Exploring the Role of Generative AI in Knowledge Sharing and Innovation: A Study of Norwegian Organizations

Abstract

Generative artificial intelligence (GenAI) is increasingly used in knowledge-intensive work, yet empirical evidence remains limited on how it influences organizational knowledge processes and innovation. Although the rapid diffusion of GenAI technologies has attracted significant attention from researchers and practitioners, there is still a limited understanding of how these tools are integrated into everyday knowledge work and how they contribute to the generation and implementation of innovative ideas. This study examines how knowledge workers in Norwegian organizations use GenAI, the factors that encourage or constrain adoption, and the influence of leadership and organizational culture on its effective use. An exploratory qualitative study was conducted through ten semi-structured interviews with knowledge workers from public- and private-sector organizations. Participants represented a variety of professional roles and organizational contexts, providing insights into both individual and organizational experiences with GenAI. The interview data were analyzed thematically to identify recurring patterns related to knowledge activities, innovation processes, and organizational conditions. The findings show that GenAI supports innovation by facilitating knowledge discovery, synthesis, translation, recombination, idea generation, and concept development. Participants associated its use with faster access to information, accelerated learning, improved problem-solving, and broader exploration of alternatives. Many described GenAI as a valuable cognitive support tool that enhanced creativity and enabled more efficient knowledge sharing across teams. However, they also raised concerns about inaccurate outputs, weak source traceability, privacy, cybersecurity, and excessive reliance on AI-generated content. Additional concerns related to the potential erosion of critical thinking skills and professional expertise if human judgment is not actively maintained. Trust, employee autonomy, and supportive leadership encouraged experimentation, while GDPR compliance, transparency, and professional accountability shaped responsible use. The study conceptualizes GenAI as a conditional knowledge-integration mechanism whose contribution to innovation depends on human validation, organizational learning, and responsible governance. The findings contribute to knowledge management and innovation research by highlighting the organizational capabilities required to harness GenAI while mitigating associated risks