Artificial Intelligence and Smart Dashboards: A Lever for Decision-Making Performance in Management Control – An Empirical Study

Abstract

This research examines the integration of artificial intelligence (AI) into management dashboards and its effect on the decision-making performance of management control within SMEs of the Souss-Massa region, in a context where traditional steering tools struggle to cope with the growing complexity of organizational environments. Theoretically, the study situates the emergence of intelligent dashboards at the convergence of artificial intelligence and Business Intelligence. Empirically, a sequential mixed-methods design was mobilized, combining an exploratory qualitative phase (nineteen semi-structured interviews) and a confirmatory quantitative phase (a questionnaire administered to eighty respondents, processed using PLS-SEM). The results confirm that artificial intelligence significantly improves the quality of intelligent dashboards (β = 0.846), which in turn strengthens the decision-making performance of management control (β = 0.397); data quality also exerts a direct and significant effect on this performance (β = 0.486), with the model explaining respectively 71.5% and 60.9% of the variance of intelligent dashboards and of decision-making performance. On the other hand, no significant moderating effect of data quality is observed, and the mediation of dashboards between AI and performance remains partial and conditional. These results indicate that artificial intelligence does not act on performance automatically: its value depends on its articulation with reliable data, suitable steering tools and the digital skills of users.