A Unified Conversational Assistant Framework for Business Process Automation
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Abstract (arXiv)
Business process automation is a booming multi-billion-dollar industry that promises to remove menial tasks from workers' plates -- through the introduction of autonomous agents -- and free up their time and brain power for more creative and engaging tasks. However, an essential component to the successful deployment of such autonomous agents is the ability of business users to monitor their performance and customize their execution. A simple and user-friendly interface with a low learning curve is necessary to increase the adoption of such agents in banking, insurance, retail and other domains. As a result, proactive chatbots will play a crucial role in the business automation space. Not only can they respond to users' queries and perform actions on their behalf but also initiate communication with the users to inform them of the system's behavior. This will provide business users a natural language interface to interact with, monitor and control autonomous agents. In this work, we present a multi-agent orchestration framework to develop such proactive chatbots by discussing the types of skills that can be composed into agents and how to orchestrate these agents. Two use cases on a travel preapproval business process and a loan application business process are adopted to qualitatively analyze the proposed framework based on four criteria: performance, coding overhead, scalability, and agent overlap.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jan 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 2; 2026: 1.
5 papers.
- 2025A Survey of Context Engineering for Large Language Modelscited by 120
- 2022AI-Augmented Business Process Management Systems: A Research Manifestocited by 27
- 2022Efficient Customer Service Combining Human Operators and Virtual Agentscited by 1
- 2025OpenDerisk: An Industrial Framework for AI-Driven SRE, with Design, Implementation, and Case Studiescited by 1
- 2026BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AIcited by 0
- 2026BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AI27 Aug 2026
- 2025OpenDerisk: An Industrial Framework for AI-Driven SRE, with Design, Implementation, and Case Studies15 Oct 2025
- 2025A Survey of Context Engineering for Large Language Models17 Jul 2025
- 2022Efficient Customer Service Combining Human Operators and Virtual Agents12 Sep 2022
- 2022AI-Augmented Business Process Management Systems: A Research Manifesto30 Jan 2022