Today’s businesses operations rely increasingly on commercial transactions that reside in complex networks of computer machines, software algorithms, and human actors. Their autonomous and intelligent characteristics suggest such socio-technical networks cannot be usefully explicated as passive tools or platforms. Neither can they be understood as manifestations of artificial intelligence because humans play a pivotal role in producing the digital traces that algorithms process. The emergence of these networks therefore instigates an urgent need to reframe past conceptualizations of machine intelligence. Seeking to engage in such theorizing, this project advances and substantiates a novel perspective on algorithmic agents by unpacking the socio-technical nature of algorithmic decision-making. While this perspective has important methodological implications for business intelligence and organizational metrics, it also paves a way for future studies of the managerial and ethical aspects of automated decision-making. This research is therefore highly relevant to scholars, practitioners, and funding agencies.