Artificial Intelligence & Leadership: Toward a Novel Approach to Risk Prevention

Abstract

This study investigates the impact of artificial intelligence (AI) adoption on proactive risk prevention, while examining the role of intelligent leadership in this relationship. Grounded in a socio-technical perspective, the research assumes that organizational performance emerges from the interaction between technological capabilities and human factors.

Using a quantitative approach, data were collected from 80 managers involved in AI integration within organizations located in the Agadir region and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that AI adoption has a positive and significant effect on proactive risk prevention, enhancing organizations’ ability to anticipate threats and reduce decision-making uncertainty.

Additionally, AI adoption positively influences intelligent leadership, reflecting a shift toward data-driven and adaptive managerial practices. However, the effect of intelligent leadership on proactive risk prevention is not significant, thereby rejecting its mediating role.

These results suggest that AI primarily acts as a direct driver of proactive risk management, rather than through leadership transformation. The study contributes theoretically by highlighting AI as an autonomous informational capability that strengthens organizational resilience, and managerially by emphasizing the importance of effectively integrating AI into decision-making processes. Finally, it provides empirical evidence from an underexplored emerging economy context.

Classification JEL: O33, M15, G32,

Paper type: Empirical Research