Projekt
Business Process Reengineering in the Age of Generative and Agentic AI: Translation, Persistence, and Renewed Relevance
Business process reengineering (BPR) is usually remembered as one of the most visible management fashions of the 1990s. It rose rapidly, promised radical redesign and major performance gains, and later lost legitimacy as many implementations failed to match the rhetoric and became associated with disruption, downsizin…
Business process reengineering (BPR) is usually remembered as one of the most visible management fashions of the 1990s. It rose rapidly, promised radical redesign and major performance gains, and later lost legitimacy as many implementations failed to match the rhetoric and became associated with disruption, downsizing, and managerial overreach. Yet the organizational problem to which BPR responded never disappeared: how should organizations redesign processes when new technologies alter what is possible? This paper revisits BPR in light of recent developments in generative and agentic artificial intelligence. This perspective article develops a conceptual interpretation rather than a systematic review or empirical test. Its purpose is to clarify an emerging pattern in management discourse and process-management research: the possible reactivation of BPR-style redesign logic under new technological and discursive conditions. Using management fashion theory as the main lens, it suggests that AI may be creating conditions under which elements of BPR’s underlying redesign logic become newly relevant. The argument is not that the BPR label has simply returned. Rather, aspects of its core ambition appear to be rearticulated through adjacent and more legitimate vocabularies such as business process management, AI-augmented business process management systems, Large Process Models, and agentic BPM. To capture this pattern, the paper introduces the concept of translated resurgence, referring to the renewed relevance of an older management idea through relabeling, reinterpretation, and mutation. The paper further argues that AI may alter the technical feasibility of radical process redesign while leaving many classic BPR risks intact. The result is best understood not as a simple revival, but as an emerging and still unsettled phase in the longer afterlife of a once-prominent management idea.