Artificial intelligence has become a foundational component of modern business analytics, transforming how organizations make decisions across domains from human resources to customer engagement. This article examines the ethical challenges inherent in AI-driven decision systems, particularly concerning bias, transparency, and accountability. As these technologies increasingly determine business outcomes, organizations must incorporate ethical design principles to ensure fairness and explainability. We present a comprehensive framework for ethical AI analytics that encompasses technical architecture, governance structures, and organizational workflows. This article demonstrates practical methods for bias detection, model documentation, and stakeholder engagement, while addressing the tension between innovation and responsibility. By implementing these ethical design principles, organizations can build more trustworthy analytics systems that align with regulatory requirements and societal expectations while maintaining a competitive advantage.
Keywords: Business Ethics, Responsible AI, algorithmic fairness, decision transparency., explainable analytics
