mlsanityData to 7 Oct 2026

AI-Augmented Business Process Management Systems: A Research Manifesto

arXiv 2201.12855 ↗First posted 30 Jan 2022cs.AI cs.SEcited by 27

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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.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Builds on 9 of its 105 references that are in the map. First posted on arXiv 30 Jan 2022.

Builds on

9 of 105 references.

References · 9

  1. 2019The relationship between trust in AI and trustworthy machine learning technologiescited by 78
  2. 2020Multi-Dimensional Event Data in Graph Databasescited by 14
  3. 2020AI Trust in business processes: The need for process-aware explanationscited by 7
  4. 2020A Unified Conversational Assistant Framework for Business Process Automationcited by 5
  5. 2020Multipurpose Intelligent Process Automation via Conversational Assistantcited by 4
  6. 2020Expecting the Unexpected: Developing Autonomous-System Design Principles for Reacting to Unpredicted Events and Conditionscited by 3
  7. 2017What Automated Planning can do for Business Process Managementcited by 2
  8. 2020Do's and Don'ts for Human and Digital Worker Integrationcited by 1
  9. 2021Inferring Unobserved Events in Systems With Shared Resources and Queuescited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 6; 2024: 4; 2025: 6; 2026: 9.

27 papers.

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  1. 2024Automating the Enterprise with Foundation Modelscited by 14
  2. 2025Agentic Business Process Management: Practitioner Perspectives on Agent Governance in Business Processescited by 10
  3. 2025Agentic AI Process Observability: Discovering Behavioral Variabilitycited by 10
  4. 2023Chit-Chat or Deep Talk: Prompt Engineering for Process Miningcited by 9
  5. 2024How well can a large language model explain business processes as perceived by users?cited by 8
  6. 2023The WHY in Business Processes: Discovery of Causal Execution Dependenciescited by 7
  7. 2024Towards a Benchmark for Causal Business Process Reasoning with LLMscited by 7
  8. 2026Agentic Business Process Management: A Research Manifestocited by 7
  9. 2022Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestrationcited by 6
  10. 2023Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoringcited by 4
  11. 2023Large Process Models: A Vision for Business Process Management in the Age of Generative AIcited by 4
  12. 2026Agentic Business Process Management Systemscited by 4
15 more
  1. 2025Selecting the Right LLM for eGov Explanationscited by 3
  2. 2025XABPs: Towards eXplainable Autonomous Business Processescited by 3
  3. 2024Monetizing Currency Pair Sentiments through LLM Explainabilitycited by 2
  4. 2025Conversational Process Model Redesigncited by 2
  5. 2022Learning to act: a Reinforcement Learning approach to recommend the best next activitiescited by 1
  6. 2023Timing Process Interventions with Causal Inference and Reinforcement Learningcited by 1
  7. 2025The WHY in Business Processes: Unification of Causal Process Modelscited by 1
  8. 2023Composition of Nondeterministic and Stochastic Services for LTLf Task Specificationscited by 0
  9. 2026Semantic Feature Analysis: Improving Agents Without Searching Over Rolloutscited by 0
  10. 2026Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trendscited by 0
  11. 2026On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discoverycited by 0
  12. 2026Agent Behavior Mining: Generative AI Agent Governance in Business Processescited by 0
  13. 2026A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLOcited by 0
  14. 2026Design and Implementation of Agentic Orchestrations and Orchestration of Agentscited by 0
  15. 2026Supporting Autonomous Process Execution within a Multi-Perspective Constraint Frame via Numeric Planningcited by 0