Because artificial intelligence (AI) increasingly mediates organizational work, fairness has become a critical governance challenge. Existing frameworks often prioritize abstract ethical principles rather than fairness-specific ones and lack actionable guidance across the entire AI lifecycle. This study addresses the principles-to-practice gap in AI fairness governance. We develop actionable AI fairness practices and draw on a socio-technical and praxiological lens, conducting discourse and thematic analyses of 60 academic, policy, and practitioner sources. From these analyses, we derive a structured set of AI fairness practices in a comprehensive, AI lifecycle-spanning matrix organized by obligation degree and organizational role. The matrix provides dynamic, role-specific guidance to support implementation and sustainment of AI fairness. By extending the AI fairness beyond abstract principles to operationalized, actionable practices, we contribute to IS scholarship and offer a modular governance scaffold.

翻译：由于人工智能（AI）日益介入组织工作，公平性已成为关键的治理挑战。现有框架往往优先考虑抽象的伦理原则而非公平性具体原则，并且在整个AI生命周期中缺乏可操作的指导。本研究旨在弥合AI公平治理中从原则到实践的差距。我们开发了可操作的AI公平实践，并采用社会技术视角与实践论视角，对60篇学术、政策及从业者来源的文献进行了话语分析与主题分析。基于这些分析，我们归纳出一套结构化的AI公平实践，并以覆盖整个AI生命周期的综合矩阵形式呈现，该矩阵按义务程度与组织角色进行划分。该矩阵提供了动态、特定角色的指导，以支持AI公平性的实施与维护。通过将AI公平性从抽象原则拓展为可操作、可实施的实践，我们为信息系统（IS）学术研究做出贡献，并提供了一个模块化的治理框架。