International Journal of Science, Engineering and TechnologyAuthors: Ashok V. Pillai
Abstract: In today’s complex regulatory landscape, organizations face increasing pressure to maintain continuous compliance and ensure audit readiness across multiple domains, including finance, healthcare, and IT. Traditional manual approaches to compliance management relying on human oversight, documentation, and periodic reviews are often labor-intensive, error-prone, and insufficient to meet the demands of dynamic operational environments. AI-based compliance automation has emerged as a transformative solution, leveraging advanced technologies such as machine learning, natural language processing, predictive analytics, and robotic process automation to monitor, enforce, and optimize compliance processes continuously. AI-driven systems enable real-time monitoring of policies and controls, automated detection of deviations, and predictive identification of potential compliance risks. They also facilitate automated generation of audit-ready documentation, ensuring that organizations can respond efficiently to internal and external audits. By reducing reliance on manual processes, AI-based compliance automation improves accuracy, enhances operational efficiency, and strengthens organizational risk management. Case studies demonstrate measurable improvements in audit readiness, faster response times, and enhanced regulatory adherence across various industries. This review highlights the critical role of AI-based compliance automation in enhancing regulatory audit readiness, reducing operational risk, and enabling proactive, adaptive compliance strategies. It provides a comprehensive understanding of the benefits, challenges, and future directions of AI-driven compliance systems, offering valuable insights for compliance officers, IT managers, auditors, and researchers seeking to implement robust, audit-ready governance frameworks.
