Artificial Intelligence (AI) is transforming modern supply chain management through predictive analytics, automation, demand forecasting, route optimization, procurement intelligence, and risk management. While AI enhances operational efficiency, cost reduction, and responsiveness, it also poses significant ethical challenges. AI-driven supply chain decisions may suffer from algorithmic bias, lack of transparency, privacy violations, workforce displacement, and sustainability tradeoffs. The increasing reliance on automated decision-making systems demands a structured ethical framework to ensure fairness, accountability, and responsible governance. This study examines the ethical implications of AI integration in supply chain decisions and proposes a structured ethical evaluation framework based on transparency, fairness, accountability, sustainability, and human oversight. This study uses conceptual analysis supported by secondary data from industry reports and academic research to evaluate the ethical risks and mitigation strategies in procurement, logistics, demand forecasting, and supplier selection. The findings suggest that ethically governed AI systems improve stakeholder trust, enhance compliance, reduce reputational risks, and strengthen long-term resilience. Organizations adopting responsible AI governance models outperform competitors in sustainable supply chain performance. The study concludes that AI ethics must be embedded into strategic supply chain planning rather than treated as a compliance requirement.