Rethinking Leadership Decision Quality in AI-Augmented Strategic Business Environments: Toward an Integrated Multidisciplinary Framework
Abstract
Artificial intelligence (AI) is increasingly embedded in strategic business decision-making through predictive analytics, pattern recognition, forecasting, generative AI, and decision support systems. These capabilities expand organisational analytical capacity, but analytical capacity does not by itself constitute strategic decision quality; strategic decisions also require contextual interpretation, leadership judgment, appropriate reliance on AI, accountability, and adaptation under uncertainty. This conceptual study addresses a mechanism gap in the literature by developing an integrated framework explaining how AI-generated analytical capability can be converted into strategically meaningful managerial decisions through Human–AI Decision Integration. The framework integrates Upper Echelons Theory, Behavioral Decision Theory and bounded rationality, and Sociotechnical Systems Theory. It positions Leadership Judgment and Leader AI Literacy as human capabilities; Calibrated Trust and Explainability as intera
