The rapid advancement of Artificial Intelligence (AI) has fundamentally reshaped the landscape of modern management, offering unprecedented opportunities for organizational transformation. This article proposes a comprehensive framework that integrates AI into management practices to drive innovation, facilitate knowledge creation, and ensure long-term business sustainability. Drawing on a synthesis of contemporary literature and empirical case studies, the framework identifies three interconnected pillars: (1) AI-enhanced decision-making and process automation as catalysts for operational and strategic innovation; (2) AI-driven knowledge management systems that enable the capture, codification, and dissemination of tacit and explicit knowledge across organizational boundaries; and (3) the strategic alignment of AI capabilities with sustainability goals, encompassing economic viability, social responsibility, and environmental stewardship. The article argues that successful AI integration extends beyond technological adoption; it requires adaptive leadership, a culture of continuous learning, and ethical governance to address challenges such as algorithmic bias, data privacy, and workforce displacement. Furthermore, the framework emphasizes the dynamic feedback loops among innovation, knowledge, and sustainability, suggesting that AI not only optimizes existing routines but also generates novel insights that feed forward into future strategic initiatives. The findings offer practical guidance for managers seeking to harness AI's transformative potential while mitigating its risks. Ultimately, this framework contributes to both academic discourse and managerial practice by providing a structured approach to navigating the complexities of AI-enabled management in an era of accelerating digital disruption and growing stakeholder demands for responsible business conduct.
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