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Artificial Intelligence (AI) has precipitated a profound reconfiguration of strategic management and operational efficacy by endowing contemporary business organizations with the capacity for data-driven decision making (DDDM). With a combination of high-tech analytics, machine-learning (ML) algorithms, and thought-processing, AI provides the executive leaders with the means to consume complex data, extract actionable data, and, consequently, enhance the quality of decisions made by the managers. This paper presents an empirical study of AI technologies, considering their strength to enhance evidence-based decision-making, enhance governance structures, and develop adaptive learning in organizations. Based on empirical research and theoretical definitions, the analysis outlines the provisions of AI in complementing managerial judgments, enabling real-time responsiveness, and improving the accuracy of the strategic planning process. The discussion argumentatively challenges the technological, behavioural, and ethical aspects of AI implementation, highlighting the centrality of data-driven intelligence in increasing the organizational culture and leadership behaviour. Based on the paradigms of human-AI symbiosis and predictive decision making, the manuscript states a conceptual framework that proves how AI has the potential to boost managerial thinking and reduce information asymmetries. The study highlights the inherent worth of a human-AI collaboration by stating that although AI can expedite the accuracy of the decisions made, its effectiveness in the long term is determined by accountable integration, algorithm transparency, and effective mechanisms of continuous learning. Finally, it is proposed that <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{A I}$</tex> is not only the computational device, but an inseparable strategic business partner, which can support the inclusive, well-regulated, and evidence-based management practice.