Speaker: Robin Killewald

Abstract: Generative AI is rapidly transforming work in professional service firms, where it is increasingly used to perform tasks at the core of service delivery. Against this backdrop, we examine how integrating the technology into practice reshapes routines and generates effects beyond the routine level. To this end, we conduct a qualitative, inductive multiple-case study in two European management consultancies comprising 31 semi-structured interviews. We identify recurring patterns of generative AI use and derive four mechanisms that explain how work is being reconfigured. Integrating these mechanisms into a framework makes it possible to describe how local adaptations of routines accumulate into broader field-level change. We contribute to research on generative AI in professional service firms by providing a mechanism-based explanation of work transformation and by showing how tensions shape these dynamics across levels. We further derive implications for managing the use of generative AI in practice.

Short Bio: Robin Killewald is a doctoral student at the University of Münster. His research focuses on digital innovation and value creation, particularly on how GenAI is reshaping knowledge work and professional services. Prior to his doctoral studies, he worked in management consulting as well as accounting and professional services, across both smaller firms and international organizations.

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Speaker: Julian Dyong

Abstract: Process mining enables organizations to analyze process executions based on event data and holds substantial potential for value creation. However, prior research on value realization has predominantly focused on the organizational level, largely overlooking the individuals who engage with process mining. These individuals interpret process data, generate insights, and initiate improvement actions, ultimately determining whether process mining delivers its promised value. This paper centers on the individual level of process mining by consolidating the emerging but fragmented literature on this topic. Through a literature review, we identify and analyze 23 studies that explicitly examine individuals in process mining contexts. Our synthesis uncovers (1) contingency factors that influence individuals in process mining, (2) core elements that constitute the role of individuals in process mining, and (3) value constructs associated with individual use. Building on these insights, we develop an integrative framework of individuals in process mining and outline a research agenda.

Short Bio: Julian Dyong is a research assistant and PhD student at the University of Münster. He works at the Chair of Business Process Management (Prof. Jan vom Brocke) and is part of the team “AI & Process” within the Flow Factory. His research explores how human actors work with data-driven technologies and how they derive valuable insights from this data. A particular focus of his work focuses on digital trace data and how people derive process knowledge from these traces.

We will have two speakers in this session.