Learning how to do AI: managing organizational boundaries in an intergovernmental learning forum

This analysis applies boundary theory to public manager efforts to overcome AI capacity gaps through a public sector collaborative learning forum. Administrative and interview data identify the types of knowledge managers are able to access, the types of organizational differences that influence learning, and the strategies public managers use to overcome them. Analysis suggests that unstructured learning fora are better suited to the transfer of tacit procedural knowledge than declarative knowledge about AI, and emphasizes the importance of social trust and network structure to overcome knowledge gaps through peer learning.