Published Paper Details:

The increasing demand for automation in enterprise environments has driven extensive research into intelligent workflow management systems that integrate Artificial Intelligence (AI), Reinforcement Learning (RL), and cloud-based solutions. This review paper systematically examines ten significant studies addressing various aspects of workflow automation, including AI-driven orchestration, adaptive Robotic Process Automation (RPA), ethical AI integration, cloud-based Business Process Management (BPM), and generative AI- based workflow design. The reviewed literature highlights the transformative potential of AI in enhancing process adaptability, decision-making accuracy, and operational efficiency across domains such as customer service, IT support, digital forensics, and education. Reinforcement Learning, in particular, emerges as a key enabler for self-optimizing and context-aware automation capable of continuous learning and improvement. However, challenges related to data privacy, system interoperability, ethical governance, and workforce adaptation remain major barriers to widespread adoption. This review contributes a unified understanding of how reinforcement learning and intelligent automation frameworks can collaboratively redefine digital workflows, paving the way for more responsive, efficient, and ethically aligned enterprise operations.