The Impact of Artificial Intelligence on Knowledge Management

Sammanfattning

This thesis explores how Artificial Intelligence (AI) can be integrated into organizational Knowledge Management (KM) systems. AI is increasingly changing how knowledge is created, shared, interpreted, and applied within organizations. While traditional KM approaches have focused on storing, transferring, and codifying knowledge, they provide limited guidance for how organizations should integrate AI into knowledge work. This creates a need for a structured approach that considers not only technological capabilities, but also human-AI collaboration, cognitive processes, and the changing role of knowledge workers. The aim of this thesis is to design a conceptual framework that supports the integration of AI into organizational KM systems. The main research question guiding the study is: How can a conceptual framework be designed to support the integration of Artificial Intelligence into organizational Knowledge Management systems? To answer this question, the thesis follows a Design Science Research (DSR) approach. A literature review was conducted to identify the research problem, define the objectives of the artifact, and support the design and development of the framework. The proposed framework is based on the Three Horizons framework and structured around four analytical dimensions: capabilities, human-AI collaboration, cognitive processes, and the changing role of knowledge workers. The artifact was evaluated through an interview-based survey with six participants representing different professional backgrounds. The interview data were analyzed using deductive thematic analysis based on predefined evaluation criteria derived from the artifact objectives and analytical dimensions. The result of the thesis is a conceptual framework that helps organizations understand and structure AI integration into KM systems across three horizons. The evaluation showed that participants perceived the framework as clear, relevant, and useful for explaining AI integration in organizational KM. The findings indicate that the framework supports organizational AI capabilities, captures the evolving relationship between human expertise and intelligent systems, addresses cognitive processes related to AI-supported knowledge work, and reflects the changing role of knowledge workers. At the same time, the evaluation identified areas for improvement, particularly the need for clearer implementation guidance, practical examples, and activities for moving between horizons. The thesis contributes a theoretically grounded and practically oriented framework for understanding AI integration into KM systems. It suggests that organizations should not approach AI integration only as a technical issue, but should also consider governance, employee training, critical evaluation, human responsibility, and the development of AI-related knowledge practices. The study is limited by its conceptual scope, the small number of interview participants, and the fact that the framework was evaluated through expert feedback rather than real-world implementation. Future research could apply the framework in organizational case studies, evaluate it across different industries, and further develop practical tools for assessing movement between the three horizons.