Responsible AI governance in Enterprise Systems: A Risk and Compliance Framework

Abstract

Artificial Intelligence deployment in enterprise environments has accelerated dramatically, yet governance frameworks struggle to keep pace with the technology's rapid evolution. This research develops a comprehensive risk and compliance framework specifically designed for responsible AI governance in enterprise systems. The study addresses critical gaps where organizations implement AI solutions without adequate oversight mechanisms, creating substantial regulatory, ethical, and operational risks. Through analysis of existing governance models and emerging regulatory requirements, we propose a multi-layered framework that integrates risk assessment, compliance monitoring, and ethical oversight into enterprise AI operations. The framework emphasizes practical implementation within existing corporate governance structures rather than creating parallel oversight systems. Our approach balances innovation enablement with appropriate controls, recognizing that overly restrictive governance inhibits beneficial AI adoption while insufficient oversight creates unacceptable risks. The research demonstrates how enterprises can establish systematic governance processes that ensure AI systems operate responsibly, comply with evolving regulations, and align with organizational values. This work contributes both theoretical frameworks for understanding AI governance challenges and actionable guidance for implementing effective oversight in diverse enterprise contexts.