This study examines how analytics maturity and AI governance are articulated as organizational capabilities that support trust in AI-driven and data-based decision-making. As organizations increasingly rely on artificial intelligence (AI) and advanced analytics, trust has become a critical concern, extending beyond technical performance to include reliability, responsibility, and institutional alignment. While existing research often treats analytics maturity as a linear progression and AI governance as a set of external constraints, this study adopts a configurational and capability-based perspective grounded in the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT).
Drawing on qualitative analysis of corporate website discourse from ten Swiss organizations across multiple industries, the study explores how AI applications, data infrastructures, governance mechanisms, and trust-related narratives are publicly communicated. The findings demonstrate that analytics maturity is not represented as a linear developmental path but as distinct configurations of interdependent resources, combining technical, organizational, and governance capabilities. AI governance emerges as an embedded organizational capability that supports trust by enabling reliability, accountability, and alignment with institutional expectations, rather than functioning solely as a compliance mechanism.
Trust is constructed differently across sectors, reflecting industry-specific logics such as clinical validation in healthcare, risk control in finance, data sovereignty in telecommunications, and operational safety in industrial and energy contexts. These findings highlight that trust in AI is not universal but context-dependent and institutionally embedded.
The study contributes by reconceptualizing analytics maturity as a configurational phenomenon, repositioning AI governance as an enabling capability, and demonstrating how trust is co-constructed through the alignment of organizational resources and institutional expectations. The results underline the importance for organizations to align technical capabilities with governance structures and communication practices to sustain trust in AI-enabled environments..