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ZENODO
Article . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
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La Révolution de l'intelligence artificielle dans les systèmes ERP : Un catalyseur pour l'optimisation du contrôle de gestion

Authors: BENNANI Hala; OUTSEKI Jaouad;

La Révolution de l'intelligence artificielle dans les systèmes ERP : Un catalyseur pour l'optimisation du contrôle de gestion

Abstract

Résumé Cet article examine l'évolution des systèmes de planification des ressources d'entreprise (ERP) à la lumière de l'intelligence artificielle (IA), soulignant le potentiel de transformation significative de ces systèmes traditionnels. Adoptant une approche méthodologique basée sur des entretiens semi-structurés avec 16 professionnels du contrôle de gestion et 10 experts en IA, cette étude offre un aperçu approfondi. L'échantillon diversifié inclut des professionnels du contrôle de gestion et des experts en IA de différentes entreprises au Maroc. Les résultats confirment les avantages considérables de l'IA dans le contrôle de gestion, mettant en lumière la capacité à identifier des tendances cachées, à détecter précocement des anomalies, à optimiser les budgets et les ressources, ainsi qu'à améliorer la performance organisationnelle globale. Toutefois, des défis majeurs émergent, tels que la confidentialité des données, la sécurité, la transparence des modèles d'IA, et les implications en termes de responsabilité. En explorant ces différents aspects, cet article vise à fournir un aperçu approfondi de la révolution de l'IA dans les systèmes ERP et de son impact sur le contrôle de gestion, tout en offrant des orientations pour les entreprises qui souhaitent tirer parti de cette transformation technologique pour optimiser leur gestion et leur performance. Mots clés : systèmes ERP ; intelligence artificielle ; contrôle de gestion ; performance. Abstract This article examines the evolution of Enterprise Resource Planning (ERP) systems in the context of artificial intelligence (AI), emphasizing the significant transformative potential of these traditional systems. Employing a methodological approach based on semi-structured interviews with 16 management control professionals and 10 AI experts, this study provides a comprehensive overview. The diverse sample includes management control professionals and AI experts from various companies in Morocco. The findings affirm the substantial advantages of AI in management control, showcasing its ability to identify hidden trends, detect anomalies early on, optimize budgets and resources, and enhance overall organizational performance. However, significant challenges emerge, such as data privacy, security, transparency of AI models, and accountability implications. By delving into these various aspects, this article aims to offer a thorough insight into the AI revolution in ERP systems and its impact on management control, while providing guidance for businesses looking to leverage this technological transformation to optimize their management and performance. Keywords : ERP systems ; artificial intelligence ; management control ; performance.

Keywords

systèmes ERP ; intelligence artificielle ; contrôle de gestion ; performance, African Scientific Journal

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average