The impact of Large Language Models on knowledge contextualization and competency development among knowledge workers

This thesis explores the impact of large language models (LLMs) on the development of skills and competencies among knowledge workers. The study employs qualitative research, with semi-structured interviews with junior consultants serving as the primary data collection method. The goal of the interviews is to identify key work activities and responsibilities of the consultants studied, as well as the ways in which LLMs are utilized in carrying out these activities. Based on the results of the interviews and using a theoretical skill acquisition model, the manner in which LLMs enable higher levels of expertise is analyzed. This is explained by the fact that achieving higher levels of expertise requires extensive experience with real-world situations, in which LLMs can assist by providing personalized and relevant information. The work benefits knowledge workers, educational institutions, and human resources managers by offering practical ways to use LLMs in practice and a theoretical basis for understanding the impact of LLMs on the skill acquisition process.