Management Control in the Age of Artificial Intelligence: Toward a Conceptual Model for Decision Support

Abstract

The rise of artificial intelligence (AI) is profoundly transforming managerial practices, particularly in the field of management control. This study aims to analyze the effects of AI on the quality of managerial decision-making through the evolution of control tools and processes. It begins with a clarification of key concepts (AI, management control, decision-making under uncertainty), followed by a focused literature review on the contributions of AI technologies such as machine learning, predictive analytics, and automation. The research adopts a hypothetico-deductive approach, drawing on decision theory and organizational contingency theory to structure the analysis and develop the conceptual framework. A theoretical model is proposed, structured around five main hypotheses: (H1) AI transforms management control tools and processes; (H2) AI enhances the quality, speed, and relevance of decision-making information; (H3) AI strengthens control mechanisms by reducing information asymmetries and improving traceability; (H4) AI improves the quality of both strategic and operational decisions; (H5) the impact of AI is moderated by contextual factors such as firm size, culture, strategy, and industry. The study also discusses the key challenges related to AI adoption, including data governance, algorithm reliability, and acceptance by management control professionals.