<![CDATA[The rising role of artificial intelligence (AI) tools in assisting and improving autonomous/self-directed English language learning (ELL) is examined in this thorough narrative overview. Although self-study provides flexibility, it has always suffered from a severe lack of timely, tailored feedback. This paper discusses how autonomous learners use AI interventions, such as conversational agents, adaptive learning systems, and natural language processing (NLP) tools, and how this affects language acquisition outcomes. A thematic analytic technique was used to synthesize literature from major academic databases (Scopus, WoS, ERIC) from 2015 to the present, with an emphasis on instructional implications, impact on learner motivation, and efficacy across skills. The results show that AI technologies work well as a virtual scaffold, offering the framework and tailored, nonjudgmental feedback required for self-regulation. In particular, speech recognition technologies increase speaking confidence and pronunciation correctness by facilitating frequent, low-anxiety practice, while AI-driven feedback systems greatly improve writing accuracy by decreasing mechanical errors. Additionally, the paper shows that AI overcomes the conventional constraints of self-study by providing learners with objective data to identify flaws and monitor progress. The review finds that AI is a revolutionary agent that fills the structural holes in independent ELL, but it warns that learners must emphasize deep learning-promoting tools above passive task fulfilment in order to employ AI effectively.]]>
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