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Artificial intelligence (AI) is increasingly portrayed as a disruptive force and is often integrated into organizational routines as part of broader digitalization efforts across organizations in different industries in order to transform work practices and improve decision-making. While previous research has highlighted the anticipated effects of algorithms on organizational routines as well as how their use affects the performance of routines, less attention has been devoted to understanding how AI influences routines design, that is, the intentional change of routines, particularly in cases where algorithms and AI technologies are simultaneously developed and implemented as part of the change process.

Drawing on Routine Dynamics and adopting a processual perspective, this thesis develops a deeper understanding of AI’s influence on the design of organizational routines, particularly in situations where the development of machine learning algorithms and integration of AI technologies are central to routine change. This is done based on a longitudinal ethnographic study of a routine design case in which an AI software company and an electricity distribution utility company engaged in an AI digitization project aimed at transitioning from manual to virtual inspection of overhead powerlines using drones and AI.

The analysis of this case shows that routine design unfolds through a broadly distributed sociomaterial assemblage spanning multiple organizational and spatiotemporal boundaries, involving a range of human and nonhuman actors. The routine design process is therefore conceptualized as a distributed algorithmic routine design, characterized by iterative design actions for preparing, repairing, and post-pairing the routine under design. Through these actions, actors are specifically engaged in developing algorithms while simultaneously orchestrating the sociomaterial assemblage required to make AI function in practice. The study further identifies design disjunctures as emergent sociomaterial challenges that reveal tensions, misalignments, and coordination difficulties across the design assemblage.

The thesis contributes to Routine Dynamics research by showing that designing routines with AI is not merely a matter of developing and integrating artifacts. Rather, it involves unpacking and continuously orchestrating the distributed sociomaterial assemblage through which AI’s agency is enacted and sustained over time. This specifically requires aligning all heterogeneous elements that constitute the design assemblage and collectively enable its continuity and performance. In doing so, the study highlights the importance of attending to both visible and invisible forms of work, the balancing of continuity and discontinuity, material artifacts, and the emergence of intentionality within ongoing nonlinear design processes. Overall, this thesis advances understanding of how AI reconfigures routine design and highlights the complex ongoing sociomaterial work required for designing and implementing algorithmic routines.