# Agentic Business Process Management: A Research Manifesto arXiv: https://arxiv.org/abs/2603.18916 ยท HTML: https://mlsanity.com/paper/2603.18916/ ## Key facts - Cited by 8 papers in the map (data through 14 Oct 2026). - Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. - Builds on 30 of its 107 references that are in the map. - First posted on arXiv 19 Mar 2026. ## Placed in - LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/) ## Builds on (most cited first, 30 of 30) - [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023) - [Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods](https://mlsanity.com/paper/1910.09457/) (2019) - [Large Language Model based Multi-Agents: A Survey of Progress and Challenges](https://mlsanity.com/paper/2402.01680/) (2024) - [Multi-Agent Collaboration Mechanisms: A Survey of LLMs](https://mlsanity.com/paper/2501.06322/) (2025) - [AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges](https://mlsanity.com/paper/2505.10468/) (2025) - [LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead](https://mlsanity.com/paper/2404.04834/) (2024) - [Machine Learning with a Reject Option: A survey](https://mlsanity.com/paper/2107.11277/) (2021) - [Active Testing: Sample-Efficient Model Evaluation](https://mlsanity.com/paper/2103.05331/) (2021) - [Design Patterns for Securing LLM Agents against Prompt Injections](https://mlsanity.com/paper/2506.08837/) (2025) - [AI-Augmented Business Process Management Systems: A Research Manifesto](https://mlsanity.com/paper/2201.12855/) (2022) - [Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges](https://mlsanity.com/paper/2510.23883/) (2025) - [Guidelines for Empirical Studies in Software Engineering involving Large Language Models](https://mlsanity.com/paper/2508.15503/) (2025) - [Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring](https://mlsanity.com/paper/2009.02098/) (2020) - [Large Language Models as Software Components: A Taxonomy for LLM-Integrated Applications](https://mlsanity.com/paper/2406.10300/) (2024) - [DOLCE: A Descriptive Ontology for Linguistic and Cognitive Engineering](https://mlsanity.com/paper/2308.01597/) (2023) - [Agentic Business Process Management: Practitioner Perspectives on Agent Governance in Business Processes](https://mlsanity.com/paper/2504.03693/) (2025) - [Agent Miner: An Algorithm for Discovering Agent Systems from Event Data](https://mlsanity.com/paper/2212.01454/) (2022) - [We Need a New Ethics for a World of AI Agents](https://mlsanity.com/paper/2509.10289/) (2025) - [How well can a large language model explain business processes as perceived by users?](https://mlsanity.com/paper/2401.12846/) (2024) - [The WHY in Business Processes: Discovery of Causal Execution Dependencies](https://mlsanity.com/paper/2310.14975/) (2023) - [Evaluating Consistency and Reasoning Capabilities of Large Language Models](https://mlsanity.com/paper/2404.16478/) (2024) - [Governance of Autonomous Agents on the Web: Challenges and Opportunities](https://mlsanity.com/paper/2202.02574/) (2022) - [Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoring](https://mlsanity.com/paper/2307.05939/) (2023) - [Large Process Models: A Vision for Business Process Management in the Age of Generative AI](https://mlsanity.com/paper/2309.00900/) (2023) - [Expecting the Unexpected: Developing Autonomous-System Design Principles for Reacting to Unpredicted Events and Conditions](https://mlsanity.com/paper/2001.06047/) (2020) - [Large Language and Reasoning Models are Shallow Disjunctive Reasoners](https://mlsanity.com/paper/2503.23487/) (2025) - [XABPs: Towards eXplainable Autonomous Business Processes](https://mlsanity.com/paper/2507.23269/) (2025) - [Expressive Power and Complexity Results for SIGNAL, an Industry-scale Process Query Language](https://mlsanity.com/paper/2310.14939/) (2023) - [The WHY in Business Processes: Unification of Causal Process Models](https://mlsanity.com/paper/2505.22871/) (2025) - [A Research Roadmap for Augmenting Software Engineering Processes and Software Products with Generative AI](https://mlsanity.com/paper/2510.26275/) (2025) ## Built on by (most cited first, 8 of 8) - [Organizational Memory for Agentic Business Process Execution](https://mlsanity.com/paper/2607.03228/) (2026) - [The Last Human Gate: Forward Deployed Engineering for Governance Automation](https://mlsanity.com/paper/2609.29345/) (2026) - [On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery](https://mlsanity.com/paper/2604.22455/) (2026) - [A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO](https://mlsanity.com/paper/2606.27188/) (2026) - [Design and Implementation of Agentic Orchestrations and Orchestration of Agents](https://mlsanity.com/paper/2606.31518/) (2026) - [DNative-Twin: Decision Graphs and Digital Twins for Reconstructable Agentic Decisions](https://mlsanity.com/paper/2609.03787/) (2026) - [From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining](https://mlsanity.com/paper/2609.07984/) (2026) - [Process Constitutions and Process Stewards: Towards the Next Generation of BPM for Agentic Organizations](https://mlsanity.com/paper/2610.05942/) (2026) ## Abstract (arXiv) This paper presents a manifesto that articulates the conceptual foundations of Agentic Business Process Management (APM), an extension of Business Process Management (BPM) for governing autonomous agents executing processes in organizations. From a management perspective, APM represents a paradigm shift from the traditional process view of the business process, driven by the realization of process awareness and an agent-oriented abstraction, where software and human agents act as primary functional entities that perceive, reason, and act within explicit process frames. This perspective marks a shift from traditional, automation-oriented BPM toward systems in which autonomy is constrained, aligned, and made operational through process awareness. We introduce the core abstractions and architectural elements required to realize APM systems and elaborate on four key capabilities that such APM agents must support: framed autonomy, explainability, conversational actionability, and self-modification. These capabilities jointly ensure that agents' goals are aligned with organizational goals and that agents behave in a framed yet proactive manner in pursuing those goals. We discuss the extent to which the capabilities can be realized and identify research challenges whose resolution requires further advances in BPM, AI, and multi-agent systems. The manifesto thus serves as a roadmap for bridging these communities and for guiding the development of APM systems in practice.