Perspective Chapter: Bridging the Principle-Practice Gap in AI Ethics – The Institutional Coupling Framework

Despite the widespread adoption of artificial intelligence (AI) ethics principles by major technology companies, governments, and international organizations, a persistent “principle-practice gap” remains: ethical commitments rarely translate into substantive changes in how AI systems are designed, deployed, and governed. This chapter proposes a novel theoretical framework – the Institutional Coupling Framework – to explain when and why AI ethics initiatives succeed or fail. Drawing on organizational institutionalism, I conceptualize ethics implementation as a problem of structural integration, where the degree of coupling between ethics structures and production systems determines outcomes. I introduce four dimensions of coupling (authority, resources, incentives, and timing) and develop six formal propositions predicting implementation success. The framework explains why organizations with clear principles and adequate tools still fail (structural decoupling), identifies a critical coupling threshold below which ethics becomes predominantly symbolic, and generates specific, testable predictions about which interventions work. This represents a shift from asking “what should ethical AI look like?” to “under what organizational conditions does ethics actually shape AI development?” The framework provides diagnostic tools for practitioners, identifies high-leverage intervention points, and offers guidance for regulators seeking to move beyond symbolic compliance.