Szczegóły publikacji

Opis bibliograficzny

Using AI tools to increase the efficiency of ERP implementation projects / Katarzyna GROBLER-DĘBSKA, Honorata Kucharska, Adam Domagała, Edyta KUCHARSKA, Jarosław WĄS // W: Emerging challenges in intelligent management information systems : proceedings of 28th European Conference on Artificial Intelligence ECAI 2025 - IMIS Workshop : [Bologna, Italy, October 25–30, 2025] , Vol. 2 / eds. Marcin Hernes, Ewa Walaszczyk, Artur Rot. — Cham : Springer Nature Switzerland, cop. 2026. — ( Lecture Notes in Networks and Systems ; ISSN  2367-3370 ; vol. 1643 ). — ISBN: 978-3-032-06610-7; e-ISBN: 978-3-032-06611-4. — S. 149–161. — Bibliogr., Abstr. — Publikacja dostępna online od: 2025-10-12. — K. Grobler-Dębska - dod. afiliacja: InfoConsulting Poland, Warszawa

Autorzy (5)

Słowa kluczowe

data integrationautomationartificial intelligenceenterprise architectureproject managementcomputer system implementation

Dane bibliometryczne

ID BaDAP163873
Data dodania do BaDAP2025-11-21
DOI10.1007/978-3-032-06611-4_12
Rok publikacji2026
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaSpringer
KonferencjaEuropean Conference on Artificial Intelligence 2025
Czasopismo/seriaLecture Notes in Networks and Systems

Abstract

ERP system implementation is complex and costly, with software modifications tailored to organizational needs being one of the most challenging stages. The scope and complexity of these modifications depend on the type of project-whether it is a first-time implementation, an upgrade, a roll-out, or a reimplementation. One of the key directions in the development of ERP systems is the integration of AI solutions, both in the context of the company’s day-to-day operations and in the automation of repetitive tasks within the implementation process itself. However, there is still a lack of tools that effectively support the automation of implementation activities. The aim of the presented research is to increase the effectiveness of ERP implementation projects through the use of AI-based tools. A solution that leverages NLP techniques to enable the reuse of modification documentation (HLS/DLS) by performing similarity comparisons and searches is proposed. The paper also includes a systematization of ERP project types, an analysis of modification similarities, and a review of implementation methodologies used by various ERP vendors (SAP, Microsoft, IFS), with particular emphasis on the impact of project type on the scope of modifications.

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