Much of the discourse on AI ethics has focused on technical improvements and holding individuals accountable to prevent accidents and malicious use of AI. While this is useful and necessary, such an “agency-focused” approach does not cover all the harmful outcomes caused by AI. In particular it ignores the more indirect and complex risks resulting from AI’s interaction with the socio-economic and political context. A “structural” approach is needed to account for such broader negative impacts where no individual can be held accountable. This is particularly relevant for AI applied to systemic issues such as climate change. This talk explains why a structural approach is needed in addition to the existing agency approach to AI ethics, and offers some preliminary suggestions for putting this into practice.