A SCALABLE AND ETHICAL FRAMEWORK FOR AI-AUGMENTED ROBOTIC PROCESS AUTOMATION

Robotic Process Automation (RPA) has become crucial for digital transformation in businesses. However, traditional RPA systems have issues with scalability, flexibility, and ethical standards. This paper introduces an AI-augmented RPA framework that brings together machine learning, process mining, and built-in governance into one structure. Unlike earlier approaches that handle these aspects separately, this model supports smart decision-making, improves workflows in real-time, and ensures compliant oversight across different industries. The framework is tested using various case studies, stakeholder surveys, and experiments based on simulations. Results show significant improvements in efficiency, fewer errors, better scalability, and more acceptances from the workforce. This study contributes to the conversation on intelligent automation by expanding the literature with a combined ethical-process mining model and offers practical advice for responsibly implementing AI-driven RPA.