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 traceability through a combination with process technology. In this paper, we provide a classification framework for agentic orchestration options along properties such as task specificity, traceability and tractability, autonomy and reactivity, and correctness assurance and present qualitative decision criteria for realizations
The proliferation of increasingly capable AI agents, particularly LLM-based ones, necessitates robust orchestration frameworks to manage their autonomy, ensure reliability, and enable their integration into critical business processes.
A strategic reader should care because effective agent orchestration is key to unlocking the full potential of AI agents for business process automation and could redefine enterprise software architecture.
The focus shifts from individual agent capabilities to structured, controllable, and traceable multi-agent systems, improving their applicability in complex, high-stakes environments.
- · Enterprise software providers
- · Businesses adopting AI agents
- · Process orchestration platforms
- · AI agent developers
- · Manual business process outsourcing
- · Unstructured workflow providers
Increased enterprise adoption of AI agents for complex business processes due to improved manageability.
New competitive landscapes emerge for software vendors offering robust agent orchestration tools.
The blurring of lines between human-driven and agent-driven processes, leading to novel organizational structures and skill demands.
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Read at arXiv cs.AI