Impact of Work Experience on the Use of Generative AI for Knowledge Management

The emergence of the latest generations of generative artificial intelligence (GenAI) systems, particularly ChatGPT, has prompted knowledge management (KM) scholars to investigate how these tools can be effectively integrated into organizational KM systems. However, as this field of study is in its infancy, the literature remains scarce and provides fragmented results. Empirical evidence is especially limited, and numerous research questions awaiting answers. One such question is how work experience influences the use of AI in new knowledge creation. To address this issue, this paper examines how and for what purpose GenAI is employed to support the creation of new knowledge, specifically focusing on how its use differs according to users' seniority levels. The hypothesis is that work experience, which shapes users' knowledge pools, affects how they utilize GenAI to support knowledge creation. Past empirical research highlighted that there are differences in AI usage between more and less experienced workers. Given the exploratory nature of the study, we employed a qualitative research method, conducting interviews with 22 software engineers from various companies who use GenAI systems in their daily activities. We choose software engineers as they are knowledge workers and are currently among the early adopters of GenAI systems. Based on a common guideline developed from knowledge creation processes, the interviews were conducted online and in person between July and November 2024. Each interview was recorded, transcribed and translated into English for analysis. Empirical research shows differences between more and less experienced workers, particularly with respect to the complexity of the tasks performed and the type of knowledge created with GenAI support. The study’s results contribute to our understanding of GenAI’s impact on KM and offer managerial insights for introducing and using the new technology within business contexts.