Artificial intelligence has moved from a specialist concern to an everyday feature of organisational work. As generative and decision-support systems become embedded in routine tasks, the ability of employees to understand, critically evaluate, and responsibly use these systems, commonly referred to as AI literacy, has become a decisive factor for whether such technologies create value or introduce risk.

Yet it remains largely unclear which mechanisms are effective in fostering AI literacy, and how they can be deliberately designed and deployed. Interventions such as training formats, learning-by-doing approaches, organisational support structures, and interface-level guidance are discussed in scattered strands of research, but their underlying mechanisms and relative effectiveness have not been systematically brought together. A structured investigation is therefore needed to clarify how AI literacy can be meaningfully promoted.

The goal of this thesis is to investigate the mechanisms through which AI literacy can be fostered in organisational settings. Existing research will first be reviewed to clarify how AI literacy is conceptualised and which mechanisms have been proposed or examined for developing it. On this basis, these mechanisms will be structured and compared, common themes and conceptual differences will be identified, and the conditions under which particular mechanisms appear effective will be examined.

Building on this analysis, the findings will be synthesised into an overview of the current state of research, and the identified mechanisms will be assessed with respect to their design and applicability. Depending on the chosen focus, the thesis may complement this analysis with an empirical component, for example expert interviews, a survey, or the design and evaluation of a concrete intervention. The thesis thereby aims to identify both the potential and the limitations of current approaches and to discuss directions for advancing the fostering of AI literacy.

If you are interested, please send your current transcript of records together with a brief statement of motivation.