A comparative analysis between AI and traditional methods in management control

Artificial Intelligence (AI) is reshaping management control by introducing predictive and automated tools capable of processing vast amounts of data in real time. Unlike traditional methods that rely on static analysis and historical records, AI-driven systems enhance agility, accuracy, and the speed of decision-making. This transformation enables organizations to anticipate changes more effectively and optimize the allocation of their resources. Nevertheless, the integration of AI also raises several challenges, particularly in terms of implementation costs, data quality, and ethical considerations. A hybrid model—combining the reliability of conventional control techniques with the innovative capabilities of AI—emerges as a promising solution. This study investigates the impact of AI on organizational performance through both theoretical analysis and empirical research conducted in Morocco and abroad. It examines how AI contributes to greater organizational agility through predictive analytics, automation, and anomaly detection, while also identifying best practices and existing gaps in the current body of knowledge.

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Publication Details

Journal
International Journal of Research in Economics and Finance
Published
2025-06-07
DOI
https://doi.org/10.71420/ijref.v2i5.109
Citations
4
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
8.91
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article

A comparative analysis between AI and traditional methods in management control

Said Yahmedi, Najoua Rhali, Zainab Joukhrane
4 citations
International Journal of Research in Economics and Finance
Supply Chain Resilience and Risk Management
8.91
article

A comparative analysis between AI and traditional methods in management control

Said Yahmedi, Najoua Rhali, Zainab Joukhrane
article en
4 citations

Abstract

Artificial Intelligence (AI) is reshaping management control by introducing predictive and automated tools capable of processing vast amounts of data in real time. Unlike traditional methods that rely on static analysis and historical records, AI-driven systems enhance agility, accuracy, and the speed of decision-making. This transformation enables organizations to anticipate changes more effectively and optimize the allocation of their resources. Nevertheless, the integration of AI also raises several challenges, particularly in terms of implementation costs, data quality, and ethical considerations. A hybrid model—combining the reliability of conventional control techniques with the innovative capabilities of AI—emerges as a promising solution. This study investigates the impact of AI on organizational performance through both theoretical analysis and empirical research conducted in Morocco and abroad. It examines how AI contributes to greater organizational agility through predictive analytics, automation, and anomaly detection, while also identifying best practices and existing gaps in the current body of knowledge.

International Journal of Research in Economics and FinanceVol. 2(5)
University of Hassan II Casablanca (MA)
Openalex Percentile: Top 3%
Supply Chain Resilience and Risk Management
8.91
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