Mapping and Mitigating the Pains of Responsible Artificial Intelligence Implementation: An Analysis of Swiss Organizations

Abstract

Despite the proliferation of Responsible Artificial Intelligence (RAI) principles, organizations struggle to translate them into practical implementation. This study investigates the challenges Swiss organizations face in implementing RAI through qualitative interviews with industry professionals and academic experts, complemented by a multi-stakeholder workshop. We first identify five critical pain points hampering RAI implementation: economic constraints, structural and procedural barriers, conceptual and technical challenges, cultural and behavioral resistance, and regulatory uncertainty. Then we propose the Control-Tangibility Framework, a novel framework that maps pain points along two fundamental dimensions: organizational control and challenge tangibility. Our framework provides organizations with a structured methodology to prioritize RAI efforts by considering both their ability to influence change and their capacity to observe aspects of the challenges. Furthermore, we provide practical insights for developing targeted implementation strategies that bridge the gap between ethical principles and operational practices. Our findings suggest that successful RAI implementation requires moving beyond compliance-focused approaches toward a comprehensive organizational transformation, supported by systematic assessment and prioritization of implementation challenges.

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