Paper Type
Short
Paper Number
PACIS2026-1711
Description
This study examines how self-service analytics (SSA) and artificial intelligence (AI) interact synergistically to enable data democratization for data-informed decision-making. Drawing on systems theory, we develop a conceptual framework explaining how synergy emerges when SSA and AI systems interact through functional symbiosis and sociotechnical intermediation, giving rise to an AI-driven SSA ecosystem that enables data democratization and data-informed decision-making. The framework identifies trust in data as a cognitive enabler moderating the relationship between strategic intent for data use and the emergence of the AI-driven SSA ecosystem, while trust in analytics as a cognitive filter moderating the relationship between the AI-driven SSA ecosystem and data democratization for data-informed decision-making. Extending systems theory, the study contributes by highlighting cognitive conditions shaping ecosystem emergence and democratization outcomes while also contributing to data democratization literature by conceptualizing SSA and AI as interdependent components that jointly enable data democratization and data-informed decision-making.
Recommended Citation
Patabandige, Gayani; Naseer, Humza; Trieu, Van Hau; Black, Stuart; and Cooper, Vanessa, "Synergy of Self-service Analytics and AI for Data Democratization" (2026). PACIS 2026 Proceedings. 8.
https://aisel.aisnet.org/pacis2026/data_analtyics/data_anltics/8
Synergy of Self-service Analytics and AI for Data Democratization
This study examines how self-service analytics (SSA) and artificial intelligence (AI) interact synergistically to enable data democratization for data-informed decision-making. Drawing on systems theory, we develop a conceptual framework explaining how synergy emerges when SSA and AI systems interact through functional symbiosis and sociotechnical intermediation, giving rise to an AI-driven SSA ecosystem that enables data democratization and data-informed decision-making. The framework identifies trust in data as a cognitive enabler moderating the relationship between strategic intent for data use and the emergence of the AI-driven SSA ecosystem, while trust in analytics as a cognitive filter moderating the relationship between the AI-driven SSA ecosystem and data democratization for data-informed decision-making. Extending systems theory, the study contributes by highlighting cognitive conditions shaping ecosystem emergence and democratization outcomes while also contributing to data democratization literature by conceptualizing SSA and AI as interdependent components that jointly enable data democratization and data-informed decision-making.
Comments
05-DataAnalytics