This article reflects on how sociology can analyse the role of artificial intelligence (AI) in scientific practice without buying into the current AI hype. Drawing on sensibilities developed in actor-network theory (ANT) it introduces the concept of agencing (agency as a verb) which refers to how scientists debate and configure the human and machine agency. It suggests that we can come to a more nuanced understanding of the effects of AI in science by attending to actors’ agencing practices. By discussing three ideal types of agencing, the article argues that AI should not be regarded as a rupture in the tooling and practices of science, but rather as a continuation of long-standing patterns of practice. That is, agency, and the space for action and judgement, is organised differently in the AI-driven laboratory; however, this is not a new configuration of epistemic agency. Rather we might understand these changes as building on statistical epistemic configurations going back to the birth of statistics in sociology in the 1700s and 1800s.