This article explores the transformative impact of artificial intelligence on enterprise knowledge management systems. AI-enhanced knowledge management (KM) systems are revolutionizing how organizations capture, organize, access, and leverage their collective intelligence assets. Traditional KM systems have long struggled with information silos, manual curation bottlenecks, and inefficient search capabilities, resulting in significant productivity losses. AI technologies, including natural language processing, machine learning, and generative AI, address these challenges by enabling intelligent automation, enhanced discovery, and dynamic knowledge representation. The article examines core AI technologies powering modern KM systems, including semantic analysis, entity recognition, clustering algorithms, recommendation systems, and content generation capabilities. It further explores architectural components such as vector databases, retrieval-augmented generation frameworks, and multimodal processing capabilities that form the foundation of effective AI-enhanced knowledge systems. Implementation considerations, including data quality governance, enterprise system integration, and change management strategies, are discussed in detail. Through comprehensive examination of research across multiple domains, this article provides a holistic overview of how AI-enhanced knowledge management systems are fundamentally transforming organizational intelligence capabilities and delivering substantial competitive advantages in today's data-driven business landscape.