Resistance to Change as a Diagnostic Insight: An Interdisciplinary Examination of Stakeholder Opposition to AI in Primary Care

Abstract

As artificial intelligence (AI) systems become more integrated into healthcare, understanding the roots of resistance is essential, particularly in complex, value-driven settings like primary care. This interdisciplinary study explores stakeholder resistance to AI through interviews with global experts in organizational transformation and resistance to change (RtC). It identifies three interconnected forms of resistance—logical, sociological, and psychological—each linked to specific concerns around ethics, professional identity, and systemic fit. Unlike prior work, this study centers RtC experts’ insights on AI resistance in primary care, a setting often excluded from co-design. Using a qualitative abductive approach, the research highlights resistance as a form of critical feedback and a mechanism for building trust. These findings inform more inclusive, reflexive, and context-sensitive strategies for embedding AI ethically within health systems.