While substantial work has been done on establishing ethical principles for AI, there remains a critical gap between theoretical frameworks and organizational implementation, particularly in sensitive domains such as human resources (HR). This chapter examines how organizations operationalize AI ethics in HR through an in-depth analysis of published research and empirical case studies. Drawing from studies of HR departments implementing AI systems, we explore the practical challenges, governance mechanisms, and organizational responses in embedding ethical considerations into HR analytics projects. The chapter reveals that while organizations are increasingly aware of AI ethics issues, their implementation of mitigation strategies tends to be limited and varies significantly based on the organizational context, oversight structures, and external regulations. Key findings highlight the crucial role of governance structures, the impact of professional backgrounds on ethical decision-making, and the effectiveness of different oversight mechanisms over time. This chapter contributes to bridging the theory-practice gap in AI ethics by providing evidence-based insights into successful implementation strategies and common pitfalls. It concludes with practical recommendations for organizations seeking to develop responsible AI practices in HR, emphasizing the need for robust governance frameworks, continuous ethical deliberation, and adaptive oversight mechanisms.