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AI-Driven ERP Systems Integrating Large Language Models for Enhanced Customer Interaction and Operational Efficiency
Journal article   Open access   Peer reviewed

AI-Driven ERP Systems Integrating Large Language Models for Enhanced Customer Interaction and Operational Efficiency

Elias Niederwieser, Dietmar Siegele and Dominik Matt
ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol.120(s1), pp.112 -117
120
2025
Handle:
https://hdl.handle.net/10863/51445

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.
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10.1515_zwf-2025-00071.04 MBDownloadView
Open Access
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https://www.degruyterbrill.com/document/doi/10.1515/zwf-2025-0007/htmlView

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