Notwithstanding the increase in research on artificial intelligence-infused English language learning, several issues remain inadequately addressed. Thus, this paper provides a systematic review and analyzes previous studies to pinpoint fruitful knowledge gaps and outline approaches for future research directions. Two approaches, bibliometric and descriptive content analysis, were employed in this study. Firstly, we extracted data for bibliometric analysis from the Scopus database, covering publications from 1996 to 2024. The findings show that the topic peaked in 2024, with 107 articles published. China was the most cited country, with 1.215 citations, and the most productive country, with 327 articles. The International Journal of Emerging Technologies in Learning published the majority of the articles. The research theme evolved to emphasize English learning and student involvement through mobile learning. We applied descriptive content analysis to selected papers published between 2014 and 2024. Theoretically, the findings suggest that addressing knowledge gaps can enhance the integration of artificial intelligence in English language learning. Empirically, the mixed studies used descriptive statistics collected through observation and questionnaires, with a medium sample size selected through random sampling, a commonly used research design. These approaches can potentially expand the scholarly literature on this subject.