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Abstract
Generative Artificial Intelligence (GenAI) has revolutionized knowledge management, offering unprecedented capabilities for creating, proofing, summarizing, and evaluating documentation. This paper explores how AI, particularly large language models (LLMs), and Retrieval Augmented Generation (RAG) systems, can streamline the development of knowledge articles while addressing ethical concerns such as data ownership and bias. We examine practical applications, including real-time collaboration, multilingual support, personalized information retrieval, and automated knowledge forecasting. Additionally, we explore AI’s role in bridging legacy systems, reducing biases, and enhancing decision-making. Ultimately, AI extends beyond generating content, shaping a more efficient, inclusive, and innovative approach to knowledge management. This article is based upon a presentation given at the 2024 NISO Plus Conference that was held in Baltimore, MD, USA, February 13–14, 2024.
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