Authors - Nallappagari Venkatarami Reddy Abstract - Business Process Automation (BPA) has become an essential requirement of modern enterprise environments owing to the need for operational efficiency, process agility, and smart decision making. Traditional methods of BPA mostly depend on rules-based approaches which are not able to adapt to the needs of a dynamic environment as these methods do not incorporate the element of adaptive intelligence and autonomous orchestration. To overcome such limitations, this study aims to develop an intelligent orchestration framework named IWOF for Autonomous Business Process Automation. In the proposed solution, PIEL, AWOE, DRAM, and PDOU have been used. Also, two new algorithms named AWIO and PARDO are developed for optimizing the process sequencing, resource assignment, and decision support tasks respectively. Experimental evaluation was performed by applying the proposed framework to datasets consisting of processes related to employee onboarding, payroll management, procurement approvals, recruitment workflow, and finance transactions. With the help of the IWOF model, Process Automation Accuracy, Workflow Completion Rate, Resource Utilization Efficiency, and Autonomous Business Process Automation Score (ABPAS) were measured to be 98.7%, 98.2%, 97.1%, and 98.9%, respectively, surpassing all other available models such as OSMAS and BPA-SME.
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