Smart ERP Systems – From Data to Decisions

Pohrib Silvia-Daniela (), Goga Alexandru-Silviu () and Pîsla Adrian ()
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Pohrib Silvia-Daniela: Technical University of Cluj-Napoca, Romania
Goga Alexandru-Silviu: University of Transylvania Brasov, Romania
Pîsla Adrian: Technical University of Cluj-Napoca, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 380-401

Abstract: In today’s rapidly evolving business environment, organizations face increasing pressure to integrate advanced technological solutions into their operations. Enterprise Resource Planning (ERP) systems have evolved from conventional management tools into intelligent platforms. This study investigates the integration of artificial intelligence capabilities within ERP systems and their impact on decision-making and process automation. Through a systematic literature review combined with empirical insights from accounting and legal practice, we examine real-world implementations of AI-enhanced ERP systems. Our findings highlight three critical success factors for modern ERP adoption: data quality management as a prerequisite for AI-driven decision-making, specialized skill development to ensure effective system utilization, and strategic change management to facilitate user adaptation. Building upon these insights, we propose a comprehensive evaluation framework that guides organizations through the integration of AI-powered ERP systems while maintaining operational efficiency and audit integrity. This study contributes to the growing body of knowledge on AI-enhanced business process automation and provides practical recommendations for enterprises navigating digital transformation.

Keywords: ERP systems; artificial intelligence; big data analytics; business process automation; digital transformation; decision support systems; audit automation; AI-driven governance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:380-401:n:1007

DOI: 10.2478/picbe-2025-0032

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