The increasing digital information during the past few decades has radically altered the physical look of knowledge organisation of libraries and the information centres. Traditional classification systems such as the Dewey Decimal Classification (DDC), Universal Decimal Classification (UDC) and Library of Congress Classification (LCC) provided the organised structures upon which printed materials may be ordered in the past. Nevertheless, the rapid growth of electronic resources, including electronic books, online journals, institutional repositories, and multimedia resources has created major issues in the useful and scalable classification systems. The manual systems of classification that highly rely on human knowledge are no longer appropriate in handling volume, complexity and dynamism of the digital information. In these ways, Artificial Intelligence (AI) has become one of the new technological solutions of the new generation that enables automated classification of information resources. Machine learning, natural language processing, deep learning, and text mining are some of the AI technologies that assist with the analysis of written resources and automatically and efficiency assign writing subjects to particular categories and with a high level of reliability. The analysed paper provides a detailed analysis of the AI-based automatic classification in the Knowledge Organization Systems (KOS). It talks about the evolution of classical classification systems and introducing AI technologies, and the principles of automatic classification. The paper also measures the advantages, problems, and future of AI in library science, in terms of the evolving role of the librarians in the automated world. The research is qualitative in nature since it is founded on literature review, conceptual analysis and case-based observations.