Introduction. This paper discusses the transformation of the two concepts – ‘knowledge’ and ‘learning’ in the context of the development of artificial intelligence technologies. The author states that these terms, which have a deep etymology, have become central in the discourse of artificial intelligence and have defined machine methods of information processing. The purpose of the study is to analyze the evolution of the meanings of the words ‘knowledge’ and ‘learning’, as well as their derivatives during the transition from different terminological systems to specialized AI terminology. Research materials and methods include etymological and component analysis of vocabulary to identify both the historical meanings of words and their modern semantics in the field of artificial intelligence. The results of the study demonstrate how the basic concepts of ‘cognition’ and ‘following the path of knowledge’ were able to transform from the sphere of philosophy into the field of information technology. For example, terms with the ‘knowledge’ component (knowledge-based AI) have evolved to describe structured data and formalized models, while terms with the ‘learning’ component (machine learning, unsupervised learning) have come to denote algorithmic processes for identifying patterns. The analysis showed a steady semantic shift: in the field of artificial intelligence, the term ‘knowledge’ is associated with the organization of data, and ‘learning’ with the methods of their processing, which does not always correspond to the humanitarian understanding of these concepts. In conclusion, the author states that the terms ‘knowledge’ and ‘learning’ have become an integral part of the AI terminology system, accurately reflecting the key processes that occur in this field of knowledge. The study confirms a significant semantic gap between the two meanings of these words, which opens up prospects for further linguistic and terminological analysis of the developing high-tech language.