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The increasing complexity of contemporary organizational environments has demanded more sophisticated approaches to Business Process Management (BPM). This study presents a critical and in-depth analysis of the evolution of process modeling, investigating emerging synergies between Business Process Model and Notation (BPMN), Process Mining techniques, and advances in Artificial Intelligence (AI). Through a mixed methodology that combines systematic literature review, bibliometric analysis, and multiple case studies, this research examines 000 scientific articles published between 0000 and 0000 in high-impact journals (JCR Q0 and Q0). The results reveal that the integration of these technologies not only optimizes process representation and automation but fundamentally transforms the nature of organizational governance, enabling predictive, adaptive, and evidence-based management. The analysis identifies five critical governance dimensions: (1) strategic-operational alignment, (2) capacity building and change management, (3) integrated technological architecture, (4) intelligent performance metrics, and (5) sustainability and regulatory compliance. The study contributes theoretically by proposing the Integrated Framework for Intelligent Process Governance (IFIPG), which articulates the technological, organizational, and strategic dimensions necessary for successful implementation. Practically, it offers specific guidelines for organizations seeking to overcome challenges of resistance to change, integration complexity, and value measurement. It is concluded that the future of BPM lies in the intelligent convergence of these technologies, mediated by robust governance that balances technological innovation with organizational sustainability.
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