How can AI agents improve business processes?
Agentic Business Process Management: The Past 30 Years And Practitioners' Future Perspectives
April 8, 2025
https://arxiv.org/pdf/2504.03693This paper explores the concept of Agentic Business Process Management (ABPM), which involves using autonomous software agents to achieve business goals and applying agent-based concepts to design and analyze these agents. It reviews the history of agents in BPM, from early goal-oriented agents to RPA and the current resurgence with LLM-based agents.
Key points relevant to LLM-based multi-agent systems include:
- LLMs are driving a new wave of interest in agent-based systems for BPM.
- Agentic BPM aims to integrate agents into business processes while retaining human oversight and control.
- Practitioner interviews reveal perceived benefits of agentic AI such as efficiency, data quality, and compliance, but also concerns like bias, over-reliance, job displacement, and lack of transparency.
- Key requirements highlighted are clear rules and guidelines, human-agent collaboration frameworks, and customization options for agent autonomy.
- Adaptability is seen as crucial but needs careful management through transparency and oversight.
- A robust methodological framework is needed to manage these systems effectively.