Organisational AI Readiness for Public Administration: A Comprehensive Review and Framework for Conceptual Modelling

Matej Babsek, Eva Murko and Aleksander Aristovnik

International Journal of Economics & Business Administration (IJEBA), 2025, vol. XIII, issue 3, 24-47

Abstract: Purpose: The aim of this paper is to assess existing artificial intelligence (AI) readiness models and to propose foundational starting points for developing a comprehensive organisational AI readiness model specifically tailored to public administration. Design/Methodology/Approach: An analysis of the models of organisational readiness for AI in 24 identified sources from the original database was conducted using the systematic literature review approach according to the PRISMA protocol. The analysis focused on identifying gaps in current AI readiness models and frameworks, with a particular focus on the requirements of public administration. Findings: The systematic review revealed that the existing models largely ignore important elements such as strategies, products/services and the socio-political environment. The proposed framework integrates these dimensions and emphasises secure IT infrastructure, workforce adaptability, citizen engagement, transparency and collaboration between government sectors. Practical Implications: The proposed framework provides a practical guide for integrating AI into organisational workflows. Public administrations can apply this model by aligning AI initiatives with strategic goals and ensuring the involvement of key stakeholders, including executives, IT experts, and policy makers. Originality/Value: The study highlights the limitations of current models, extends the theoretical understanding of organisational AI readiness and provides a structured, human-centred approach for future AI applications in public administration. Further research should validate the framework for future model development in diverse administrative settings.

Keywords: Artificial intelligence; public administration; AI readiness; AI preparedness; organisation; systematic literature review. (search for similar items in EconPapers)
JEL-codes: H83 O38 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ers:ijebaa:v:xiii:y:2025:i:3:p:24-47

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