Framework Classifies Agentic Orchestration for Business Process Management.
Summary
This paper introduces a classification framework for agentic orchestration in Business Process Management, balancing AI agent autonomy with robustness and traceability. It provides criteria and metrics for designing and implementing agentic orchestrations, demonstrated through a predictive light sensing scenario.
Why it matters
Professionals involved in process automation, AI integration, or enterprise architecture can use this framework to systematically design, implement, and evaluate agentic workflows, ensuring a balance between AI autonomy and business process control.
How to implement this in your domain
- 1Utilize the proposed classification framework to analyze and categorize existing or planned agentic workflows.
- 2Apply the qualitative decision criteria to select appropriate orchestration patterns for specific business processes.
- 3Define and track quantitative metrics to assess the performance, robustness, and traceability of agentic implementations.
- 4Pilot agentic orchestration in a controlled scenario, like predictive sensing, to gain practical experience.
Who benefits
Key takeaways
- Agentic BPM balances AI autonomy with process robustness and traceability.
- A new framework classifies agentic orchestration options by key properties.
- Qualitative criteria guide scenario realization, and quantitative metrics assess performance.
- This work aids in designing and implementing effective agentic workflows.
Original post by Stefanie Rinderle-Ma, Juergen Mangler, Johannes Loebbecke, Dominik Voigt, Nataliia Klievtsova, Matthias Ehrendorfer
"arXiv:2606.31518v1 Announce Type: new Abstract: Agentic Business Process Management has gained momentum recently. The prospect is that the autonomy of AI agents, i.e., predominantly LLM-based agents, can be balanced with a certain level of robustness, tractability, and traceabili…"
View on XOriginally posted by Stefanie Rinderle-Ma, Juergen Mangler, Johannes Loebbecke, Dominik Voigt, Nataliia Klievtsova, Matthias Ehrendorfer on X · view source
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