mlsanityData to 7 Oct 2026

Large Language Models for Business Process Management: Opportunities and Challenges

arXiv 2304.04309 ↗First posted 9 Apr 2023cs.SEcited by 24

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Abstract (arXiv)

Large language models are deep learning models with a large number of parameters. The models made noticeable progress on a large number of tasks, and as a consequence allowing them to serve as valuable and versatile tools for a diverse range of applications. Their capabilities also offer opportunities for business process management, however, these opportunities have not yet been systematically investigated. In this paper, we address this research problem by foregrounding various management tasks of the BPM lifecycle. We investigate six research directions highlighting problems that need to be addressed when using large language models, including usage guidelines for practitioners.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2023.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 10; 2025: 6; 2026: 1.

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  1. 2023Generative AIcited by 119
  2. 2023Large Language Models can accomplish Business Process Management Taskscited by 34
  3. 2024PM-LLM-Benchmark: Evaluating Large Language Models on Process Mining Taskscited by 16
  4. 2023Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not todaycited by 14
  5. 2024ProMoAI: Process Modeling with Generative AIcited by 12
  6. 2024WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management Taskscited by 11
  7. 2024How well can a large language model explain business processes as perceived by users?cited by 8
  8. 2024Exploring the Potential of Large Language Models for Improving Digital Forensic Investigation Efficiencycited by 7
  9. 2024Towards a Benchmark for Causal Business Process Reasoning with LLMscited by 7
  10. 2024NeurDB: An AI-powered Autonomous Data Systemcited by 5
  11. 2023Tailoring Machine Learning for Process Miningcited by 4
  12. 2023Large Process Models: A Vision for Business Process Management in the Age of Generative AIcited by 4
12 more
  1. 2024Bridging Domain Knowledge and Process Discovery Using Large Language Modelscited by 4
  2. 2024NLP4PBM: A Systematic Review on Process Extraction using Natural Language Processing with Rule-based, Machine and Deep Learning Methodscited by 3
  3. 2025ConDABench: Interactive Evaluation of Language Models for Data Analysiscited by 3
  4. 2023Conceptual Model Interpreter for Large Language Modelscited by 2
  5. 2025Automated Business Process Analysis: An LLM-Based Approach to Value Assessmentcited by 2
  6. 2025Evaluating the Process Modeling Abilities of Large Language Models -- Preliminary Foundations and Resultscited by 1
  7. 2025On LLM-Assisted Generation of Smart Contracts from Business Processescited by 1
  8. 2023Evaluating the Inclusiveness of Artificial Intelligence Software in Enhancing Project Management Efficiency -- A Reviewcited by 0
  9. 2024Responsible AI in NLP: GUS-Net Span-Level Bias Detection Dataset and Benchmark for Generalizations, Unfairness, and Stereotypescited by 0
  10. 2025Evaluation of LLMs for Process Model Analysis and Optimizationcited by 0
  11. 2025Documenting SME Processes with Conversational AI: From Tacit Knowledge to BPMNcited by 0
  12. 2026BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AIcited by 0