# AI-Augmented Business Process Management Systems: A Research Manifesto

arXiv: https://arxiv.org/abs/2201.12855 · HTML: https://mlsanity.com/paper/2201.12855/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 105 references that are in the map.
- First posted on arXiv 30 Jan 2022.

## Builds on (most cited first, 9 of 9)

- [The relationship between trust in AI and trustworthy machine learning technologies](https://mlsanity.com/paper/1912.00782/) (2019)
- [Multi-Dimensional Event Data in Graph Databases](https://mlsanity.com/paper/2005.14552/) (2020)
- [AI Trust in business processes: The need for process-aware explanations](https://mlsanity.com/paper/2001.07537/) (2020)
- [A Unified Conversational Assistant Framework for Business Process Automation](https://mlsanity.com/paper/2001.03543/) (2020)
- [Multipurpose Intelligent Process Automation via Conversational Assistant](https://mlsanity.com/paper/2001.02284/) (2020)
- [Expecting the Unexpected: Developing Autonomous-System Design Principles for Reacting to Unpredicted Events and Conditions](https://mlsanity.com/paper/2001.06047/) (2020)
- [What Automated Planning can do for Business Process Management](https://mlsanity.com/paper/1709.10482/) (2017)
- [Do's and Don'ts for Human and Digital Worker Integration](https://mlsanity.com/paper/2010.07738/) (2020)
- [Inferring Unobserved Events in Systems With Shared Resources and Queues](https://mlsanity.com/paper/2103.00167/) (2021)

## Built on by (most cited first, 28 of 28)

- [Automating the Enterprise with Foundation Models](https://mlsanity.com/paper/2405.03710/) (2024)
- [Agentic Business Process Management: Practitioner Perspectives on Agent Governance in Business Processes](https://mlsanity.com/paper/2504.03693/) (2025)
- [Agentic AI Process Observability: Discovering Behavioral Variability](https://mlsanity.com/paper/2505.20127/) (2025)
- [Chit-Chat or Deep Talk: Prompt Engineering for Process Mining](https://mlsanity.com/paper/2307.09909/) (2023)
- [How well can a large language model explain business processes as perceived by users?](https://mlsanity.com/paper/2401.12846/) (2024)
- [Agentic Business Process Management: A Research Manifesto](https://mlsanity.com/paper/2603.18916/) (2026)
- [The WHY in Business Processes: Discovery of Causal Execution Dependencies](https://mlsanity.com/paper/2310.14975/) (2023)
- [Towards a Benchmark for Causal Business Process Reasoning with LLMs](https://mlsanity.com/paper/2406.05506/) (2024)
- [Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration](https://mlsanity.com/paper/2212.06564/) (2022)
- [Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoring](https://mlsanity.com/paper/2307.05939/) (2023)
- [Large Process Models: A Vision for Business Process Management in the Age of Generative AI](https://mlsanity.com/paper/2309.00900/) (2023)
- [Agentic Business Process Management Systems](https://mlsanity.com/paper/2601.18833/) (2026)
- [Selecting the Right LLM for eGov Explanations](https://mlsanity.com/paper/2504.21032/) (2025)
- [XABPs: Towards eXplainable Autonomous Business Processes](https://mlsanity.com/paper/2507.23269/) (2025)
- [Monetizing Currency Pair Sentiments through LLM Explainability](https://mlsanity.com/paper/2407.19922/) (2024)
- [Conversational Process Model Redesign](https://mlsanity.com/paper/2505.05453/) (2025)
- [Learning to act: a Reinforcement Learning approach to recommend the best next activities](https://mlsanity.com/paper/2203.15398/) (2022)
- [Timing Process Interventions with Causal Inference and Reinforcement Learning](https://mlsanity.com/paper/2306.04299/) (2023)
- [The WHY in Business Processes: Unification of Causal Process Models](https://mlsanity.com/paper/2505.22871/) (2025)
- [Composition of Nondeterministic and Stochastic Services for LTLf Task Specifications](https://mlsanity.com/paper/2311.18114/) (2023)
- [Semantic Feature Analysis: Improving Agents Without Searching Over Rollouts](https://mlsanity.com/paper/2604.10513/) (2026)
- [Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends](https://mlsanity.com/paper/2604.14034/) (2026)
- [On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery](https://mlsanity.com/paper/2604.22455/) (2026)
- [Agent Behavior Mining: Generative AI Agent Governance in Business Processes](https://mlsanity.com/paper/2606.20669/) (2026)
- [A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO](https://mlsanity.com/paper/2606.27188/) (2026)
- [Design and Implementation of Agentic Orchestrations and Orchestration of Agents](https://mlsanity.com/paper/2606.31518/) (2026)
- [Supporting Autonomous Process Execution within a Multi-Perspective Constraint Frame via Numeric Planning](https://mlsanity.com/paper/2607.16738/) (2026)
- [Process Constitutions and Process Stewards: Towards the Next Generation of BPM for Agentic Organizations](https://mlsanity.com/paper/2610.05942/) (2026)

## Abstract (arXiv)

AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses research challenges that need to be surmounted to realize this vision. To this end, we define the concept of ABPMS, we outline the lifecycle of processes within an ABPMS, we discuss core characteristics of an ABPMS, and we derive a set of challenges to realize systems with these characteristics.