| Sumario: | Background: Generative AI (GenAI) offers scalable feedback and planning support, yet rigorous evidence on how AI‐supported instruction shapes EFL learners' self‐regulated strategies and achievement remains limited. Objectives: The main objectives are to test whether a feedback‐oriented GenAI integration improves (a) cognitive, metacognitive, and resource‐management strategies and (b) English achievement in university EFL coursework. Methods: Ten intact classes of undergraduates (N = 310) at Allameh Tabataba'i University were randomised at the class level to an AI condition (n = 139) or control (n = 171). The AI group completed a 6‐h AI‐literacy workshop and 12 weeks of guided practice using ChatGPT, Poe, and Bard within a draft‐first → AI critique → human evaluation workflow; the control group received the same curriculum without AI. Outcomes included adapted SILL subscales (cognitive, metacognitive, and resource management) and a researcher‐developed achievement composite (comprising reading, vocabulary, and writing). A MANCOVA with pretests as covariates, followed by prespecified ANCOVAs, reported adjusted means with 95% CIs and accounted for class‐level clustering. Qualitative data comprised 834 biweekly reflective journals, which were thematically analysed using double coding (Cohen's κ = 0.88). Results: The AI group outperformed the control across all four outcomes; a MANCOVA indicated a significant multivariate effect, with follow‐up ANCOVAs showing partial η2 values of approximately 0.16–0.22. The journals illuminated mechanisms—planning/monitoring, time efficiency, confidence, and calibrated help‐seeking—and flagged the risks of cognitive offloading without explicit guardrails. Conclusions: When embedded in coherent pedagogy and supported by AI literacy, feedback‐oriented GenAI can strengthen the use of self‐regulated strategies and improve language achievement in university EFL contexts. Implementation should include clear usage norms and reflective monitoring to sustain learning quality. Practitioner Notes: What is already known about this topic: ○Self‐regulated learning strategies (cognitive, metacognitive and resource management) are essential for successful second language acquisition.○AI‐powered tools like ChatGPT are increasingly used in language learning, but empirical research on their pedagogical effects is limited.○EFL learners often struggle with applying strategies consistently without structured support.What this paper adds: ○Provides empirical evidence that AI tools significantly improve the use of self‐regulated learning strategies among EFL learners.○Demonstrates that AI‐mediated instruction leads to measurable gains in English language achievement○Offers a structured model of integrating AI tools in language courses with clear training protocols○Identifies learner perceptions of AI as a scaffold for autonomy, confidence, and time management.Implications for practice and/or policy: ○Teachers should be trained to embed AI tools purposefully within language learning tasks to support strategic engagement.○AI‐based interventions can complement traditional instruction and support individualised learning.○Institutions should consider policy frameworks for ethical and pedagogically sound use of generative AI in EFL education.○Further research and teacher development are needed to maximise the benefits of AI while mitigating risks such as overreliance or misinformation.
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