A comparative analysis between AI and traditional methods in management control

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.