Comparative Analysis of Traditional and AI-Driven Data Governance: A Systematic Review and Future Directions in IT

Abstract

In this context, this paper aims to offer a systematic review of data governance with a specific focus on the traditional approach to data management and the AI-based approach. The second paper reviews advancements in data governance frameworks, concurring with the importance of stringent control where data volume and variability are rising. The literature review also discusses core concepts tied to conventional governance frameworks, focusing on how AI revolutionizes data handling. By comparing the cases, the study points to how AI offers fresh opportunities regarding data governance responsibilities, productivity, and issues such as real-time data management. Finally, the review brings out the key conclusions on the subject matter, culminating in exploring how AI integrates reliability, conformity, and the lifelong management of data for organizations.