As Artificial Intelligence (AI) systems increasingly inform mission-critical decisions across enterprises, the need for robust, ethics-centric AI governance grows exponentially. Traditional IT governance frameworks fail to address ethical challenges such as algorithmic bias, transparency gaps, accountability failures, privacy violations, and stakeholder harm. This research develops a comprehensive understanding of ethical models for enterprise AI governance by integrating principles from ethics, organizational management, socio-technical theory, and regulatory policy. A multi-dimensional Ethics-Centric AI Governance Framework (ECAIGF) is proposed, supported by conceptual diagrams, governance cycle models, and a responsibility matrix. The study highlights the necessity of aligning enterprise values, regulatory compliance, human oversight, explainability, and risk mitigation mechanisms. Recommendations for practical enterprise adoption and future research directions are also provided.