Three Layers of Trust in AI Interfaces: Interface, Behavior, and Organization

As artificial intelligence (AI) systems become deeply integrated into sectors such as healthcare, finance, and autonomous services, establishing and maintaining user trust has emerged as a critical determinant of system adoption and sustained engagement. Despite increasing attention to trust in AI, existing models often treat it as a singular construct, neglecting the multifaceted ways in which user interfaces shape the perception and evolution of trust. This paper introduces a novel three-layered model of trust in AI interfaces- Interface Trust, Behavior Trust, and Organizational Trust-to reflect the dynamic and layered nature of trust formation. Drawing upon interdisciplinary literature and domain-specific case studies in healthcare and finance, we demonstrate how the AI interface serves as the primary channel through which users engage with system logic, evaluate behavior, and perceive organizational credibility. Through this model, we argue that trust begins with interface design and transparency, is sustained through reliable AI behavior, and is ultimately anchored in the perceived integrity and accountability of the organization behind the system. This paper provides theoretical foundations and practical design guidelines to foster trust across these three layers, offering insights into how trust can be engineered, measured, and maintained throughout the lifecycle of AI-human interaction.