HUMAN INTUITION AND INFORMATION SUPERIORITY IN AI-DRIVEN RISK ANALYSIS: A CONCEPTUAL FRAMEWORK FOR HYBRID STRATEGIC DECISION-MAKING

Abstract

The increasing adoption of artificial intelligence (AI) in risk analysis has significantly improved data processing, predictive modeling, and anomaly detection. However, its effectiveness in high-level strategic decision-making remains limited. This paper identifies a critical gap in the literature: the insufficient conceptualization of human intuition as a structured and operational component of risk management systems. Building on a practitioner-developed methodology, this study reconceptualizes risk management as a dynamic process of transforming uncertainty into strategic opportunity, enabled by information superiority and human-centered capabilities. The paper develops a hybrid intelligence framework that integrates AI-driven analytics with human intuition, organizational competence, and contextual interpretation. The findings contribute to both theory and practice by positioning human intuition not as a cognitive bias, but as a strategic asset essential for navigating complex, uncertain, and adversarial environments.