Abstract
The integration of artificial intelligence (AI) into project management is reshaping organizational capabilities by enhancing decision-making, automating routine tasks, and optimizing resource allocation. However, this technological transformation also brings a host of ethical challenges that threaten to undermine trust, transparency, and accountability. Key concerns include algorithmic bias, opacity in decision-making processes, and the erosion of human oversight. Although global ethical frameworks such as those proposed by the EU, OECD, and IEEE offer foundational guidance, they often lack the operational specificity required for application within the dynamic and context-sensitive environment of project management. This paper contends that addressing these shortcomings necessitates a transition from abstract ethical principles to tangible, enforceable mechanisms. Focusing specifically on ethical auditing, this study explores how systematic assessments can be employed to identify, evaluate, and mitigate ethical risks throughout the AI project lifecycle. Drawing upon recent literature and case studies, this paper proposes a multi-dimensional ethical audit model designed for the unique demands of project-based work. By translating normative values into concrete evaluation criteria, ethical audits serve as both diagnostic and preventive tools that can support responsible AI deployment. The paper further emphasizes the critical role of interdisciplinary collaboration in designing audit processes that are context-aware and culturally responsive.