<![CDATA[The impact of AI on language testing has sparked a major upheaval in education thanks to advances in technology and the need for better testing efficiency. The objective of this review is to study and evaluate what is happening at present, what are the big challenges and where there are opportunities in AI-powered language assessment. The research systematically examines existing studies by employing the PRISMA framework, carrying out an extensive search through academic databases to locate, evaluate, and interpret peer-reviewed articles concerning AI in language assessment. It uses qualitative thematic analysis to integrate key patterns, obstacles, and future prospects. While AI has given us new methods for evaluating languages, problems related to bias, maintaining data privacy, and the importance of human role are still major issues. By covering many aspects, the review gives insights into the developing AI in language testing. It draws attention to how AI may improve accuracy, save time and allow for more assessment on condition that certain difficulties are addressed. According to the study, it is essential to put in a balance between using technology and relying on people for language assessment. By proposing recommendations for future research and practical applications, this review provides actionable insights for educators, policymakers, and developers to make informed decisions about integrating AI into language assessment. It emphasizes the importance of designing equitable, transparent, and pedagogically sound AI systems, thereby shaping the responsible and effective use of AI in educational contexts.]]>
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