In the contemporary business environment marked by digital transformation, artificial intelligence (AI) has emerged as a disruptive force capable of reconfiguring traditional processes through business process re-engineering (BPR). The integration of AI into BPR allows organizations to redesign workflows, optimize efficiency, reduce redundancy, and improve decision-making accuracy. Traditionally, BPR sought radical organizational change by rethinking core business functions from the ground up. Today, AI acts as an enabler of that transformation by bringing automation, predictive analytics, natural language processing, and machine learning to the forefront of strategic operations. Through intelligent data processing and self-learning systems, AI enables the continuous monitoring and improvement of processes that were once static. AI-based tools such as robotic process automation (RPA), neural networks, and decision support systems have redefined operational models by removing human limitations and minimizing errors. Moreover, AI not only accelerates re-engineering but also provides adaptive frameworks for dynamic business environments where agility and responsiveness determine competitiveness. This study examines the convergence of AI and BPR in achieving organizational excellence, focusing on how AI redefines process redesign, enhances workflow optimization, and introduces data-driven innovation into managerial practices. The objective is to understand the mechanisms through which AI enhances process intelligence, reduces operational friction, and aligns business functions with strategic goals. The findings highlight how AI-driven re-engineering contributes to sustainable competitive advantage, cost reduction, and improved customer satisfaction across multiple industries. The paper concludes that AI is no longer a supportive tool but a central driver of radical process transformation, pushing organizations toward a future of cognitive automation and intelligent process design.