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Organising public sector AI adoption: Navigating between separation and integration

In this article, Friso Selten and Bram Klievink explore how public organisations strategically manage the adoption of AI. Artificial Intelligence (AI) has the potential to improve public governance, but the use of AI in public organisations remains limited.

Friso Selten & Bram Klievink
01 March 2024
Read the full article here

Managing AI adoption in the public sector is complex because of the inherent tension between public organisations' identity, characterised by formal and rigid structures, and the demands of AI innovation that require experimentation and flexibility. Friso Selten and Bram Klievink findings show that public organisations navigate this tension either by creating separate departments for data science teams, or by integrating data science teams into already existing operational departments.

The case studies reveal that separation improves the technical expertise and capabilities of the organisation, whereas integration improves the alignment between AI and primary processes. The findings also show that both approaches are characterised by different AI adoption barriers. The article empirically identifies the processes and routines public organisations develop to overcome these barriers.

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