Predicting the future via a cycle of data acquisition, analysis, and insight extraction increasingly defines the practice of business intelligence (BI), traditionally conceived of as the use of data analytics to aid organizational decision making. With the addition of artificial intelligence into BI, the practice of data-driven insight generation has become ‘augmented’ launching a spectrum of opportunities for human-machine collaboration commonly referred to as augmented analytics. The proposed research project is designed to investigate how business intelligence is changing at the level of work practice, worker skill, and technology design in relation to increased augmentation by AI. It is organized as a set of four integrated, ethnographic case studies. The first phase of the project will establish an empirical base regarding the work practice of BI practitioners, the way that the BI work varies when situated in different organizational contexts and workflows, the sociotechnical skills that define BI work practices, and the way BI analysts accommodate AI when it is embedded into tools and processes. The final phase will synthesize the project via a series of engagements with designers and developers as well as BI educators.