🤖 AI Summary
This study addresses the inadequacy of traditional Business Process Management (BPM) in effectively governing organizations of autonomous AI agents. To this end, it proposes a next-generation BPM framework centered on a "process constitution" and "process stewards," shifting the paradigm from modeling human work to governing autonomous agents. Methodologically, the framework establishes a machine-parsable system of value constraints by constructing machine-interpretable constitutional definitions and value-aligned governance agent technologies. Through these mechanisms, the research ensures accountability, contestability, and human interpretability within agent-based organizations. Ultimately, this work provides a novel theoretical foundation and technical pathway for the normative governance of autonomous AI systems.
📝 Abstract
Business Process Management (BPM) was built on a foundational assumption that organizations are populated primarily by human actors whose work can be made visible, governable, and improvable through process models. That assumption is depreciating. AI agent ecosystems increasingly execute, coordinate, and adapt organizational work with limited human direction, challenging not only BPM's methods but its core conception of what a process is. We argue that BPM faces a constitutive shift from modeling human work to governing autonomous agents, for which we propose two new concepts: the \emph{Process Constitution}, a machine-interpretable, value-laden framework that defines the space of admissible agent behavior, and the \emph{Process Steward}, a governance agent that interprets and enforces it. The central value proposition of this new generation of BPM is not efficiency but \emph{organizational legibility}: the capacity to keep agentic organizations accountable, contestable, and humanly understandable. We outline what this means and sketch the research agenda it opens.