Abstract
<jats:p>This chapter examines how large language models are reshaping business process management from process documentation to intelligent decision support. It shows that the relevance of LLMs in BPM lies not only in text generation but also in their ability to connect dispersed procedural knowledge, formal process representations, analytical interpretation, and managerial judgment. The chapter adopts a continuum-based perspective covering process documentation, process analysis, execution support, and decision support. It argues that LLMs can help formalize fragmented process knowledge, interpret textual evidence on bottlenecks and deviations, support users during process execution, and improve decision preparation through contextualized explanations and recommendations. At the same time, their contribution remains dependent on contextual grounding, data quality, governance mechanisms, and human oversight. The chapter concludes that the future of BPM will likely rely on hybrid sociotechnical arrangements in which LLMs augment rather than replace human actors.</jats:p>