This study provides a systematic review of the use of AI in English language teaching and learning (ELT/L), identifying both the affordances and challenges. A total of 42 studies were analyzed using PRISMA principles, revealing trends in geographical locations, learner ages, and years of study. Grounded coding was used to identify the affordances of AI in ELT/L in areas such as speaking, writing, reading, pedagogy, and self-regulation. Challenges identified include technology breakdowns, limited capabilities, fear, and standardizing language. The findings highlight the increasing use of AI in ELT/L, with a majority of studies conducted in Asia, particularly in China, Taiwan, and Japan. The number of studies has increased significantly over the past decade, with a sharp rise in 2020 and 2021. Most studies focused on higher education, with fewer studies involving K-12 and adult learners. AI is being used in ELT/L for various purposes, including pronunciation practice, grammar checking, vocabulary learning, and self-regulation. The study also identified axial codes for AI use in ELT/L, including subskills, pedagogies, and technologies. Challenges include technical issues, limited AI capabilities, and the potential for over-reliance on AI. The study provides practical implications for educators, policymakers, and researchers, emphasizing the need for further research into AI's role in ELT/L.This study provides a systematic review of the use of AI in English language teaching and learning (ELT/L), identifying both the affordances and challenges. A total of 42 studies were analyzed using PRISMA principles, revealing trends in geographical locations, learner ages, and years of study. Grounded coding was used to identify the affordances of AI in ELT/L in areas such as speaking, writing, reading, pedagogy, and self-regulation. Challenges identified include technology breakdowns, limited capabilities, fear, and standardizing language. The findings highlight the increasing use of AI in ELT/L, with a majority of studies conducted in Asia, particularly in China, Taiwan, and Japan. The number of studies has increased significantly over the past decade, with a sharp rise in 2020 and 2021. Most studies focused on higher education, with fewer studies involving K-12 and adult learners. AI is being used in ELT/L for various purposes, including pronunciation practice, grammar checking, vocabulary learning, and self-regulation. The study also identified axial codes for AI use in ELT/L, including subskills, pedagogies, and technologies. Challenges include technical issues, limited AI capabilities, and the potential for over-reliance on AI. The study provides practical implications for educators, policymakers, and researchers, emphasizing the need for further research into AI's role in ELT/L.