Paper Type
ERF
Abstract
AI is increasingly embedded in public sector operations, reshaping policy development, service delivery, and administrative decision-making. While governments promote frameworks for “trustworthy” and “responsible” AI, little is known about how governance evolves as employees integrate AI into everyday work. This study examines the co-evolution of AI governance and organisational control within a public organisation. Drawing on a socio-technical perspective, we conceptualise governance as a dynamic interplay between frontline AI use and managerial responses. An interpretive qualitative single-case study was conducted in a Kenyan public organisation, based on sixteen semi-structured interviews across hierarchical levels. Findings reveal a pronounced governance–practice gap: generative AI adoption emerged bottom-up, leading to widespread “shadow AI” use, while formal controls lagged behind. Governance was adapted incrementally through strengthened human oversight and informal managerial guidance, while accountability remained firmly human-centred. The study highlights responsible AI integration as an adaptive organisational process rather than a static compliance exercise.
Paper Number
1863
Recommended Citation
Jonathan, Gideon Mekonnen; Kuika Watat, Josue; Aasi, Parisa; and Ayeni, Foluso, "Bridging the Governance-Practice Gap: A Socio-Technical Study of AI Co-evolution" (2026). AMCIS 2026 Proceedings. 22.
https://aisel.aisnet.org/amcis2026/sig_osra/sig_osra/22
Bridging the Governance-Practice Gap: A Socio-Technical Study of AI Co-evolution
AI is increasingly embedded in public sector operations, reshaping policy development, service delivery, and administrative decision-making. While governments promote frameworks for “trustworthy” and “responsible” AI, little is known about how governance evolves as employees integrate AI into everyday work. This study examines the co-evolution of AI governance and organisational control within a public organisation. Drawing on a socio-technical perspective, we conceptualise governance as a dynamic interplay between frontline AI use and managerial responses. An interpretive qualitative single-case study was conducted in a Kenyan public organisation, based on sixteen semi-structured interviews across hierarchical levels. Findings reveal a pronounced governance–practice gap: generative AI adoption emerged bottom-up, leading to widespread “shadow AI” use, while formal controls lagged behind. Governance was adapted incrementally through strengthened human oversight and informal managerial guidance, while accountability remained firmly human-centred. The study highlights responsible AI integration as an adaptive organisational process rather than a static compliance exercise.
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