Generative Artificial Intelligence and Data Governance: Challenges and Frameworks in Enterprise Applications

This study examines generative artificial intelligence (GenAI) adoption in enterprise settings, analyzing critical risks across four dimensions. The analysis emphasizes the imperative for systematic data governance in GenAI systems and establishes the necessity of constructing enterprise-specific governance frameworks. Through a lifecycle-oriented examination of GenAI implementation, we identify seven core governance components. Building upon established data governance frameworks, we propose an Enterprise GenAI Data Governance Framework that integrates technical controls with organizational policies. This framework aims to address unique challenges in generative model deployment while maintaining compliance with evolving AI regulations.