This study presents a new paradigm in the integration of digital knowledge management systems with artificial intelligence (AI). AI’s contributions to knowledge acquisition, sharing, analysis, and decision-making processes play a critical role in enhancing organizational competitiveness, learning capacity, and sustainable growth. The study explores knowledge management systems through techno-centric and non-techno-centric perspectives, elaborating on how AI-supported applications such as machine learning, artificial neural networks, predictive systems, content mining, expert systems, and intelligent automation are integrated into the knowledge cycle. Moreover, ethical challenges posed by AI—including cognitive transformation, algorithmic bias, data privacy, and anti-human automation—are also addressed. The role of machine learning-based systems in decision-making, their contribution to organizational learning, and their capacity to enhance user experience are emphasized. Knowledge management is approached not merely as a technical system but as a multidimensional structure that must also be supported by human-centered, cultural, and ethical frameworks. In this context, the study aims to outline a roadmap for sustainable and ethical digital transformation at the intersection of knowledge systems and AI.