Theory and applications of artificial intelligence in management control

Abstract

The rapid adoption of Artificial Intelligence (AI) in organizational management practices represents one of the most significant transformations in the history of accounting and management control. This article presents a systematic literature review (SLR) on the theoretical foundations, technological aspects, and practical applications of AI in Management Control Systems (MCS), conducted in accordance with the PRISMA 2020 guidelines. Based on a final set of 112 peer-reviewed articles published between 2000 and 2025, primarily from journals indexed in Scopus and Web of Science, the review summarizes the findings across ten different application areas. The study critically examines the relevance of eight theoretical frameworks. The results show that AI technologies lead to significant advances in terms of forecast accuracy, anomaly detection, real-time information generation, and strategic decision support. The article also examines the evolving role of management controllers in AI-enhanced environments, where human judgment increasingly operates in interaction with algorithmic intelligence. An original conceptual framework is proposed, illustrating the mediating mechanisms through which AI improves organizational performance by transforming management control systems. From a theoretical perspective, this article contributes by synthesizing and integrating eight frameworks that were previously scattered throughout the literature; from a methodological perspective, it combines a systematic review adhering to the PRISMA 2020 guidelines with a bibliometric analysis, providing a unique mapping of the MCS-AI field.