<p>Artificial intelligence (AI) is increasingly applied to enable circular economy (CE) models by optimizing resource use, product design, waste management, and recycling. However, alongside potential environmental and economic benefits, the deployment of AI in circular systems raises significant ethical concerns that can influence real-world adoption of CE principles. This review critically examines key ethical issues at the intersection of AI and the CE, drawing on recent literature, case studies, and policy frameworks. We identify and discuss themes including algorithmic transparency and explainability, data privacy and bias, impacts on labor and employment, social inclusion and fairness, responsible AI deployment, and the role of human-in-the-loop oversight. We synthesize insights from academic studies, industry examples, and governance initiatives (e.g. the EU AI Act and OECD AI Principles) to illuminate how these ethical challenges affect the implementation of circular economy practices. Our analysis finds that issues like opaque algorithms, biased data, workforce displacement, and unequal access can undermine trust and equity in AI-driven circular solutions, thereby impeding their societal acceptance. Conversely, emerging principles of responsible AI—emphasizing transparency, accountability, fairness, and human oversight—offer pathways to mitigate risks and foster more inclusive, trustworthy circular economy transitions. The review concludes with recommendations for policymakers, organizations, and practitioners on aligning AI ethics with circular economy goals, highlighting the need for interdisciplinary collaboration to ensure that AI contributes to a sustainable and just circular future.</p>