Jan Vom Brocke

Digital Transformation (DT) has become a strategic imperative for organisations to stay competitive. Yet, it often faces resistance. Regulation is often argued to be one source of resistance. However, regulation can also drive transformation: its role is multifaceted and especially its management in the context of DT is underexplored. Drawing on an empirical case study of an organisation undergoing large‐scale DT in a highly regulated industry, we conceptualise Regulatory Resilience as a socio‐technical organisational capability that enables organisations to dynamically respond to regulation‐induced resistance while leveraging regulatory forces for DT. Our findings reveal five distinct mechanisms through which Regulatory Resilience operates to mitigate the effects of both stable and volatile regulation and transform regulatory pressure into a capability‐building process. This study contributes to Information Systems research by challenging the view of regulation as a static, exogenous hurdle, repositioning it instead as a constitutive force that organisations actively manage through sociotechnical means. By identifying the specific mechanisms through which organisations reconcile regulatory pressures with innovation, we advance theory on the interrelated dynamics of resistance and resilience showing that Regulatory Resilience not only enables DT but is itself strengthened by DT's technological and organisational conditions, requiring organisations to deliberately cultivate it to sustain transformation.

How do we conceptualize our bodily engagement with information systems (IS) artifacts? How do IS artifacts choreograph bodily action across the physical environment and digital realms? And what are the implications for IS use and design in personal and work contexts? These three questions framed our conference “Sense and Movement in the Digital Age”, held at the University of Agder in Norway on 29–30 January 2026 and joined by scholars and practitioners from IS and other disciplines. This paper synthesizes the main insights by positioning sense and movement within established and emerging IS discourse: process science, digitally-mediated multisensory bodily experience, digital technologies for well-being, affective artificial intelligence, and organizational sensing and moving. If IS artifacts choreograph what can be sensed and how movement unfolds, it also shapes how we relate to one another and how we express our feelings. The task before IS research is therefore modest but consequential: to revisit what it means to be human in the digital age by digging deeper into sense and movement. We outline a research agenda in this direction.

Academic publishing norms are being actively renegotiated. Generative AI, growing expectations for transparency in authorship and contribution, and heightened attention to conflicts of interest in peer review have made ethical ambiguities more visible, while existing rules and guidelines often address them only partially. Doctoral students and early-career scholars are especially exposed to these grey areas, yet access to trusted, practice-based guidance remains uneven. To address this gap, a mentorship panel organised through the AIS Doctoral Student College brought together senior Information Systems scholars and doctoral students to discuss concrete ethical scenarios in academic publishing. Across two global online sessions, 192 participants from 30 countries engaged in discussions in which eight senior scholars responded to participant-submitted scenarios on plagiarism, generative AI in research, and conflicts of interest in peer review. The sessions generated 28 practical takeaways and a consistent cross-cutting message: ethical publishing requires not only technical compliance with rules, but also transparency, scholarly honesty, and a sustained commitment to research integrity. Building on these insights, this report introduces the TRUST framework—Transparency, Responsibility, Understanding, Support, and Timeliness—as practical guidance for navigating ethical grey areas in academic publishing.

Artificial intelligence (AI) brings great potential for manufacturers, but clashes with the established culture due to the unexplainable and opaque nature of the solutions it provides. Having little experience in AI and machine learning (ML), most manufacturing leaders experience barriers implementing AI. This is especially true in lean environments, since these are often nearly perfected and hence intolerant of failure. Cultural barriers to adoption abound, even if the quality of the AI is assured. Deeply grounded in the case of Siemens' Digital Industries division, this 5‐year practitioner research investigates AI adoption in lean quality management. Collaborating with key executives involved in the case and fellow researchers, we investigate the challenges and solutions of AI adoption in lean quality management. We identify three distinct paradoxes: (1) Human‐driven versus AI‐driven analysis, decisions and actions, (2) transparency versus opacity and (3) specification‐driven versus discovery‐driven processes to achieve quality. Rooted in Siemens' experience, we derive four strategies for overcoming these paradoxes. Our findings have important implications for practice, as we present clear and realistic steps and guidance for effective AI integration into lean quality management environments. Our results contribute to the discourse on AI adoption, pointing to the importance of recognising potential cultural clashes as well as strategies for overcoming these which go beyond the technology itself.