AI-Driven Ethical Compliance in Hyper Automation: Building Transparent RPA Systems for Regulatory Adherence

This paper focuses on the ethical compliance of AI, RPA, and blockchain in hyper automation system. It presents machine learning models for deploying real time prediction of regulatory risk and presents the architecture of a cloud integrated, blockchain expands framework to develop transparent and auditable RPA systems. In healthcare and finance, the tradeoff between automation efficiency and compliance needs is sectorally analyzed, and the analysis delineates reasons for aspirations of safe places for pockets of privacy from the lure of high profits from commercialization. Using an ethical design and governance approach, a methodology combining AI architecture is offered for responsible automation in the study. The research makes a contribution to the development of secure, accountable hyper automation systems required to support regulated, high stakes industries by addressing transparency, traceability, and risk mitigation.