Adaptive and intelligent instructional systems are used to deal with the issue of learning personalisation in contexts where human instructors are not immediately available, so their role is transferred entirely or in part onto the computer. Even though such systems are mostly developed for well-defined domains that have a rather straightforward acquisition order, such as mathematics or computer programming, they found their application in ill-defined domains as well. Natural language learning is one such domain, and developing adaptive instructional systems for this specific purpose is notoriously complex and challenging due to the nature of language systems. The paper at hand examines the theoretical background of adaptivity and intelligence in instructional systems, and discusses their application in learning and teaching of natural languages. Moreover, the paper reviews adaptive and intelligent language learning systems in existence and identifies their characteristics in a systematic manner. The discussion section offers a more detailed view of selected systems for language learning that exhibit interesting and innovative implementation solutions. The paper concludes by suggesting possible developmental directions and future work in the field.