In project-based organizations, the effective management of knowledge is critical to supporting timely decision-making, sustaining innovation, and minimizing inefficiencies. However, traditional Knowledge Management (KM) systems often struggle to address the complexity, fragmentation, and dynamic pace of project environments. At the same time, Artificial Intelligence (AI) offers promising capabilities for enhancing knowledge processes, yet current applications often lack transparency, contextual understanding, and seamless integration into decision-making workflows. This thesis presents a conceptual framework for an AI-enhanced Decision Support System (DSS) tailored to the needs of knowledge management in project environments. Developed using the Design Science Research (DSR) methodology, the framework combines foundational DSS architecture with modern AI technologies, including machine learning, natural language processing, and semantic reasoning.