A Organização do Conhecimento na Era da Inteligência Artificial

The intersection between Artificial Intelligence (AI) and Knowledge Organization (KO) has led to a reconfiguration of information systems, promoting more dynamic and adaptive approaches to knowledge management. Using a bibliometric approach, this study analyzes the scientific evolution of this field, mapping emerging trends, challenges and opportunities. OC, traditionally based on static categorization models, has been widely impacted by AI, especially by machine Knowledge Organization (KO) faces unprecedented epistemological and methodological challenges in light of the rise of Artificial Intelligence (AI), particularly machine learning, which has been reshaping practices of classification, indexing, and information retrieval. This study addresses the question: how is AI transforming the foundations, methods, and roles attributed to KO? The objective is to understand the impacts of this convergence and to identify trends that may guide the adaptation of the field to new technological realities. To this end, a systematic literature review and a bibliometric analysis were conducted, based on the Web of Science and Scopus databases. The methodology applied explicit inclusion and exclusion criteria, metadata extraction, and the use of bibliometric indicators of production, co-authorship, co-citation, and co-occurrence of terms. This approach enabled the articulation of both quantitative and qualitative results, evidencing the evolution of research in the field. The findings reveal an exponential growth of publications since 2018, particularly concentrated in Europe, Asia, and North America, with an emphasis on interdisciplinary collaboration networks. Four emerging research axes were identified: the epistemology of KO and AI; hybrid methodologies of knowledge representation; ethical challenges of automation; and implications for professional training. It is concluded that the integration of AI into KO is not merely an instrumental shift but rather a paradigmatic reconfiguration that requires new theoretical and practical frameworks. This study contributes to broadening the critical understanding of this phenomenon and provides a basis for future research in methodological consolidation and ethical governance of KO in the age of AI.