Unpacking AI at work: Data work, knowledge work, and values work

The rise of data-driven artificial intelligence (AI) technologies has sparked intense debates about their implications for work. These discussions often portray AI as an agentic force that turns data into knowledge and ultimately, “better” decisions, casting shadows over the labor that sustains and supports these technologies. This paper argues that to develop a grounded understanding of how AI contributes to transformations in the workplace, we must unpack AI at work , that is, how algorithms are shaped by, and in turn, shape everyday work practices. Building on a longstanding tradition of research that examines the interplay between technology and work, this study foregrounds three types of work that gain renewed significance in the context of AI: data work, knowledge work , and values work . Drawing on the empirical example of hiring, this study illustrates how these forms of work are critical not only for understanding how AI technologies are brought to life but also for recognizing deeper, often unforeseen changes in the workplace. By surfacing the hidden, interrelated, and ever-evolving nature of work for AI, the AI at work lens put forward in this study offers critical implications for information systems and organizational research, as well as practical insights for practitioners, policymakers, and regulators. • Dominant AI narratives obscure the human labor that shapes and sustains these technologies. • Proposes an AI at work lens to unpack how algorithms are shaped by, and in turn, shape everyday work practices. • Data work, knowledge work, and values work gain new contours and significance in the context of AI. • An AI at work lens reveals the multifaceted, interrelated, and constantly evolving nature of work with AI.