AI-Driven ERP Systems
Abstract Large Language Models (LLM) offer significant potential for automating complex tasks across domains. This article presents a novel Enterprise Resource Planning (ERP) system that leverages LLM to fulfill customer requests by accessing the ERP database for real-time updates, modifications, and availability checks, enhancing interaction and efficiency. Using a graph-theoretic framework, the system supports stateful workflows with cycles, branching, and human-in-the-loop (HITL) interactions, allowing precise control over application flow. This approach redefines LLM deployment in ERP applications, providing enhanced automation and responsiveness in customer service.
Authors
- Dietmar Siegele (ORCID: https://orcid.org/0000-0003-1755-1055)
- Elias Niederwieser
- Dominik T. Matt (ORCID: https://orcid.org/0000-0002-2365-7529)
Institutions
- Free University of Bozen-Bolzano (IT)
- Fraunhofer Italia Research (IT)
Publication Details
- Journal
- Zeitschrift für wirtschaftlichen Fabrikbetrieb
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1515/zwf-2025-0007
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00