tasks and alleviate these pressures, its integration into the teacher's workflow presents a complex psychological paradox. Grounded in the Job Demands-Resources (JD-R) Theory, this qualitative phenomenological study investigates the lived experiences of 16 ELT professionals across diverse institutional contexts in Turkey. The findings reveal that GenAI functions not as a static benefit but as a Conditional Job Resource; its capacity to enhance well-being is contingent upon the teacher’s Critical AI Literacy (CAIL). The analysis uncovers an efficiency paradox, where the reduction of manual labor often leads to a treadmill effect of work intensification rather than psychological recovery. Furthermore, the integration of GenAI instigates a fundamental shift in professional identity from creator to curator, introducing a new cognitive Verification Burden. The study distinguishes between high-agency Architects, who utilize CAIL to maintain pedagogical sovereignty, and Imposters, who experience efficiency as a threat to their competence. The research concludes that for GenAI to serve as a sustainable resource for well-being, the profession must cultivate human-in-the-loop competencies that empower teachers to navigate the boundary between automation and agency.