Interplay Among Sensegiving, Sensebreaking, and Sensemaking in Technology Adoption

Abstract

Artificial Intelligence (AI) is reshaping healthcare, offering transformative potential in diagnostics and patient care. Yet, its adoption disrupts established workflows and professional roles, necessitating alignment across multidisciplinary teams. This study explores how sensegiving, sensebreaking, and sensemaking interact through feedback loops during AI adoption in Dutch hospitals. Drawing on 28 interviews with doctors, nurses, and technicians across seven hospitals, we examine how the three processes evolve across three stages: initial adoption, integration into workflows, and ongoing optimization. Findings highlight the pivotal role of feedback loops among sensegiving, sensebreaking, and sensemaking in fostering mutual refinement and collaboration. While sensegiving strategies by doctors framed AI as a supportive tool, sensebreaking among nurses and technicians revealed tensions around role autonomy and operational fit. These tensions were addressed through dynamic, inclusive sensegiving approaches. By revealing how alignment evolves amidst professional role conflicts, this study provides actionable insights for managing disruptive technology adoption in hierarchical settings.

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