A Conversational Digital Assistant for Intelligent Process Automation
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Abstract (arXiv)
Robotic process automation (RPA) has emerged as the leading approach to automate tasks in business processes. Moving away from back-end automation, RPA automated the mouse-click on user interfaces; this outside-in approach reduced the overhead of updating legacy software. However, its many shortcomings, namely its lack of accessibility to business users, have prevented its widespread adoption in highly regulated industries. In this work, we explore interactive automation in the form of a conversational digital assistant. It allows business users to interact with and customize their automation solutions through natural language. The framework, which creates such assistants, relies on a multi-agent orchestration model and conversational wrappers for autonomous agents including RPAs. We demonstrate the effectiveness of our proposed approach on a loan approval business process and a travel preapproval business process.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Jul 2020.
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Citing papers per year: 2022: 4; 2023: 2; 2024: 1; 2025: 1.
8 papers.
- 2024SNAP: Semantic Stories for Next Activity Predictioncited by 8
- 2022Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestrationcited by 6
- 2022A Case for Business Process-Specific Foundation Modelscited by 5
- 2023ProtoNER: Few shot Incremental Learning for Named Entity Recognition using Prototypical Networkscited by 2
- 2022Natural Language Sentence Generation from API Specificationscited by 0
- 2022A No-Code Low-Code Paradigm for Authoring Business Automations Using Natural Languagecited by 0
- 2023TESS: A Multi-intent Parser for Conversational Multi-Agent Systems with Decentralized Natural Language Understanding Modelscited by 0
- 2025A Nascent Taxonomy of Machine Learning in Intelligent Robotic Process Automationcited by 0
- 2025A Nascent Taxonomy of Machine Learning in Intelligent Robotic Process Automation19 Sep 2025
- 2024SNAP: Semantic Stories for Next Activity Prediction28 Jan 2024
- 2023TESS: A Multi-intent Parser for Conversational Multi-Agent Systems with Decentralized Natural Language Understanding Models19 Dec 2023
- 2023ProtoNER: Few shot Incremental Learning for Named Entity Recognition using Prototypical Networks3 Oct 2023
- 2022Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration13 Dec 2022
- 2022A Case for Business Process-Specific Foundation Models26 Oct 2022
- 2022A No-Code Low-Code Paradigm for Authoring Business Automations Using Natural Language15 Jul 2022
- 2022Natural Language Sentence Generation from API Specifications1 Jun 2022