Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
This paper provides a comprehensive review of the literature on the AI implementation in the public sector. Using the ADO framework, it analyzes the antecedents, decisions, and outcomes of an implementation of AI. In particular, the review identifies key drivers for the adoption of AI, such as technological advancements, policy directives, and the need for efficiency and transparency. Decision-making processes include the selection of the right policies, technologies, and work practices. Finally, the outcomes show an effect on the workforce, socio-economic benefits, services offered, trust, and policy-formulations. As such, the paper contributes to a greater theoretical understanding of an AI implementation in the public sector and highlights the current gaps in the literature. Practically, it offers insights and proposes a framework that will be useful for both policymakers and practitioners aiming to implement AI effectively in public sector organizations.
Recommended Citation
Henk, Anastasiya and Henk, Oliver, "From Antecedents to Outcomes: A Structured Literature Review on AI Implementation in Public Sector Organizations" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 3.
https://aisel.aisnet.org/hicss-58/dg/ai/3
From Antecedents to Outcomes: A Structured Literature Review on AI Implementation in Public Sector Organizations
Hilton Waikoloa Village, Hawaii
This paper provides a comprehensive review of the literature on the AI implementation in the public sector. Using the ADO framework, it analyzes the antecedents, decisions, and outcomes of an implementation of AI. In particular, the review identifies key drivers for the adoption of AI, such as technological advancements, policy directives, and the need for efficiency and transparency. Decision-making processes include the selection of the right policies, technologies, and work practices. Finally, the outcomes show an effect on the workforce, socio-economic benefits, services offered, trust, and policy-formulations. As such, the paper contributes to a greater theoretical understanding of an AI implementation in the public sector and highlights the current gaps in the literature. Practically, it offers insights and proposes a framework that will be useful for both policymakers and practitioners aiming to implement AI effectively in public sector organizations.
https://aisel.aisnet.org/hicss-58/dg/ai/3