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Business process agility remains an intriguing issue for business process management (BPM) when it comes to modeling human-centric processes. Several attempts were made from academia to find alternative approaches, with the reputable adaptive case management to be introduced recently as an alternative to BPM methodology and case management modeling and notation (CMMN) standard, as an alternative language of business process management notation (BPMN), targeting the modeling of human-centric processes characterized by agility. This chapter identifies the nature of human-centric processes, as its main objective is to examine whether using CMMN for the design and modeling of such processes could cover their agility requirements.

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Knowledge‐intensive processes (KiPs) have emerged characterizing tasks that are data‐driven, change dynamically and depend on the knowledge and experience of knowledge workers. Case Management Model and Notation (CMMN) language was introduced for modeling unstructured, agile human‐centric processes. As the available Business Process Modeling (BPM) methods and practices are not adequate for modeling KiPs, this paper presents an empirical study of the applicability of CMMN to modeling KiPs. After experienced modelers designed the models of three KiPs scenarios utilizing CMMN, their perceptions were collected assessing the support of CMMN to the KiPs characteristics. Specifically, the modelers assessed the support of the newly introduced CMMN notation elements to the KiPs characteristics. Three of them, that is, knowledge‐driven, unpredictable, and goal‐oriented, were highlighted as the ones that get the greater support by CMMN when it comes to modeling KiPs; the participating modelers suggested that the applicability of CMMN to modeling KiPs is mostly reinforced by the Sentries element. Considering that in a knowledge‐driven economy, organizations are called to transform their way of thinking and manage KiPs, we value the modelers' opinions since they shall apply such practices in the future. This research is a first step to assess whether CMMN may be a “fit” for modeling KiPs. When considering the potential of CMMN for KiPs modeling, the perceptions of such real CMMN users are also first indications of the CMMN future in terms of application.