Advancing Cloud-Based Automation: The Integration of Privacy-Preserving AI and Cognitive RPA for Secure, Scalable Business Processes
Keywords:
Cognitive RPA, Cloud-Based Automation, AI-driven automation, Explainable AI (XAI), Intelligent Decision-Making, Machine Learning, Business Process Optimization, AI GovernanceAbstract
This review integrates privacy-preserving AI with Cognitive Robotic Process Automation (RPA) to improve secure and scalable cloud-based automation. Cognitive RPA, based on artificial intelligence and machine learning, can make intelligent decisions and automate complex business processes. Privacy-preserving AI techniques, such as federated learning, differential privacy, and encryption, ensure data security and compliance with regulatory standards. The study examines the benefits, implementation strategies, and challenges of Cognitive RPA across various industries, highlighting the need for standardized AI governance frameworks. While AI-driven automation offers efficiency and security advantages, challenges such as high computational costs, regulatory compliance, and system integration remain key concerns. Future research should focus on developing explainable AI (XAI) frameworks, refining privacy-preserving mechanisms, and expanding real-world case studies to ensure ethical, transparent, and scalable automation solutions.
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