ABSTRACT Governing Artificial Intelligence (AI) is difficult, in part, because AI systems never stand still in any one place. They are usually made by private companies, hidden within proprietary infrastructures, spanning jurisdictions, behaving in ways that are difficult to predict, and talked about in messy discourses of hype and panic. I suggest here that all this dynamism and uncertainty could be tackled by understanding AI and its governance as multi-scalar phenomena.