Now is the time to have a serious conversation between two particular domains that have typically operated in isolation: experts in sustainability and experts in AI. Moreover, although on some points, their perspectives and understandings of the problems they confront are likely to differ, the perils we face demand that we find common ground: on how to talk about AI use in energy, agriculture, or logistics, on how to operationalize cross-cutting values, including ethical principles and environmental mandates, on how to ensure meaningful stakeholder engagement and how to trigger public deliberation that takes account of both area experts’ and data specialists’ viewpoints. The intersection of AI and sustainability is a point of relevance for the implementation of each of the selected causes and complications. However, some of them carry a more prominent AI dimension. It is those cybersecurity, ethics, and human mitigation that can cause particularly great technological difficulties or negative consequences. On the other hand, when considering energy efficiency or development distribution, the dimensions of the issues pertaining to the scope, scale, or extent of usage of the novel technologies are more related to unexpected, emergent, or cascading effects. The complexity of the ideas and systems currently needs to be better articulated for the community of sustainability experts, stakeholders, and beneficiaries. There are risks and overlooked capabilities associated with them that have not traditionally been part of the conversation within sustainability domains.